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Diabetes Care Volume 37, August 2014
Leukocyte Profiles Differ Between
Type 1 and Type 2 Diabetes and Are
Associated With Metabolic
Phenotypes: Results From the
German Diabetes Study (GDS)
Barbara Menart-Houtermans,1,2
Ruth Rütter,1,2 Bettina Nowotny,1
Joachim Rosenbauer,2,3 Chrysi Koliaki,1,2
Sabine Kahl,1,2 Marie-Christine Simon,1,2
Julia Szendroedi,1,2,4 Nanette C. Schloot,1
and Michael Roden,1,2,4 for the German
Diabetes Study Group*
Diabetes Care 2014;37:2326–2333 | DOI: 10.2337/dc14-0316
OBJECTIVE
Altered immune reactivity precedes and accompanies type 1 and type 2 diabetes.
We hypothesized that the metabolic phenotype relates to the systemic cellular
immune status.
PATHOPHYSIOLOGY/COMPLICATIONS
RESEARCH DESIGN AND METHODS
A total of 194 metabolically well-controlled patients with type 1 diabetes (n = 62,
mean diabetes duration 1.29 years) or type 2 diabetes (n = 132, 1.98 years) and 60
normoglycemic persons underwent blood sampling for automated white blood
cell counting (WBC) and flow cytometry. Whole-body insulin sensitivity was measured with hyperinsulinemic-euglycemic clamp tests.
RESULTS
Patients with type 2 diabetes had higher WBC counts than control subjects along
with a higher percentage of T cells and activated T helper (Th) and cytotoxic T (Tc)
cells but lower proportions of natural killer (NK) cells. In type 1 diabetes, the
percentage of activated Th and Tc cells was also higher compared with control
subjects, whereas the ratio of regulatory T (Treg) cells to activated Th cells was
lower, suggesting diminished regulatory capacity. Parameters of glycemic control
related positively to Treg cells only in type 2 diabetes. Upon age, sex, and body
mass adjustments, insulin sensitivity correlated positively with monocytes, while
circulating lipids correlated positively with T cell subsets in type 1 diabetes.
CONCLUSIONS
Immune cell phenotypes showed distinct frequencies of occurrence in both diabetes types and associate with insulin sensitivity, glycemia, and lipidemia.
Hyperglycemia defines both type 1 and type 2 diabetes irrespective of the different
underlying pathogenesis. In type 1 diabetes, T cell–mediated b-cell destruction
accompanied by islet-directed autoantibodies persists for a variably long period
until hyperglycemia occurs (1). In addition, innate immunity is upregulated and
systemic immune markers are altered, which may affect b-cell function (2,3). Altered
immune reactivity also accompanies and precedes type 2 diabetes and its associated
complications by mechanisms related to subclinical inflammation (4). Although adipose tissue and innate immune cells contribute to increased release of cytokines
1
Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine University, Düsseldorf,
Germany
2
German Center for Diabetes Research, Partner
Düsseldorf, Düsseldorf, Germany
3
Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes
Research at Heinrich-Heine University, Düsseldorf,
Germany
4
Department of Endocrinology and Diabetology,
University Clinics Düsseldorf, Heinrich-Heine University, Düsseldorf, Germany
Corresponding author: Michael Roden, michael.
[email protected].
Received 2 February 2014 and accepted 13 April
2014.
Clinical trial reg. no. NCT01055093, clinicaltrials
.gov.
This article contains Supplementary Data online
at http://care.diabetesjournals.org/lookup/
suppl/doi:10.2337/dc14-0316/-/DC1.
N.C.S. and M.R. contributed equally to this study.
*A full list of German Diabetes Study Group
members can be found in the APPENDIX.
© 2014 by the American Diabetes Association.
Readers may use this article as long as the work
is properly cited, the use is educational and not
for profit, and the work is not altered.
care.diabetesjournals.org
and chemokines, cell types responsible
for subclinical inflammation in type 2 diabetes remain to be precisely defined (5).
White blood cell (WBC) count has
long been used for the diagnosis of inflammatory diseases. A recent systematic meta-analysis reported higher WBC
counts in persons with than without
type 2 diabetes (6). Of note, patients
with poorly controlled diabetes have a
greater risk for infections and atherosclerosis (7), both being independent
causes or consequences of inflammation and abnormal WBC.
