University of Groningen
Influenza vaccination-induced B cell response in monoclonal gammopathy of
undetermined significance (MGUS)
Tete, Sarah
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Influenza vaccination-induced
B cell response in monoclonal
gammopathy of undetermined
significance (MGUS)
Sarah M. Tete
Studies presented in this thesis were financially supported by
Groningen University Institute for Drug Exploration (GUIDE)
University of Southampton
Jan Kornelis de Cock Stichting
Printing of this thesis was financially supported by
University of Groningen
University Medical Centre Groningen
Groningen University Institute for Drug Exploration (GUIDE)
Cover Design
Gerber van Erven & Off Page
Thesis layout and printing
Off Page, Amsterdam
www.offpage.nl
ISBN (printed): 978-90-367-7266-2
ISBN (digital): 978-90-367-7265-5
Copyright © 2014 by Sarah Tete
No parts of this book may be reproduced, stored in a retrieval system or transmitted, in any
form or by any means, without prior written permission of the author. All rights reserved.
Influenza vaccination-induced
B cell response in monoclonal
gammopathy of undetermined
significance (MGUS)
PhD thesis
to obtain the degree of PhD at the
University of Groningen
on the authority of the
Rector Magnificus Prof. E. Sterken
and in accordance with
the decision by the College of Deans.
This thesis will be defended in public on
Monday 20 October 2014 at 11.00 hours
By
Sarah Mugove Tete
born on 12 February 1987
in Kwekwe, Zimbabwe
Supervisor
Prof. N.A. Bos
Co-supervisor
Dr. S.S. Sahota
Assessment committee
Prof. A.M.H. Boots
Prof. P. Heeringa
Prof. J.C. Wilschut
Paranymps
Thembile Mzolo
Melissa Newling
Dedicated to my beloved mother and late grandmother
For all the sacrifices you made
TABLE OF CONTENTS
TABLE OF CONTENTS
Chapter 1
Introduction
Chapter 2
Immune defects in the risk of infection and response to
vaccination in monoclonal gammopathy of undetermined
significance and multiple myeloma
27
IgG antibody and TH1 immune responses to influenza
vaccination negatively correlate with M-protein burden
in monoclonal gammopathy of undetermined significance
57
Hampered influenza-specific IgG B cell responses whereas
IgM and IgA responses are maintained in monoclonal
gammopathy of undetermined significance
75
Monoclonal paraprotein influences baseline B cell repertoire
diversity and pertubates influenza vaccination-induced
B cell response
91
B cell repertoire diversification in monoclonal gammopathy
of undetermined significance (MGUS)
109
Chapter 7
Summary and discussion
123
Chapter 8
Nederlandse samenvatting
135
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Acknowledgements -Dankwoord
9
145
7
CHAPTER
Introduction
1
INTRODUCTION
MONOCLONAL GAMMOPATHY OF UNDETERMINED
SIGNIFICANCE
Understanding disease susceptibility in human aging is currently at the forefront
of grand challenges in research, and it is being increasingly realized that
immunosenescence plays a pivotal role in this phenomenon. Evidence is accruing
that shows aging impairs normal immune responses, and there is intense interest
in how this impacts on systemic disease, such as cancer. Immunosenescence in
aging also directly underpins an impaired response to common infections, and
this may be compounded further by onset of systemic disease, especially disease
of a hematological nature.
This thesis focuses on monoclonal gammopathy of undermined significance
(MGUS), a non-malignant lymphoproliferative plasma cell condition and how
it impacts on immunity in aging, using responses to influenza vaccination as a
read-out. In MGUS, plasma cells accrue to <10% of the bone marrow, the primary
disease niche and is characterized by the presence of a serum monoclonal
immunoglobulin (M protein) (<30g/L). IgG is the predominant M protein isotype
with more than 60% of cases being IgG, 19% IgM, 17% IgA, and 3% biclonal [1].
More recently, a subtype of MGUS in which the secreted M protein lacks IgH has
been defined as light-chain MGUS, occurs in approximately 0.8 % of the population
aged over 50 years [1, 2]. Overall, MGUS is associated with advancing age and
has a prevalence of >5% in people over 70 with less than 2% of MGUS patients
falling under the age of 40 [3]. It has always been recognized that some cases of
MGUS will progress to malignant symptomatic multiple myeloma (MM), but recent
and seminal studies have shown that MM is consistently preceded by MGUS [4,5].
Thus, MGUS and MM are two different phases of the same disease, but with
profoundly differing outcomes and impact on immune status, and response to
infection and vaccination.
FROM PRECURSOR DISEASE TO MULTIPLE MYELOMA
MGUS pathogenesis
The aetiology of MGUS is as yet unknown. However, several observations point
towards the role of environmental factors and genetic predisposition in the
development of MGUS. The rate of MGUS varies strikingly with race. MGUS is
more prevalent in African Americans and Africans (Ghananians) with a risk ratio of
2 to 3 compared to whites [6,7].The cumulative risk of MM is similar in these MGUS
populations, indicating an increased risk of MGUS in blacks that may partly explain
the higher incidence rate of MM in African Americans. The lowest incidences of
MGUS are found in the Japanese population [8,9]. Possibly, the higher risk of MGUS
in blacks also reflects unidentified environmental influences, which may interact
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CHAPTER 1
with genetic factors. There is also evidence for familial aggregation for MGUS and
MM. Healthy relatives of MM patients have been reported to have an elevated
incidence of immunoglobulin abnormalities, without any other signs of plasma cell
lymphoproliferative disorders [10]. In a study of 304 MGUS and 407 MM patients,
first degree family members of MGUS or MM patients were found to have at least a
2-fold greater risk of MGUS compared to the general population [11]. The prevalence
of MGUS in first degree relatives increased with age and in relatives over 80 was
higher (13%) than in the general population (7%). A larger Swedish population
based study of 4,458 MGUS patients and their relatives (n=14,621) as well as 17
505 healthy control subjects and their relatives (n= 58,387) assessed the risk of
MGUS and lymphoproliferative malignancies among first degree relatives. MGUS
relatives had a 3-fold increased risk of developing MGUS and MM compared to
the relatives of healthy controls [12]. The precise role of environmental and genetic
factors in the development of MGUS and MM however needs to be fully defined.
Despite its apparent ‘benign’ manifestation, there are marked primary cytogenic
changes in MGUS that are shared with MM. In both, disease forms two broad subsets,
hyperdiploid and non-hyperdiploid disease. Fluorescence in situ hybridization (FISH)
has identified IgH translocations in approximately 50% of MGUS and 50-70% of
MM [13]. Approximately 50% of MGUS is associated with IgH translocations, the
remaining 50% is associated with hyperdiploid or IgH non-translocated MGUS
[13]. Translocations involving the IgH locus on chromosome 14q32 result in the
juxtapositioning and aberrant expression of the oncogene translocated to the IgH
locus under the influence of strong transcriptional enhancers (ref – cite Bergasgel
review). Chromosomal loci and genes dysregulated in the translocations include
11q13 (cyclin D1 gene), 6p21 (cyclin D3), 4p16 (FGFR3 and MMSET), and 16q23
(c-maf) [13,14]. These translocations usually occur near or within IgH switch regions,
and may be mediated primarily by errors in IgH switch recombination or by errors in
somatic hypermutation, resulting in the dysregulation of oncogenes on the derivative
chromosomes [15]. These aberrations are considered to be a critical step in the
development of the MGUS clone, and it has been suggested that they immortalize
the MGUS clone but do not promote progression to clinical symptomatic disease.
In progression to malignancy, the premalignant clone in some cases escapes
the regulatory mechanisms that restrict its size and progression to MM or other
plasma cell disorder occurs. The progression occurs at a constant rate of 1% per
year but the sequences of genomic and cellular events associated with progression
are not fully defined as yet
The bone marrow microenvironment also undergoes marked changes with
progression from MGUS to MM, and plays a defining role in transformation [16].
Indeed, bone marrow angiogenesis increases significantly in the advanced stages
of the disease due to loss of angiogenesis inhibitory activity [17]. Furthermore,
INTRODUCTION
various cytokines including IL-6 and TNF- have been implicated in progression
to MM [18]. IL-1 produced by the myeloma cells induces IL-6 secretion by bone
marrow stromal cells, which in turn supports the growth and survival of the myeloma
cells, but also contributes to development of skeletal disease, diagnostic for MM
disease [20]. The development of bone lesions is mediated by the imbalanced
activity of osteoblasts (bone forming) and osteoclasts (bone resorping) in MM.
Increased expression of RANKL (receptor activator of nuclear factor B ligand)
Figure 1. Clinical Progression of MGUS. A multi-step process from stable MGUS clone to
progressive malignant myeloma tumor.
In the asymptomatic phase of monoclonal gammopathy, MGUS, patients have elevated levels of
monoclonal protein and may remain stable for many years. Smoldering multiple myeloma is the disease
transition phase between MGUS and MM. However, some MGUS patients may skip this stage and
progress straight to malignant multiple myeloma. The dotted line represents healthy individuals who
are diagnosed with multiple myeloma after showing symptoms and with no previous serum protein
electrophoresis carried out to check for M-protein. BM; bone marrow, , FLC; free light chain, HC;
healthy individual, MM; multiple myeloma, SMM; smouldering multiple myeloma, SPEP; serum protein
electrophoresis
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CHAPTER 1
by osteoblasts is accompanied by a reduction in the level of its decoy receptor,
osteoprotegerin (OPG) [21]. As a result RANKL/OPG ratio is increased leading
to osteoclast activation, increased bone resorption and turnover. Furthermore,
osteoclast overactivity is also mediated by increased levels of macrophage
inflammatory protein–1 (MIP-1 ) and IL-6 [22].
Predictors of progression from precursor MGUS disease to MM
It is imperative to identify MGUS patients who will progress to clinical malignant
MM disease. However, at present it is difficult to predict which MGUS patients will
progress to MM at the time of diagnosis and reliable biologic markers that allow
us to predict progression are lacking. Several clinical markers are associated with
higher risk of progression. Serum levels of monoclonal protein are a prognostic
factor with levels >15g/L associated with higher risk [23,24]. The evolving pattern of
monoclonal protein at the first 3 years of follow-up is also an important prognostic
factor with increasing levels in MGUS being associated with higher risk of progression
[24]. However, stable monoclonal protein does not exclude the development of MM
[3]. The immunoglobulin isotype is a further independent predictor of progression
with IgA and IgM MGUS being at a higher risk of progression that IgG MGUS
[23,24]. Abnormal free light chain (FLC) ratio is also an independent prognostic
factor [25,26]. Using the FLC assay, free kappa ( ) and lambda ( ) light chains can
be quantified. Increased concentrations of one free light chain result in kappa/
lambda ratios higher or lower than normal range (0.26-1.65mg/L) depending on
the excess FLC secreted by plasma cells in addition to intact immunoglobulin [27].
In a risk stratification model; a non-IgG isotype, M-protein concentration more
than 15 g/L, and an abnormal FLC ratio are considered adverse prognostic factors
with the number of risk factors correlating with the progression risk. Indeed, the
absolute risk of progression in MGUS patients with 0, 1, 2, and 3 risk factors is 5%,
21%, 37%, and 58%, respectively, at 20 years [26].
Of high clinical relavence in the transition of asymptomatic MGUS to activeMM,
key monoclonal gammopathy stages can also be defined, as asymptomatic
smoldering MM (SMM), plateau phase disease and active disease. SMM is
distinguished from MGUS by higher cutoff values with serum M-protein ≥ 30 g/l
and/or bone marrow clonal plasma cells ≥ 10% while maintaining a lack of end-organ
damage. Despite MGUS and SMM being both asymptomatic precursors of MM,
they differ from each other as the risk of progression to MM is much higher in SMM
(10% per year) as compared to MGUS (1% per year)[27, 28] . This 10-fold increased
risk alone suggests that SMM differs biologically to MGUS.
Although recent therapies and better supportive care have improved the
survival of MM, it as yet remains incurable in most cases [median survival 4-5 years]
providing further impetus to define the pathogenesis and progression of disease,
to inform therapy including immunotherapy [29, 30].
INTRODUCTION
CLINICAL MANAGEMENT AND TREATMENT INTERVENTION
IN MGUS
Currently no treatment is recommended for patients with MGUS; rather patients are
monitored and observed at 6 months to 2 yearly intervals for changes in their clinical
and immunochemical status until they progress to MM before treatment is started.
The International Myeloma Working Group (IMWG) guidelines suggest monitoring
of MGUS patients based on risk category [31]. Low-risk MGUS (M-protein <15g/ L,
normal FLC ratio and IgG isotype) are followed at 6 months with serum protein
electrophoresis (SPEP), calcium and creatinine measurements as well as complete
blood count. If they remain stable, they are monitored every 2-3 years thereafter.
However check-up should be carried out if symptoms of MM arise [31]. In patients
with intermediate or high-risk MGUS, that is with any 2 or 3 risk factors respectively,
a bone marrow examination by conventional cytogenics and fluorescent in-situ
hybridization (FISH) should be carried out so as to rule out underlying malignancy.
Patients are then followed in 6 months and then monitored annually.
Preventative studies for MGUS need to consider the risk of progression
to malignancy and should be aimed at patients who are at the highest risk of
progression. Amongst the first preventative studies directly in MGUS is the report
by Golombick et al in which curcumin was administered [32]. Curcumin is derived
from turmeric (Curcuma longa), a tropical herb that belongs to the ginger family
and is native to southern and south eastern tropical Asia [33]. Curcumin inhibits
the proliferation of MM cells by downregulating IL-6, an important growth factor
for myeloma cells, and inhibits osteoclastogenesis by the suppression of RANKL
signaling [22,34]. In the study by Golombick et al, 4g daily curcumin reduced
M-protein levels by 12 to 30% in 50% of patients with M-protein levels ≥ 20g/L
and a decrease in bone resorption was also indicated in some patients [35]. The
same group further conducted a randomized, double-blind placebo-controlled
crossover 4g study, followed by an open-label extension 8 g study to investigate
the effects of curcumin on paraproteinemia, serum-free light chains, and bone
turnover in MGUS and SMM patients [36]. Curcumin administration decreased the
free light-chain ratio (rFLC), serum creatinine levels and urinary deoxypyridinoline
(uDPYD), a marker of bone resorption in comparison to the placebo group [36].
However, the effect on progression to symptomatic disease was not reported.
Clinical trials with curcumin remain as preliminary studies.
Other placebo controlled clinical trials with dehydroepiandiosterone (DHEA), an
adrenal sex hormone, that has anti-inflammatory properties such as suppression of
inflammatory cytokine production as well as with Clarithromycin, an antibiotic, were
carried out at Mayo clinic in patients with MGUS [37]. Other agents like anakinra, a
targeted IL-1 receptor antagonist, green tea catechin extract (Polyphenon E) and
celecoxib are subjects of investigation (clinicaltrial.gov).
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The development of novel therapies with less cytoxicity has renewed the
interest in early treatment at the SMM disease stage. Thalidomide, an antiinflammatory, antiangiogenic and immunomodulatory drug has been trialed in
SMM and prewviously untreated MM and achieved partial response in 38% of 16
patients [38]. Furthermore, a phase 3 trial with lenalidomide-dexamethasone in
SMM reported a longer till till progression as well as higher survival rates in the
treated group versus observational group. Response was achieved in 79% after
induction therapy [39].
Therapeutic clinical trials in asymptomatic individuals with MGUS/SMM pose
a challenge to researchers. However, identifying the right target group at highest
risk for progression may prove to be of great benefit in preventing onset of MM.
IMMUNE STATUS IN MGUS
The outcome of progression in MGUS not only depends on the pre-malignant clone
but also on its interaction with other cells and the microenvironment. In this, the
host immune response to the lymphoproliferative clone thwarts progression, but
eventually is overcome as generally observed in the equilibrium-escape phases in
cancer. However, MGUS-MM also directly influences immune capacity, as apparent
in response to infection. These aspects are central to this thesis, and are discussed
further below.
Excess mortality due to bacterial infections has been reported in MGUS [40].
Other than an increased risk of a broad range of bacterial infections that include
pneumonia, osteomyelitis, septicemia, pyelonephritis, endocarditis and meningitis,
MGUS also has increased risk of developing viral infections herpes zoster and
influenza [41]. The increased risk of developing infections may have clinical
importance for vaccination as well as for monitoring of MGUS patients. Specifically
for influenza where the changing nature of the major influenza antigen means that
yearly revaccination with a new circulating strain is required, and vaccination in
high risk groups is of considerable importance [42]. However, data concerning
the safety and efficacy of influenza vaccination is lacking in MGUS. Because of
the increased susceptibility of MGUS patients to influenza infections, it has been
questioned whether these patients can mount sufficient immunological response
to benefit from vaccination. We investigate this question directly in this thesis, and
assess its implications.
NORMAL IMMUNE RESPONSE TO INFLUENZA INFECTION
Influenza virus entrance is through the respiratory tract, which is also the site
of replication. The mucosal system is therefore the first immunological barrier
against influenza infection. The nasopharyx-associated lymphoid tissue (NALT) that
consists of the Waldeyer’s ring, an organized mucosal inductive site, is important in
INTRODUCTION
the induction of the mucosal immune response together with the regional draining
lymph nodes [43,44]. Upon infection with influenza virus, several components of the
innate immune system are triggered and mediate viral clearance [45]. Macrophage
viral clearance is through apoptosis-dependent phagocytosis [46]. In addition,
macrophages secrete IL-2 which induces natural killer (NK) cell IFN- production.
These NK cells are detected 2 hours after infection in pulmonary lymphocytes [47].
Type-1 IFNs secreted by NK cells enhance NK cell mediated cytoxicity important
for inhibiting viral replication. Importantly, the NK cell receptor, NKp46 binds to
hemagglutinin (HA) of influenza virus to activate the lysis of virus-infected cells [48].
Following escape of the innate immune clearance, the influenza virus is detected
by the adaptive immune system.
Dendritic cells (DC) also migrate into or converge under the epithelia of nose
and airways where they capture antigen [49]. DCs migrate to draining lymph nodes
so as to present antigen to T cells [44] leading to T cell activation. Myeloid DCs
are crucial in antigen presentation but have limited type1 IFN production [50].
However, plasmacytoid DCs (pDCs) are a major source of type 1 IFN and are
important for influenza response [51] as they can activate influenza-specific CD4+
and CD8+ T cells [52]. Importantly, pDCs play a role in normal B cell maturation
into plasmablasts as well as regulating their differentiation to antibody secreting
plasma cells through type 1 IFNs and IL-6 [53,54]. NK cells also interact with DCs
to activate innate immunity and promote adaptive immune responses to influenza
[55,56]. NKG2D and NKp46 contribute to increased IFN- production by influenzaspecific DC-activated NK cells [55]. Furthermore, IFN- production by NK cells is
also T-cell dependent, with IL-2 produced by virus-specific T cells influencing IFNproduction [57].
Follicular T helper cells are the predominant specialized CD4+ T cells responsible
for the generation of isotype switched antibodies. Upon antigen encounter via
follicular dendritic cells and interaction with helper T cells, naïve B cells that
recirculate through secondary lymphoid tissues migrate to follicules where they
proliferate and seed germinal centers or migrate to extrafollicular sites [58,59].
TGF- 1 and IL-21 derived from germinal center follicular T helper cells promote
the differentiation of antigen activated B cells into IgA plasmablasts with mucosal
homing properties [60]. Downregulation of CXCR5 and upregulation of CCR10 lead
to the extravasation of plasma cells from GC to local mucosa [55] while primed
B cells leave as memory B cells [61]. Importantly, secretory IgA plays a vital role
in response to natural infection as secretory IgA can neutralize influenza viruses
before passing the mucosal barrier and clear infection in infected epithelia [62,63].
Nonetheless, induction of local and systemic anti-viral IgG antibody responses
is necessary in order to neutralize the virus. Most neutralizing antibodies bind to
the exposed loop surrounding the receptor-binding site so as to interfere with
attachment [64,65] and peak in the serum 3-4 weeks at primary infection. However,
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reinfection induces more rapid response. Hemaglutinin (HA) specific antibodies
not only prevent HA binding to cell surface sialic acid or prevent viral fusion but
also mediate antibody-dependent cell-mediated cytoxicity (ADCC). These ADCC
antibodies have been shown to be isotype subtype specific, and broadly reactive
antibodies within a subtype persist up to a year after live attenuated influenza
vaccination. Interestingly, in sero-positive adults, cross-reactive influenza specific
ADCC antibodies trigger NK activation in the absence of neutralizing antibodies
[66]. Recovery from viral infection with the antibody response therefore relies on
interaction with other immune cells.
Cytotoxic T lymphocytes (CTL) play a role in recovery from influenza infection
by killing of infected host cells, with granzyme mediated apoptosis [67]. The role
of CD8+ T cells in the recovery from infection discerned from studies showing
delayed clearance in CD8+ T cell-deficient mice [68,69] as well as studies in B cell
deficient mice where CD8+ T cells promote resistance and recovery [70]. CD4+
T cells alone cannot clear the virus efficiently in the absence of B cells but have an
indirect role in sustaining the response [71]. A Th1 response due to the production
of IFN- , leads to the recruitment of the CTL response and also provide help for
antibody production [67].
NORMAL HUMORAL RESPONSE TO INFLUENZA VACCINATION
The main strategy effective in preventing influenza infection is vaccination with
its effectiveness depending on antigenic match to the circulating virus strains.
Intranasal vaccination results in increased mucosal as well as serum antibody
levels. The induction of mucosal IgA antibodies is important in viral neutralization
and preventing infection with IgA antibodies providing heterosubtypic crossprotection [72-74]. In addition to the systemic response on which seasonal
vaccination protection is based, parenteral vaccination induces a local immune
response in the tonsils [75]. This may result from activated antibody presenting
cells migrating from draining lymph nodes and homing to tonsils [76]. The currently
used influenza vaccines predominantly activate the systemic immune system and
only negligible mucosal IgA. As a result, although vaccination predominantly
induces IgG antibody secretion lower levels of IgA and IgM are also detected in
the serum [77-79]. The secretion of influenza-specific antibodies by plasmablasts
leads to a rise in serum antibodies and in a week following vaccination, a rise in
titers of all 3 antibody classes (IgA, IgG and IgM) is detected with IgA and IgM
levels peaking after 2 weeks [77,80]. IgG levels on the other hand increase till
they reach a peak 4 weeks post vaccination [75,78]. Importantly, the neutralizing
IgG antibodies elicited by seasonal influenza vaccination have been shown to be
heterosubtypic [81,82].
INTRODUCTION
AIMS OF THIS THESIS
While it is clear that pre-malignant conditions occur with high frequency in the
aging population, the extent to which MGUS specifically impacts on protective
immunity in humans is largely unknown. This thesis therefore examines immune
function in MGUS, focusing on impact of disease on humoral responses and on
response to inflenza vaccination to model immune capacity against infection, as
well as in relation to disease progression to malignant plasma cell disease MM.
In Chapter 2 we first review the known immune defects in the literature associated
with humoral immunity and risk of infections as well as response to vaccination in
MGUS and MM. This provides a back-drop to design and conduct experimental
studies to evaluate immune response to influenza vaccination in MGUS.
As MGUS is more prevalent with increasing age, a substantial number of the
patients fall under the high-risk group of elderly individuals, so they receive seasonal
influenza vaccination. Whether this vaccination is effective has not been investigated
in MGUS before. In Chapter 3, we therefore evaluated the immunogenicity of
2010-2011 seasonal trivalent influenza vaccine (TIV) in MGUS patients. 19 MGUS
patients who fulfilled the diagnostic criteria as well as age-matched healthy controls
were recruited in this clinical study. The data defines the humoral and Th-1 response
to influenza vaccination in relationship to M protein levels in MGUS.
In Chapter 4, we investigate the antigen-specific memory B cell responses to
influenza vaccination. Memory B cells are of importance in influenza vaccination
response as the protective efficacy of the vaccine is largely determined by its
ability to elicit a humoral response. Furthermore, we elucidate changes in B-cell
subpopulations in blood. We hoped to shed light on whether possible B cell
dysregulation in MGUS influences B-cell memory.
Since MGUS patients have an enlarged clonal B cell population, which puts them
at risk for malignant B cell expansion, we characterized the B cell repertoire in
MGUS and matched aged individuals to investigate the impact of MGUS on the
B cell repertoire diversity and how it affects response to vaccination (chapter 5).
Using the method of B cell spectratyping, we amplified the CDR3 region of the
immunoglobulin heavy chain variable (IGHV) region genes and modeled data to
assess diversity in MGUS patients before and after influenza vaccination.
In chapter 6, we further investigate B cell repertoire usage; we exploited the
technology of Next Generation Sequencing to investigate the IgG immunoglobulin
heavy chain variable gene repertoire in high M protein MGUS. We compared the
peripheral B cell repertoire of MGUS with those of HC to investigate if MGUS is
associated with a biased immunoglobulin heavy chain gene usage. Furthermore,
we investigated the clonal diversity of the repertore and how it affected the
response to influenza vaccination.
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Finally, chapter 7 comprises a summary and general discussion of the findings
of this thesis. Also the future perspectives of influenza vaccination in MGUS
are presented.
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CHAPTER
Immune defects in the risk of infection
and response to vaccination in monoclonal
gammopathy of undetermined significance
and multiple myeloma
Sarah M. Tete1, 2, Marc Bijl3, Surinder S. Sahota2 & Nicolaas A. Bos1
(SSS & NAB Joint Senior Authors)
1
Department of Rheumatology and Clinical Immunology, University of
Groningen, University Medical Center Groningen, Groningen, Netherlands;
2
Cancer Sciences Unit, University of Southampton Faculty of Medicine,
Southampton, UK; 3Department of Internal Medicine and Rheumatology,
Martini Hospital, Groningen, Netherlands
Tete S, Bijl M, Sahota S and Bos NA. Frontiers in Immunology.
2014: (5) 257
2
IMMUNE DEFECTS IN THE RISK OF INFECTION AND RESPONSE TO VACCINATION...
29
INTRODUCTION
Understanding immunosenescence has now emerged as a priority to counter
immunological susceptibility to disease in normal aging. Evidence is revealing that
the B-cell compartment and the associated immune synapse in the aging immune
response underlie an increased susceptibility to infections and decreased response
to vaccination [1]. In age-related immunosenescence, onset of hematological
disease may further ameliorate immune capacity, and a combination of these
factors has as yet received little attention. To address this, we focus on a nonmalignant B-cell clonal expansion in late age, on monoclonal gammopathy of
undetermined significance (MGUS) where plasma cells accrue to <10% of the
bone marrow. This condition provides a unique model to understand how immune
susceptibility is impaired in aging by disease. The model extends and acquires
a further urgency when it is recognized that MGUS almost invariably precedes
transformation to malignant multiple myeloma (MM) [2], in which humoral immune
capacity deteriorates further. Currently however, how the efficacy of B-cell response
to generate protective humoral immunity diminishes in these disease states is
largely undefined. Understanding this will be crucial for successful intervention
with vaccination to counter infections in MGUS and MM, and reduce the associated
morbidity and mortality. Consequently, this review examines B-cell dysfunction in
monoclonal disease spanning MGUS to MM.