Recent analyses addressed the role of
pro- and anti-inflammatory immune cell
subsets in diabetes with a focus on regulatory T (Treg) cells, which can downregulate and modulate proinflammatory or
autoimmune cellular immunity (8,9). In
type 1 diabetes, function or life span of
Treg cells was found to be increased (10),
decreased (8,9,11), or unchanged (12,13).
This discrepancy is likely due to differences in disease duration and progression
as well as methodological aspects (12,14).
Similarly, the few published studies on
type 2 diabetes reported either decreased (15,16) or unchanged (9) frequencies of Treg cells.
Here, we tested the hypothesis that
the systemic cellular immune status relates not only to type of diabetes but
also to the metabolic phenotype. To
this end, we analyzed patients of the prospective observational German Diabetes
Study (GDS), which consecutively includes patients with recently diagnosed
diabetes at adult age, aiming at characterization of their phenotypes and monitoring their disease progression.
RESEARCH DESIGN AND METHODS
Participants
Patients aged 18–69 years with either
type 1 or type 2 diabetes are recruited
for the ongoing GDS. General inclusion
criteria of GDS are new-onset type 1 or
type 2 diabetes (diabetes duration ,12
month) and age between 18 and 69
years. Exclusion criteria of GDS are pregnancy; diabetes other than type 1 or
type 2; clinical coronary artery disease;
hepatic, renal, psychiatric, or addictive
diseases; or immunosuppressive treatment. Diagnosis of type 1 diabetes is
based on ketoacidosis with immediate insulin substitution, detection of at least
one islet cell–directed autoantibody (islet
cell autoantibody, GAD, islet antigen-2
Menart-Houtermans and Associates
antibody) or of C-peptide (C-Pep) below
the detection limit. Those characterized
as type 2 diabetic patients are tested to
be islet antibody negative and have a
typical history of type 2 diabetes presenting with hyperglycemia and are not
requiring immediate insulin treatment.
GDS patients are reinvestigated 5 and
10 years after their first visit.
For the current study, 194 patients (62
type 1 and 132 type 2 diabetic, diabetes
duration #5 years) of the GDS were consecutively included between February
2011 and May 2012. Mean duration
of diabetes here was 1.29 6 1.85 years
for type 1 diabetic and 1.98 6 2.25 years
for type 2 diabetic patients (P = 0.035).
Healthy volunteers (n = 60) were fulfilling
the inclusion and exclusion criteria of
GDS except for the presence of diabetes.
They underwent a standardized 75-g oral
glucose tolerance test to exclude dysglycemia. All participants gave written informed consent for the study protocol,
which was approved by the ethics board
of Heinrich-Heine University.
Laboratory Methods
Automated blood cell count for leukocytes including lymphocytes, monocytes, and granulocytes was performed
on the Sysmex KX21 (Sysmex Corporation,
Kobe, Japan). Fasting blood glucose (FBG)
was measured by the hexokinase method
(Epos analyzer 5060; Eppendorf, Hamburg,
Germany), C-Pep chemoluminimetrically
(Immulite 1000; Siemens, Erlangen, Germany) and hemoglobin A1c (HbA1c) using
high-pressure liquid chromatography (Varianz II; Bio-Rad Laboratories, Richmont,
CA). Plasma total cholesterol (TC), HDL
and LDL cholesterol, and triglycerides
(TG) were measured at the Institute for
Clinical Chemistry and Laboratory Diagnostic at the University Clinics Düsseldorf with
standardized methods.
Hyperinsulinemic-Euglycemic Clamp
Test
For assessment of insulin sensitivity, a
subgroup of 114 type 2 and 52 type 1
diabetic patients and 29 normoglycemic
control subjects underwent a clamp
test. No participants consumed alcohol
for at least 24 h, ingested food for 10–12 h,
or smoked for at least 8 h before the clamp.
Patients also stopped their glucoselowering medication for at least 3 days
or their regular insulin after the evening
dose before the day of the clamp (17).
As part of the GDS study, patients
underwent an intravenous glucose tolerance test prior to the clamp test (18). The
hyperinsulinemic-euglycemic clamp
was started with a priming insulin dose
(10 mU z [kg body wt]21 z min21 for 10 min)
followed by continuous insulin infusion of
1.5 mU z (kg body wt)21 z min21, corresponding to 66 mU/m2 z min (Insuman
Rapid; Sanofi, Frankfurt, Germany). Blood
glucose concentrations were measured
every 5 min and maintained at 5 mmol/L
with a variable intravenous 20% dextrose infusion. In healthy control subjects, primed continuous insulin infusion
(40 mU/m2 z min) was used. Rates of
whole-body insulin sensitivity are given
as mean glucose infusion rates (M value:
mg glucose z kg21 z min21) per individual
mean plasma insulin concentrations (I: mU
insulin z L21) during steady state (M/I).
Characterization of Leukocytes
Fresh venous blood was drawn in the
morning into sodium-heparin tubes
from fasted individuals and examined
within 2 h. Leukocytes were analyzed
by FACS and flow cytometry using a
dual laser FACSCalibur cytometer (Becton
Dickinson, Heidelberg, Germany) and
Cellquest software (Becton Dickinson).
Briefly, blood cells were stained with
fluorescence-conjugated antibodies in
four different colors. After lysis of erythrocytes (Lysis buffer; Becton Dickinson)
and two washes, stained PBMC were
resuspended and fixed with CellFIX
(BD Biosciences). Twenty thousand lymphocytes were collected in a forward
scatter/side scatter (FSC/SSC) lymphocyte gate and saved together with the
monocytes and granulocytes. The flow
cytometer was calibrated daily with appropriate single-stained samples for setting compensation, and acquired data
were analyzed by FlowJo software (version 7.6.1; TreeStar, Inc., Ashland, OR).
The following fluorescence-conjugated
antibodies were used to identify cell populations: CD3 (T cells), CD4 (T helper cells
[Th cells]), CD8 (cytotoxic T cells [Tc
cells]), CD14 (monocytes), CD19 (B cells),
CD25 (activated/regulative T cells [Treg
cells]), CD56 (natural killer cells [NK/
NKT cells]) (all from BD Biosciences,
Heidelberg, Germany), CD183 (Th1
cells), CD194 (Th2 cells), CD103 (integrin on Treg cells) (all from BD Pharmingen, Heidelberg, Germany), and
CD127 (FoxP3 cells) (BioLegend, San
Diego, CA).
2327
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Leukocyte Phenotyping in Diabetes
Statistical Analysis
Data are presented as means 6 SD or
as individual data and median values.
Comparisons between groups were done
using the nonparametric Kruskall-Wallis
test followed by the Dunn test. ANCOVA
was performed to compare groups adjusting for the potentially confounding
variables age, sex, and BMI. A closed
testing procedure was applied for adjusted pairwise comparisons. All reported significant differences between
groups are results of the adjusted analyses unless stated otherwise. Spearman
nonparametric correlations and partial
correlations adjusted for age, sex, and
BMI were estimated. Two-sided P values
#0.05 were considered to indicate statistical significant differences. All analyses were performed using GraphPad
PRISM 4 (GraphPad Software, San
Diego, CA) and IBM SPSS software (version 21, 2013; SPSS, Chicago, IL).
RESULTS
Anthropometric and Metabolic Data
Type 2 diabetic patients were older and
had higher BMI, fasting C-Pep, TC, LDL,
and TG but lower HDL than type 1 diabetic and control subjects (Table 1).
Type 2 and type 1 diabetic patients
had higher FBG and higher HbA1c than
control subjects. Whole-body insulin
sensitivity (M/I, expressed as mg
glucose z kg21 z min21/mU insulin z L21)
was 66% lower in type 2 diabetic
(0.042 6 0.025) and 45% lower in type
1 diabetic (0.067 6 0.035) than in control subjects (0.122 6 0.072; KruskalWallis test: P , 0.001; Dunn multiple
comparison test: type 2 diabetic vs.
type 1 diabetic P , 0.001, type 2 diabetic
vs. control P , 0.001, type 1 diabetic vs.
control P , 0.05).