Monoclonal gammopathy of undetermined significance incidence increases
with advancing age. It is usually diagnosed by chance and is characterized by the
presence of a serum monoclonal immunoglobulin (M-protein) (<30 g/L). MGUS is
present in 3% of people over 50 years and up to 5% over 70 years [3, 4]. A newly
described subtype of MGUS in which the secreted M-protein lacks IgH to skew the
free light-chain-(FLC)-ratio, defined as light-chain MGUS, occurs in approximately
0.8% of the population aged over 50 years to establish an overall prevalence of
MGUS to 4.2% in persons aged 50 years and older [5, 6]. MGUS requires clinical
vigilance, to establish onset of MM. Seminal observations by Landgren and coworkers established that MM patients invariably had a previously recognized
M-protein as MGUS during a nationwide population-based cohort screen [2]. These
paradigm shifting findings were substantiated by Weiss et al. by detection of a
monoclonal gammopathy in prediagnostic sera in 90% of 30 myeloma patients
[7]. As yet, it is difficult to accurately predict the subset that will progress in MGUS
after initial diagnosed and this remains an important area of investigation [3,
8]. Interestingly, light-chain MGUS is also a precursor of light-chain MM, which
comprises 20% of all MM cases; this association has important implications for
understanding the nature of the “feeder” cell for plasma cell malignancy [9–11].
Furthermore, progression rates differ, as IgH MGUS transforms at the rate of 1%
per year but light-chain MGUS has a progression rate of 0.3% per year, which is
2
30
CHAPTER 2
significantly lower [4, 6, 12]. Of particular relevance to the need to understand
immune capacity in disease, it has been established that loss of immune control,
among other factors is implicated in malignant transformation from asymptomatic
disease to MM [13–16]. The immune status in MGUS and MM therefore needs to
be fully understood, for therapeutic intervention to prevent progression and to
counter susceptibility to infection.
In clinical diagnosis, MGUS lack the overt clinical CRAB symptoms that define
MM: hypercalcemia, renal insufficiency, anemia, and bone lesions [11]. In the
MGUS–MM transition, key stages of high clinical relevance can also be defined,
as asymptomatic smoldering MM (SMM), plateau phase disease, and active disease.
SMM fulfills the diagnostic criteria for MM, with serum M-protein ≥30 g/L and/or
bone marrow clonal plasma cells ≥10% however without clinical CRAB symptoms
or end organ damage that dictate therapeutic intervention. Although SMM is an
asymptomatic precursor of symptomatic MM, it differs from MGUS as the risk
of progression to MM is much higher (10% per year) as compared to MGUS (1%
per year) [11, 17]. This 10-fold increased risk alone suggests that SMM differs
biologically to MGUS. The SMM–MM transition is at present a focal area of
research, driven by the need to understand the molecular and cellular basis of full
blown clonal transformation. Although recent therapies and better supportive care
have improved the survival of MM, it remains largely incurable (median survival
4–5 years) [18, 19].
THE RISK AND SPECTRUM OF INFECTIONS IN MGUS AND MM
It is important when assessing susceptibility to infection in MGUS and MM that
healthy controls are age-matched, to obviate an aging immunosenescence and this
has generally been the case in reported studies. The risk of bacteremia in MGUS is
increased ~2-fold as compared to healthy controls, with an increased susceptibility
to a broad range of bacterial infections that include pneumonia, osteomyelitis,
septicemia, pyelonephritis, endocarditis, and meningitis [20]. In viral infections,
MGUS patients have an increased risk of developing influenza and herpes zoster
infections at a risk comparable to that for bacterial infections [20]. High monoclonal
protein at diagnosis associates with higher risks of infection: MGUS patients with
monoclonal protein >25 g/L at diagnosis have the highest risk of infections, and
the risk is still significantly increased in MGUS patients with monoclonal protein
<5 g/L as compared to healthy controls [20]. M-protein levels are most likely
a surrogate for clonal expansion and concomitant immunosuppression. MGUS
patients have an increased mortality due to bacterial infections, with a hazard
ratio of 3:4 [21].
Depressed antibody titers to a number of common infectious pathogens have
been found in several conditions associated with presence of an M-protein. Serum
IMMUNE DEFECTS IN THE RISK OF INFECTION AND RESPONSE TO VACCINATION...
IgG antibody levels directed to 24 different microorganisms were evaluated in
Waldenstrom’s macroglobulinemia, a lymphoma subtype secreting monoclonal
IgM paraprotein, and in MGUS and MM [22]. Significantly depressed antibody levels
to a number of antigens, particularly staphylococcal, moraxella, pneumococcal,
varicella zoster, and also for fungal antigens such as Candida and Aspergillus were
observed in MGUS [22]. However, a significant decrease in antibody titers was also
observed in WM and MM, revealing that humoral immune response to most of
these pathogens is suppressed. There appears to be an increased susceptibility
to infections in MGUS that worsens as disease progresses to MM, as indicated
by antibody titers. The duration of antibody response and their protective value
however varies between different pathogens, with some specific antibody levels
that remain stable over a long time. The variability in humoral response to different
pathogens indicates a requirement to carefully dissect responses to individual
infectious agents in MGUS and MM.
There is clear evidence of immune dysfunction in MM that leads to vulnerability
to infection, a leading cause of morbidity and mortality. Lymphocytopenia [23],
hypogammaglobulinemia [24], and granulocytopenia secondary to bone marrow
infiltration and therapy [25] are factors that are consistently found to increase the
susceptibility of MM patients to infections. In a study of 3107 newly diagnosed MM
patients in the UK Medical Research Council Trial from 1980 to 2002, infections
caused 135 deaths [45%) of all deaths, occurring within 60 days of diagnosis and
with two-thirds of these being attributed to pneumonia [26]. The risk of infection is
highest in the first 3 months and decreases with response to treatment, revealing
a direct causative links as tumor burden is reduced. The most frequent infections
are bacteremia and pneumonia caused by Haemophilus influenzae, Streptococcus
pneumoniae, and Escherichia coli [27–29]. These microorganisms predominate
in the early stages of disease and in plateau phase, but in the terminal phase of
the disease the spectrum of causative microorganisms widens [29, 30]. Recurrent
bacterial infections at presentation meet the diagnostic criteria for symptomatic
MM [11].
In addition to intrinsic disease-derived factors, the type of therapy used in
symptomatic MM also plays a role in susceptibility to infection. Chemotherapy
can disrupt the mucosal barriers thereby increasing the risk of infections [31].
Induction therapy for MM has changed recently and the traditional oral melphalan
and prednisone (MP) as well as vincristine–adriamycin–dexamethasone (VAD)
combinations have been replaced by dexamethasone, thalidomide, bortezomib,
and lenalidomide-based regimens [32, 33]. Although well- and better-tolerated,
the use of novel therapies results in an increased risk of opportunistic infections
as well as the shift in the spectrum of infections in MM. Novel therapeutic agents
increase the risk of viral infections; bortezomib therapy for instance, increases the
risks of herpes zoster reactivation in the first few months of treatment due to the
31
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CHAPTER 2
immunosuppressive effects on T cells [34, 35]. Dexamethasone use is associated
with a greater risk of infections, and associates with depressed cell-mediated
immunity against cytomegalovirus and varicella-zoster virus [36, 37]. Notably,
high-dose dexamethasone is associated with higher rate of infections (18%) in
comparison to low-dose dexamethasone (9%), as shown in a randomized controlled
trial of newly diagnosed MM [38]. The lack of immune reconstitution due to poor
disease response to therapy leaves patients with an on-going immune deficiency
that perpetuates their risk of infections. It is also conceivable that infections may
have a potential role in enhancing the survival of myeloma cells but this has as
yet not been fully addressed. Infections are frequent in MM and microorganisms
are known to induce B-cell activation through Toll-like receptors (TLR). MM cells
express TLR and TLR-specific ligands have been shown to induce cell proliferation
and prevent apoptosis of human myeloma cell lines [39, 40]. This further exemplifies
an unwanted tumor adaptation to exploit local niche characteristics.
NORMAL AGE-ASSOCIATED CHANGES IN HUMORAL RESPONSE
The immune status of patients with MGUS or MM has to be seen in the light
of the aging immune system. Qualitative as well as quantitative changes in
the humoral immune response occur with late age. The B-cell repertoire and
maturation response are critical in mediating protection against infection [41].
Antigen response in B cells may occur with T-cell help for T-cell-dependent (TD)
maturation, or can result in T-cell-independent (TI) antibody formation. Both
can generate B-cell memory, although the TD pathway is largely responsible for
long-term memory by generating plasma cells that home to and reside in the
bone marrow; both pathways are a pre-requisite in vaccination aimed at inducing
protective antibody titers [42].
A number of studies have shown a decline in total CD19+ B cells frequencies
with age, and shifts in specific B-cell subset populations [43–45]. A decrease in
naïve B cells together with memory and plasma cells has been reported [46]. In
B-cell memory, the IgM component (CD19+ IgM+ IgD+ CD27+) plays an important
role in response to bacterial infections and declines with age [47]. There are also
age-related decreases in the IgD− CD27+ switched memory B-cell pool [43, 47, 48].
Furthermore, a decrease in the number and percentage of circulating plasma cells is
seen with age [49]. Newly arising subpopulations termed “age-associated B cells,”
defined as CD21low, CD23low, CD11c+ that seem to be more responsive to TLR7
and TLR9 ligands than direct B-cell receptor (BCR) stimulation have been described
[50] Antigen-specific B cells populations are altered with the changes evident as
decreased antibody responses to influenza and pneumococcal vaccination [47, 51].
In mechanistic insights, key observations suggests an intrinsic defect in deletional
class switch recombination (CSR) due to decreased expression of activation-
IMMUNE DEFECTS IN THE RISK OF INFECTION AND RESPONSE TO VACCINATION...
induced cytidine deaminase (AID) with age [43, 52]. AID is a pre-requisite for both
TD and TI B-cell responses. As a result, weak and low affinity antibody responses
are elicited. Induction of sustainable B-cell responses is therefore a challenge in
the elderly.
Changes in B-cell subpopulations impact on the available repertoire in aging
and this has been mapped by spectratyping and gene sequencing studies looking
at immunoglobulin heavy-chain variable region complementarity-determining
region 3 (CDR3) use. These studies reveal a collapse in BCR diversity due to B-cell
oligoclonal expansions that occur with age [53]. Oligoclonality is also associated
with poor health status (frailty) [54]. This loss of diversity will clearly impair the B-cell
response to new antigenic challenge.
Senescence of humoral immunity impairs immunogenicity and efficacy of
vaccination with a number of studies providing evidence that age impacts on
response [55–57]. Immune response to influenza vaccination declines with age. In
young adults, vaccination is 70–90% effective against influenza (protective titers
against two or three of the influenza viral strains) especially when the vaccine
matches the circulating strains [58, 59]. However, in the elderly population, influenza
vaccination is only 60% effective, although it may be up to 80% effective in the
prevention of serious influenza complications [60, 61]. Other than the inferior
antibody response generated in the elderly in comparison to that of young adults
[56, 62], a decreased anti-viral cell-mediated response is also apparent [56].
Infections caused by encapsulated extracellular bacteria such as Streptococcus
pneumonia and Haemophilus influenza type B (Hib) are an important health issue in
aging. The bacterial polysaccharide capsule per se provides a challenge for vaccine
design to counter invasive disease. Capsular polysaccharides as antigens do not
generate a memory response [63] and the antibody response to polysaccharide
vaccine is short-lived [64]. However, polysaccharide vaccines are more immunogenic
when conjugated to a carrier protein [65, 66], as a result of the switch from a TI
to a TD response. A 23-valent pneumococcal polysaccharide vaccine is currently
licensed for use in the elderly since they become infected with a broad range
of serotypes. Nonetheless, the effectiveness of the 23-valent pneumococcal
polysaccharide vaccine in the elderly remains controversial. In a study by Rubins
and colleagues, only 20% of the elderly (>65 years) had a twofold increase in
specific antibody following vaccination. Moreover, they did not respond to the
most prevalent serotypes causing invasive disease [67]. An earlier study of elderly
males showed a response to all seven measured serotypes that was comparable to
that of young adults [68]. Other studies have shown that vaccination reduces the
incidence of hospitalization and mortality in the elderly [69–71] and is effective in
45% vaccinated individuals in preventing Streptococcus pneumonia infection [70].
Nasopharyngeal carriage of Streptococcus pneumonia has the highest prevalence
in infants and naturally induced anti-polysaccharide IgG prevents carriage in the
33
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CHAPTER 2
adult [72]. However, in the elderly naturally acquired anti-polysaccharide IgG
and IgM decrease with age [73], and additional protection is not conferred by
simultaneously administering pneumococcal and influenza vaccinations in the
elderly [74, 75]. Of the six serotypes of encapsulated Haemophilus influenza, type
b is the most virulent, causing invasive diseases such as meningitis, septicemia,
and pneumonia. A number of Hib-conjugate vaccines are licensed for use and
the estimate of protective anti-Hib polysaccharide antibodies, 0.15–1 μg/mL [76,
77], are based on the assumption that protection from invasive disease is solely
mediated by antibodies, with negligible contributions of cell-mediated immunity. In
the elderly, Hib polysaccharide conjugate vaccine-induced specific IgG antibodies
are of comparable affinity as those generated in young adults [78], and Hib
polysaccharide conjugate vaccination elicits a strong and rapid response in the
elderly that results in protective titers [79].
In addition to diminution of antibody responses, an increase in reactivity
toward autologous antigens that leads to autoantibody production in the elderly
is indicative of a wider malaise in humoral responses, suggesting loss of tolerogenic
control and check-points [80–82].
Alterations in T-cell immunity that can contribute to the development of
infections also occur with aging; these thymic atrophy-related changes in T-cell
proportions as well as function changes have been reviewed elsewhere [83–85].
IMMUNE DEFECTS IN MGUS AND MM
B-Cell Function
B-cell dysfunction is less profound in MGUS than in MM. This can be tracked by studies
on uninvolved polyclonal serum immunoglobulins as hypogammaglobulinemia,
which reflects the influence of the tumor clone on the spectrum of immunoglobulin
production. Hypogammaglobulinemia occurs at a lower frequency in MGUS
(25–28%) [3, 86, 87], is more frequent in SMM (45–83%) [17, 88, 89] and is
often associated with MM [25, 90]. The frequency of hypogammaglobulinemia
associates with disease progression and the reciprocal depression of uninvolved
immunoglobulins is a prognostic factor for progression to MM [17, 88, 89, 91, 92].
These findings support the concept that progressive immunodeficiency is a feature
of disease progression in MM.
B-cell enumeration
Circulating CD19+ B cells in MGUS are numerically normal or decreased in
comparison to age-matched HCs [93–95]. In MM, the significant depression of
circulating CD19+ B-cell frequencies correlates inversely with stage of disease, and
coupled with defective cell-mediated immunity in late stage disease contributes
to the increased risk of infection [25].
IMMUNE DEFECTS IN THE RISK OF INFECTION AND RESPONSE TO VACCINATION...
Plasma cells are the long-term depots of antibody generating cells in the normal
BM. MGUS plasma cells display phenotypic heterogeneity as compared to their normal
counterparts. Based on the expression of CD19 and CD56, two distinct subpopulations
of plasma cells can be seen. The first population of plasma cells is polyclonal and
has an identical phenotype to normal BM plasma cells, observed as CD19+ CD56−
CD38+ CD138+. A second population of abnormal plasma cells is characterized by
restricted intracytoplasmic light-chain expression and lack of expression of CD19
and/or CD56 [96] These abnormal plasma cells can be detected at low frequencies
(limit of detection 0.01% of leukocytes) by using combined immunophenotyping and
clonality assessment [97, 98]. Abnormal MGUS clonal plasma cells have the same
phenotype as MM clonal plasma cells [99]. There is a progressive replacement of
normal BM polyclonal plasma cells by clonal (tumor) plasma cells as disease advances
from MGUS to MM [100, 101]. Normal plasma cells have been found to make up to
86% of total BM plasma cells in MGUS and 0–32% in MM [96]. The number of residual
polyclonal plasma cells in BM can therefore distinguish between MGUS and MM
with 98% MGUS patients having >3% normal plasma cells and only 1.5% MM having
>3% normal plasma cells. From these observations alone, it is apparent that normal
(polyclonal) long-lived plasma cell memory deteriorates markedly in MM.
Not only is the increase in aberrant clonal plasma cell populations likely to
impact on normal plasma cell compartment, but also associates with egress into
the circulation. The circulating abnormal plasma cells have been found to be a
significant predictor of progression in MGUS [91, 100, 102, 103], and clonal plasma
cells can also be detected in the peripheral blood of SMM as well as MM [104–106].
Circulating abnormal plasma cells can be detected in up to 20% of MGUS patients
[102, 103] and up to 80% MM [107, 108]. The increase in circulating plasma cells
parallels their increase in bone marrow [101].
T-Cell Function
Several studies have sought to evaluate defects in T-cell frequencies and function
broadly in MGUS and myeloma. At present, there is limited evidence for both
decreased antigen-specific T-cell responses and less so for T-dependent B-cell
antigen-specific responses.
Significant aberrations in T-cell count and function have been described in
MGUS and MM. A decrease in CD4+/CD8+ ratio due to increased CD8+ T cells in
the bone marrow and circulation has been reported in both conditions [95], or due
to lower CD4+ T-cell numbers [102], whereas others have shown that the MGUS
CD4+/CD8+ ratio and absolute numbers do not differ significantly from healthy
controls [109]. Within the CD4+ T-cell compartment in MM, selective loss of the
naïve CD4+ CD45R+ subset has been reported [110].
Th1/Th2 cytokine balance regulates the immune response. Th1/Th2 polarization
depends on the local cytokine concentrations that induce differentiation of
35
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naïve T lymphocytes to either Th1 cells, which promote cell-mediated immunity,
or Th2 cells, which promote antibody-mediated immunity [111, 112]. In many
hematological malignancies, however, the balance is changed [113, 114]. In MGUS,
the balance seems comparable to healthy individuals [115], whereas in MM, there
is an imbalanced Th1/Th2 ratio that results in a defective Th1 response [115]. This
defective Th1 response correlates with disease stage and is related to elevated
levels of IL-6 and increased numbers of IL-6+CD3+ T cells. Local concentrations
of IL-12 that induce differentiation of naïve T lymphocytes to a Th1 phenotype,
however, are compromised by IL-10 and fail to induce polarization of activated
T lymphocytes in vivo in MM [115].
To examine T-cell response to infectious agent antigens, Maecker et al.
characterized the in vitro CD8+ T-cell response in HLA-A*0201+ MM patients and
healthy individuals to influenza A and Epstein–Barr virus-derived immunodominant
epitopes using major histocompatibility complex (MHC)/peptide tetramers [116].
Following in vitro stimulation, 67% healthy individuals showed an increased
frequency of antigen-specific T cells for both antigens while in myeloma the
magnitude of the response was reduced, with <30% reacting to both viral antigens
[116]. These findings need to be expanded to examine antigen-specific T-cell
capacity in vivo to vaccination to a wider spectrum of infection-related antigens.
Chemotherapy aggravates the immunodeficient state of myeloma patients,
resulting in significant reductions in CD4+ as well as specific reductions in CD4+
CD45RO+ cells as compared to untreated myeloma; this decrease is strongly
associated with opportunistic infections [25].
The induction of effector T-cells in response to active vaccination (e.g., to
counter infection) will be influenced by functional regulatory T-cells (Tregs). Treg
cells play an important role in modulating immune response, maintaining immune
homeostasis, and suppressing excessive immune responses where any imbalances
lead to impaired immune functions. Several subsets of Tregs have been identified;
naturally occurring CD4+CD25+FoxP3+ Tregs (nTregs) that are generated in the
thymus, and peripherally inducible Tregs that include type I T-regulatory (Tr1) that
constitutively express IL-10 and Th3 CD4+ Tregs that produce TGF- [117–119).
Furthermore, CD8+ as well as double-negative Treg (DN Treg) cells have also been
described [120, 121]. Tregs can regulate the effector Th1 and Th2 responses by
production of soluble cytokines IL-10 and transforming growth factor- (TGF- )
and/or contact dependent mechanisms [122, 123].
There is significant discrepancy in the literature regarding the frequency of Treg
cells and their function in MGUS and MM that is probably related to the differences
in techniques and markers used to identify these cells. A report by Prabhala et al.
showed that the frequency of CD4+FoxP3+ Tregs in MGUS and MM is reduced
and they were functionally impaired as the Tregs had significantly reduced ability
to suppress T-cell proliferation [124]. In contrast, Beyer et al. found a significantly
IMMUNE DEFECTS IN THE RISK OF INFECTION AND RESPONSE TO VACCINATION...
increased frequency of CD4+CD25hiFoxP3+ Tregs in MGUS as well as treated and
untreated myeloma. Using allogenic T cell stimulation, they showed that these
cells also maintained their functionality as they inhibited proliferation and IFNproduction [125]. Other studies confirmed that CD4+CD25+FoxP3+ Treg cells
were increased and this increase correlated with disease activity in MM [126, 127].
A marked decrease in DN Tregs has also been reported in MM [126]. A reduced
frequency or compromised Treg activity on the other hand may be deleterious
to the host, as this results in dysfunctional T cell responses and increased risk of
infections [128].
DC Function
Dendritic cells (DCs) as professional antigen presenting cells play a central
role in recruiting host adaptive immunity. Using blood dendritic cell antigen
(BDCA) labeled DCs, plasmatoid DC (pDC) (BDCA-2+) and myeloid DC1 (mDC1)
(BDCA-1+) cells were found to be suppressed in MGUS and further reduced as
the disease progressed in MM [94]. The reduced number of circulating mDCs
and pDCs in MM are characterized by a lower expression of HLA-DR, CD40, and
CD80, in addition to an impaired induction of T cell proliferation and cytokine
stimulation [129, 130]. The functional defects result from IL-6 inhibiting the
growth of CD34+ DC progenitors and switching development and maturation
of CD34+ cells from DC toward monocytic cells with phagocytic activity but with
no antigen-presentation capacity [129]. Enumeration of high potency CMRF44+
CD14− CD19− DCs in MM in peripheral blood approached relatively normal
numbers, expressing expected levels of CD80 and CD86. They did however
exhibit functional defects with reduced capacity to up-regulate CD80 and CD86
expression after CD40L and IL-2 stimuli. This stimulatory defect may result from
tumor-derived TGF- 1 and IL-10 that down-regulate CD80 [131]. Potentially, this
can be abrogated by anti-TGF- 1 and IL-10 antibodies. IL-12 and IFN- can
also neutralize the failure to stimulate CD80 upregulation [132]. As in other
immune compartments, specific therapeutic agents can impact on DC function:
bortezomib, a major drug in MM, significantly impairs the immunostimulatory
capacity of mDCs [133, 134]. An additional consideration is that pDCs have
been strikingly shown to interact with MM cells to induce tumor cell growth and
survival [135]. Nonetheless, DCs remain a major target for immunotherapeutic
intervention in MM [136].
While DC considerations in MGUS and MM have relevance to understanding
many aspects of immune response to vaccination against infection, in relation to
T-dependent B-cell responses in germinal canters, it is the follicular DC specialized
subset that is important in generating B-cell memory, coupled with TFH cells
[137]. As yet, disease impact on these secondary lymphoid organ immune cell
interactions has not been investigated in MGUS or MM.
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CHAPTER 2
NK Cell Function
Natural killer cells have a role in immune response to viral infection [138, 139],
and interface with adaptive immunity. They also play an important role in initial
immune response to tumor cells, but as yet there is no concrete evidence for a
surveillance and anti-tumor role for NK cells in response to the premalignant clone
in MGUS. Increased numbers of NK cells have been described in MGUS, in newly
diagnosed MM and in low tumor burden MM [140–142]. NK cell function is intact in
the setting of MGUS and newly diagnosed MM. However, NK cytotoxicity against
MM decreases as disease progresses [140, 141, 143]. The downregulation of NK
cell activating receptors NKG2D, NKp30, and CD244 in MGUS and MM in the
bone marrow niche but not in the circulation suggests a possible mechanism of
immune escape of the tumor clone [144]. MHC I molecules are critical determinants
of NK cell activity. The expression levels of MHC class I polypeptide-related chain
A (MICA), a soluble ligand of NKG2D is increased on plasma cells in MGUS and
is strongly expressed in advancing disease in MM [145]. However, the soluble
NKG2D ligand, MICA, shed by MM cells as disease progresses, as a result of
the upregulation of ERp5 [146] down-regulates NKG2D on effector NK cells.
NKG2D levels are diminished in MM with MICA shedding, which contributes to
immune suppression [146, 147]. Normal to increased lytic activity of peripheral
blood, NK cells have been described in MGUS but in MM with MICA shedding
NK activity is decreased [146]. The immunomodulatory agents thalidomide and
lenalidomide have been reported to enhance NK cell cytotoxicity against MM cells
[148], highlighting an aspect of current therapy that appears to potentiate immune
capacity in disease, and increased NK cells are also seen in the peripheral blood
of patients that respond to therapy [149].
The Immunosuppressive Microenvironment of MM
A number of factors induce the immunosuppressive microenvironment that
promotes tumor survival in MM and simultaneously induces immune dysfunction.
Immunosuppressive factors include increased levels of IL-6, IL-10, IL-15, and TGF[150]. They reduce anti-tumor immunity by suppressing NK cell cytotoxicity, and
IL-10 and IL-6 have been implicated in DC dysfunction, as discussed above [115,
129]. TGF- also has a central role in inhibiting IL-2-induced T cell proliferation
[151]. Vascular endothelial growth factor (VEGF) is an important cytokine in the MM
microenvironment as it not only promotes the secretion of IL-6 but also the growth
and migration of MM cells [152]. Specific tumor adaptations in MM cells mediate
immunosuppression. Cyclooxygenase-2 (COX-2) overexpression by MM cells,
which correlates with poor outcome, is also implicated in suppressing macrophagemediated or T-cell-mediated tumor killing [153]. For effective therapy against
infection, a combinational approach is required: tailored vaccination together with
strategies to combat the immunosuppressive MM microenvironment.