Diabetes Care Volume 37, August 2014
Table 1—Patient data
T2D
N subjects
Sex (male/female)
T1D
CON
132
62
60
86/46
37/25
35/25
34 6 11
Age (years)
53 6 12*†
38 6 12
BMI (kg/m2)
32 6 7*†
26 6 6
25 6 4
FBG (mg/dL)
133 6 40*
134 6 50*
79 6 11
FBG (mmol/L)
7.5 6 2.5*
7.2 6 2.3*
4.4 6 0.6
HbA1c (%)
6.7 6 1.1*
6.7 6 1.0*
5.1 6 0.4
HbA1c (mmol/mol)
C-Pep (ng/mL)
49 6 13*
3.4 6 1.5*†
50 6 10*
1.5 6 1.3
32 6 4
1.7 6 0.8
191 6 36
TC (mg/dL)
215 6 38*†
189 6 40
HDL cholesterol (mg/dL)
48 6 14*†
62 6 21
65 6 22
LDL cholesterol (mg/dL)
137 6 36*†
113 6 37
111 6 33
TG (mg/dL)
194 6 128*†
104 6 57
105 6 61
Data are means 6 SD unless otherwise indicated. Anthropometric and metabolic data of type 2
diabetic (T2D) patients, type 1 diabetic (T1D) patients, and healthy control subjects (CON). *P #
0.05 vs. control, †P # 0.05 vs. type 1 diabetic.
NK Cells, B Cells, and T Cells Gated on
Lymphocytes
NK cells are identified by their CD56 positivity and are part of the innate immune
system owing to their ability to rapidly
lyse infected cells at the first encounter
without prior immunization. Type 2 diabetic patients had lower proportions of
CD32CD56+ NK cells than type 1 diabetic
patients (P = 0.037) and control subjects. In the total study population, NK
cells associated positively with age (r =
0.161, P # 0.01) and negatively with sex
(r = 20.24, P # 0.001), indicating higher
values for men. CD19+ B cells belong to
the adaptive immune system and are
responsible for the humoral immune response by the production of specific
WBC Count
After adjustment for age, sex, and BMI,
type 2 diabetic patients had more leukocytes (P # 0.001 and P # 0.001), lymphocytes (P # 0.001 and P = 0.005), and
granulocytes (P = 0.004 and P # 0.001)
than type 1 diabetic patients and control subjects, whereas there were no
differences between type 1 diabetic
and control subjects (Fig. 1A–C). Monocyte counts were higher in type 2 than
in type 1 diabetic patients (P = 0.006)
but comparable in control subjects
(Fig. 1D).
Figure 1—Leukocyte subtypes in type 2 diabetic (T2D) patients (triangles), type 1 diabetic (T1D)
patients (squares), and control (Con) subjects (circles) analyzed by differential blood cell count.
Scatter plots show individual data with medians; P values refer to comparison of data adjusted
for age, sex, and BMI. **P # 0.01, ***P # 0.001.
care.diabetesjournals.org
antibodies. Numbers of CD19+ B cells did
not differ between groups. The frequency of CD3+ T cells, the main cell subset of cell-mediated specific immunity,
was higher in type 2 than in type 1 diabetic patients (P = 0.038), with no differences in other group comparisons.
Males had fewer CD3+ T cells than females (P # 0.001) in all groups combined (Supplementary Table 1).
Th Cells, Tc Cells, and NKT Cells
Upon contact with the first antigen, immature T cells develop to CD4+ Th cells
or CD8+ Tc cells, both being key players
in the adaptive immune system. The
CD4+/CD8+ ratio can be used to describe
the immune balance in immune disorders such as HIV or autoimmune diseases. In our study, proportions of
CD4+ Th cells were higher (P # 0.001),
whereas those of CD8+ Tc cells were
lower (P = 0.002) in type 2 diabetic patients than in control subjects. These differences were lost after adjustment for
age, sex, and BMI, mainly due to opposing correlation with age (CD4: r = 0.337,
Menart-Houtermans and Associates
P , 0.001; CD8: r = 20.286, P , 0.001)
(Supplementary Fig. 1). NKT cells act at
the interface of the innate and adaptive
immune system. Upon activation, NKT
cells produce large amounts of cytokines
(interleukin [IL]-2, IL-4, interferon-g, tumor necrosis factor [TNF]a), and impaired
function of this cell type contributes
to the development of autoimmune diseases. In our investigations, the percentage of NKT cells did not differ between
groups (data not shown). Th cells were
further classified into proinflammatory
Th1 and anti-inflammatory Th2 cells according to their surface epitopes, chemokine receptors CXCR3 (CD183) and CCR4
(CD194). After adjustment for age, sex,
and BMI, the proportion of CD183+ Th1
cells was not different between type 2
diabetic and control subjects but was
higher in type 1 diabetic compared with
control subjects (P = 0.007) (Fig. 2A).
CD194+ Th2 cells were not different between the groups, while double-positive
CD183+CD194+ Th cells were more frequent in both type 2 diabetic (P = 0.005)
and type 1 diabetic (P # 0.001) than in
control subjects.
Activated Th Cells, Treg Cells, and
FoxP3+ Treg Cells
Subsets of Th cells (CD4+) were gated for
surface expression of CD25, the IL-2 receptor a-chain, which is expressed in
association with CD127, the a-chain of
the receptor of IL-7 (14,19). Intensity of
CD25+ staining distinguishes activated/
effector (CD4 + CD25 + ) and regulatory
T cells (CD4+CD25++), while low or negative staining of CD127 identifies positivity for the intracellular transcription
factor, FoxP3 (Forkhead box protein 3:
CD4+CD25++CD1272 ) (14). Regulatory
T cells suppress immune responses
by a cell contact–dependent mechanism
or by secretion of cytokines (IL-10,
transforming growth factor-b). The frequency of CD4+CD25+-activated Th cells
was higher in type 2 diabetic (P , 0.001)
and type 1 diabetic (P , 0.001) than in
control subjects (Fig. 2B). Also, the subset of CD4+CD25++ Treg cells was slightly
higher in type 2 diabetic (P = 0.046) and
Figure 2—A: The percentage of CD 183+ Th1 cells was increased in type 1 diabetic (T1D) patients versus control (Con) subjects. B and C: CD4+ CD25+
activated and CD4+ CD425++ Treg cells of CD4+ Th cells were increased in type 2 diabetic (T2D) patients and T1D patients versus control subjects.
D: Gated out of CD25+ activated Th cells, CD1272 FoxP3 cells of activated Th cells were lower compared with control subjects. CD183+ proinflammatory Tc1 cells (E) and CD25+ regulatory Tc cells (F) gated out of CD8+ Tc cells were increased in type 2 diabetic patients versus control subjects
and in type 1 diabetic patients versus control subjects. The differences between the diabetes groups did not reach significance. Data shown as scatter
plots with medians. P values refer to comparison of adjusted data. *P # 0.05, **P # 0.01, ***P # 0.001.
2329
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Leukocyte Phenotyping in Diabetes
clearly higher in type 1 diabetic (P =
0.005) compared with control subjects
(Fig. 2C). The percentage of FoxP3 +
Treg cells of activated Th cells tended
to be lower in type 2 diabetes (P =
0.052) and was lower in type 1 diabetes
(P = 0.017) compared with control subjects (Fig. 2D). Various regulatory immune cell types associated positively
with age and/or BMI in the different cohorts (Supplementary Table 1).
Activated and Regulatory Tc Cells
CD8+ Tc cells were further classified into
CD8+ Tc1 cells with Th1-like and CD8+
Tc2 cells known for a Th2-like cytokine
secretion pattern. Although CD8+ Tc cell
count was similar in all groups after adjustment of the data, proinflammatory
CD8+CD183+ Tc1 cells were more frequent in type 2 diabetic (P # 0.001)
and type 1 diabetic (P = 0.006) than in
control subjects (Fig. 2E). Percentage of
CD8+CD25+ regulatory Tc cells was also
higher in type 2 diabetic (P = 0.023) and
type 1 diabetic (P = 0.007) subjects after
adjustment for age, sex, and BMI
(Fig. 2F). On Treg cells, we further examined the expression of integrin aEb7
(CD103), a type I transmembrane glycoprotein binding to E-cadherin and mediating homing of lymphocytes to sites
of inflammation. After adjustment,
type 2 diabetic patients exhibited
higher frequency of CD103 + cells of
CD4+CD25++ Treg cells (3.4% vs. 1.7%,
P = 0.045) and of CD8+CD25+ Treg cells
(10.8% vs. 9.9%, P = 0.02) than control
subjects. There were no differences between type 1 diabetic patients and control subjects (data not shown).
Correlation Analyses of Immune
Parameters
Out of the described 21 immune cell
subsets, 16 correlated with age, 7 with
sex, and 14 with BMI in all groups combined (Supplementary Table 1). Because
of the higher age and BMI at the onset of
disease in type 2 diabetes and overall
more male than female participants in
the groups (Table 1), we performed partial correlation analyses after adjustment for age, sex, and BMI.
In type 2 diabetic patients, the proportion of Treg cells and their subgroup
of FoxP3 Treg cells associated positively
with parameters of glycemia, FBG, and
HbA1c. Activated T cells correlated negatively with HDL and positively with TG.