IMMUNE DEFECTS IN THE RISK OF INFECTION AND RESPONSE TO VACCINATION...
39
HUMORAL IMMUNE RESPONSE TO INFLUENZA,
PNEUMOCOCCAL, AND HIB VACCINATION IN MM
Vaccination Following Chemotherapy
Patients with MM undergoing chemotherapy are at an increased risk of contracting
influenza, but it remains uncertain as to whether these patients are able to mount
sufficient immune response to benefit from vaccination. Previous studies have
shown heterogeneous responses to influenza vaccination in myeloma (discussed
below). A comparison of studies of immune response to influenza vaccination
is limited by differences in read-outs used to interpret response to vaccination.
Most studies measure antibody levels by the hemagglutinin inhibition (HI) test,
and responses are defined as ≥2.5-fold rise HI after vaccination. Seroconversion is
defined as a ≥4-fold rise in titer and seroprotection as a titer of at least 1:40 [154,
155]. Vaccination against influenza in MM is still a matter of clinical uncertainty, in
part as knowledge about the protective efficacy against clinical disease (influenza)
itself is limited, especially in aging. Controlled studies in MM evaluating influenza
vaccination with clinical endpoints (contracting influenza and severity of infection)
are lacking. Despite this clinical uncertainty, influenza vaccination is recommended
in MM patients.
In a study of MM patients the results of influenza vaccination were disappointing
as only 10% achieved protection against two viral strains and 19% developed
protective antibody titers to all three strains in the vaccine [156]. Comparable
observations were noted in another study of 70 patients with hematological
malignancies of which 16 were MM cases, and of the 70 only 4 responded, but
none were MM, to achieve seroprotection to all 3 viral strains [157]. Moreover,
two doses of influenza vaccine failed to improve antibody response to influenza
vaccination in patients with hematological malignancy undergoing therapy
or with recently discontinued therapy as the response rate did not increase
following a second booster dose of the vaccine [158, 159]. Overall, the booster
influenza vaccination strategy failed to increase the antibody response in
immunocompromised patients.
Notwithstanding these observations, patients with hematological malignancies,
even under treatment, can mount protective immune responses against influenza
vaccination. Indeed, in a study of 34 patients with chronic lymphoproliferative
disorders and MM, some receiving therapy, response rates were comparable to
healthy controls [160]. More than 60% achieved seroprotective responses to all
three viral strains, and of the six patients with MM, three developed seroprotection
to all three viral strains. However, these studies were limited by the low number
of subjects and by patients on diverse therapy with varying dosage intensity. This
precluded detection of a relation between response to vaccination and disease
state and stage and also the relation between vaccination response and treatment.
2
40
CHAPTER 2
Initial studies in the early 80s that utilized the 14-valent pneumococcal
capsular polysaccharide vaccine showed that MM patients responded poorly to
immunization. The antibody concentrations to 12 of the 14 polysaccharides in
the vaccine were simultaneously measured by radioimmunoassay. Radiolabeled
polysaccharides were incubated with sera and the resulting antigen–antibody
complexes were precipitated and quantified with a scintillation counter as
nanograms of antibody protein nitrogen/milliliter [161]. The interpretation of an
adequate response to the 14-valent pneumococcal vaccine was variable since the
antibody concentrations needed for protection were difficult to define [162]. Low
levels of antibody were reported to pneumococcal capsular polysaccharides before
and after vaccination in MM patients, significantly lower than those in healthy
controls [163–165]. Lazarus et al. showed that in MM patients before vaccination,
the grand geometric mean antibody concentrations for all serotypes combined was
91 ng/mL, which is less than their presumed protective level of 215 ng antibody
nitrogen/mL [165]. Following vaccination, the grand geometric mean antibody
concentration remained significantly lower in MM than in healthy controls (91 versus
820 ng antibody nitrogen/mL). Thirty percent of the patients had an antibody
response that might be protective for half of the vaccine serotypes. Geometric
mean titers >215 ng antibody nitrogen/mL developed only for serotypes 3, 18C, and
23F. Similarly, Schmid et al. observed antibody titers >200 ng antibody nitrogen/
mL only for serotypes 1, 4, 18C, and 23F in myeloma patients [163]. A study of
42 MM patients reported immunization responses that were inferior to those of
HCs and the low anti-pneumococcal titers correlated with risk of serious infection
[166]. MM patients with IgG M-protein were shown to have lower antibody titers
compared to those with IgA or Bence Jones MM. In line with these observations,
Schmid et al. also showed that patients with IgA MM consistently responded with
higher antibody titers than IgG MM and had higher increases in levels of antibodies
after pneumococcal vaccination [163]. These studies indicate that generation of
antibodies to pneumococcal capsular polysaccharide vaccination is impaired.
This may be because pneumococcal polysaccharides are particularly weakly
immunogenic in the immune suppressed state of these patients. Polysaccharide
vaccines are more immunogenic when conjugated to a carrier protein (discussed
above). However, MM patients elicit sub-protective to protective antibody responses
to Hib polysaccharide conjugate vaccination: Nix and colleagues reported that 45%
of MM had protective in comparison to 97% HC while 75% of MM patients had
protective titers in a study by Robertson and colleagues [156, 167]. A more recent
study utilizing the currently used 23-valent pneumococcal vaccine reported that
the response to pneumococcal vaccination was again disappointing, with 56%
having a fourfold rise in titer and 39% achieving protective antibody titers 4–6
weeks after vaccination [156]. These responses to adjuvant in conjugated vaccine
flag up deficiencies in pre-requisite Th responses in MM.
IMMUNE DEFECTS IN THE RISK OF INFECTION AND RESPONSE TO VACCINATION...
41
Transplantation
Ablative chemotherapy followed by bone marrow transplantation generally results
in an acute immunosuppression in both arms of innate and adaptive immune system
that lasts for several months, resulting in a protracted functional recovery. B-cell
reconstitution after hematopoietic stem cell transplantation (HSCT) is slow, with
B cells reaching normal levels 4–8 months post-transplant [168, 169]. Re-population
of T cells is also prolonged (170], appearing as abnormal subpopulations that
show an inverted CD4/CD8 ratio [171, 172]. The prolonged and severe immune
suppression following autologous and allogenic stem cell transplantation not
only compromises immunity and pose a risk for infection but also results in poor
responses to vaccination [173–175]. Impaired antibody responses to influenza
have been demonstrated in this setting [159, 176], however, a longer transplant
to vaccination interval is associated with better serological responses. Similarly,
poor responses to pneumococcal vaccination prior to transplant [177] as well as
vaccination after transplant have been reported [173, 178, 179].
In a randomized Phase 1/2 study in advanced MM undergoing high-dose
mephalan and autologous stem cell transplantation (ASCT), post-transplant
conjugate pneumococcal vaccination resulted in no or low antibody responses
and did not increase after booster vaccination [180]. However, vaccination before
transplant together with the adoptive transfer of T-cells early after transplant
followed by booster vaccination resulted in robust and sustained antibody
response as well as accelerated T-cell recovery [180]. This achieved protective
titers against four serotypes (6B, 14, 19F, and 23F) in 60% of cohort as compared
to 18% when there was no vaccination. In another study of MM, autologous T cell
transfer resulted in poor or no influenza vaccine responses unless the patient had
received influenza vaccination prior to autologous T-cell collection [181]. Clearly,
the priming of the autologous T cells by pre-transplant vaccination most likely
enhances antigen-specific antibody induction following transfer.
These studies demonstrate that a T-cell adoptive transfer can accelerates the
numerical and functional recovery of CD4+ and CD8+ T-cells that may provide
help in restoring humoral immunity in MM. Strategies to enhance lymphocyte
recovery and function (both B- and T-cell) in a transplant-associated therapeutic
intervention could further improve outcome in achieving protective serological
and cellular immunity to infectious agents in MM.
A detailed summary of the many strategies that have been assessed to date in
vaccination against infection in MM is compiled in Table 1.
Conclusion and Future Directions
Immunosenescence in aging compounds immune function in MGUS and MM, which
incrementally deteriorates as disease progresses to symptomatic phase. Focusing
on humoral immunity, as this is a pre-requisite to counter infection in these disease
2
CHAPTER 2
Table 1. Results of studies of the efficacy of influenza, pneumococcal and Hib vaccination
in multiple myeloma (Continued)
Influenza
Vaccine
Pneumococcal
42
Study
Study design
Number of patients
Myeloma Treatment
(Robertson
et al., 2000)
MM (n=48)
IFN / chemotherapy/ high-dose MP/total
body radiation + autologous stem cell
transplantation 6 months before
(Rapezzi et
al., 2003)
MM (n=6)
CLL (n=13)
NHL (n=7)
HD (n=8
MP + Prednisone/ MP + Prednisone+ VAD
(Stadtmauer
et al., 2011)
MM (n=21)
High-dose MP+ autologous stem cell
transplantation
(Lazarus et
al., 1980)
MM (n=13)
BCNU+ Adriamycin/ MP+ Prednisone/
cyclophosphamide/ BCNU+ Prednisone+
cyclophosphamide/ MP+ Adriamycin+
vincristine
(Schmid et
al., 1981a)
MM (n=37)
HC (n=10)
MP + prednisone/ vincristine+
cyclophosphamide + prednisone (and
doxorubicin/ MP) or another combination of
3 or more/
No chemotherapy for at least 3 months
before vaccination
(Hargreaves
et al., 1995)
MM (n=41)
HC (n=62)
MP/ MP+ Adriamycin+ BCNU+
cyclophosphamide/ Vincristine+
cyclophosphamide+ MP+ prednisone/
vincristine+ BCNU+ Adriamycin+ prednisone/
vincristine+ adriamycin+ dexamethasone/
vincristine+ adriamycin+ MP+ prednisone
(Robertson
et al., 2000)
MM (n=48)
IFNá/ chemotherapy/ high-dose MP/total
body radiation + autologous stem cell
transplantation 6 months before
(Rapoport
et al., 2005)
MM (n=42)
High-dose MP + autologous stem cell
transplant
(Hinge et al.,
2012)
MM (n=60)
High-dose MP + autologous stem cell
transplantation
IMMUNE DEFECTS IN THE RISK OF INFECTION AND RESPONSE TO VACCINATION...
Measure
of efficacy
Response
Conclusions
GMT,
Titers
≥1: 40
Poor response. 19% achieved
seroprotection and 59% had no
seroprotective levels to any of the
3 strains
Poor responses and patients are
susceptible to infections with influenza
GMT,
Titers
≥1: 40
Seroprotection rates achieved by more
than 60%. Of the patients 3 of 6 MM
achieved seroprotection rates
Vaccination is well tolerated and safe in
CLPD and MED MER
GMT,
≥4 fold rise
in titers
Primed subjects had significantly higher
GMT at all times
73% of primed subjects had
seroconversion to any of the 3 vaccine
strains and only 30% of unprimed
subjects
Transfer of influenza-primed autologous
T cells after transplantation improves
subsequent vaccine responses
GMT,
Poor response. 30% achieved protective
≥2 fold rise
response to 6 or more serotypes
in titer
Antibody response is depressed.
Advisable to vaccinate patients as
response was highly variable
GMT
At least 2 fold increase in titers to at least
≥2 fold rise
8 antigens in 43% compared to 100%
in titers
HC. Poorer response in those receiving
multi-agent (≥3) chemotherapy
Very low antibody titers before and
after vaccination but as response was
heterogeneous vaccination can be
offered
GMT,
≥2 fold rise
in titer
Poor response
45% achieved protective titers
Poor response associated with
increased risk of septicemia
GMT
titers≥
1:640
39% achieved protective titers
Poor responses, likely to be poorly
sustained. Repeat vaccination is
desirable
GMT
60% of pre-transplant vaccination+
post-transplant T cell infusion recipients
achieved protective titers.
18% of post-transplant vaccine & pretransplant+ late T cell infusion recipients
achieved protective titers
Early adoptive T cell transfer
followed by post-transplant
booster immunization improves
immunodeficiency. Pre-transplant
vaccination regime superior to posttransplant vaccination regime
GMT
Titers
≥1: 40
Poor response. 33% responded
Reasonable to vaccinate patients with
disease control (responding well to
induction therapy) as they have higher
response rate
43
2
CHAPTER 2
Table 1. Results of studies of the efficacy of influenza, pneumococcal and Hib vaccination
in multiple myeloma (Continued)
Vaccine
Hib
44
Study
Study design
Number of patients
Myeloma Treatment
(Robertson
et al., 2000)
MM (n=46)
IFNá/ chemotherapy/ high-dose MP/total
body radiation + autologous stem cell
transplantation 6 months before
(Nix et al.,
2012)
MM (n=20)
Chronic renal failure
(n=59)
Diabetes mellitus (n=30)
HC (n=32)
Intermittent chemotherapy
CLPD, Chronic lymphoproliferative disorders; HC, Healthy controls; HD, Hodgkin disease; MP, mephalan;
NHL, non-Hodgkin Lymphoma; VAD, vincristine-adriamycin-dexamethasone
settings, it is evident that a complex array of factors underlies a diminution of
immune capacity. This is manifest as both numerical imbalances in B-cell and
T-cell populations, and in impaired lymphocyte functionality; the immunological
synapse and cross-talk between these two key immune players is not fully defined
yet in MGUS or MM, and remains a key area for further investigation. Clonal
expansions in MGUS and MM directly compete with niche space for long-term
memory of infection, affecting polyclonal normal plasma cells in the bone marrow.
Direct immunosuppression by tumor cells, including via cytokine imbalance and
other mechanisms such as aberrant ligand expression to block NK cell activity,
further affect the capacity of the immune system to mount effective challenge
to infection, or to vaccination aimed at enhancing immunity to both viral and
bacterial agents. Because of the morbidity and mortality that follow infection
in MM, clinical therapy still aims at vaccinating against specific bacterial threats.
Mounting effective immunity to capsular polysaccharide infection-related antigens
for instance, has as yet not been optimized although linking antigen to T-cell
recruiting adjuvant is a notable advance. The complications generated directly by
therapeutic drugs that weaken the immune response must be understood further,
to select the best strategy to restore anti-infection immunity in MM. Conversely,
use of immunomodulatory drugs in MM will need further investigation in how
to best harness their pro-immune function during vaccination against infection.
Exploiting transplantation in therapy by prior vaccination to educate T-cells to
enhance humoral response to vaccination is indicative of the types of strategy that
can be utilized to counter infection. It is also highly likely that current advances
in understanding how aging in the normal healthy population affects immune
responses will be exploited in developing the best strategies to institute immunity
against infection in MGUS and MM.
IMMUNE DEFECTS IN THE RISK OF INFECTION AND RESPONSE TO VACCINATION...
Measure
of efficacy
Response
Conclusions
≥1.02µg/L
75% protective titers and 41% had a ≥4
fold increase in titers
Specific immunity comparable to HC.
>0.15µg/
mL
45% MM achieved titers that correlate
to natural protection in comparison to
97% HC
Lack of protective immunity against
Hib in MM. Increased risk of invasive
disease is a rationale for immunization
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any
commercial or financial relationships that could be construed as a potential conflict
of interest.
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2
CHAPTER
IgG antibody and TH1 immune responses to
influenza vaccination negatively correlate
with M-protein burden in monoclonal
gammopathy of undetermined significance
Sarah M. Tete, BSc1. 2, Kasper R. Wilting, MD3, Gerda Horst, BSc1,
Michiel A. Klijn, MD4, Johanna Westra, pHD1, Aalzen de Haan, pHD5,
Anke L.W. Huckriede, pHD5, Hanneke C. Kluin-Nelemans, MD pHD6,
Surinder S. Sahota, pHD2, Marc Bijl, MD pHD7, Nico Bos, pHD1
1
Department of Rheumatology and Clinical Immunology, University of
Groningen, University Medical Center Groningen, Groningen, Netherlands;
2
Cancer Sciences Division, University of Southampton School of Medicine,
Southampton, UK;
3
Department of Medical Microbiology, University of Groningen, University
Medical Center Groningen, Groningen, Netherlands;
4
General Practitioners Practice, Huisartsen Boterdiep, Groningen,
Netherlands;
5
Department of Medical Microbiology, Molecular Virology section,
University of Groningen, University Medical Center Groningen, Groningen,
Netherlands;
6
Department of Hematology, University of Groningen, University Medical
Center Groningen, Groningen, Netherlands;
7
Department of Internal Medicine and Rheumatology, Martini Hospital,
Groningen, Netherlands
Tete et al, Hematology and Leukemia 2013, 1:3
3
58
CHAPTER 3
ABSTRACT
Background
The emergence of non-malignant conditions such as monoclonal gammopathy
of undetermined significance (MGUS) in the elderly may further alter their
increased susceptibility to infections, however this remains poorly defined.
The immune response to influenza vaccination has not been examined in
MGUS, a benign plasma cell monoclonal expansion in the bone marrow that
secretes elevated levels of monoclonal immunoglobulin (M-protein). Preexisting antibody titers to infectious agents can be depressed, but the degree
of immunosuppression in response to active vaccination remains unclear.
Furthermore, the association of M-protein levels with impaired antigen
specific response has not been examined to date in MGUS.
Methods
We investigated antibody as well as T cell responses in 19 MGUS patients
and age-matched healthy controls following influenza vaccination. H1N1
and H3N2 influenza-specific IgG antibodies were measured by ELISA. The
frequencies of H1N1 and H3N2 specific IFN- secreting cells were measured
by ELISpot.
Results
Polyclonal isotype-switched immunoglobulin levels were significantly
reduced in the MGUS cohort (p<0.05). At the cohort level, HIN1 and H3N2
influenza-specific IgG titers were comparable in MGUS and HCs. However,
a key distinction emerged in relation to M-protein levels. MGUS patients
with high M-protein had decreased influenza specific IgG titers which they
failed to expand post-vaccination. Low M-protein MGUS H1N1-specific IFNresponses were high and comparable with HCs but showed no discernible
increase post-vaccination, while cellular responses to H1N1 in high M-protein
MGUS were markedly reduced.
Conclusions
Overall, MGUS showed depressed immune responses to influenza vaccination
that varied strikingly with M-protein levels.
IgG AND TH1 RESPONSES CORRELATE WITH M-PROTEIN BURDEN
59
INTRODUCTION
Monoclonal Gammopathy of undetermined significance (MGUS) is a pre-malignant
condition that mainly affects the elderly. It is characterized by the clonal proliferation
of plasma cells resulting in the observed monoclonal protein (M-protein). It is
diagnosed by presence of M-protein in the serum at levels <30g/L, bone marrow
plasma cell infiltration of <10% and no clinical manifestations of organ damage
or the presence of a B cell malignancy. MGUS is associated with a lifelong risk of
progression to multiple myeloma or other related malignancy at a rate of 1% per
year [1].Multiple myeloma is a plasma cell proliferative disorder which features a
reduction in polyclonal immunoglobulin levels and more profound B cell dysfunction
than MGUS. Infections are a leading cause of morbidity and mortality and their
spectrum has been reported to change subsequently relative to disease activity
and immunosuppressive treatment that leaves the patients immunocompromised
[2]. Recent studies have shown that myeloma is almost always preceded by MGUS
therefore establishing a key role for MGUS in the pathway to myeloma [3, 4].
The increased susceptibility of myeloma patients to infections has been assessed
extensively [5-7], however the risk of infections in MGUS has been less well studied.
An increased risk of bacterial as well as viral infections has been described in
a small number of studies [8-10]. MGUS also has variable consequences on the
immune system. Polyclonal immunoglobulin levels are normal or reduced in
MGUS but the degree of immunosuppression, if present at all, is unknown and
therefore it is unclear whether patients with MGUS have compromised humoral or
cellular immunity. Whether the low polyclonal immunoglobulin levels and or high
monoclonal protein concentration are associated with impaired antigen specific
response has not yet been established in MGUS.
Both B and T cells are important in the immune response. Little is known
of the B cell function in MGUS, yet B cell function dysregulation in myeloma is
more profound and has a consequence on the immune response as the humoral
response to vaccination is hampered. Disturbances in the T cell compartment may
also result in impaired immune response, however these have been studied in less
detail in MGUS. Absolute numbers of CD4+ and CD8+ T cells were shown to be
comparable to healthy controls in MGUS [11]. Significantly increased frequencies of
CD4+CD25+FoxP3+ T reg cells in MGUS as well as treated and untreated myeloma
have been reported. These cells were shown to maintain their functionality as they
inhibited proliferation and IFN- production [12, 13].
Influenza has a high incidence and vaccination reduces the morbidity
and mortality caused by influenza virus infection. Influenza vaccination is
recommended for individuals in high-risk groups including the elderly and
immunocompromised [14]. As MGUS is more prevalent with increasing age,
a substantial number of the patients fall under the high-risk group of elderly
3
60
CHAPTER 3
individuals, so they receive seasonal influenza vaccination. Whether this
vaccination is effective is unknown.
Therefore, we devised a prospective study to investigate the impact of
monoclonal protein on the humoral and cell-mediated immune responses in MGUS
patients following vaccination with a trivalent subunit influenza vaccine in order to
analyze whether MGUS monoclonal protein burden is associated with functional
deficits of the immune system. MGUS patients show suboptimal response to
vaccination with M-protein concentration impacting their response.
METHODS
Patients and controls
Patients that were known with MGUS at the University Medical Centre Groningen
hematology department were included in the study when they fulfilled the standard
diagnostic criteria for MGUS: serum M protein levels <30g/L, clonal plasma cells in
bone marrow <10% and no myeloma related dysfunction or other B-cell proliferative
diseases [15]. Patients were excluded if they had current infection, defined as fever
in combination with clinical focal signs of infection and the need for therapeutic
antibiotic treatment, influenza vaccination within the 6 months prior to the study,
pregnancy or malignancy. The duration of MGUS varied between patients from 1
till 19 years since diagnosis. Persistent monoclonal proteins were detected in all
MGUS patients.
For control purposes, sex and age matched healthy individuals who had no
co-morbidities or malignancy, condition associated with immune dysfunction or
use of immune modulating drugs were included parallel to the MGUS patients.
The healthy controls were recruited from the populations visiting general physician
practice for yearly vaccination. Healthy controls with monoclonal protein in their
serum were excluded. All participants included gave written informed consent
in accordance with the Declaration of Helsinki. The institutional medical ethics
committee of University Medical Centre Groningen approved the study.
All MGUS patients and controls were vaccinated between October 2010 and
January 2011. They received an intramuscular injection of the influenza vaccine
(InfluvacÒ, Solvay Pharmaceuticals, Netherlands). The vaccine, a subunit preparation
of licensed 2010-2011 trivalent inactivated virus, contained A/California/7/2009
(H1N1), A/Perth/16/2009 (H3N2) and B/Brisbane/60/2008. Information on influenza
vaccination in the previous years was obtained. Local and systemic adverse
reactions for up to 7 days post vaccination were recorded by participants using a
standard questionnaire which included the reporting of pain, itching, induration at
site of injection, fever, myalgia and flu-like symptoms. No serious adverse reactions
were observed.
IgG AND TH1 RESPONSES CORRELATE WITH M-PROTEIN BURDEN
61
Evaluations
At study entry, baseline standard laboratory parameters were measured; complete
blood counts including leukocyte differentiation, lymphocyte subsets (CD3+, CD4+,
CD8+, CD19+ cells) and total IgM, IgA and IgG immunoglobulin levels. Normal
ranges of serum immunoglobulins in our lab were defined as: 7-16 g/L IgG,
0.7-4 g/L IgA and 0.4-2.3 g/L IgM. The presence of a monoclonal immunoglobulin
was determined by immunofixation.
Further venous blood samples were obtained at the day of vaccination (day 0),
7 days and 28 days post-vaccination. Serum was separated by centrifugation and
stored at -20°C until further analysis. Peripheral blood mononuclear cells (PBMCs)
were isolated by density gradient centrifugation of CPT vacutainer tubes (BD)
drawn venous blood immediately after venipuncture. PBMCs were then frozen
in RPMI 1640 (Cambrex Bioscience, Verviers, Belgium) supplemented with
10% human pooled serum, 50 µg/mL gentamicin (Gibco, Paisley, UK) and 10%
dimethylsulfoxide(Merck, Germany). PBMCs were stored in liquid nitrogen until
further use.
Measurement of anti-influenza IgG antibodies by ELISA
The levels of anti-influenza specific IgG antibodies to A/H1N1 and A/H3N2 were
determined by an in-house ELISA. In short, ELISA plates (Coaster) were coated with
1 µg/ml subunit of A/H1N1 and A/H3N2 and subsequently incubated with serum
samples collected at day 0, day 7 and day 28 following vaccination. The detection of
influenza-specific antibodies was done with mouse anti-human IgG-HRP (Southern
Biotech, USA), followed by incubation with TMB substrate (Sigma). Absorbance
at 450nm was read with an Emax microplate reader and antibody concentrations
calculated by SOFTmax PRO software (Molecular Devices, Sunnyvale, USA). For a
standard curve, a dilution series of human IgG standard, N protein (Siemens) was
used on every plate and the antibody contents of the samples were read from the
linear part of the sigmoid curve.
IFN- ELISpot
Pre and post vaccination PBMC samples from MGUS patients and matched healthy
controls were simultaneously thawed and further analysed. Viability was evaluated
by trypan blue staining and then the thawed PBMCs were incubated overnight
at 37°C before proceeding with the ELISpot assay. Before plating, the cells were
counted using an automated cell counter (Beckman Coulter, Fullerton, CA, USA).
96 well filtration plates (MAISPWU10, Millipore, Ireland) were coated overnight
at 4°C with 100µl of 15µg/mL anti-human IFN- (Mabtech, Nacka Strand, Sweden).
Plates were subsequently washed and blocked for 2 hours at 37°C with culture
medium (RPMI 1640 supplemented with 10% fetal calf serum and 50 µg/mL
gentamycin). 200, 000 PBMCs were added per well in duplicates and in combination
3
62
CHAPTER 3
with different stimuli to make up a volume of 200µL/well and incubated at 37°C/5%
CO2. -propiolactone inactivated whole virus (WIV) of A/California/7/2009 (H1N1)
and A/Perth/16/2009 (H3N2) at a final concentration of 2 µg/mL was used to
stimulate the PBMCs. Concanavalin A at 2.5 µg/mL was used as a positive control
while PBMCs in culture medium alone were used as a negative control. Following 48
hour incubation and washing the plates once with phosphate buffered saline (PBS),
secreted cytokine was detected with 50 µL of 1 µg/mL biotinylated anti-human
IFN- (Mabtech). After incubating the plates at room temperature for 3 hours,
the plates were washed again and 100µL/well of 1:1 000 diluted streptavidinalkaline phosphatase (Mabtech) was added and incubated for 1.5 hours at room
temperature. Plates were then subsequently washed and developed with 100 µL/
well BCIP/NBT plus substrate (Mabtech) for 15 minutes before washing the plate
under tape water and analysing on an ELISpot reader (automated-video-analysis
system, Sanquin, Amsterdam, Netherlands)
Statistical analysis
Data were analysed with Graphpad Prism 4 (Graphpad software Inc.). Mann-Whitney
U test, Wilcoxon signed rank test and Fisher’s exact test for categorical data were
used as appropriate. For correlations, Spearman’s rank correlation coefficient was
used. P-values < 0.05 were considered statistically significant.
RESULTS
A total of 19 MGUS patients gave informed consent and were included; their
median age (range) was 66 (49-81) and 63% were male. They also had a similar
vaccination history to healthy controls, with the majority of the participants having
been vaccinated in the preceding influenza season. Ninety percent of the patients
were vaccinated against influenza the previous year compared to 79% of healthy
controls. The study demographics are shown in Table 1.
The concentration of M-protein varied from unquantifiable levels to 24.8g/L.
M-protein was detected by immunofixation but was unquantifiable in 8 patients
by serum protein electrophoresis because the concentration of the M-protein was
small or the M-protein migrated in the fraction. It has been recently shown that
MGUS patients with unquantifiable M-protein are qualitatively similar to MGUS with
quantifiable M-protein as they have persistent M-protein and also progress to plasma
cell malignancies at a similar rate [16]. Significantly reduced relative numbers of
CD19+ B cells were observed in the MGUS cohort compared to the healthy controls
(p=0.05). Significantly reduced serum levels of non-involved polyclonal IgG (p=0.023)
and IgA (p=0.027) but not IgM (p=0.08) immunoglobulin were also observed for the
MGUS cohort compared to the healthy controls. A proportion of MGUS patients
(8/19; 42%) exhibited subnormal serum polyclonal IgG levels (< 7g/L) (Table 1).
IgG AND TH1 RESPONSES CORRELATE WITH M-PROTEIN BURDEN
63
Table 1. Baseline characteristics of MGUS patients and controls
Healthy Controls
(n=19)
MGUS
(n=19)
P-value
63.7 (8.39)
65.9 (7.56)
NS
11/8
12/7
NS
15 (78.9)
17 (89.5)
NS
lymphocytes (10E9/L), median (range)
1,77 (1,05-3,52)
1,82 (1,2-3,13)
NS
CD3 (x10 /L), median (range)
1,26 (0,70-2,68)
1,36 (0,71-2,3)
NS
CD4+ (x109/L), median (range)
0,84 (0,55-1,55)
0,82 (0,44-1,49)
NS
Age (years), mean (SD)
Sex (male/female)
Vaccination 2009/2010, N. (%)
+
9
CD8 (x10 /L), median (range)
0,44 (0,09-0,71)
0,47 (0,12-1,09)
NS
CD19+ (x109/L), median (range)
0,21 (0,07-0,63)
0,14 (0,01-0,36)
¥
+
9
CD16 /CD56 NK (x10 /L), median (range)
0,37 (0,11-0,98)
0,26 (0,12-1,03)
NS
monocytes (x109/L), median (range)
0,49 (0,27-0,98)
0,48 (0,26-0,84)
NS
Immunoglobulin G (g/L), median (range)
11.18(6.9-14.7)
7,5 (4,3-14,7)
<0.05
Immunoglobulin A (g/L), median (range)
1.95 (0.70-4.30)
0,85 (0,1-2,6)
<0.05
Immunoglobulin M (g/L), median (range)
1 (0,40-1,70)
0,7 (0,1-1,7)
NS
Monoclonal protein size (g/L), median (range)
NA
10.7(0.01-24.8)
+
+
9
Non-involved immunoglobulins
Monoclonal protein isotype, N (%)
IgG
10 (53)
IgA
5 (26)
IgM
4 (21)
NS, not significant; ¥, significant decrease in CD19+ cells relative numbers, p<0.05; NA, not applicable
Monoclonal protein load correlates with influenza-specific H1N1 IgG
responses
To determine vaccine-specific antibodies, we assayed the serum concentration
of IgG antibodies to H1N1 and H3N2 using ELISA. Before vaccination, influenzaspecific IgG titers to H1N1 and H3N2 strains were comparable and did not differ
significantly in both the healthy controls and MGUS. A significant response to both
the H1N1 and H3N2 strain was observed both in healthy controls and MGUS at day
7 and this response was also sustained at day 28 (Figure 1). We examined whether
the magnitude of the influenza specific IgG antibody response after vaccination
was associated with the monoclonal protein size. A negative relationship was found
between the level of M-protein and influenza-specific IgG titers whereby high
levels of M-protein were associated with depressed influenza H1N1 specific IgG
titers post-vaccination. An inverse correlation between M-protein levels and H1N1-
3
64
CHAPTER 3
Figure 1. Influenza-specific IgG response in HC and MGUS. H1N1 and H3N2-specific IgG titers
for HC (n=19) and MGUS (n=19) at day 0, 7 and 28. Bars and error bars denote group median and
interquartile range. *p<0.05; ** p<0.01; *** p<0.00
specific IgG titers was observed at day 7 (p=0.02, spearman’s r=-0.51) and day 28
(p=0.0123, spearman’s r=-0.56) (Figure 2A).
To further assess how high M-protein concentration affects the kinetics
of the influenza specific response, subjects were further stratified into two
groups according to their concentration of M-protein; low M-protein and high
M-protein. We used a cut-off concentration for low M-protein MGUS of <15g/L,
as monoclonal protein concentrations of ≥15g/L have been described as a risk
factor for progression to myeloma [15, 17]. The levels of prevaccination influenza
specific IgG titers were significantly lower in the high M-protein group and the
antibody levels post-vaccination remained depressed in high M-protein MGUS.
As a group, the low M-protein MGUS patients showed significantly increased
influenza specific IgG levels to H1N1 at day 7 (p=0.002) and day 28 (p=0.002)
but high M-protein MGUS did not show a significant difference in titers pre and
post-vaccination (Figure 1B). Similar responses were observed for H3N2 where
low serum M-protein was associated with significantly increased H3N2 specific
IgG response at day 7 (p=0.0007) and day 28 (p=0.0002). On the other hand, in
patients with high M-protein levels no discernible increase in H3N2 specific IgG
levels at both day 7 and day 28 occurred. (Figure 2B).
Next, we assessed whether having an IgG MGUS was associated with lower
responses compared to other isotypes. Patients were further stratified according
to whether they had IgG M-protein or non-IgG (IgA and IgM). Patients with an IgG
MGUS had similar levels of H1N1 specific IgG compared to those with other MGUS
isotypes. However, for the H3N2 strain, IgG MGUS patients had significantly lower
titers prevaccination (p=0.0435). Even though they had a significant rise in titers at
day 28 their response was lower than that in non-IgG MGUS individuals (p=0.04)
(data not shown).
IgG AND TH1 RESPONSES CORRELATE WITH M-PROTEIN BURDEN
65
3
Figure2. High monoclonal protein concentration is associated with lower influenzaspecific IgG response. (A) Correlation curve for MGUS HIN1-specific IgG titers and monoclonal
protein concentration at day 7 (black square) and 28 (grey triangle) after vaccination. A linear
regression line is shown for the 2 time-points. Each symbol represents a single MGUS patient
(n=19). (B) Influenza-specific IgG titers for low (n=13) and high (n=6) monoclonal protein MGUS.
Low monoclonal protein is defined as concentrations <15g/L and High monoclonal protein
concentration as ≥15g/L. Bars and error bars denote group median and interquartile range
High M-protein levels are associated with lower numbers of IFNsecreting cells
Influenza specific IFN- secreting cells were identified in healthy control and MGUS
before vaccination. Their frequencies did not differ between the healthy controls
and MGUS patients for both the H1N1 and H3N2 influenza strains. A significant
rise in H1N1-specific IFN- secreting cells was observed at day 28 in the healthy
control group (Figure 3A). A significantly higher fold increase in IFN- secreting
cells was shown for healthy controls compared to the MGUS group who failed to
expand the numbers of H1N1-specific IFN- secreting cells (p=0.035) (Figure 3B).
Comparison of H3N2-specific IFN- secreting cells did not reveal any significant
expansions in numbers after vaccination within and between the healthy control
and MGUS groups (data not shown).
In order to assess whether monoclonal protein concentration has an influence
on influenza specific cell mediated responses, we computed correlations between
the concentration of M-protein and the number of influenza specific IFN- secreting
cells. High levels of M-protein were associated with lower IFN- responses than that
those in the MGUS cohort with low M-protein. The number of H1N1-specific IFNsecreting cells at day 28 was inversely correlated with monoclonal protein levels
(p=0.0182) with a Spearman’s rank correlation coefficient of -0.5812 (Figure 4A).
No correlations were observed for the H3N2 strain. In an analysis stratified by
M-protein concentration, levels ≥15 g/L were associated with significantly lower
66
CHAPTER 3
Figure 3. H1N1-specific IFN- response in healthy controls and MGUS. (A) IFN- secreting cells
in healthy controls (n=16) and MGUS (n=16) at day 0, 7 and 28 days post-vaccination. Bars and
error bars represent group median and interquartile range. (B) Healthy controls show a higher
fold increase in H1N1-specific IFN- secreting cells at day 28 compared to MGUS. Comparisons
were made using Mann-Whitney u-test. *p<0.05
number of IFN- secreting cells specific for the H1N1 strain but not for H3N2. The
number of IFN- secreting cells in high M-protein MGUS was significantly lower at
day 0 (p=0.0235) and at day 28 (p=0.0092) compared to the MGUS cohort with low
M-protein (< 15g/L) even though low M-protein levels were not associated with a
significant increase in IFN- secreting cells (Figure 4B)
DISCUSSION
This study shows that high M-protein levels in MGUS are associated with impaired
humoral and cell-mediated response to vaccination. The immune response
to influenza vaccination is influenced by factors such as age, host immune
defects as well as the type of vaccine administered [18-20]. The presence of
M-protein in the serum of MGUS patients is a consequence of the monoclonal
expansion of plasma cells and this could possibly affect humoral and/or cellular
immune response. Hypogammaglobulinaemia which is often associated with
myeloma, [21] is also associated with decreased immune responses. However
hypogammaglobulinaemia has been reported at a lower frequency in MGUS
[22-24]. The depressed humoral response seen in MGUS is partly reflected
by a diminished production of polyclonal immunoglobulins as displayed by a
large fraction of the patients. Our data demonstrated a decrease in polyclonal
immunoglobulin levels in MGUS and hypogammaglobulinaemia in 42% of the
patients. Whether such factors, together with the detected monoclonal protein
load, lead to a decrease in specific antibody production has not been investigated
IgG AND TH1 RESPONSES CORRELATE WITH M-PROTEIN BURDEN
67
3
Figure 4. The influence of M-protein on H1N1-specific IFN- response in MGUS. (A) Monoclonal
protein size is shown to correlate with the frequency of H1N1-specific IFN- secreting cells at day
28 post-vaccination in MGUS patients (n=16). When M-protein was detected but concentration
was too low to quantify, a value of 0.01 g/L was assigned. (B) H1N1 and H3N2-specific IFNsecreting cells in Low monoclonal protein MGUS (<15g/L) (n=11) and High monoclonal protein
MGUS (≥15g/L) (n=5). Bars and error bars denote group median and interquartile range. *p<0.05;
** p<0.01; *** p<0.001
before. Also of importance is the fact that MGUS predominantly affects the
elderly in whom further age-associated changes and decline in functioning of the
immune system have been described. These changes include a decrease in naïve
B cell generation, decrease in class switch recombination resulting in decreased
IgG production, altered balance of CD4+ T cell memory cells and decreased
T cell proliferative responses [25-28]. These age-associated changes result in the
consequentially observed increased risk of infection and reduced response to
vaccination [29, 30]. This should not bias our results as we specifically included
age-matched controls.
IFN- production described in our study following vaccination is presumably
a result of CD4+ T-cells and limited CD8+ T-cell help. Vaccination with subunit
trivalent inactivated vaccine leads to Th-cell help for antibody production but no
CTL responses [31]. The data from our study indicates that pre-existing influenza
specific IFN- secreting cells can be detected before vaccination in healthy
individuals as well as in MGUS. This could be because of previous encounter
with the virus and also previous vaccinations. Vaccination elicited a substantial
T cell response in healthy controls as a significant increase in IFN- secreting cells
was demonstrated whereas MGUS patients failed to expand the response. This
suggests that the protective role exerted by IFN- during secondary response
to influenza virus could be affected in MGUS, and this has consequences on
induction of antibody responses as well as delayed resolution of the immune
68
CHAPTER 3
response. It remains to be investigated whether the observed poor response could
also be partially due to quantitative and functional defects in T-cells. Defects in
the T-cell compartment, if present, may also contribute to the less favourable
vaccination responses, as T cell dependent B cell responses were poor.
Following influenza vaccination, secretion of influenza-specific antibodies
leads to a rise in serum antigen-specific antibodies. [32, 33] IgG antibodies are
the predominant antibody class induced after vaccination and increase till they
reach a peak 4 weeks post vaccination [34] [32, 35, 36]. Our results show that the
amount and, to a lesser extent, the type of M protein have a significant influence
in the development of influenza specific IgG antibodies after vaccination. High
M-protein MGUS patients had lower pre-vaccination influenza-specific IgG titers,
which they failed to increase post-vaccination. Furthermore, increasing M-protein
concentration was associated with decreased H1N1-specific IgG response in
MGUS. Therefore, poor post-vaccination influenza specific IgG antibody levels
observed in MGUS patients with high M-protein may predict response to influenza
vaccination. This suggests that these patients are likely to be less protected by
vaccination. Patients with IgG MGUS showed significantly lower H3N2-specific IgG
titers both pre and post vaccination compared to healthy controls. IgG M-protein is
associated with decreased polyclonal IgG production possibly due to suppression
of normal B cell differentiation. This then leads to attrition of the plasma cell
compartment therefore limiting the number of plasma cells specific for some
antigens. In vaccination studies with myeloma patients, IgG myeloma patients
had lower serological responses compared to those with IgA paraprotein or Bence
Jones [37]. In line with these observations, another study showed that patients with
IgA myeloma consistently responded with higher antibody titres and had higher
increases in levels of antibodies after pneumococcal vaccination compared to IgG
and IgM myeloma.[38].
A large population-based study in MGUS by Kristinsson et al describing
an increased risk of bacterial and viral infections that included influenza also
showed that higher M-protein concentrations at diagnosis were associated with
higher risks of infection [8]. Our results indicate that M-protein load has a great
influence on the response to vaccination. The reduced response observed in
MGUS may be a consequence B cell dysregulation that results in the M-protein
with high M protein being a probable marker of more profound underlying
B cell dysfunction. The high M-protein levels together with the consistently
observed accompanying hypogammaglobulinaemia are important factors that
influence the immune responses to influenza vaccination. We postulate that the
clonal expansion of plasma cells lead to decreased B cell repertoire diversity.
This alteration in repertoire consequently limits the number of cells available
to respond to antigenic challenge and therefore may contribute to decreased
humoral response. However no repertoire analysis has been carried out in MGUS,
IgG AND TH1 RESPONSES CORRELATE WITH M-PROTEIN BURDEN
but data in the elderly suggests that B cell diversity decreases with age and
the immunoglobulin repertoire diversity correlated with antibody response and
health status [39, 40].
Although there were similar absolute numbers of circulating CD19+ B cells
in healthy controls and MGUS patients, a decrease in the relative number of
B cells was observed in MGUS and this might have contributed to the hampered
responses. Other B cell subsets important in immune response and aging
that include naïve and memory B cells have not been studied [41-44]. There is
evidence suggesting that B cells not only function as antibody producers but
also as antigen presenting cells and are required for primary T-cell expansion and
differentiation [45]. This change in MGUS B cell frequencies observed in our study
could also result in insufficient help for T-cells therefore being consequential of
the impaired T-cell responses. Our study had some limitations in that the sample
size was small and the numbers of subjects in subgroups were low when stratified
for M-protein concentration as well as the type of M-protein. On the other hand,
showing such significant results in the relative low number of patients studied
suggest a strong effect for the high M-protein group. Larger studies are required
to confirm our findings. Our MGUS cohort is a heterogeneous group, ranging
from individuals with steady and low M-protein levels to those with increasing
and high M-protein levels inclined towards transformation to myeloma and other
B cell proliferative disorders therefore their degree of immunosuppression is
likely to vary.
In summary, MGUS patients displayed subnormal polyclonal immunoglobulin
levels. The presence of this hypogammaglobulinaemia together with M-protein
load has an influence on the humoral and cellular mediated immune response to
vaccination. Moreover, our results suggest that the level of M-protein may be a
predictor of poor vaccination response.
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CHAPTER
Hampered influenza-specific IgG B cell
responses whereas IgM and IgA responses
are maintained in monoclonal gammopathy
of undetermined significance
Sarah M. Tete1, 2, Melissa Newling3, Johanna Westra1, Aalzen de
Haan4, Marc Bijl5, Surinder S. Sahota2 and Nicolaas A. Bos1
1
Department of Rheumatology and Clinical Immunology, University of
Groningen, University Medical Center Groningen, Groningen, Netherlands;
2
Cancer Sciences Academic Unit, University of Southampton School of
Medicine, Southampton, UK;
3
Faculty of Medical Sciences, Biomedical Science, University of Groningen,
University Medical Center Groningen, Groningen, Netherlands;
4
Department of Medical Microbiology, Molecular Virology section,
University of Groningen, University Medical Center Groningen, Groningen,
Netherlands;
5
Department of Internal Medicine and Rheumatology, Martini Ziekenhuis,
Groningen, Netherlands;
(Manuscript in press)
4
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ABSTRACT
Introduction
Patients with monoclonal gammopathies frequently have deficient immune
function that is condition-related. The degree of this immune deficiency
increases with progression of disease. As a result, patients with monoclonal
gammopathies are prone to infections that include influenza virus. Monoclonal
gammopathy of undetermined significance (MGUS) patients with high
monoclonal protein elicit poor IgG responses to influenza vaccination.
Methods
We therefore investigated whether the poor influenza-specific IgG response
observed in MGUS translated to poor seroprotection rates in this cohort.
Furthermore, we analysed the memory B cell subsets in MGUS as well as
quantifying the influenza-specific memory B cells after administration of
trivalent inactivated influenza vaccine. Peripheral memory B cell subsets
were measured by flow cytometry and stimulated total and influenza-specific
memory B cells were detected using an enzyme-linked immunospot (ELISpot)
assay at day 0 as well as at day7- and day 28 post-vaccination.
Results
MGUS show low seroprotection rates (37%) with the Hemagglutination
inhibition (HI) response correlating with the lower H1N1-specific IgG titers.
The frequency of IgG+ cells in the IgD-CD27+ fraction at day 0 correlated
with the fold increase in HI titers as well as the H1N1-specific IgG titers at day
28 post-vaccination in HC suggesting a recall memory response. In contrast,
the frequency of the IgG+ cells in the IgD-CD27+ fraction is decreased at
baseline in MGUS. Furthermore, the frequency of influenza-specific IgG
memory B cells is significantly lower post-vaccination in MGUS in comparison
to HC, as measured by ELISpot.
Despite the poor IgG response, MGUS elicit significant IgM and IgA
antibody responses to influenza vaccination. However, the protective capacity
of these two antibodies is questionable in MGUS.
Conclusion
MGUS is associated with poor IgG memory response that is likely to impair
the long maintenance of serologic response.
HAMPERED INFLUENZA-SPECIFIC IgG B CELL RESPONSES
77
INTRODUCTION
As a precursor condition to multiple myeloma (MM), MGUS does not present with
clinical features of MM or other lymphoproliferative malignancies [1]. However, it is
characterized by monoclonal immunoglobulin <30g/L, normal to decreased levels
of IgG as well as by B lymphocyte percentages ranging from low to normal [2-4].
Additionally, there is increased susceptibility to infections in MGUS [5]. Furthermore,
immune responses to influenza vaccination vary with M-protein levels as MGUS
with high M-protein (>15g/L) has lower influenza-specific IgG titers which they fail
to expand post-vaccination [6].
Influenza vaccination-induced immunity is primarily antibody based, relying on
the activation of naïve B cells as well as the recall of memory B cells (MBCs) to rapidly
respond upon re-encounter with antigen. Clonally expanded B cells can differentiate
into MBCs or plasma cells that secrete antibodies at an increased rate as well as with
higher affinity for antigen [7]. Several subsets of MBCs have been identified based
of the expression of IgD and CD27: IgD-CD27+ classical memory switched (IgG+ or
IgA+) cells, CD27+ unswitched memory cells that predominantly express IgD and
IgM, but also IgM-only cells. Furthermore, IgD-CD27- (double negative (DN)) memory
B cells have been described. Although a definite origin of the different memory B cell
subsets remains to be established , it is proposed that isotype switched cells originate
from germinal center (GC) reactions while IgM memory may be early emigrants from
the GC which began participating in the GC reaction but exited before isotype
switching [8]. Alternatively, IgM memory may develop through GC-independent
pathways [9]. On the other hand, CD27+IgD+IgM+ cells may represent a recirculating
fraction of marginal zone B cells [10][9]. Mutated, isotype switched DN B cells contain
fewer somatic hypermutations in their immunoglobulin genes and have increased
IgG3 use, further distinguishing them from their CD27+ counterparts [11].
Characteristics of the B cell response, and predominantly the nature of
long-term B cell memory, are key determining factors of the protective capacity
of many vaccines. These MBCs are of importance when the protective efficacy
of a vaccine is largely determined by its ability to elicit a humoral response as in
influenza vaccination. Indeed, parenteral vaccination with the seasonal trivalent
inactivated vaccine induces systemic immune response on which protection is
based. The influenza-specific circulating antibodies induced by vaccination decline
within 6 months while longer-lasting MBCs pool remains to respond upon antigen
re-encounter, in so doing heightening resistance to infection [12][13].
There is limited data concerning the B cell response to influenza vaccination
in MGUS. We evaluated the peak effector responses by measuring antigenspecific titers by both ELISA and hemagglutination inhibition test. Furthermore,
we investigated whether the inferior response to influenza vaccination in high
monoclonal protein MGUS was associated with alteration in total as well as antigenspecific MBC responses to influenza.
4
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CHAPTER 4
METHODS
Study population
Patients were included in the study when they fulfilled the standard diagnostic
criteria for MGUS[14]. For control purposes, sex and age matched healthy
individuals were included parallel to the MGUS patients. Healthy controls with
monoclonal protein in their serum were excluded. The patient characteristics have
been previously described [6]. All participants included gave written informed
consent in accordance with the Declaration of Helsinki. The institutional medical
ethics committee of University Medical Centre Groningen approved the study. All
MGUS patients and controls received an intramuscular injection of the influenza
vaccine (Influvac, Solvay Pharmaceuticals, Netherlands) between October 2010 and
January 2011. The vaccine, a subunit preparation of licensed 2010-2011 trivalent
inactivated virus, contained A/California/7/2009 (H1N1), A/Perth/16/2009 (H3N2)
and B/Brisbane/60/2008.
Cell and serum isolation
Venous blood samples were obtained at the day of vaccination (day 0), 7 days
and 28 days post-vaccination. PBMCs were isolated using CPT vacutainer tubes
according to manufacturer’s instructions. The PBMCs were frozen in RPMI 1640
(Roswell Park Memorial Institute medium; Lonza, Verviers, Belgium), supplemented
with 10% human pooled serum, 50 µg/mL gentamicin (Gibco, Paisley, UK) and
10% dimethylsulfoxide (Merck, Germany) and then stored in liquid nitrogen until
further analysis. Serum was separated by centrifugation and stored at -20°C until
further analysis
Influenza-specific IgA and IgM antibodies by ELISA
The level of anti-influenza specific serum IgA and IgM antibodies against A/H1N1
and A/H3N2 were determined by an in-house enzyme-linked immunosorbent assay
(ELISA). ELISA plates (Costar) were coated with 1 µg/mL of A/H1N1 and A/H3N2.
The plates were incubated overnight on a shaker. Subsequently, serum samples
collected at day 0, day 7 and day 28 following vaccination were added to the plates
and then serially diluted (1:4) in PBS /0.05% Tween-20 /2% BSA. To detect influenzaspecific antibodies, 1µg/ml goat anti-human IgA-HRP (Southern Biotech) or 1µg/ml
mouse anti-human IgM-HRP (Southern Biotech) conjugate antibodies were used
followed by incubation with 3,3’,5,5’- tetramethylbenzidine (TMB) substrate. The
substrate reaction was stopped by adding H2SO4 (UMCG pharmacy). Absorbance
at 450nm was read with an Emax microplate reader and antibody concentrations
calculated by SOFTmax PRO software (Molecular Devices, Sunnyvale, USA). For a
standard curve, a dilution series of human IgG standard, N protein (Siemens) was
used on every plate and the antibody contents of the samples were read from the
linear part of the sigmoid curve.
HAMPERED INFLUENZA-SPECIFIC IgG B CELL RESPONSES
79
Hemagglutination Inhibition assay
Hemagglutination Inhibition (HI) test to A/California7/2009/H1N1 was performed
according to standard techniques as previously described [15]. The HI assay was
performed using guinea pig erythrocytes and egg-grown influenza viruses as antigens.
Memory B cell assay
PBMCs were plated in 24-well plates at a cell concentration of 0.5x106 cells/ml was
in RPMI 1640/10%FCS supplemented with 0.1µg/ml IL-21 ( Immunotools, Germany),
0.1µg/ml B cell activating factor (BAFF) (PeproTech, USA) and 3.2µg/ml CpG-ODN2006 (InvivoGen). For negative control PBMCs were cultured in medium (RPMI
1640, supplemented with 50 µg/mL gentamicin and 10% FCS) alone. Cells were
subsequently incubated for 6 days at 37 °C, 5% CO2.
The samples were run in duplicates for detection of cells secreting total IgG
antibodies as well as cells secreting TIV-specific IgG. MAIPSWU10 multiscreen
filtration plates (Millipore, USA) were pre-wetted with 70% ethanol for 2 min and
washed 3 times with 150 µL/well PBS (phosphate buffered saline; UMCG pharmacy).
For coating, TIV (Influvac, Solvay Pharmaceuticals, The Netherlands) was diluted to
1µg/ml in PBS. To detect total Ig secreting cells, wells were coated with 2.5μg/ml
goat anti-human IgG (Bethyl Laboratories, USA). Wells with PBS only were used as
uncoated controls. The plates were incubated overnight at 4°C. After washing the
plates 3 times with 150 µL/well 0,01% Tween-20 (Sigma-Aldrich, USA), plates were
blocked with 2% BSA and incubated at 37°C for 2 hours. The cultured PBMC were
washed thoroughly before counting. The cells were subsequently resuspended in
RPMI 1640 (+ 50 µg/mL gentamicin)/10% FCS and added to the plates in duplicates
with 200μl cell suspension/well. The plates were incubated at 37°C for 18 hours.