Leukocyte, lymphocyte, and monocyte
Diabetes Care Volume 37, August 2014
counts exhibited weak positive correlations with C-Pep. Furthermore, M/I was
positively associated with T cells and
CD103+ Treg cells (r = 0.190, P = 0.046,
and r = 0.366, P # 0.001). All correlations between immune cells and metabolic parameters are shown in Table 2.
In type 1 diabetic patients, monocyte counts related positively to M/I
(r = 0.469, P = 0.003) (Supplementary
Fig. 2) and negatively with HDL (r =
20.364, P # 0.05), while total leukocyte and lymphocyte counts were not
correlated with metabolic parameters.
Granulocyte count associated positively
with C-pep. The frequency of CD3 +
T cells associated negatively with HDL
and positively with TG. CD4+ Th cells
correlated positively and CD8+ Tc cells
negatively with TC. Anti-inflammatory
CD194+ Th2 cells and double-positive
CD183+CD194+ Th cells, but not Treg
cells, were positively associated with
HbA 1c . All correlations between immune cells and metabolic parameters
in type 1 diabetic patients are shown
in Table 2.
Finally, M/I negatively correlated
with FBG (r = 20.352, P # 0.001),
HbA1c (r = 20.235, P = 0.013), C-Pep
(r = 20.36, P # 0.001), and TG (r =
20.298, P # 0.001) but positively with
HDL (r = 0.367, P # 0.001) in type 2 but
not in type 1 diabetic patients.
CONCLUSIONS
This study demonstrates upregulation
of cellular immune activity in both metabolically well-controlled type 2 and
type 1 diabetes patients despite short
disease duration. Long-standing type 2
diabetes is frequently accompanied by
subclinical inflammation (20,21). While
our finding of increased total WBC as
well as lymphocytes, monocytes, and
granulocytes counts in new-onset type
2 diabetic patients is in agreement
with a recent meta-analysis (6), our
study extends these observation by
demonstrating distinct associations of
WBC with metabolic parameters.
We report that the number of total
leukocytes in type 2 diabetes associates
positively with BMI, C-Pep, and LDL and
the number of monocytes correlates negatively with FBG. Even more interesting is
the positive correlation of ambient glycemia (as assessed by FBG and HbA1c), with
anti-inflammatory CD4+CD25++ Treg cells
and CD4+CD25++CD1272 FoxP3 cells. The
regulation of nutrient uptake and use is
critically important for the control of immune cell number and function (19).
While quiescent T cells mainly use oxidative phosphorylation to generate ATP,
they switch from phosphorylation of glucose, amino acids, and fatty acids to the
more glycolytic metabolism during T-cell
activation, cytokine production, and
memory development (22). Of note,
CD4+ T-cell subsets show distinct metabolic differences in that Treg cells are
the least glycolytic cell type of CD4+ T cells
but exhibit greater lipid oxidation and mitochondrial membrane potential (22). In
our study, percentages of regulatory
T cells correlate positively with parameters
of glycemia but not of lipidemia. As reported, glucose lowering by medication
or gastric banding surgery can decrease
WBC and improve immune cell-mediated
inflammation (23,24). Taken together,
the observed positive relationship of
Treg cells with FBG and HbA1c is in line
with the contention that hyperglycemia
specifically affects the immune system
in type 2 diabetes.
In our type 2 diabetic patients, insulin
sensitivity correlated positively with the
adhesion molecule CD103 on regulatory
Th cells. Insulin resistance, defined by
reduced glucose disposal (M/I) to skeletal muscle and liver, not only is typical
for type 2 diabetes but may also occur in
long-standing type 1 diabetes (25,26).
Not only chronic blood glucose (glucose
toxicity) (27) but also lipid elevation
(lipotoxicity) drives the insulin resistance in both diabetes types (28). Here,
we confirm the inverse relationship of
glycemia with M/I for recent-onset type
2 diabetes, which has previously been
reported mainly for longer-standing diabetes (29,30). The absence of such relationships in our type 1 diabetes cohort
is likely due to the short duration of hyperglycemia until disease onset, while
subclinical hyperglycemia generally
exists long before the clinical manifestation of type 2 diabetes. In addition, subclinical inflammation can contribute to
insulin resistance in type 2 diabetes
(30,31), but less is known about its role
and the impact of autoimmunity in type
1 diabetes (32).