After the incubation, cells were discarded and the plates were washed with PBS
/0,01% Tween-20 (6 × 150μl/well). Subsequently, 100 µL/well anti-human IgG-HRP
(Bethyl Laboratories, USA) was added and plates incubated at room temperature
for 1 hour. Unbound conjugate antibody was then washed away with PBS (3x 150µl/
well) and then developed using TMB substrate (Sanquin, NL) in the dark, at room
temperature. To stop the reaction, the plates were washed extensively under the
tap and dried in a light-shielded place. Finally, the number of spots per well were
quantified with an ELISpot plate reader (A.EL.VIS, Germany).
Immunofluorescent staining and flow cytometric analysis of B cell subsets
PBMCs were counted by the Coulter Counter (Beckman Coulter, USA) and a cell
suspension of 2x106cells/mL was made. The following monoclonal antibodies were
used in this study: CD19 (e-fluor 605), CD24 (PerCP- E-Fluor 710), CD27 (APC-E-Fluor
780), CD38 (PE-Cy7), all obtained from eBioscience. IgG (FITC) from Santa Cruz
Biotechnology, IgD (V450) and IgM (APC) were from BD Biosciences. Cells were
incubated with directly conjugated monoclonal antibodies for 60 minutes at 4°C.
4
80
CHAPTER 4
After staining, cells were washed with 1% BSA (Sigma-Aldrich, USA). Nine color flow
cytometric analysis was carried out on the BD LSR II (BD Biosciences, USA) with BD
FACSDiva Software. Cells were gated on SSC versus FSC to collect lymphocytes and
then on CD19 cells versus SSC to gate B cells. Between 0.5 x105 and 1x 106 cells were
collected. Further analysis for B cell subsets was done by Kaluza (Beckman Coulter,
USA). We measured the frequency of CD19+: IgM memory (IgD+/ IgM+/ CD27+),
switched memory B cells (IgD-/ CD27+/CD38low /CD24+) as well as CD27- memory
(IgD-/ CD27-) and plasmablasts (IgD-/ CD27+/CD38 high/CD24-).
Statistical analysis
Data analysis was done by Graphpad Prism 5 (Graphpad software). Data are
presented as median (range) if not otherwise stated. The Mann–Whitney test was
used to compare groups. The Spearman rank test was used to test correlations
between variables. Differences were considered statistically significant at p < 0.05.
RESULTS
Reduced Hemagglutination Inhibition response in MGUS
We analysed the serum Hemagglutination Inhibition titers before and 28 days after
vaccination to evaluate whether the antibody production to one of the seasonal
vaccine strains mirrors the responses observed by ELISA analysis. H1N1-specific
IgG responses were established in the same MGUS cohort as for this study and
were recently reported separately [6]. Hemagglutination inhibition titers were
recorded according to criteria used to assess the immunogenicity of influenza
vaccines [16]: i.e. seroprotection rates (percentage of vaccinees who achieved titers
of ≥ 1:40 post-vaccination), seroconversion (the proportion of subjects with a 4 fold
or greater rise in antibody titer from the prevaccination titer), Geometric mean titers
(GMT) of HIN1 before and post-vaccination and mean fold increase (MFI) in GMT.
The inferior response of MGUS patients observed by ELISA was also paralleled
by HI antibody titer response. Correlations between the HI titer and serum IgG
levels were observed at day 28 post-vaccination for healthy controls (Spearman’s
r= 0.72; p=0.008) as well as for MGUS (Spearman’s r= 0.58; p=0.008) (Figure 1A).
No difference in HI antibody titers between controls (n=19) and MGUS (n=19)
were detected before vaccination. In both groups, titers of influenza specific
antibodies increased after vaccination, but responses were dampened in MGUS
(p=0.07). The fold increase in GMT was lower in MGUS (1.3) compared to healthy
controls (2.6) (Figure 1B). The poor increase in antibody titers therefore resulted
in lower seroconversion rates, with only 3 (16%) MGUS patients seroconverting
compared to 42% of healthy controls. The seroprotection rates achieved in healthy
controls (58%) were higher than those achieved in MGUS (42%), however without
reaching significance (p=0.06).
HAMPERED INFLUENZA-SPECIFIC IgG B CELL RESPONSES
81
4
Figure 1. Hemagglutination inhibition antibody responses of HC and MGUS to H1N1
component of 2010 TIV. (A) Correlation curve for H1N1 HI titer and H1N1-specific IgG in HC
(grey triangles) and MGUS (black squares) at day 28. (B) Geometric mean titers against H1N1 (A/
California/7/2009) at day 0 and day 28 post-vaccination for HC (n=19) and MGUS (n=19). Bars and
error bars denote group median and interquartile range. Mean fold increase in GMT is shown as
numerical values below. ** p<0.01; *** p<0.001.
The frequency of TIV-specific IgG memory B cells does not increase
following vaccination in MGUS
We have analysed the composition of the peripheral B cell pool in 5 HC and
6 MGUS patients in which additional PBMCs were available. To further explore
influenza vaccination-induced alterations in the B cell compartment, we compared
circulating B cell subsets at baseline to those obtained post-vaccination (day 7
and day 28). No statistically significant difference in the relative frequencies of
CD27+ memory B cells and plasmablasts was observed between HC and MGUS
at baseline (data not shown). Following vaccination, the frequencies of the B cell
subsets remained relatively constant in HC except for plasmablasts; which showed
a trend to an increase (but not statistically significant) at day 7 post-vaccination
(data not shown).
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Additionally, to investigate immunoglobulin expression on B cells, we
evaluated the expression of IgG on IgD - CD27+ B cells. At baseline, the majority
of the cells were of IgG isotype for both HC and MGUS. However, the frequency
of these IgG+ cells was significantly lower in MGUS compared with HCs (p=0.05)
(Figure 2A). The lower frequency of IgG+ cells in the IgD-CD27+ fraction in MGUS
at baseline was due to a concomitant increase in IgM+ cells in the IgD-CD27+
fraction (p=0.0037).
Furthermore, The frequency of these IgG+ cells in the CD27+ B fraction
demonstrated positive associations with the H1N1-specific serum IgG at day 28 in
HCs (Spearman’s r=0.7033, p=0.0073) and MGUS (spearman’s r=0.7494, p=0.002).
Following vaccination (day 7), there was a significant decrease in the frequency of
IgG+ IgD- CD27+cells in HC (p=0.04), however the decrease was not significant in
MGUS. Additionally, the frequency of IgG+ in the isotype-switched CD27+ fraction
at day 0 was positively correlated with the fold increase in hemagglutination
inhibition titers at day 28 in HCs only (Spearman’s r=0.5522, p=0.0328) (Figure 2B).
Figure 2. Analysis of influenza vaccination-induced changes in IgG responses. (A)The changes
in frequencies of IgG+ IgD- CD27+ cells in response to influenza vaccine challenge in HC and
MGUS at day 0, day 7 and day 28. (B) The frequency of the IgG+ (CD27+ cells) correlates with
IgG titers and the fold increase in HAI in HC. (C) IgG secreting TIV-specific memory B cells in
HC and MGUS at day 0, day 7 and day 28 post-vaccination. The number of TIV-specific memory
B cells was calculated as a % of total IgG secreting MBCs. *p<0.05
HAMPERED INFLUENZA-SPECIFIC IgG B CELL RESPONSES
Therefore, the increase in influenza-specific IgG titers is associated with higher
numbers of total IgG+CD27+ cells.
Influenza-specific memory B cell levels are expressed as the frequency of total
IgG-switched memory B cells (total IgG secreting cells) to normalize the data for
differences in cell recovery as well as for changes in the overall memory B cell
population. In order to detect the effect of influenza vaccination, we assayed the
number of influenza-specific IgG MBCs at day 7- and day 28 post-vaccination.
There were detectable TIV-specific IgG memory B cells at baseline for both HC
(range 12 to 74 per 105PBMCs) and MGUS (range 0 to 106 per 105PBMCs). However,
TIV-specific IgG memory B cells were absent in 1 MGUS patient at baseline. The
TIV-specific IgG memory B cells averaged 4.1% (1.6- 7.2) of total IgG memory B cells
in HC and 2.6% (0- 5.6) in MGUS. Vaccination resulted in a significant increase in the
frequency of TIV-specific IgG memory B cells in HC (p=0.03) but not in MGUS at
day 7 post-vaccination. This resulted in HC having significantly higher percentages
of TIV-specific IgG memory B cells (p=0.03) that averaged 17% of total IgG memory
B cells in comparison to 4.3% in MGUS where the frequencies of the TIV-specific
IgG memory B cells did not show a significant increase (Figure2C). Of note is that
the number of total IgG memory B cells at day 28 post-vaccination negatively
correlate with monoclonal protein concentration (Spearman’s r =-0.87, p=0.03)
(data not shown).
MGUS patients mount significant IgA and IgM response to influenza
vaccination
Baseline frequencies of DN (IgD-CD27-) memory B cells as well as IgM+IgD+CD27+
memory B cells were comparable between HC and MGUS. However, vaccination
resulted in an increase in the frequency of DN memory B cells at day 7 in MGUS
(p=0.01) (Figure3A). Furthermore, IgM+ IgD+ CD27+ memory B cells were
decreased in MGUS in response to vaccination at day 7 (p=0.01) (Figure 3B). This
decrease at day 7 post-vaccination may indicate a difference in responding cells
in comparison to HCs as the frequency of these cells is lower than those in HC at
the same time-point (p=0.009).
We further examined humoral immune responses in 19 HC and 19 MGUS
patients. We determined the H1N1 influenza-specific IgM and IgA antibody
responses before vaccination (day 0) as well as after vaccination (day 7 and day
28 post-vaccination). Influenza-specific IgM and IgA were detected at baseline in
both HCs and MGUS. Vaccination resulted in a significant increase in both IgM
(p=0.0009) and IgA (p=0.005) levels at day 7 post-vaccination in HCs with the
levels being maintained at day 28 post-vaccination. Similarly, MGUS showed an
increase in H1N1 influenza-specific IgM (p=0.002) (Figure 3C) and IgA (p=0.0003)
(Figure 3D) antibody titers at day 7. However, MGUS had a trend to higher day 7
IgM titers in comparison to HCs, though not statistically significant (p=0.07)
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Figure 3. Effect of influenza vaccination upon peripheral B cell subset proportions and
antibody titers. Frequencies of (A) IgD- CD27- memory B cells and (B) IgM+ IgD+ CD27+ memory
B cells at day 0, day 7- and day 28 post-vaccination. Vaccination results in a significant increase in
H1N1-specific IgM (C) and as well as IgA (D) in both HC and MGUS. *p<0.05; ** p<0.01; *** p<0.001.
DISCUSSION
Serum titers of hemagglutination inhibiting antibodies are an universally established
correlate of protection for influenza with seroprotection rate accepted as a proxy
end point [17, 18]. The HI results in our study confirmed hampered vaccine-specific
antibody responses as observed by IgG ELISA as we showed that MGUS had
reduced HI response. Moreover, H1N1 specific IgG antibody levels correlate with
the HI response[6]. The poor post-vaccination influenza specific IgG antibody
levels observed in MGUS may therefore predict or mirror response to influenza
vaccination. The seroprotection rate was lower in MGUS (37%) in comparison to
age matched HCs (58%) suggesting that these MGUS patients are likely to be less
protected by vaccination.
After TIV vaccination, naïve and memory B cells that encounter antigen
differentiate into effector B cells that appear in the circulation and peak around
HAMPERED INFLUENZA-SPECIFIC IgG B CELL RESPONSES
day 7 and subsequently decline [19]. In this study, we see a non-significant increase
in total plasmablasts at day 7 post-vaccination in both HC and MGUS. However, we
did not selectively look at influenza-specific antibody secreting cells to determine
the association between the serum response and effector cells. We observed TIV
specific MBCs in both HC and MGUS before vaccination. This is in agreement
with other studies where pre-existing influenza specific MBCs are present in the
circulation [20]and reflect prior vaccination or natural infection. Previous reports
have shown that following polyclonal stimulation and ELISpot, antigen-specific IgG
MBCs account for up to 6% of the total IgG memory at day30 post-vaccination
[19, 20]. The responses we observed in this study were higher with TIV-specific
MBCs making up to 29% of total IgG MBCs at day 7 and up to 14% at day 28 postvaccination in HCs. The differences in the immune responses observed could be
due to the differences in the composition of the TIV vaccines in the various years.
Furthermore, all the HC and MGUS patients in this study were vaccinated the
previous year with A/California/2009 that was present in the current TIV. Therefore,
a recall response was likely to be elicited. Another difference is that the previous
studies used Staphylococcus aureus Cowan, CpG and Pokeweed mitogen [19, 21]
as polyclonal stimuli while we used IL-21, BAFF and CpG. There may therefore be
differences in the MBC activation efficiency between the assays. However this
discrepancy was accounted for by measuring the frequencies of TIV-specific MBC
in the activated total MBC population rather than as numbers of TIV-specific MBC
per stimulated PBMCs.
The expansion of MBCs following vaccination is enriched for antigen-specific
cells in HC. However, vaccination did not result in a significant increase in antigenspecific MBCs in MGUS. This poor antigen-specific memory response is likely
to impair the maintenance of serologic response [22]. Notably, MGUS had lower
frequencies of IgG+ IgD- CD27+ cells at baseline and influenza-specific IgG
secreting cells are significantly lower in response to vaccination. Moreover, the
higher levels of IgG+IgD-CD27+ cells in HC at baseline were associated with higher
fold-increase in the HI titers but not for MGUS implying that higher frequency
of IgG+IgD-CD27+ cells are advantageous for antibody responses. Interestingly,
we noted that in a subset of MGUS assayed by ELISpot, high monoclonal protein
concentration is associated with lower (total) IgG MBCs following vaccination.
This implies that, at least in this small subset of MGUS, high monoclonal protein
concentration is associated with a limited humoral immunologic memory that will
potentially limit the response to influenza vaccination.
In the IgD- CD27+ fraction, there is a decrease in the frequency of IgG+ cells that
is compensated by an increase in IgM+ cells in MGUS at day 0 before vaccination.
This may then limit the repertoire of IgG+ cells that is available to respond to
vaccination. While, there is evidence of hampered IgG responses in MGUS, the
IgM response is not negatively affected. Indeed, serum H1N1-specific IgM titers
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in MGUS were comparable to HC as they also increased following vaccination.
Furthermore, the change in frequencies in IgM+ (IgD+CD27+) memory B cells
frequencies at day 7 may reflect differences in responding cells between HCs
and MGUS. Some IgM memory B cells may differentiate into cross-reactive IgM
antibody secreting cells leading to the increase in H1N1-specific IgM as observed.
The rest of the IgM memory may be recruited into the secondary response to
compensate for the hampered IgG response.
Interestingly, DN memory B cells are also substantially expanded in the
peripheral blood of MGUS at day 7, suggesting their participation in the early
phase of memory responses although their antigen specificity was not determined.
Whether distinct pathways are responsible for the induction of CD27− and CD27+
memory B cells after antigen challenge remain debatable. However, these CD27memory B cells may result from incomplete germinal center reactions therefore
explaining their failure to acquire CD27 [23, 24]. This also explains their lower
somatic hypermutation rates in comparison to CD27+ counterparts [25, 26]. A study
by Moir and colleagues showed that influenza-specific IgG MBCs can be found in
the CD27- compartment albeit at frequencies 10 times lower than in the CD27+
compartment of HC [25]. This would suggest that the influenza-specific response
within the CD27−IgG+ B-cell subset would not be as effective as from its CD27+
counterpart.
We analyzed the relationship between memory response to influenza vaccination
as well as the peripheral blood B cell subsets as they are easily accessible. However,
by measuring peripheral blood B-cell subsets instead of antigen-specific B cells
we indirectly assess the cells involved in the response to vaccination. Another
limitation was the small group sizes of the HC and MGUS included in the different
analyses. Nevertheless, we found several differences between the HC and MGUS
but larger sample sizes are needed to confirm our results.
In conclusion, we have shown that MGUS elicit a significant IgM and IgA antibody
responses to influenza vaccination despite the restricted IgG B cell response. Poor
antigen-specific memory response in MGUS is likely to impair the maintenance of
serologic response. The poor IgG memory response is related to high monoclonal
protein in MGUS suggesting defect in B cell immunity.
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CHAPTER
Monoclonal paraprotein influences
baseline B cell repertoire diversity and
pertubates influenza vaccination-induced
B cell response
Sarah M. Tete1, 2, David Kipling3, Johanna Westra1, Aalzen de Haan4,
Marc Bijl5, Deborah K. Dunn-Walters6, Surinder S. Sahota2
and Nicolaas A. Bos1
Department of Rheumatology and Clinical Immunology, University of
Groningen, University Medical Center Groningen, Groningen, Netherlands;
2
Cancer Sciences Academic Unit, University of Southampton School of
Medicine, Southampton, UK;
3
School of Medicine, Cardiff University, Cardiff, UK;
4
Department of Medical Microbiology, Molecular Virology section,
University of Groningen, University Medical Center Groningen, Groningen,
Netherlands;
5
Department of Internal Medicine and Rheumatology, Martini Ziekenhuis,
Groningen, Netherlands;
6
Peter Gorer Department of Immunobiology, King’s College London School
of Medicine, London, UK
1
Manuscript submitted
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ABSTRACT
Introduction
Monoclonal gammopathy of undetermined significance (MGUS) arises from
a monoclonal expansion of plasma cells in the bone marrow, secreting
monoclonal (M) paraprotein. MGUS is associated with increased susceptibility
to infections, which may reflect altered B-cell repertoire.
Methods
To investigate this, we examined the IgM, IgG and IgA B-cell repertoire
diversity in MGUS at baseline and after influenza vaccination (n=16) in
comparison to healthy controls (HCs) (n=16). The CDR3 region of the
immunoglobulin heavy chain variable (IGHV ) region gene was amplified and
B-cell spectratypes analyzed by high-resolution electrophoresis. Spectratype
Gaussian distribution, kurtosis and skewness were quantified to measure
repertoire shifts.
Results
Both HC and MGUS baseline spectratypes show inter-individual variability
that is more pronounced in the IGHG and IGHA repertoire. Overall, baseline
B cell repertoire is more altered in MGUS, with oligoclonality observed in
50% (p=0.01). Post-vaccination, significant differences emerged in MGUS
in relation to M-protein levels. High M-protein concentration is associated
with a more oligoclonal IgG and IgA response at day 7 post-vaccination, and
in contrast to HCs vaccination also induced significant perturbations in the
MGUS IgM repertoire at day 7 (p=0.005).
Conclusion
Monoclonal expansion in MGUS has an effect on the baseline B cell repertoire
and influences the recruited repertoire upon vaccination.
MONOCLONAL PARAPROTEIN INFLUENCES BASELINE B CELL REPERTOIRE DIVERSITY...
93
INTRODUCTION
Aging is associated with changes in the functioning of the immune system that
is manifest as poor responses to infections and vaccination [1-3]. As antibody
responses are the mainstay of protection against many infectious agents, recent
investigations have focused on amelioration of the humoral responses in aging,
including underlying B-cell repertoire shifts [4-6]. During aging, the emergence
of a non-malignant condition like Monoclonal Gammopathy of Undetermined
Significance (MGUS) in the elderly may further alter this susceptibility to infection
or response to vaccination. MGUS is a condition that is generally identified
surreptitiously, and arises from monoclonal expansion of plasma cells in the bone
marrow, with potential to transform to full malignancy such as multiple myeloma
[7, 8]. In MGUS, the expansion of plasma cells results in the secretion of elevated
levels of monoclonal protein (M-protein), which can increase to reflect a further
expansion [9, 10].
MGUS is associated with hypogammaglobulinaemia in20-28% of cases [11-13]
possibly reflecting an impact of the monoclonal clone on normal plasma cells in
the BM niche. Accordingly, these changes in humoral capacity are likely to play
a part in the increase in susceptibility to infection and decreased response to
vaccination. A two-fold increased risk of bacteremia as well as a broad range of
bacterial and viral infections has been described in MGUS patients compared to
the general population [14]. These include pneumonia, influenza and herpes zoster
infections [15, 16]. Furthermore, high monoclonal protein at diagnosis of MGUS
has also been shown to be associated with higher risks of developing infections.
[15] Besides the increased risk of infections, significantly depressed background
antibody levels to a number of common infectious antigens have been reported,
notably to staphylococcal, pneumococcal, varicella zoster and fungal antigens such
as candida and aspergillus [16].
Responses to vaccination in MGUS remain poorly understood. Of infectious
agents, influenza is a significant morbidity factor in aging and influenza vaccination
is recommended in this high-risk group [17]. Influenza vaccination has an efficacy
of 70% in healthy young adults [18], but the efficacy is decreased in the normal
elderly population [19, 20]. In MGUS specifically, we have recently shown that
the humoral immune response to influenza vaccination negatively correlates with
the size of the M-protein [21]. MGUS patients with high M-protein levels elicited
poor responses compared to age matched controls and this implies that high
M-protein is a marker of underlying B cell dysregulation resulting in the poor
immune response [21]. There is therefore a clear need to understand the nature
of this immune dysregulation in MGUS patients, in order to develop strategies
to counter their elevated susceptibility to infections and decreased response
to vaccination.
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B cell dysregulation impacts on the B cell repertoire and diversity can be
mapped by analyzing the immunoglobulin variable region (IGV ) gene repertoire
[22]. The Complementary Determining Region 3 (CDR3) covers the junctional
region where the 3 segments (IGHV-IGHD-IGHJ) are joined[23]forming the core
antigen-binding site in an antibody molecule [22]. CDR3 diversity is therefore a
critical measure of functional diversity of any B cell repertoire.
In a normal diverse B cell population a large number of clones derived from
random V(D)J rearrangements result in a Gaussian distribution of CDR3 sizes. Where
repertoire is perturbed, as with biases in repertoire usage or clonal expansions,
the CDR3 distribution is altered and can be assayed by spectratyping [24, 25].
Spectratyping has been used to show that the B cell repertoire is compromised in
the elderly. Aging is associated with oligoclonal expansions of cells and a collapse
in the diversity of the B cell repertoire [4]that correlates with a general phenotype
of frailty [26]. Vaccination has also been shown to induce changes in the B-cell
repertoire. However, these changes are attenuated in aging and resolution of the
response differs. Importantly, the IgM and IgA responses were impaired in the
elderly and challenge resulted in smaller CDR3 sizes [4].
The onset of a monoclonal expansion in the elderly may further alter repertoire
diversity, and thus far this has not been evaluated. To address this, we sought to
delineate the baseline B cell repertoire in MGUS and humoral response to vaccination
against influenza. We hypothesized that monoclonal plasma cell expansions in
MGUS located in the BM may further alter the aging humoral response. To test
this hypothesis, we analyzed the B cell repertoire using spectratype resolution of
the CDR3 region of IGHV genes and modeled data to assess diversity in MGUS
patients before and after influenza vaccination.
METHODS
Volunteers and sample collection
MGUS patients from the University Medical Centre Groningen hematology
department and age-matched healthy controls were recruited during the 2010-2011
influenza vaccination season. The MGUS patients fulfilled the standard diagnostic
criteria for MGUS: serum M protein levels <30g/L, clonal plasma cells in bone marrow
<10% and no myeloma related dysfunction or other B-cell proliferative diseases. All
participants gave written informed consent in accordance with the Declaration of
Helsinki. The institutional medical ethics committee of University Medical Centre
Groningen approved the study. All participants received influenza vaccination
(Influvac 2010/2011, Solvay Pharmaceuticals, Netherlands) and blood samples were
collected prior to the vaccination, as well as 7 days and 28 days post-vaccination.
Peripheral blood mononuclear cells (PBMCs) were isolated from the blood by
density gradient centrifugation of CPT Vacutainer tubes (BD). PBMCs were then
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95
frozen in RPMI 1640 (Cambrex Bioscience, Verviers, Belgium) supplemented with
10% human pooled serum, 50 µg/mL gentamicin (Gibco, Paisley, UK) and 10%
dimethylsulfoxide(Merck, Germany). PBMCs were stored in liquid nitrogen until
further use.
Nucleic acid extraction and cDNA synthesis
Total DNA and RNA were extracted using the Qiagen Allprep DNA/RNA mini kit
according to the manufacturers’ specifications. First strand cDNA was synthesized
from RNA following standard protocols using Superscript-III (Invitrogen) in a reverse
transcriptase system (Promega).
Spectratypes
cDNA was used for the amplification of the IGH gene CDR3 region using a PCR with
primers specific for the constant regions C (GGAAGAAGCCCTGGACCAGGC),
Cµ (CAGGAGACGAGGGGGAA) or C (CACCGTCACCGGTTCGG) in combination
with Fw3Fam (ACACGGCTGTGTATTACTGT). The cDNA was amplified in 25 cycles
of 98°c (45s), 45s annealing temperature of 61°c/55°c/55°c for alpha, gamma and
mu respectively, 45s at 72°c and 1 final cycle of 5min at 72°c. This was done in
a 25µl reaction mixture containing 20mM each of dNTP, 10µM of each primer
(Fw3Fam plus one of the isotype specific primers), 0.2 Phusion DNA polymerase
(NEB, Hitchin, UK) in a 5X reaction buffer containing 1.5mM MgCl2. 5µl of each
reaction sample was added to 1.5µl Tamra 350 size standard in formamide and run
on the ABI 3730 xl capillary sequencer.
Multiple different methods and software tools for high CDR3 spectratyping
analysis have been utilized; mainly on T cell repertoires [27-29]. However, in this study,
raw spectratype data (fragment sizes) was analyzed and peak profiles visualized
using Genescan software (Applied Biosystems) where the fluorescence intensity of
each band was depicted as a peak. Data was then exported to Excel and frequency
distributions of the CDR3 lengths were obtained. For further analysis, the Excel files
were then imported into the R statistical programming environment (R Development
Core Team, 2011) and the raw peak data was normalized so that the relative proportion
of DNA fragments per CDR3 size was determined before spectratype curves were
generated. A reference Gaussian distribution was generated using the mean and SD
from each sample and B cell repertoire diversity was assessed by comparing the mean
CDR3 size and correlating the spectratype to the reference Gaussian distribution
(CGD). The divergence from the reference Gaussian distribution is therefore a direct
measure of the corresponding repertoire diversity. To take account the shape of
the spectratype distribution; the variability of the data, kurtosis and skewness were
measured for each spectratype distribution. Kurtosis measures the distribution of
the peaks, how much data is located at the tails as opposed to a distinct peak
near the mean. Normally distributed data is given a value of zero while data that is
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mainly centrally located near the mean and decline rapidly with a slim tail is given a
positive value (leptokurtosis, k> 0). A negative value is given to a distribution when
there is more data in the tails and the peak is flatter (platykurtosis, k< 0). Skewness
is a measure of symmetry of the distribution. For a symmetric distribution a value
of zero is given as the mean and median values coincide. A left/ negatively skewed
distribution has a left tail that is long relative to the right tail and the mean of the
data is less than the median; values are less than zero. A right skewed distribution
has positive a value for skewness and the right tail is longer.
Statistical analysis
Statistical analysis was performed using Graphpad prism 5.0 (Graphpad Inc,
USA). Mann-Whitney U test, Wilcoxon signed rank test and Chi squared test for
categorical data were used as appropriate. For correlations between different
measurements, Pearson’s correlation analysis was used. P-values < 0.05 were
considered statistically significant.
RESULTS
A total of 16 MGUS patients and 16 age-matched HCs were included in this
study (Table 1). Our MGUS cohort exhibited considerable heterogeneity in
terms of the type and size of M protein as well as duration of the condition. The
concentration of M-protein varied from unquantifiable levels to 24.8g/L. M-protein
was detected by immunofixation but was unquantifiable in 7 patients by serum
protein electrophoresis because the concentration was very low or the M-protein
migrated in the fraction. A concentration of 0.01g/L was therefore assigned to
this subset of MGUS patients. The study demographics are shown in Table 1.
Table 1. Baseline characteristics of MGUS patients and controls
Age (years). median (Range)
Sex (male/female)
Vaccination 2009/2010. N (%)
Healthy Controls
(n=16)
MGUS
(n=16)
P
63 (49-82)
64 (48-81)
NS
11/5
11/5
NS
NS
14 (87.5)
16 (100)
Duration of MGUS, years. Median (range)
NA
4(1-19.2)
Monoclonal protein size, g/L. median (range)
NA
6(0.01-24.8)
IgG
NA
8 (50)
IgA
NA
4 (25)
IgM
NA
4 (25)
Monoclonal protein isotype. N (%)
NS, not significant; NA, not applicable.
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Baseline analysis of the IgM, IgG and IgA repertoire shows more
variability in MGUS
Spectratyping profiles can map polyclonality in a normal healthy immune humoral
response arising from a homeostatic B-cell repertoire and accurately identify
deviant repertoires that are altered by specific conditions. There are various
alterations in the spectratype profiles that can be seen in a deviant repertoire.
These alterations affect the shape and distribution of the spectratypes and
can be modeled by CGD, kurtosis and skewness. Fig 1A shows representative
spectratypes and the metrics measured from 4 healthy controls at day 0 and
a comparative analysis of samples from 4 MGUS patients is shown in Fig 1B. In
healthy controls, a polyclonal distribution of the CDR3 spectratypes was observed,
although inter-individual variability occurred, as shown by the variations in CGD,
kurtosis and skewness. The B cell repertoire was variable in MGUS with some
showing polyclonal distribution of the CDR3 spectratypes similar to the healthy
controls. Nonetheless, loss in diversity indicated by a few dominant expansions
in the CDR3 sizes was observed in a subset of MGUS patients. These oligoclonal
specratypes (CGD<0.6) were observed in the MGUS baseline repertoire at higher
frequency than in healthy controls. 50% of the MGUS patients had oligoclonal
spectratype profiles for at least one of the three IGHV immunoglobulin gene
repertoire sin comparison to only one (6%) healthy control (data not shown,
p=0.01).
A spectratype distribution was considered to be normal (approximately
symmetric) if the skewness was between -0.5 and 0.5. However, a moderately
skewed distribution had skewness between -1 and -0.5 or between 0.5 and 1
while a highly skewed distribution had skewness values less than -1 or greater
than 1 [30]. Based on this interpretation, 3 MGUS IGHM spectratypes showed
moderate skewness compared to 2 HC samples while 5 MGUS IGHA spectratypes
were moderately skewed in comparison to 3 in HC. IGHG spectratypes showed
increased skewness in MGUS, with 3 MGUS IGHG samples moderately skewed and
2 were highly skewed in comparison to none in HC, in which all spectratypes were
approximately symmetric. Inter-individual variability in the HCs B cell repertoire
was more pronounced in the IGHG (p=0.001) and IGHA (p=0.036) spectratypes
than in IGHM. Of the healthy controls, 69% had IGHM CGD values of 0.9 or higher,
indicating repertoire complexity as depicted by the large number of different sized
CDR3 (Table 2).
We subsequently investigated whether age was associated with a less diverse
repertoire in HC and MGUS. No age-related changes were observed in the IGHM,
IGHG or IGHA spectratypes of the healthy controls. However, age was associated
with a decrease in MGUS baseline IGHG CGD index, regardless of the monoclonal
protein isotype, with a Pearson’s r of -0.55 (p=0.04) (Fig 1C).
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Figure 1. IGHM, IGHG and IGHA spectratypes show inter-individual variability. (A)
Spectratypes from 4 example MGUS patients at day 0 show inter-individual variability that is more
pronounced in IgG and IgA. The x-axis represents the CDR3 sizes in base pair and the y-axis is the
frequency of occurrence of the CDR3 sizes. The table shows how the spectratypes differ between
individuals as measured by the mean CDR3 size, how close the individual spectratypes match a
Gaussian distribution (CGD) and the difference in shape by kurtosis (k<0: platykurtic, k=0: normal,
k>0: leptokurtic) and skewness (left-skewed distribution>0, right-skewed<0). (B) Spectratypes
from 4 representative HCs show the CDR3 sizes and their distributions. Some spectratypes with
a prominent (oligoclonal) CDR3 size have a high peak signal that results in lower match to CGD
such as in donor 140 (IgM and IgG). (C) Age was associated with a significant decrease in IGHG
CGD in MGUS patients.
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99
Table 2. Samples matching Gaussian distribution; CGD≥ 0.9
HC
MGUS
IGHM N (%)
11/16 (68.8)
9/16 (56)
IGHG N (%)
6/16 (37.5)
2/16 (12.5)*
IGHA N (%)
7/16 (43.8)
3/16 (18.8)*
* Significantly lower MGUS samples matching CGD than IGHM samples, p<0.05
Vaccination induces change in the MGUS B-cell repertoire that correlates
with M-protein load
Following encounter with antigen, specific B cells expand and this leads to the
change in baseline repertoire distribution (Fig 2A,B). There was a pronounced shift
in the shapes of the spectratypes at day 7 that then return to the baseline shape
at day 28. Some profiles in the MGUS patients indicated a diverse repertoire at
day 0. However, in response to vaccination, there are marked differences in the
spectratypes between patients (Fig 2B). Perturbations in the repertoire evidenced
by oligoclonal CDR3 profiles and lower CGD were seen in some patients at day 7
that do not return to baseline values at day 28 but remain oligoclonal. In 3 MGUS
patients, a perturbed repertoire with a dominant CDR3 length was seen at day
7 in response to vaccination. However, on day 28, the spectratypes remained
oligoclonal but with a different pattern as a different sized dominant peak was
seen (data not shown). Interestingly, distortions in some of the MGUS spectratype
profiles that could be related to the monoclonal expansion of B cells in MGUS
were observed in 3 of the patients. In these patients, the spectratype profiles had
a major CDR3 length that is dominant in the repertoire, demonstrated as a peak
expansion. The major CDR3 length dominated the profiles at all 3 time-points,
before and after vaccination (Fig 2C). Of note, the dominant CDR3 length was seen
in the isotype of the spectratype profile that matched the isotype of the M-protein
from the MGUS patient, for example: the peak expansion was observed on IGHG
spectratypes for an IgG MGUS patient.
Influenza vaccination resulted in change in CGD index of the spectratypes that
were mostly in the IGHG and IGHA isotypes but not in IGHM in the healthy controls.
MGUS patients show a trend towards having a lower baseline IGHG repertoire
diversity (p=0.07) in comparison to healthy controls (Fig 2D). Nonetheless, a
significant change in the CGD similar to that of healthy controls was observed for
IGHG (p=0.05) and IGHA (p=0.03) spectratypes day 7 post-vaccination. In contrast
to healthy controls, there is significant repertoire perturbation in the MGUS IGHM
spectratypes at day 7 (p=0.005) with the CGD returning to baseline values at day
28. This resulted in significantly lower IGHM CGD values for MGUS at day 7 in
comparison to healthy controls (p=0.006).
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To investigate whether influenza vaccination has an influence on the
immunoglobulin IGHV gene repertoire selection we looked at the change in mean
CDR3 sizes. No change in the CDR3 size was observed in healthy controls following
Figure 2. Vaccination results in changes in the B cell repertoire. (A) Spectratypes from a HC
donor at day 0 and, day 7 and day 28 post-vaccination. Perturbations occur at day 7 and the
spectratypes returning to day 0 shapes at day 28. (B) Representative spectratypes from 3 MGUS
patients show that there are variations in the spectratype patterns following influenza vaccination.
(C) Spectratypes from 3 MGUS patients where monoclonal expansion of cells of a particular
CDR3 size dominate the spectratypes before and after vaccination. MGUS donor number and
spectratype isotypes are shown on the right y-axis (D) Vaccination induced change in repertoire
is shown by the change in CGD following vaccination. (E)Change in mean CDR3 length following
vaccination. (F) Monoclonal protein concentration negatively correlates with day 7 CGD values
for IGHG and IGHA spectratypes. *p<0.05; ** p<0.01.
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vaccination for both IgM and IgG. However, there was a significant increase in the
mean CDR3 length at day 7 in the IgA repertoire (p=0.05) that then returned to
smaller length at day 28 as seen at baseline. There is evidence of repertoire bias
towards use of longer CDR3 length in the IgG and IgA repertoire but not in IgM
for MGUS patients in response to vaccination (Fig 2E). The mean CDR3 length at
day 7 in MGUS was significantly higher than in healthy controls (p=0.008) for IgG.
M-protein levels significantly correlated with CGD at day 7 in the IgG and
IgA repertoire (Fig 2F). Higher M-protein concentration was associated with more
oligoclonal response at day 7 in the MGUS IGHA repertoire, with CGD as low as
0.1, indicating expansions in a few distinct CDR3 sizes (r2= -0.51, p= 0.04). This
notion that a few CDR3 sizes expand in response to vaccination is supported by
the observation that leptokurtosis was significantly correlated with M-protein at day
7 for the IGHA spectratypes (r2= 0.66, p=0.005). Additionally, CGD at day 7 was
also negatively correlated with M-protein concentration for the IGHG spectratypes
(r2=-0.66, p= 0.005) but not for IGHM. Further stratification of the MGUS patients
into 2 groups based on M-protein concentration showed that M-protein >10g/L
(n=7) was associated with a significantly lower CGD at day 7 post-vaccination for
both IGHA (p= 0.0164) and IGHG (p=0.05) in comparison to MGUS with M-protein
concentration <10g/L.
Furthermore, we investigated whether a less diverse repertoire could predict a
worse response to vaccination. H1N1-specific IgG responses were established in
the same MGUS cohort as for this study and were recently reported separately [21].
We therefore looked for correlation between the spectratypes metrics and H1N1
influenza-specific IgG responses. No correlations were observed for the healthy
controls. However, lower CGD at day 7 in the IGHM repertoire was associated with
lower H1N1 influenza-specific IgG responses at day 28 in MGUS (r2= 0.55, p=0.02).
Those with higher serum IgG response showed less perturbation in the IGHM
repertoire following vaccination (Fig 3).
Figure 3. H1N1-specific IgG response at day 28 correlate with IGHM spectratypes at day 7.
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DISCUSSION
In this study we have investigated the B cell repertoire in MGUS by looking at CDR3
spectratypes at baseline and examined the effect of vaccination on the IGHM,
IGHG and IGHA CDR3 spectratypes. Naïve B-cell repertoires show a characteristic
Gaussian distribution of CDR3 length diversity reflecting polyclonality of the B cells.
Deviation from Gaussian distribution is considered to be a sign of oligoclonal
expansions. There were inter-individual variations in the spectratype metrics in all
3 isotypes that were more prominent in the IGHG and IGHA spectratypes for both
healthy controls and MGUS patients. The IGHG and IGHA samples contain isotype
switched B cell populations and reflect an individual’s prior antigen exposure so
inter-individual variation was expected in these repertoires.
Oligoclonality of the baseline spectratypes indicating lack of repertoire
complexity was observed in 50% MGUS patients. It is unclear at present what
underlies the increased frequency of perturbations in the MGUS peripheral B cell
repertoire. The host immune system is capable of responding to pre-malignant cells
[31-33], and it is plausible that the immune response against specific antigens in
MGUS [34] may also lead to an alteration in the baseline repertoire that will play a role
in shaping the repertoire available to respond to vaccination. This chronic immune
activation has a potential in suppressing the neoplastic growth [32] but may also
result in a restricted (memory) B-cell repertoire with an exhausted ability to generate
expansion responses to vaccination, possibly related to the decrease in baseline
IGHG CGD in MGUS, with IGHG highly relevant to B-cell response to infectious
agents. The relationship between the MGUS clone and its microenvironment is
important for the maintenance of the clone in the bone marrow but could also
induce immune dysfunction. The observation of dendritic cells suppression in MGUS
may be related to increased immunosuppressive cytokines such as IL-6 [35] that
interfere with dendritic cell maturation and antigen presenting capacity. Increased
regulatory T cells in MGUS may also play a role in modulating the immune response
[36]. Furthermore, we reported a decrease in the relative numbers of CD19+ B cells
in this cohort of MGUS patients as well as a decrease in total serum IgG and IgA [21].
Hypogammaglobulinaemia is reported in ~25% of MGUS, and this may reflect the
impact of the monoclonal plasma cells on pan-antibody production [13] as clonal
plasma cells compete with diverse normal plasma cells for bone marrow niche space
[37, 38].When we linked B-cell repertoire diversity to age in a healthy elderly cohort
and contrasted these with aged individuals with MGUS, no age related differences
in repertoire diversity were observed in the healthy controls. However, increased
age was associated with a less diverse IGHG repertoire in MGUS indicating that
other than the aging-related alterations in peripheral B cell compartment, there
are also defects intrinsic to MGUS that may contribute to the repertoire alteration
seen with age. The potential immunosuppression in MGUS could then make this
MONOCLONAL PARAPROTEIN INFLUENCES BASELINE B CELL REPERTOIRE DIVERSITY...
repertoire alteration more pronounced with advancing age. These alterations that
occur in the immune system of MGUS are likely to contribute to increased risk of
infections and poor vaccination response.
The majority of the HCs and all the MGUS patients were vaccinated the previous
year with the same H1N1 influenza strain that was included in the TIV vaccine.
Therefore it is likely that the switched isotypes contain influenza specific memory
B cells that will rapidly proliferate and differentiate in response to the second
vaccination generating plasma cells and a discernible rise in serum antibodies with
IgG being the most relevant for protection [39, 40]. There is less perturbation in
the healthy controls B cell IGHM repertoire at day 7 post-vaccination presumably
because a recall response is elicited to influenza vaccination. Influenza specific
antibody secreting cells (ASCs) are also detected in the peripheral blood and peak
1 week after vaccination that are predominantly IgG and IgA [39] consistent with
the timing of the repertoire perturbations 7 days post-vaccination. As we used
RNA for analyzing immunoglobulin sequences of total peripheral B cells, and ASCs
are known to produce >100-fold more mRNA than resting B cells, the change in
the spectratype shapes at day 7 may also reflect the greater proportion of ASC
expansion more than mature B cells. In contrast to healthy controls, vaccination
induces significant perturbations in MGUS IGHM repertoire at day 7 that returns
to baseline pattern at day 28. Of note is that the IGHM spectratypes reflect a
repertoire that largely consists of naïve B cells [41] therefore the change at day
7 suggests a perturbation of the antigen-inexperienced repertoire in MGUS.
However, clonal expansions within the IgM memory population cannot be excluded
in these MGUS patients. Moreover, the perturbations in the MGUS IGHM repertoire
observed 7 days post-vaccination are shown to correlate to vaccine response with
a perturbation in the repertoire being associated with a worse H1N1 influenzaspecific IgG response.
A striking observation is that high monoclonal protein is associated with
more oligoclonal response at day 7 in both the IGHG and IGHA spectratypes in
MGUS. Multiple myeloma monoclonal protein reflects the monoclonal plasma cell
burden and it is highly likely that the relationship is the same in MGUS in which
high monoclonal protein is associated with higher risk of progression [12]. This
implies that high monoclonal protein is a marker of increased underlying B cell
dysfunction, limiting the pool of B cells available to respond to antigenic challenge.
As a consequence, a limited B cell repertoire responds to the vaccine challenge in
MGUS. The observation that some spectratypes remain perturbed at day 28, but
with a different sized dominant peak, suggests that many different factors may play
a role in shaping the responding repertoire. It may relate also to the slow resolution
of infection or another kinetic aspect of the humoral immune response altered
by MGUS cells. Whether the different sized dominant peaks observed are due to
an independent effect such as a secondary infection subsequent to vaccination
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remains uncertain. Spectratype distributions with a major CDR3 length of the
same size dominated the profiles at all 3 time-points before and after vaccination
in 19% of MGUS patients, of the same isotype as secreted M protein secreted and
are most likely to reflect circulating MGUS monoclonal cells. Circulating aberrant
monoclonal plasma cells have previously been detected by immunofluorescence
microscopy and flow cytometry in up to 20% of MGUS [15-17].
Our results are in contrast to Ademokun et al’s observation that pneumococcal
vaccination resulted in expansion of clones with smaller CDR3 sizes in healthy
controls [4]. MGUS spectratypes assessed in our study show that there is a
preferential expansion of longer CDR3 in the IGHG and IGHA repertoire at day
7 post-vaccination. The significance of this finding is however unclear but the
differences could be due to the differences in antigens and immune pathways of
response as pneumococcal vaccination results in a TI-2 response and no memory
while influenza vaccination results in a T-dependent response. It may also indicate
differences in expression of IGHV and IGHJ genes. Long CDR3 lengths have
been associated with self-reactive or polyreactive B-cells [42, 43]. Furthermore,
antibodies with long CDR3 are shown to be enriched in pre-B cells and immature
cells [44]; however CDR3 lengths are discerningly decreased as B cells progress
through development. Memory B cells that have shorter, more hydrophilic CDR3
regions are usually more selected while naïve B cells generally have the longest
CDR3 regions and less mutations [41, 43, 45]. Our results are consistent with these
findings in that the IGHM repertoire consists of the longest CDR3s.
In summary, these results define the impact of MGUS cells on humoral immunity,
and the impact of monoclonal protein burden on perturbations of the B cell
repertoire induced by vaccination. We have shown that B cell repertoire diversity
is altered in MGUS with oligoclonal expansions being seen in a subset of the
patients. It remains to be investigated how MGUS results in the disturbance of B
cell subsets composition and memory maintenance, and these studies are currently
in progress in our laboratory.
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CHAPTER
B cell repertoire diversification
in monoclonal gammopathy of
undetermined significance (MGUS)
Sarah M. Tete 1. 2, Graeme Cowan3, Johanna Westra1, Aalzen de Haan 4,
Mark Bijl5, Kharim Gharbi6, Surinder S. Sahota2, Nico Bos1,
Department of Rheumatology and Clinical Immunology, University of
Groningen, University Medical Center Groningen, Groningen, Netherlands
2
Cancer Sciences Division, University of Southampton School of Medicine,
Southampton, UK
3
Department of Biological Sciences, University of Edinburgh, Edinburgh, UK
4
Department of Medical Microbiology, Molecular Virology section,
University of Groningen, University Medical Center Groningen, Groningen,
Netherlands
5
Department of Internal Medicine and Rheumatology, Martini Hospital,
Groningen, Netherlands
6
The gene pool, University of Edinburgh, Edinburgh, UK
1
6
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ABSTRACT
Introduction
MGUS is associated with increased risk of infections as well as poor IgG
responses to influenza vaccination. However, the diversification B cell
repertoire in MGUS remains poorly understood but can have important
implications with respect to infections and vaccination responses.
Methods
We therefore investigated the peripheral IgG repertoire diversity in MGUS
and how vaccination affects the repertoire diversification. We carried out high
throughput IGHV gene analysis in 3 high-monoclonal protein MGUS and 3
healthy controls before and 7 days after influenza vaccination.
Results
IGHV gene usage in MGUS was derived from all the 7 IGHV gene families
and was comparable to healthy controls. IGHV1-69, IGHV1-18 and IGHV2-5
where the most dominantly used genes. When we analysed the somatic
hypermutation frequencies, the MGUS baseline repertoire had increased
number of reads with high mutations (>8%) indicating more frequent immune
activation. Following vaccination, mutational frequencies were comparable to
healthy controls. In terms of clonality, MGUS presented with a more restricted
B cell repertoire at day 7 post-vaccination. In MGUS, there was an increase in
average clone size that was related to the accumulation of greater numbers
of larger clone sizes.
Conclusion
MGUS show a decrease in diversity of clones expanding in response to
vaccination and it is likely that exhaustion of memory results in a B cell
response made up of more antigen-inexperienced cells.
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INTRODUCTION
Aging is associated with the alterations the B cell repertoire that affect the
response to challenge with vaccines such as influenza where the antibody response
is an established correlate of protection. Aging features oligoclonal expansion of
B cells as well as the emergence of pre-malignant conditions such as monoclonal
gammopathy of undetermined significance (MGUS) [1].
The diversification B cell repertoire in MGUS remains poorly understood but can
have important implications with respect to infections and vaccination responses.
Not only is the risk of infections high in MGUS, but also high monoclonal protein
MGUS with elicit poor response to influenza vaccination [2,3]. By using the method
of complementary determining region 3 (CDR3) spectratyping, we have shown that
B cell repertoire diversity is altered in MGUS with oligoclonal expansions being
seen in a subset of the patients. Furthermore, spectratyping revealed that influenza
vaccination results in an oligoclonal repertoire perturbation in high monoclonal
protein MGUS. Even though it is quantitative, spectratyping is not sufficient to
make unbiased clonality assessment of the immunoglobulin gene repertoire as
the sequence itself is not known.
However, additional investigations into more detailed immunoglobulin gene
repertoire usage by next generation sequencing need to be carried out in MGUS
as it will provide high coverage and eliminate the bias of high mRNA in plasma
cells. B cell receptor (BCR) diversity is generated from the random rearrangement
of variable (V), diversity (D), and joining (J) gene segments to provide a variety
of BCRs necessary for binding diverse antigens. Additional BCR diversification
is by introduction of point mutations through somatic hypermutation (SHM), a
recombination process in the germinal centers through the action of activationinduced cytosine deaminase [4]. During clonal expansions, mutations can
accumulate that improve antigen binding affinity.
The size of the B cell repertoire in humans makes sequencing by the Sanger
method challenging. Only a small pool of sequences is sampled and rare
sequences in the repertoire are more likely to be lost. We therefore designed
a study focused on the IgG repertoire analysis using Illumina sequencing by
synthesis with 4-color cyclic reversible termination. Illumina sequencing has a
greater sequencing depth [5] with an output with 25 million sequencing reads
[6] and 2x250 bp paired read lengths. Paired-end sequencing can permit the
identification of the immunoglobulin IGHV and IGHJ gene segments as well as
characterization of IGHD gene segments. Analysis of the B cell receptor diversity
will therefore give insights into B cell clonality in healthy and pre-malignant
populations as well as give insight into the effect of influenza vaccination on the
antibody repertoire.
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METHODS
Patient selection
MGUS patients who fulfilled the standard diagnostic criteria for MGUS [7] were
enrolled in this study after informed consent. The inclusion criteria were serum
monoclonal protein (<30g/L), clonal plasma cells in bone marrow <10%, no
myeloma related dysfunction or other B-cell proliferative diseases. Additionally,
3 HC with no malignancy, conditions associated with immune dysfunction or use
of immune modulating drugs were included. All participants were vaccinated
with the 2010/2011 trivalent inactivated influenza vaccine (TIV) containing
A/California/7/2009 (H1N1)-like virus, A/Perth/16/2009 (H3N2)-like virus and a
B/Brisbane/60/2008-like virus. PBMCs were isolated from day 0 before vaccination
and day 7 after vaccination samples as previously described and frozen 2. After
thawing, total DNA and RNA were extracted using the Qiagen Allprep DNA/RNA
mini kit according to the manufacturers’ specifications.
Library preparation
First strand cDNA was synthesized from RNA following standard protocols using
Superscript-III (Invitrogen) in a reverse transcriptase system (Promega). PCR
amplification of cDNA was done using Phusion high fidelity polymerase with C
forward primer containing 15 nucleotide multiplexing identifiers (MID) and illumina
adapters and FR1 VH1 to VH7 reverse primer sets. Amplified PCR products were
visualized on electrophoresis gel and gel extracted. High throughput 250base
paired-end sequencing was performed using Illumina MiSeq platform. Low quality
sequences with quality score <Q=30 were filtered out; Q=30 corresponds to the
probability P=0.001 that a base has been called incorrectly. Raw reads were then
split into MID groups and Fast Length Alignment of Short reads (FLASH) [8] was
used to match consensus reads from the same cluster.
V-D-J assignment
We used VDJFasta [9], a bioinformatics Perl extension, to explore the V-D-J
recombinations from the sequences and to align the V-D-J segments. The
percentage match of each IGHV sequence to germline gene with the highest
homology was measured and, accordingly, somatic hypermutation was calculated
to be the percentage difference from the corresponding germline gene.
Clonality assessment
For clonality assessment, nucleotide sequences were clustered based on
CDR3 similarity. Sequences with immunoglobulin genes CDR3 region similarity
(identical or related) and using the same V and J gene segments represented
clonal clusters.
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Immunodiversity
Clonal clusters (clonotypes) were ordered from the largest to the smallest thereby
creating a cumulative frequency distribution. Diversity index, D10, was calculated
as the highest copy number clonotypes that make up 10% of the total sequences.
D10=C/S x 100
Where C is the minimum number of distinct largest clones that make up 10% of
total sequences and S is the total number of distinct clones.
RESULTS
Three MGUS and 3 HC were included in this study. The MGUS patients had an
average age of 60 (range 53-66) and HC had an average age of 58 (range 53-61).