The current study did not address
serum concentrations of cytokines. Interestingly, a recent analysis showed that
an inflammatory score derived from the
proinflammatory plasma cytokines, IL-6,
care.diabetesjournals.org
Menart-Houtermans and Associates
Table 2—Correlations between immune cell subsets and metabolic parameters
Type 2 diabetic patients (n = 132)
FBG r
HbA1c r
C-Pep r
M/I r
TC r
HDL r
LDL r
TG r
20.047
0.047
0.212*
20.108
0.172
20.089
0.186*
0.028
3103/ mL whole blood
20.159
20.016
0.187*
20.125
0.115
20.057
0.084
0.077
Monocytes
3103/ mL whole blood
20.182*
20.126
0.239**
20.072
0.019
20.046
0.023
0.050
Granulocytes
CD3+ T cells
3103/ mL whole blood
% of lymphocytes
0.046
20.053
0.089
20.037
0.140
0.024
20.049
0.190*
0.153
20.116
20.061
20.021
0.191*
20.062
20.027
20.025
CD3+CD56+ NKT cells
% of CD3+ T cells
20.069
20.124
20.014
0.068
0.052
0.272**
0.024
20.074
CD4 Th cells
% of CD3+ T cells
0.014
20.013
0.011
0.027
0.033
0.029
0.003
0.006
CD8+ Tc cells
% of CD3+ T cells
0.003
0.043
20.008
20.075
20.037
20.072
0.016
20.031
CD183+ Th1 cells
% of CD4+ Th cells
20.012
20.033
20.088
20.168
0.010
0.107
0.065
20.158
CD194 Th2 cells
% of CD4+ Th cells
20.009
0.044
0.018
0.012
0.014
20.146
0.014
0.021
CD183+CD194+ Th cells
% of CD4+ Th cells
0.175*
0.252**
20.214*
20.005
0.009
20.088
0.006
0.037
CD4+CD25+ Th cells
CD4+CD25++ Treg cells
% of CD4+ Th cells
% of CD4+ Th cells
20.024
0.236**
0.084
0.237**
0.121
20.048
20.129
20.049
0.168
0.120
20.187*
20.120
0.069
0.108
0.235**
0.048
CD4+CD25++ Treg cells
% of CD4+CD25+ Th cells
0.304***
0.223*
20.156
0.004
0.032
20.018
20.015
0.100
% of CD4+CD25+ Th cells
0.364***
0.263**
20.174
20.016
0.017
20.058
20.027
0.127
0.036
20.006
0.022
0.029
0.085
0.002
0.120
20.097
20.153
0.366***
0.069
0.293***
Immune cell subtypes
Leukocytes
3103/ mL whole blood
Lymphocytes
+
+
+
+
CD4 CD25 CD127
Treg cells
+
2
+
CD8 25 Treg cells
% of CD8+ Tc cells
CD103+ cells
% of CD4+CD25++ Treg cells
20.106
0.012
% of CD8+ CD25+ T cells
20.144
20.179*
FBG r
HbA1c r
C-Pep r
M/I r
TC r
+
CD103 cells
Immune cell subtypes
0.102
0.051
0.168
0.060
Type 1 diabetic patients (n = 62)
HDL r
0.005
20.094
0.109
0.021
LDL r
TG r
Leukocytes
310 / mL whole blood
0.151
0.224
0.212
0.243
20.021
20.118
0.127
20.028
Lymphocytes
3103/ mL whole blood
20.052
20.034
0.052
0.218
0.073
20.085
0.157
0.076
Monocytes
3103/ mL whole blood
0.092
0.134
0.120
0.469**
20.054
20.364*
0.122
0.118
Granulocytes
3103/ mL whole blood
0.192
0.215
0.370*
0.300
20.133
20.190
0.052
20.049
CD3+ T cells
% of lymphocytes
0.009
20.080
20.041
0.107
0.012
20.260*
0.067
0.281*
CD3+CD56+ NKT cells
% of CD3+ T cells
0.029
20.024
20.134
20.149
0.114
0.030
0.099
20.035
CD4+ Th cells
CD8+ Tc cells
% of CD3+ T cells
% of CD3+ T cells
20.214
0.133
20.060
0.002
0.207
20.132
0.184
20.071
0.272*
20.316*
0.143
20.245
0.186
20.187
0.112
20.140
20.161
3
CD183+ Th1 cells
% of CD4+ Th cells
20.053
20.064
20.149
0.096
20.095
20.007
20.065
CD194+ Th2 Cells
% of CD4+ Th cells
0.228
0.342**
20.050
0.014
0.058
0.063
0.039
0.092
CD183+CD194+ Th cells
% of CD4+ Th cells
0.065
0.291*
20.088
0.099
20.038
20.235
0.106
20.109
CD4+CD25+ Th cells
% of CD4+ Th cells
0.165
0.283*
0.046
20.264
20.097
0.120
20.089
20.188
CD4+CD25++ Treg cells
% of CD4+ Th cells
0.110
0.099
20.002
20.258
20.234
20.097
20.183
20.155
CD4+CD25++ Treg cells
% of CD4+CD25+ Th cells
0.152
0.074
20.027
0.023
20.128
20.022
20.183
20.051