The MGUS patients had monoclonal protein concentration averaging 17.1g/L
(range 12.9- 22.8g/L). The duration of MGUS follow-up is shown in figure 1A. All
MGUS cases had poor response to vaccination as they had low H1N1-specific IgG
titers that remained low after vaccination (Figure 1B). Recognizing that we have
evaluated merely three samples, our results should be considered as descriptive,
as a definitive conclusion cannot be drawn.
IGHV and IGHJ classification
After filtering for quality, alignment of sequences to IGH germline genes and
translational rescue, samples yielded an average of 420 744 sequences. The
number of reads per HC samples ranged from 203 724 to 558 151 while for MGUS
they ranged from 420 580 to 491 382 sequences.
We compared the IGH repertoire in 3 MGUS with that in 3 HC. For each individual,
the IGHV and IGHJ gene usage was calculated. The diversity of the IGHV gene
usage and IGHJ gene usage in MGUS was comparable to HC at baseline. VH genes
used by these MGUS cases were derived from all 7 human IGHV gene families. The
most dominant IGHV gene family was IGHV1, 37.85% followed by IGHV3, 30.4%;
IGHV2, 18.9%; IGHV4, 9.9%; IGHV5, 1.5%; IGHV7, 1.4% and lastly IGHV6, 0.1%.
This IGHV family gene usage was comparable to HC where IGHV3, IGHV2, IGHV4,
IGHV5, IGHV6 and IGHV7 accounted for 34.2%, 32.4%, 25.8%, 6.1%, 1.3%, 0.5%
and 0.1% of the repertoire respectively with IGHV7 usage being the least frequent
in HC. When we considered the individual IGHV genes in MGUS, IGHV1-69 (12.7%),
followed by IGHV2-5 (12.5%), IGHV1-18 (10.1%) and IGHV3-23 (6.02%) were the
most frequent (Figure 2A). However, in HC the most frequently used IGHV genes
were IGHV2-5, IGHV1-18, IGHV1-69 and IGHV3-30 that represented 21.4%, 16.4%,
9.2% and 7.7% respectively, of all the potentially functional VH genes identified. At
day 7 post-influenza vaccination, there was a slight shift in the IGHV gene usage.
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Figure 1. A) MGUS patients included in the study had high monoclonal protein B) as well as
poor H1N1-specific IgG responses at day 0, day7- and day 28 post-vaccination
The most frequently used IGHV genes at day 7 in MGUS were IGHV1-18 (15.4%),
IGHV1-69 (13.7%), VH3-30 (9.02%) and IGHV1-58 (7.5%). In HC, IGHV2-5 (24.5%) was
the most frequently used at day 7 post-vaccination, followed by IGHV3-30 (13.8%),
IGHV2-70 (7.9%) and IGHV3-53 (5.6%) (Figure 2B).
When we analysed the IGHJ gene usage, The IGHJ repertoire was similar
between MGUS and HC. IGHJ4 was predominantly used in both MGUS (56%) and
HC (57.4%) IgG repertoire. At day 7 post-vaccination, IGHJ4 still dominated the
HC IgG repertoire (49.5%) followed by IGHJ5, IGHJ6, IGHJ3, IGHJ2 and IGHJ1
(Figure 2C). However, a slight increase in the IGHJ6 usage was noted for MGUS,
with IGHJ4 representing 41% of the repertoire while IGHJ6 usage increased to 35%.
IGH gene hypermutation
We next performed comparative analysis of somatic hypermutation patterns
between HC and MGUS. However, Illumina sequencing may introduce errors in
sequences, with substitution error rate per nucleotide of 0.001% [10]. However, this
is lower than the estimated somatic hypermutation rate of approximately 0.1% [11].
B CELL REPERTOIRE DIVERSIFICATION IN MONOCLONAL GAMMOPATHY...
Because all the samples were sequenced at the same time, we therefore assume
that the error rate is constant in all sequences.
By aligning the sequences to the reference germline genes, the frequency of
mutations in the IgG repertoire was quantified. At baseline, HC show average
mutational frequency of 6.6% when mutations were measured relative to the
reference germline sequence. The IgG repertoire in MGUS showed mutational
frequency averaging 7.4% at baseline (Figure 3A). Furthermore, MGUS baseline
repertoire has a higher number of reads with >8% mutations (39%) in comparison to
HC (27%). An increase in mutational frequencies in MGUS is likely to indicate more
frequent immune activation as somatic hypermutation is highest in IgG memory
B cells and allows for the generation of high-affinity antibodies. However, our
sample size is not big enough to draw definitive conclusions. Vaccination did not
result in an overall change in mutational frequencies in the HC IgG repertoire at day
7 post-vaccination (Figure 3A, 3B). The overall mutational frequency in MGUS was
comparable to HC at day 7 post-vaccination. While the overall distribution seemed
to be largely comparable between HC and MGUS, we found differences for reads
with a lower number of mutations. There was an increase in day 7 sequences (52.1%
of sequences) with lower mutational frequencies of 2-6% in comparison to baseline
repertoire (37%) (Figure 3C). Silent v non-silent mutations were investigated in HC
and MGUS. Silent (synonymous) mutations do not result in the replacement of
amino acids, as opposed to non-synonymous mutations. However, the frequency
of both silent and non-silent mutations was comparable between HC and MGUS
at both time points (data not shown).
Clonality
We quantified the effect of sequence diversification by analyzing the number of
clones and also clone size. At baseline, the average clone size was comparable
between HC and MGUS; with the HC averaging 36 sequences per clone and MGUS
also averaging 36. Vaccination was associated with a decrease in the average clone
size in the HC IgG repertoire at day 7 post-vaccination; average 21.4. This is related
to an increase in the proportion of smaller clone sizes at day 7. However, in 2 of
the 3 MGUS cases, an increase in the average clone size was observed at day 7
post-vaccination (Figure 4A). This indicates accumulation of greater numbers of
larger clones. Clone sizes of 100- 1 000 show an increased accumulation in MGUS
in comparison to HC. At day 7 post-vaccination, clones of sizes 100- 1 000 averaged
7.7% of all clones in MGUS which is an increase from an average of 4.2% at baseline
(Figure 4B, 4C). In HC clones of sizes 100- 1 000 averaged 3% at day 7; which is
a decrease from 4.1% at baseline. In the remaining MGUS case, a decrease in the
average clone size was seen which was comparable to HC.
We further investigated the clonality of the IgG repertoire by quantifying the
fraction of sequences represented by the biggest clone at baseline and at day 7
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A
B
C
Figure 2. IGHV and IGHJ gene usage. The relative frequencies of individual IGHV gene usage were
calculated for each individual A) at day 0 and B) at day 7 post-vaccination were identified from the
immunoglobulin gene sequences using VDJ Fasta. C) IGHJ family gene usage in HC (dark columns,
day 0 followed by day 7) were compared to MGUS (grey columns, day 0 then day 7). One sequence per
clone was chosen to represent each clonotype. The graphs show mean and error bars represent ±SEM.
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117
post-vaccination. At baseline, the biggest clones were of comparable size between
HC (average 3.7%) and MGUS (average 3.5%). Following vaccination, the biggest
clone in the HC IgG repertoire decreased and accounted for an average of 1.8% of
the sequences. However, in MGUS an increase in the clone size was observed with
the biggest clone representing an average of 10.5% of the repertoire (Figure 4D).
To investigate whether there is decreased diversity (increased clonality) of the
repertoire, we further looked at the minimal number of clones that make up at least
10% of the IgG repertoire. We assumed that the most abundant clones at day 7
post-vaccination are the clones that expand in response to vaccination. There was
6
Figure 3. IGHV somatic hypermutation frequencies at baseline and changes induced by
vaccination. Mutations for each read were defined as the number of mismatches to germline
reference V, D and J genes. A) The average mutational rate (%) of sequences from 3 HC and 3
MGUS patients at day 0 and day 7 post-vaccination. Error bars represent ±SEM. B) Sequences
from HC and C) MGUS were grouped according to the level of SHM and the proportion of each
mutational frequency group calculated.
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comparable repertoire diversity between HC and MGUS prior to vaccination as
similar frequency of clones account for at least 10% of the repertoire. However, a
trend to an increase in diversity of the IgG repertoire was observed in HC at day
7 post-vaccination with increased number of clones accounted for at least 10% of
the repertoire (Figure 4E). This implies that vaccination resulted in expansion of
more but smaller sized clones in HC. In contrast to HC, MGUS showed a decrease
Figure 4. Differences in clonality of the HC and MGUS IgG IGHV repertoire in response to
vaccination. A) The average clone size was calculated for HC and MGUS at day 0 and day 7 postvaccination. Clones were grouped by clone size and the proportion of each group was calculated
for the 3Hc and 3 MGUS patients B) before and C) 7 days after vaccination. D) The biggest
clone size as well as the E) diversity of most dominant clones that represent at least 10% of the
repertoire (D10) was calculated at day 0 and day 7 post-vaccination. Error bars represent ±SEM.
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119
in the diversity of clones that made up at least 10% of the repertoire. In MGUS,
there is a decrease in repertoire diversity day 7 post-vaccination in comparison
to baseline as well as in comparison to HC. This small pool of diversity is due to
expansion of a few distinct large clones in MGUS in response to vaccination. This
implies that the IgG B cell diversity of cells that respond to vaccination is limited.
DISCUSSION
In this study, we evaluated the B cell response in MGUS using illumina paired-end
sequencing. We investigated the IgG IGHV repertoire from PBMCs using RNA from
3 MGUS and 3 HCs. We utilized the 2010/2011 TIV as antigen challenge in order to
investigate the IgG B cell responses following vaccination. To analyze the vaccineinduced changes in repertoire we used samples from day 7 post-vaccination since
plasmablast response peaks around day 7 [12]. Of interest is whether the reduced
IgG response to influenza vaccination in MGUS is due to a decrease in repertoire
diversity; whether immune suppression and the repeated immune stimulation by
unrelated antigens limits the repertoire available to respond to vaccine challenge.
We observed variations between the IgG B cell repertoire of MGUS and HC in
response to influenza vaccination. We showed that HC responded with diverse B cell
populations, whereas MGUS presented with a more restricted B cell repertoire at day
7 post-vaccination. In MGUS, the increase in average clone size was related to the
accumulation of greater numbers of larger clone sizes. The distribution of clones in
MGUS was different from that observed in HC as fewer but larger clones encompassed
up to 10% of the of the total sequence reads. In agreement with this, the largest clone
sizes in MGUS were at least 2 times the size of HC. The most abundant clones at
day 7 after TIV vaccination likely resemble memory-derived IgG plasmablasts that
are increased in the circulation at that time [12]. The decreased diversity of clones
in response to influenza vaccination may therefore restrict the antibody response
in MGUS. Furthermore, higher mutational frequencies in the baseline repertoire of
MGUS may limit optimal affinity maturation of the antibodies in the face of antigenic
challenge. The higher mutational frequencies are likely due to longer or more
frequent exposures to antigen in MGUS. Because we analysed the peripheral B cell
compartment, we expect that the IgG repertoire contains recirculating memory B cells
that have encountered a variety of antigens and are likely to contain high mutations
in comparison to a more naïve/ less antigen experienced repertoire.
We analysed IGHV gene usage in order to determine whether usage of
particular gene families or individual genes is associated with skewing of the MGUS
IgG antibody repertoire. Comparison of peripheral B cells of MGUS with those
of HC did not reveal significant bias in IGHV and IGHJ family usage. This is not
surprising considering that the MGUS-specific clone makes up a minor part of the
peripheral repertoire in a subset of MGUS unlike in MM where there is increased
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detection of monoclonal MM cells in blood. The most dominant clones in the
MGUS peripheral repertoire accounted for 3.5% of all the reads therefore they
cannot cause a significant gene usage bias.
Because we used RNA for analyzing the immunoglobulin sequences, and
plasma cells are known to produce up to a 1000 fold more RNA than resting
B cells, bias towards picking up the same plasma cells several times over may be
expected. However, since the HC and MGUS samples did not show a difference
in their total IgG positive cells as well as plasmablasts before and after vaccination
and the samples were all analysed at the same time under the same conditions, we
do not expect the bias to affect one group more than the other.
More samples need to be included in order to explore the variations in
clonality as well as the clonal diversification between MGUS and HC in response
to vaccination. In summary, our study demonstrates normal IGHV gene usage in
MGUS. However, a decrease in the diversity of expanded clones in response to
TIV was observed in MGUS.
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Tete SM, Wilting KR, Horst G, Klijn MA,
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8. Magoc T, Salzberg SL. FLASH: fast length
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D, Huerta G, Mehta GR, et al. Precise
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repertoire. Proc Natl Acad Sci U S A
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10. Loman NJ, Misra RV, Dallman TJ,
Constantinidou C, Gharbia SE, Wain J, et
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CHAPTER
Summary and discussion
Sarah M. Tete
7
SUMMARY AND DISCUSSION
125
IMMUNE ALTERATIONS AND VACCINATION IN MONOCLONAL
GAMMOPATHY OF UNDETERMINED SIGNIFICANCE
Monoclonal gammopathy of undetermined significance (MGUS) is known to be
associated with aging where immunosenescence advances as a common feature.
Indeed, MGUS predominantly affects the elderly, with a median age of diagnosis
of 70 [1]. However, it has been recently established that MM almost invariably arises
from preceding MGUS [2,3]. Even so, not all cases of MGUS progress to MM or
related plasma cell proliferative disorders. In the MGUS-MM transition, a number
of changes in the bone marrow microenvironment where the non-malignant MGUS
clone is maintained most likely occur. Among these, there is evidence that loss of
immune control is implicated in malignant transition [4].
It is still a challenge to predict which MGUS cases will progress to a malignant
gammopathy following diagnosis, when a ‘watch and wait’ clinical decision
is implemented. However, there are several clinical markers that are used as
guidelines for monitoring MGUS progression, as treatment is not currently an
option. Based on the levels of monoclonal protein, excess free light chains and
monoclonal protein isotype, the risk of progression is stratified [5]. Identifying
the MGUS patients who will progress will clearly benefit from early preventative
therapeutic intervention, and this is currently a major goal in disease management.
Understanding the immune system and microenvironment in MGUS therefore has
a great clinical relevance. How the MGUS clone influences the immune system, in
both progressive and non-progressive MGUS, is largely unknown.
In Chapter 2 we review the status of immune alterations in MGUS as well as MM.
There is immune dysfunction in MGUS that increases as the monoclonal gammopathy
progresses to active MM. The intrinsic defect in the production of immunoglobulins
presents as hypogammaglobulinaemia that accelerates with disease progression
[6]. Significant decrease in circulating CD19+ B cells is a prominent finding with this
depression correlating with disease stage [7,8]. Furthermore, increased monoclonal
protein is associated with the increased accumulation of clonal plasma cells in the
bone marrow and elevated production [9]. The clonal plasma cells progressively
replace the normal bone marrow plasma cells and are also found in the circulation
as disease progresses. There are also aberrations in dendritic cell (DC) and T cell
counts as well as function that will impact on the B cell response [7,8,10]. As a
result of immune dysfunction, infections are a frequent occurrence in MGUS and
MM [11-13]. Also of consideration is that MGUS and MM typically affect an older
population who are affected by age-related immunosenescence, so a combination
of therapy, age and disease-related alterations in the immune system contribute
to the increased risk of infections in these patients.
In patients with hematological malignancies, the degree of immunosuppression
and exposure to immunosuppressive therapy is variable and also data concerning
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efficacy of vaccination in these patients varies. With respect to the underlying
disease and the immunosuppressive treatment, safety and efficacy of vaccines
is of considerable importance. Protective efficacy of conventional vaccination
is questionable in patients with acquired immunodeficiency as in MM as they
display an array of immune dysfunctions, which may influence their response to
conventional vaccination. The loss of immune capacity in MM is evident in studies
that investigated the response to influenza, pneumococcal and Haemophilus
influenza type b (Hib) vaccination [14-16]. The goal of vaccination is to decrease
the risk of infections as well as the associated morbidity and mortality. The available
evidence on the efficacy of vaccination in both MGUS and MM is as yet inadequate.
Thus far, no vaccination studies have been carried out systematically in the early
stage of monoclonal gammopathy, in MGUS.
In Chapter 3, we therefore investigated the impact of MGUS on the humoral and
cell-mediated response to vaccination with trivalent inactivated influenza vaccine
(TIV). MGUS patients present with immune response with striking variability.
However, this is not surprising considering that MGUS patients are a heterogeneous
group with variations in the duration of the condition and also covering a spectrum
from healthy persons with stable and low monoclonal protein concentrations to
patients that border transformation to MM. Indeed, some have influenza H1N1specific IgG titers as well as H1N1-specific IFN- -secreting cell frequencies that are
comparable to healthy controls. Remarkably, MGUS with high monoclonal protein
had lower influenza H1N1-specific IgG titers, which they failed to expand postvaccination. Contrary to HCs, MGUS patients revealed impaired T-cell responses,
as the number of IFN- -secreting cells did not increase post-vaccination. Further
expanding on the IgG response, MGUS achieved seroprotection rates (37%) that
were low compared to healthy age-matched adults (58%) for H1N1 (Chapter 4).
This response parallels the overall IgG response with correlations being observed
between the HI titer and serum IgG levels at day 28 post-vaccination. In chapter 4,
we went further to investigate whether the inferior response to influenza vaccination
in high monoclonal protein MGUS was associated with an alteration in memory
B cell response. Notably, high monoclonal protein in MGUS is associated with
lower numbers of IgG secreting memory B cells. MGUS reveal a restricted
influenza-specific memory B cell response that may impair the maintenance of
serologic memory. The decrease in the frequency of IgG+ cells within the IgDCD27+ compartment may explain the poor serum antibody response and also the
restricted memory B cell response to influenza vaccination in high monoclonal
protein MGUS. A decrease in naïve, IgD- CD27+ switched memory B cells as
well as a decrease in plasma cells has been reported with age. Consequently,
vaccination has limited success with poor antibody responses to vaccination being
elicited. Influenza vaccination is of limited efficacy in aging as there is a decrease in
influenza-specific antibody generation [17-19]. Seroprotection against influenza is
SUMMARY AND DISCUSSION
reduced in the aging population. Indeed, in adults aged 60-74 years seroprotection
is 41- 58%, and 29-46% in those aged over 75 years. This is low in comparison to
young adults were seroprotection rates are >70% [20]. Since the seroprotection
rates are lower in MGUS in comparison to age matched healthy controls, MGUS
is an important factor influencing the outcome of vaccination and not the age of
the vaccinees.
There was a degree of compensation for the poor IgG response in MGUS, with an
increased involvement of IgM memory and perturbations in the IgM repertoire, as
judged in response to vaccination at day 7. Nonetheless, the IgM response in MGUS
was not sufficient to achieve seroprotective antibody titers (hemagglutination
inhibition titers >40). IgM+IgD+CD27+ B cells have been considered responsible for
the secretion of low-affinity natural antibodies in healthy adults [21, 22]. Therefore,
this possibly explains the poor seroprotective antibody titers in MGUS despite the
high IgM levels. Our studies suggest dysfunction of long-term serologic memory
and indicate the importance of functional B cell response for protection against
infection. Studies that investigated the status of serologic antibody responses to
staphylococcal, moraxella, pneumococcal and varicella zoster antigens showed
depressed background antibody levels in MGUS and MM [23].
B CELL REPERTOIRE IN MGUS AND VACCINATION INDUCED
REPERTOIRE PERTURBATION
Because B cell dysregulation is associated to the B cell repertoire, we analysed
B cell diversity in response to influenza vaccination in MGUS contrasting them to
age-matched HCs. In Chapter 5, we assessed the B cell repertoire by amplifying
the CDR3 region of the immunoglobulin heavy chain variable (IGHV) region gene
and assayed the CDR3 size distribution by spectratyping. HCs typically have a
diverse IGHV repertoire at day 0, and in response to vaccination clonal expansions
are evident at day 7 with the repertoire resolving by day28 post-vaccination. It
has been previously demonstrated by spectratyping that the B cell repertoire
is compromised in the elderly. The changes associated with aging involve the
oligoclonal expansions of cells and a collapse in the diversity of the B cell repertoire.
This loss in B cell repertoire diversity correlates with a general phenotype of frailty
[24]. A study of combined influenza and pneumococcal vaccination in the elderly
(>70 years) showed that the a decreased B cell repertoire diversity, as measured by
spectratyping, correlated with impaired IgA and IgM anti-pneumococcal antibody
responses [25].
The MGUS B cell repertoire in our study showed inter-individual variability
with up to 50% showing oligoclonality in at least one of the three immunoglobulin
isotypes studied. Indeed, these cases presented with oligoclonal spectratype
profiles. The clonal expansions in the periphery contribute to the limited repertoire
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and poor antibody response in MGUS. Furthermore, circulating MGUS clonal
plasma cells can be detected by spectratyping in a small subset of patients.
Circulating clonal (‘tumor’) plasma cells are present in up to 20% of MGUS patients
[26,27] and spectratyping can detect these clonal cells in this subset of MGUS.
Circulating clonal plasma cells have been previously detected in both MGUS and
MM and they could be part of the malignant plasma cell compartment which has
the potential to re-circulate to new location and spread disease. This could explain
the increased frequency of circulating myeloma plasma cells in progressive disease
and the dissemination throughout the bone marrow [28].
Not only was high monoclonal concentration in MGUS associated with poor
influenza-specific IgG responses, but also with a more oligoclonal IgG and IgA
response at day 7 post-vaccination that suggests that the clonal response in MGUS
is limited to restricted antigen-responding B cell clones. In Chapter 6, we expanded
our B cell repertoire analysis by massive parallel sequencing of the IgG IGHV
repertoire using next generation sequencing and specifically focusing the analysis
on MGUS with high monoclonal protein. In agreement with the spectratyping data,
there was an oligoclonal accumulation of larger clones in the MGUS repertoire that
also relates to the increase in average clone size. Furthermore, there was a decrease
in the IGHV diversity of the clones that expanded in response to vaccination. The
higher mutational frequencies seen in the baseline MGUS repertoire are likely
due to longer or more frequent exposures to antigen. We expect that the IgG
repertoire contains recirculating memory B cells that have encountered a variety
of antigens and are likely to contain high mutations in comparison to a more
naïve/ less antigen experienced repertoire. Prospective studies are necessary
to investigate the memory B cell response and memory maintenance in MGUS.
These studies need to be able to identify influenza-specific memory B cells after
a first round of vaccination as well as after a second round of vaccination with the
same influenza antigen a year later. A recent study has shown that haemagglutinin
specific B cells can be sorted by flow cytometry thus allowing further repertoire
IGHV gene analysis [29].
MONOCLONAL PROTEIN: THE MGUS CLONE PROMOTING
IMMUNE DYSFUNCTION
With seminal findings establishing that MGUS precedes MM and that MGUS
patients will develop malignant monoclonal gammopathy at the rate of 1% per year,
the influence of the MGUS clone on the immune host function is of importance.
Clonal MGUS plasma cells accumulate in the bone marrow and may affect normal
plasma cells at this site. The concentration of monoclonal protein most likely reflects
clonal plasma cell accumulation levels in the bone marrow. The decrease in serum
IgG levels and appearance of hypogammaglobulinaemia in MGUS may be related
SUMMARY AND DISCUSSION
Figure 1. B cell repertoire is altered in MGUS. The MGUS IgG repertoire is more clonal at
baseline (circle size represents clonal size). Oligoclonality of the repertoire is evident in MGUS
and (day 7) following influenza vaccination, the recruited repertoire is significantly perturbed in
with a few expanded clones dominating the response.
to this competitive replacement of long lived bone marrow plasma cells from
their bone marrow niche by the expanded MGUS clone [9]. Mature bone marrow
plasma cells contribute significantly to serum immunoglobulin levels [30] and their
displacement from niches may therefore explain the lower IgG levels in some
MGUS subjects. The proportion of normal bone marrow plasma cells has been
shown to be predictive for the progression of MGUS as well as disease outcome
in MM [31]. During normal B cell activation or plasma cell differentiation, antigen,
activation strength and co-stimulatory factors may regulate the entrance into pool
of long-lived plasma cells. Theses bone marrow plasma cells have higher affinity
than corresponding memory B cells [32]. However, the number of bone marrow
niches is limited and have been shown to be functionally impaired with age [33,34].
The MGUS clone can impact on immune function specifically, for instance
with the autocrine synthesis of IL-6 [35]. In comparison to HCs, IL-6 levels have
been reported to be increased in MGUS. IL-6 is immunosuppressive to DCs [36]
by interfering with their maturation and antigen presenting capacity. DCs have a
central role in the initiation and coordination of the immune response to influenza,
inducing T cell proliferation. Increased IL-6 may therefore inhibit Th1 responses.
This may explain the poor Th1 response in high monoclonal protein MGUS.
Immunosurveillance has a role in controlling the stepwise progression of the
MGUS clone [4]. It is also conceivable that the immune response against specific
antigens in MGUS play a role in limiting the repertoire available to respond to
vaccination and explain the oligoclonality seen in the MGUS baseline repertoire
129
7
130
CHAPTER 7
in our observations. Chronic immune activation leads to formation of new plasma
cells hence more competition for survival niches [32]. This may however shorten
the longetivity of resident bone marrow plasma cells. Chronic immune activation
may also exhaust the ability of the memory B-cell repertoire to generate expansion
responses to vaccination [37,38]. A consequence of the limited B cell diversity
available to respond to viral challenge is that few clones dominate the response
to influenza vaccination (chapter 6).
We therefore speculate that monoclonal protein concentration in MGUS reflects
the level of underlying immune suppression, with the increase in monoclonal
protein being associated with the gradation of immune suppression. As a result,
immune responses are poor and vaccination is less effective.
FUTURE PERSPECTIVES: IMPROVING INFLUENZA VACCINE
EFFICACY IN MGUS
The goal of vaccination is to decrease the risk of infections and associated morbidity
and mortality. Influenza specific IgG responses are decreased in high monoclonal
protein MGUS: in the light of poor influenza-specific responses in MGUS, as shown
in this thesis, more effective vaccinations are required to provide protection from
influenza, and other infectious agents that compromise disease management.
For favorable clinical outcomes, it is important to introduce vaccination at the
right time to the appropriate patient group. MGUS are a heterogeneous group
with the duration of condition as well as the monoclonal protein concentration
varying considerably between individuals. Therefore, influenza vaccination should
be recommended early in MGUS as it may be beneficial; especially to the low
monoclonal protein MGUS cohort. Other than the low number of participants in our
study that may limit definitive conclusions, another limitation was that we studied
only the immune response to vaccination but not the vaccine clinical efficacy in
preventing laboratory confirmed influenza illness.
Boosting vaccination can be promising for improving protection at early stages
of monoclonal gammopathies where priming is inadequately immunogenic.
Therefore, re-vaccination may provide protection as immune dysfunction is less
severe compared to the more advanced stages of active disease. Furthermore,
adjuvants may benefit the activation of the innate immune system so as to enhance
humoral and cellular immune responses. There is a defect in both the innate and
adaptive arms of the immune system in monoclonal gammopathies that affect
vaccine efficacy. Adjuvants increase the level of inflammatory mediators at the site
of injection and can stimulate DCs and CD4+ T cell priming [39-41]. TLR agonists
as adjuvants could reverse the defective Th1 response seen in high monoclonal
protein MGUS. TLR agonists such as GLA-SE can stimulate DCs to produce Th1promoting cytokines such as TNF- , IL-1 , IL-6 and IL-12 [42,43]. The oil-in-water
SUMMARY AND DISCUSSION
131
emulsion-based adjuvant, AS03A is highly immunogenic, enhancing the antibody
and CD4+ T cell mediated responses to vaccination [44] and inducing long term
protection [45].
In light of the poor immune response in MGUS and MM, it is fundamental to
understand the underlying immune defects before effective vaccination strategies
to optimize immunogenicity can be developed. Other than the conventional
split and subunit influenza vaccines, new vaccines are under development that
promising opportunities to modify vaccine design in order to activate specific
immune pathways to counter influenza infection. Similar strategies may enhance
immunity in MGUS and MM to other infectious agents important in disease. For
these interventions, it will be crucial to fully understand the relationship between
the tumor clone (pre-malignant and malignant) and immune microenvironment.
The studies presented in this thesis are a step in this direction.
7
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Nederlandse samenvatting
Sarah M. Tete
8
NEDERLANDSE SAMENVATTING
137
ALTERATIES VAN HET IMMUUNSYSTEEM EN VACCINATIE IN
MONOKLONALE GAMMOPATHIE VAN ONBEPAALDE
BETEKENIS (MGUS)
Monoklonale gammopathie van onbepaalde betekenis (MGUS) wordt vaak
geassocieerd met veroudering waarbij immunosenescence een veelvoorkomend
kenmerk is. MGUS komt inderdaad overwegend voor bij ouderen met een mediane
leeftijd bij diagnose van 70 jaar[1]. Echter is onlangs vastgesteld dat multipel
myeloom (MM) bijna steevast voortkomt uit voorgaande MGUS[2, 3]. Niet alle
gevallen van MGUS evolueren naar MM of aanverwante plasmacel proliferatieve
stoornissen. Bij de MGUS-MM overgang zullen een aantal veranderingen in het
micromilieu van het beenmerg, waar de niet-maligne MGUS kloon zich bevind,
ontstaan. Er zijn onder andere aanwijzingen dat een verlies van de werking van het
immuunsysteem zicht voortdoet tijdens deze kwaadaardige overgang[4]. Het is nog steeds een uitdaging om te voorspellen welke MGUS gevallen zich
zullen ontwikkelen naar een kwaadaardige gammopathie zodra na de diagnose een
klinische observatie wordt uitgevoerd. Er zijn echter verschillende klinische markers
die worden gebruikt als richtlijnen voor het monitoren van de voortgang van MGUS,
omdat behandeling op dit moment geen optie is. het risico van ziekte progressie
is gelaagd op basis van het niveau van het monoklonaal eiwit, de concentratie van
vrije lichte ketens en het isotype van het monoclonale eiwit [5]. Het identificeren
van de MGUS patiënten die zich ontwikkelen tot MM zullen duidelijk profiteren
van vroege therapeutische interventie, hetgeen op dit moment een belangrijke
doelstelling van de ziektebehandeling. Het begrijpen van het immuunsysteem
en het micromilieu van MGUS patiënten is dan ook van grote klinische relevantie.
Hoe de MGUS kloon invloed heeft op het immuunsysteem, in zowel progressief
en niet-progressieve MGUS, is grotendeels onbekend. In Hoofdstuk 2 behandelen we de status van immuun alteraties in MGUS
evenals MM. Er is een dysfunctie van het immuunsysteem in MGUS dat toeneemt
naarmate de monoklonale gammopathie zich verder ontwikkeld tot actieve
MM. Het intrinsieke defect in de productie van immunoglobulines resulterend
in hypogammaglobulinaemia versnelt zich met de ziekteprogressie[6]. Een
significante daling in CD19+ B cellen is een opvallende observatie, die correleert
met de ziekte fase[7, 8]. Verder wordt de verhoogde concentratie van monoklonaal
eiwit gekoppeld aan de toegenomen accumulatie van klonale plasmacellen in
het beenmerg [9]. De klonale plasmacellen vervangen stapsgewijs de normaal
beenmerg plasma cellen en zijn ook te vinden in de bloedcirculatie zodra de
ziekte vordert. Er zijn ook afwijkingen in de dendritische cellen (DC) en T cellen
aantallen en werking, die van invloed zijn op de B cel-respons[7, 8, 10]. Ten gevolge
van immuunsysteem dysfunctie zijn infecties een veel voorkomend verschijnsel in
MGUS en MM[11-13]. Hierbij moet ook in overweging worden genomen dat MGUS
8
138
CHAPTER 8
en MM doorgaans ouderen treft waarbij leeftijdsgebonden immunosenescence
ook een rol speelt, waardoor een combinatie van therapie, leeftijd en ziektegerelateerde veranderingen in het immuunsysteem bijdragen aan het verhoogde
risico op infecties bij deze patiënten.
Bij patiënten met hematologische maligniteiten is de mate van immunosuppressie
en blootstelling aan immunosuppressieve therapie een variabele. Ook gegevens
over de effectiviteit van vaccinatie bij deze patiënten verschilt per onderzoek. Met
betrekking tot de onderliggende ziekte en de immunosuppressieve behandeling
is de veiligheid en de effectiviteit van vaccins hierbij van groot belang. De
beschermende werkzaamheid van conventionele vaccinatie is twijfelachtig bij
patiënten met verworven immuundeficiëntie zoals in MM, gezien het feit dat
ze een scala aan immuun-dysfuncties vertonnen die van invloed kunnen zijn
op hun reactie op conventionele vaccinatie. Het verlies van immuun capaciteit
in MM is aangetoond in studies die onderzoek deden naar de reactie op griep,
pneumokokken en Haemophilus influenzae type b (Hib-) vaccinaties[14-16]. Het
doel van vaccinatie is verminderen van het risico op infectie, alsmede de daarmee
samenhangende morbiditeit en mortaliteit. De beschikbare gegevens over de
werkzaamheid van vaccinatie bij zowel MGUS en MM is nog onvoldoende . Tot op
heden zijn er geen vaccinatie studies verricht in de vroege fase van monoklonale
gammopathie: MGUS.
In Hoofdstuk 3 zijn wij daarom nagegaan wat het effect is van MGUS op de
humoraal en celgemedieerde respons op vaccinatie met trivalent geïnactiveerde
influenza vaccin (TIV). MGUS patiënten lieten een opvallend grote variatie zien in
hun immuun respons. Dit is echter niet verwonderlijk aangezien MGUS patiënten
een heterogene groep vertegenwoordigen met variaties in de duur van de
aandoening en breed spectrum beslaan van gezonde personen met stabiele en
lage monoklonale eiwit concentratie tot aan patiënten die op de grens zijn van
een overgang naar MM. Enkelen hadden inderdaad influenza H1N1-specifieke
IgG-titers evenals H1N1-specifieke aantallen van IFN- -afscheidende cellen
die vergelijkbaar zijn met gezonde controles. Opvallend is dat MGUS gevallen met
een hoog monoklonaal eiwit lagere influenza H1N1-specifieke IgG-titers hadden
die zij niet meer vermenigvuldigden post-vaccinatie. In tegenstelling tot gezonde
controles bleken MGUS patiënten een verminderde T-cel respons te hebben,
omdat het aantal IFN- -afscheidende cellen niet was toegenomen na de vaccinatie.
Verder bleek dat MGUS gevallen een laag seroprotectie percentage (37 %) hadden
in vergelijking met gezonde leeftijdsgenoten (58 %) voor H1N1 ( Hoofdstuk4). Deze
reactie evenaarde de totale IgG-respons met correlaties tussen de HI titer en de
serum IgG concentratie op dag 28 na de vaccinatie. In hoofdstuk 4 gingen we verder
onderzoeken of de mindere respons op influenza vaccinatie bij hoge monoklonale
eiwit MGUS samen hing met een verandering in de B-geheugencellen respons. Met
name hoge monoklonaal eiwit MGUS bleek samen te hangen met lagere aantallen
NEDERLANDSE SAMENVATTING
IgG-afscheidende B-geheugencellen. MGUS liet een beperkte influenza-specifieke
B-geheugencel respons zien dat afbreuk zou kunnen doen aan de handhaving van
het serologische geheugen. De daling in de frequentie van de IgG+ cellen binnen
het IgD-CD27+ compartiment kan zowel de slechte antilichamen respons in het
serum verklaren als ook de beperkte B-geheugencel respons op influenza vaccinatie
bij hoge monoklonale eiwit MGUS. Een afname van de naïeve B-cellen, IgD-CD27+
veranderende B- geheugencellen en de plasmacellen is gedocumenteerd bij
veroudering. Dientengevolge heeft vaccinatie een beperkt succes met een
slechte antilichamen respons op deze vaccinatie. Influenza vaccinatie is van
beperkte effectiviteit in ouderen vanwege een afgenomen productie van influenzaspecifieke antilichamen [17-19]. Seroprotectie tegen influenza is dan ook lager in de
oudere bevolking. Bij volwassenen van 60-74 jaar is de seroprotectie percentage
tussen de 41 - 58 %, en 29 tot 46% bij personen ouder dan 75 jaar. Dit is laag in
vergelijking met jonge volwassenen die een seroprotectie percentage kennen van
>70%[20]. Aangezien de seroprotectie percentages lager zijn in MGUS gevallen
in vergelijking met gezonde controles van dezelfde leeftijd blijkt dat MGUS een
belangrijkere invloed heeft op het resultaat van de vaccinatie dan de leeftijd van
de gevaccineerde.
Er was een zekere mate van compensatie voor de slechte IgG-respons in
MGUS, met een grotere betrokkenheid van het IgM-geheugen en de verstoring
van het IgM-repertoire, zoals beoordeeld in de reactie op vaccinatie op dag 7.
Echter was de IgM-respons in MGUS onvoldoende om seroprotectieve antilichaam
titers (hemagglutinatie inhibitie titers >40) te bereiken. IgM+IgD+CD27+ B cellen
worden verantwoordelijk geacht voor de secretie van natuurlijke antistoffen met
een lage affiniteit bij gezonde volwassenen [21, 22]. Dit verklaart wellicht de slechte
seroprotectieve antilichaam titers in MGUS ondanks de hoge IgM concentratie.
Onze studies duiden op een disfunctie van het lange termijn serologische geheugen
en wijzen op het belang van een functionele B cel respons voor bescherming tegen
infectie. Studies die onderzoek deden naar de status van serologische antilichaam
responsen op van staphylococcus, moraxella, pneumokokken en varicella zoster
antigenen toonden verminderde achtergrond antilichamen in MGUS en MM [23]. B CEL REPERTOIRE IN MGUS EN VACCINATIE OPGEWEKTE
REPERTOIRE VERSTORINGEN Omdat B cel disregulatie gekoppeld is aan het B cel repertoire, hebben wij een
analyse gedaan van de B cel diversiteit in de respons op influenza vaccinatie in
MGUS door deze te vergelijken met gezonde controles van dezelfde leeftijd.
In Hoofdstuk 5 hebben wij het B cel repertoire geëvalueerd door te focussen op
de CDR3 regio van de immunoglobuline zware keten variabele (IGHV) regio gen
en het evalueren van de distributie van de CDR3 groottes middels spectratyping.
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Gezonde controles hebben meestal een divers IGHV repertoire op dag 0, en in
reactie op de vaccinatie is klonale expansie zichtbaar op dag 7 en keert de normale
repertoire distributie terug op dag 28 na vaccinatie. Het is al eerder aangetoond
middels spectratyping dat het B cel repertoire is aangetast bij ouderen. De
veranderingen die worden geassocieerd met het verouderingsproces zijn o.a. de
oligoklonale expansie van cellen en de ineenstorting van de diversiteit van het
B cel repertoire. Dit verlies van B cel repertoire diversiteit correleert met een
algemeen fenotype van zwakheid [24]. Een studie van gecombineerde influenza en
pneumokokken vaccinatie bij ouderen ( >70 jaar) toonde aan dat een afgenomen
B cel repertoire diversiteit, zoals gemeten middels spectratyping, correleert met
een slechte IgA en IgM anti-pneumokokken antilichaam responsen [25].
Het MGUS B cel repertoire in onze studie toonde een interindividuele
variabiliteit waarvan op tot 50 % oligoklonaliteit liet zien in ten minste één van de
drie bestudeerde immunoglobuline isotypes. deze gevallen toonden inderdaad
oligoklonale spectratype profielen. De klonale expansie in de periferie droegen bij
aan het beperkte repertoire en de slechte antilichaamrespons in MGUS. Bovendien
kunnen circulerende MGUS klonale plasmacellen worden gedetecteerd
door spectratyping in een kleine subset van patiënten. Circulerende klonale
(‘tumor’) plasmacellen waren aanwezig in 20% van de MGUS patiënten [26,
27] en spectratyping kan deze klonale cellen detecteren in deze subset van
MGUS. Circulerende klonale plasmacellen zijn al eerder gedetecteerd in zowel
MGUS en MM en zij zouden onderdeel kunnen zijn van het maligne plasma cel
compartiment dat het potentieel bezit om te recirculeren naar een nieuwe locatie en
zo de ziekte te verspreiden. Dit zou een verklaring kunnen zijn voor de verhoogde
frequentie van de circulerende myeloom plasmacellen in progressieve ziekte en
de verspreiding van deze cellen in het beenmerg [28]. Hoge monoklonale concentratie in MGUS hangt niet alleen samen met slechte
influenza-specifieke IgG-responsen, maar tevens ook met een meer oligoklonale
IgG en IgA respons op dag 7 na de vaccinatie die erop zouden wijzen dat de
klonale respons in MGUS beperkt is tot beperkte antigeen-reagerende B cel
klonen. In Hoofdstuk 6 hebben we onze B cel repertoire analyse uitgebreid
door massieve parallelle sequencing van het IgG IGHV repertoire middels
next generation sequencing en onze analyse specifiek te richten op MGUS
met hoog monoklonaal eiwit. In overeenstemming met de spectratyping
gegevens was er een oligoklonale accumulatie van grotere klonen in het MGUS
B-cel repertoire dat tevens samenhangt met de toename van de gemiddelde
kloongrootte. Bovendien was er een daling in de IGHV diversiteit van de klonen
die uitdijden in reactie op de vaccinatie. De hogere mutationele frequenties die
te zien zijn in het baseline MGUS B-cel repertoire zijn waarschijnlijk het gevolg van
langere of meer frequente blootstelling aan het antigeen. Wij nemen aan dat het
IgG-repertoire recirculerende B geheugencellen bevat die verschillende antigenen
NEDERLANDSE SAMENVATTING
zijn tegen gekomen en waarschijnlijk hoge mutaties bevatten in vergelijking met
een meer naïef/ minder antigeen ervaren repertoire. Toekomstige studies zullen nodig zijn om onderzoek te doen naar de
B-geheugencel respons en de geheugen handhaving in MGUS. Deze studies
zullen influenza-specifieke B-geheugencellen moeten kunnen identificeren na de
eerste ronde van vaccinatie evenals na de tweede ronde van de vaccinatie met
dezelfde influenza-antigeen een jaar later. Een recente studie heeft aangetoond
dat hemagglutinine specifieke B cellen kunnen worden gesorteerd middels
flowcytometrie waardoor verdere IGHV genen repertoire analysering mogelijk
is [29].
In het licht van de slechte immuunrespons in MGUS en MM is het van groot
belang om inzicht te krijgen in de onderliggende immuun gebreken voordat
effectieve vaccinatie strategieën ter optimalisering van de immunogeniciteit
ontwikkeld kunnen worden. Naast de conventionele gesplitste en subunit influenza
vaccins zijn er nieuwe vaccins in ontwikkeling met veelbelovende mogelijkheden
voor het modificeren van het vaccin design om zodoende specifieke immuun routes
te activeren die de influenza infectie bestrijden. Soortgelijke strategieën kunnen
ook bijdragen tot een betere immuniteit ten opzichte van andere infectieuze
agentia die een belangrijke rol spelen in MGUS en MM. Voor deze interventies is
het belangrijk om volledig inzicht te krijgen in de relatie tussen de tumor kloon
(pre-maligne en maligne) en het immuun-micromilieu. De studies gedaan in dit
proefschrift zijn reeds een stap in deze richting.
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Acknowledgements -Dankwoord
Sarah M. Tete
&
ACKNOWLEDGEMENTS -DANKWOORD
147
ACKNOWLEDGEMENTS
After a long 4 years adventure that brought me here to Groningen, the journey
is over. As great as it feels to see all the chapters finished, it feels even better for
me to look back at the journey and realize how many great individuals inspired me
and gave me encouragement throughout my PhD. I express my gratitude to all the
people who helped me through and I will not forget how important you were to
my professional up build but also to my personal life.
To my promoter, Prof Nicolaas Bos, I am grateful that you gave me this
opportunity to work with you. I have learnt a great deal from you: You fed my
scientific curiosity, and allowed me to develop as an independent researcher. Thank
you for your unlimited support and enthusiasm. Your enthusiasm overflows that you
sometimes can get sucked up in it as you light up to share your ideas. I began to
understand that being enthusiastic is believing in what you are working on, meeting
challenges and willing to work hard to achieve your goals.
I would also like to thank my co-promoter, Dr Surinder Sahota. You saw potential
in me and you took the risk of supervising me as well recommending me to Prof
Nico Bos considering that I was coming straight from my Bachelor studies in
Pharmacology and jumping right into the deep end of PhD research. I have learnt
and developed a lot while working in your lab. You provided me with a vibrant and
a success oriented research environment. I will always be grateful for your generous
support and guidance.
Dear Dr Marc Bijl, I am extremely grateful for the guidance and constant support
you gave me in setting up my project. This clinical study would not have succeeded
without your help. You always motivated me and pushed me to work harder. I was
sad to see you move to Martini ziekenhuis even though you were still a stone throw
away. However, you have not ceased to be supportive and inspirational till the end.
Thank you for your positivity.
To the “vaccination team”, thank you for your enthusiasm. With your support
and a lot of hard work, I have accomplished more than I expected.
To Dr Hannie Westra, thank you for constant support throughout the journey.
You were always there when I had questions or needed anything in the lab, thank
you for your time. I also appreciate the time you took to review my manuscripts.
To Dr Aalzen de Haan, thank you for your enthusiasm and scientific curiosity. You
always gave me something to think about during the numerous vaccination meetings.
I appreciate the time you took to review my manuscript. Amongst other things, you
made me know what ‘quick and dirty’ means and also the idiom and gesture of licking
the index finger and sticking it in the air. It was my great pleasure to interact with you.
To Gerda Horst, I am grateful for the time you took to familiarize me with the
lab and also for teaching me some techniques. Thank you for your warmness and
kindness. It was a pleasure to work with you.
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ACKNOWLEDGEMENTS -DANKWOORD
To Dr Sander van Assen, I appreciate the advice you gave me during our weekly
meetings. I have learnt a lot from you and you made me understand how much
work a clinical study involves. I thank you for support.
To Dr Kasper Wilting, I am grateful to you for all the support and help you gave
me from the beginning of my project. Your involvement in the participant selection
and vaccination is greatly appreciated. It was a pleasure to work with you.
To Prof Hanneke Kluin-Nelemans, I am grateful to you for helping with MGUS
cohort selection and advice you gave in setting up this study.
Many thanks to Prof Anke Huckriede for producing and supplying the influenza
antigens I used in my project. I am also grateful for the time you took to revise
the manuscripts.
I would also like to express my gratitude to Dr Deborah Dunn-Walters
for being a source of inspiration and for giving me the opportunity to learn
Spectratyping in your lab. I would also like to thank Dr Bryan Wu for the
technical support you provided me as I performed experiment in your lab at
Guys hospital, London.
I would also like to thank Dr Rene Benne, Heleen Feikens and members of the
lab for accommodating at the Infectieziekte lab. I thank you for the assistance
provided to complete my HI experiments. Special thanks to Gioia Smid for the
day to day supervision and wonderful company during the time I spent there.
To Dr Graeme Cowan, I am grateful for the collaboration in my project and
advice. I enjoyed my visit to Edinburgh and having the opportunity to pick each
other’s brains. I appreciate the time and effort you took to write the scripts on
Pearl for data analysis. I enjoyed working with you and I hope we will continue to
collaborate in the future.
The wonderful people from the POLI Reumatology, you have helped a lot during
the influenza vaccination. Thank you for your help.
Joke Hellinga, thank you for helping with the blood drawing and sample
collection.
Melissa Newling, thank you for the great work you put in the project. You are
a wonderful person and a pleasure to work with. Most importantly, thank you for
accompanying me through this journey till my defense. I greatly appreciate your
help. I wish you luck in your studies and I hope you find what you are looking for.
Nicky and Deb at Southampton hospital Cancer Sciences, thank you for your
technical support and advice as well as stuffing me with delicious cakes every time.
Dear Niels, it was a great pleasure to work with you. I have learnt a lot from
you during my phD. I wish you success in your career, for you the sky is the limit.
Futhermore, I thank you for your friendship. I enjoyed the many lunches we shared
together. Dr Liesbeth Brouwer and Prof Mieke Boots, it was a great pleasure
working with you. I appreciate all the feedback and discussions we had thoughout
my time in Groningen. Thank you for your support.
ACKNOWLEDGEMENTS -DANKWOORD
Nishath, your intelligence astounds me. You are more than a friend. In all you are
a mother and a sister to me. You taught me perseverance and to believe in myself
above all people. Your heart is full of love and you are always open to give and share
with anyone in your path. When I moved to Groningen with nowhere to stay, you
opened your heart and house to me and made it a home to share with me. Over
the years I have known you to be an insightful lady who values her family. Despite
leaving your husband and sons behind in Oman, you managed to make it through
the 4years. Your true beauty is first inward, and your true strength is found in your
poise, thoughtfulness, intelligence and self-assurance. I enjoyed the time we spent
together, sharing the office with you has been an experience. I have learnt a lot
of things about research and human nature from you than you can ever imagine.
Thank you from your friendship and never-ending advice J I will never forget your
kindness. I wish you success in your career. Noone can stand in your way.
To my friends Eelke and Divya, thank you for your kindness and encouragement.
Having you to talk to during stressful times has been a blessing. Let your creativity
and determination pave a great future for you. Success! Good luck!
I would like to thank all my colleagues and fellow PhD students over the past
4 years. Dear Prof Koese, Monireh, Annie, Lisa, Sylvia, Gwenny, Erlin and Jolien,
thank you for your company and support. It was great to have people to talk to on
the 11th floor considering the rest of the department was located far in the hospital.
Thank you for your help Johan. You were always kind and easy to approach. Nato,
Alexander, Nynke, Paulina, Deena, Nikola, Qi, Fleur, Koen, Christien, thank you
for your encouragement and kind words. Minke and Wayel, I am grateful for the
support and advice you gave me with FACS experiments. I wish you all success
in the future.
I would also like to say a big thank you to my family for I would not have been
here without your love and support. It is challenging to write it down as there are
so many things to be grateful for.
To my dearest mother, thank you for your never ceasing love. You are always
there to support and encourage me. I am aware of the sacrifices you made to bring
me up, you made me who I am today. ´Thank you` seems inadequate for all that
you have done for me. You always taught me the values of education and that with
hard work you bear success. You encouraged me to aim higher, always. Now we
can laugh about the countless hours spent at work and the never-ending work, but
at the time it was hard. More importantly, you have made me appreciate the value
of family, for with their love I feel fulfilled. Your love knows no distance. Thank you
for being you, mother.
Mainini Margi, thank you for your love and support. Knowing that there is
someone who looks out for me makes the distance bearable.
During my phD, I met the most wonderful person, Gerber. I feel blessed to have
you supporting me in every decision I make. I cannot imagine having come this far
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ACKNOWLEDGEMENTS -DANKWOORD
without you. Thank you for the time you took in helping me with the final stages
of my thesis. I appreciate you always being there when I needed to ´rant`. When I
feel low, you always lift me up. Thank you for your love and always believing in me.
Thank you for being my strength and my rock. Jij bent mijn alles en zelfs nog meer!
Dearest Hendrikus and Dineke, thank you for welcoming me like I am one of
yours. Your hearts are full of love. Whenever I come visit, you always make me feel
at home. I can always look up to you and I appreciate the love and support you
give me.
Lieve Opa en Oma van Erven, ik ben echt dankbaar dat jjullie in mijn leven zijn.
Uw liefde is eindeloos. Ik kijk altijd uit om tijd met jullie door te brengen. Uw thuis
en harten zijn altijd open. Dank u voor uw liefde en steun.
To my dearest Sylvia and Michel Boeting. I couldn’t miss all those countless
meetings in the city for anything. Your friendship means a lot to me. I have enjoyed
every moment we spent, Sylvia, you are more like a sister to me. You are always full
of love and encouragement. As to our time in Groningen, I say Donovans misses
us. Thank you for your limitless love and support. I am sure Max Kimutai will grow
into a charmer and break a few hearts. I wish blessings upon your family.
My dear Elizabeth, I feel blessed to have you in my life. You are always full of
words of encouragement and support. We have spent countless years together;
we studied together, shared a house and worked together. Over the years you
became more of a sister than just a friend. I wish you and my new brother-in-law a
life filled with happiness. Thank you for your love and encouragement.
To my great friends Marlene and Jolvie, we have shared a lot of ´fresh air`
together. You and your other halves made my life in Groningen even more
wonderful. You are always full of life. Thank you for being there for me. Do come
and visit any time.
To Playtorn, you are always very welcoming and cheerful. Thank you for inviting
me into your home. I enjoyed every moment I spent with you and your family. It’s a
pity I did not have enough time to spend with your beautiful and clever daughters
while I was still in Groningen. I hope we meet again and share some laughter in
the near future.
To my paranymph and friend, Thembile, thank you for your friendship and
warmth. I am grateful to have you to share this adventure with. I wish you success
in your PhD.
To George, Mustapha, Jenneke, Alpha, Musa, Samie, Karin, Rumbi, Ketty, Rita,
Nunu, Sarah, Alice, Sunil, Smitha, Laverne and all my friends in Groningen, thank
you for your warm friendships.
Thank you, Ndinotenda, Dankjewel
Sarah