CD4+CD25+CD1272
Treg cells
% of CD4+CD25+ Th cells
20.014
20.015
0.008
0.079
20.184
20.138
20.165
20.026
0.099
0.205
20.034
20.144
0.080
20.062
0.097
0.002
+
+
CD8 CD25 Treg cells
% of CD8+ Tc cells
CD103+ cells
% of CD4+CD25++ Treg cells
20.051
0.001
20.080
0.150
0.075
0.150
0.063
20.119
CD103+ cells
% of CD8+ CD25+ T cells
20.121
20.243
0.079
20.037
0.110
20.081
0.161
0.019
Partial correlations after adjustment for age, sex, and BMI. M/I = insulin sensitivity expressed as M value normalized by the individual steady-state
mean plasma insulin concentration. Boldface indicates a significant correlation. *P # 0.05, **P # 0.01, *** P # 0.001
TNFa, osteopontin, fractalkine, MCP-1,
and anti-inflammatory adiponectin, inversely relates to insulin sensitivity. The
inflammatory score independently predicted fasting plasma glucose and insulin
resistance in type 2 diabetic patients with
high sensibility and specificity (33). These
results are supported by our findings of
greater fractions of T cells and activated
Th and Tc cells in type 2 diabetic patients.
Also, type 1 diabetic patients showed
higher insulin resistance and had elevated parts of activated Th and Tc cells
than control subjects. Of note, studies
in mice suggest an interaction between
insulin action, TNFa-converting enzyme, and TNFa (34).
In our type 2 diabetic cohort, low HDL
and high TG associated with activated
CD4+CD25+ T cells in line with a proinflammatory condition. Lipids, particularly
fatty acids, may directly suppress lineage-
specific cytokine production in different
T-cell subsets (22). In addition, the low
HDL and high TG reflect a dyslipidemic
profile typical for insulin-resistant states.
Restribution and accumulation of lipids
in nonadipose tissues such as skeletal
muscle can also occur in poorly controlled type 1 diabetes (35) and may induce dysregulation of cellular metabolism
and function (28). This may coexist with
impaired adaptation of mitochondrial
2331
2332
Leukocyte Phenotyping in Diabetes
function to prevalent metabolic states in
type 2 diabetes (36) but also in insulinresistant patients with poorly controlled type 1 diabetes (26). Thus, lower
capacity for lipid oxidation and accumulation of toxic lipid intermediates such
as diacylglycerols, ceramides, or acylcarnitines may impair not only insulin
signaling but also functionality of immune cells commonly in type 1 and
type 2 diabetes.
The type 1 diabetic patients exhibited
a higher proportion of proinflammatory
Th1 cells than control subjects along
with higher activated CD4 + CD25 + Th
cell subsets. This is in line with the function of T cells to destroy the insulinproducing pancreatic b-cells in type 1
diabetes (37). In contrast with the
type 2 diabetic patients, the number
of WBC counts did not differ between
type 1 diabetic and healthy persons. We
found that CD3+ T cells associate positively with TG and negatively with HDL
in type 1 diabetic patients. Additionally,
TC associated positively with CD4 +
Th cells and negatively with CD8 +
Tc cells, indicating an influence of cholesterol metabolism on the adaptive immune system. These findings also point
to an upregulated proinflammatory
state with higher TC and lower HDL in
type 1 diabetic patients, similar to our
findings in type 2 diabetes, but involving
different immune cells. Changes in lipid
homeostasis are critical for T-cell growth,
activation, and function, as metabolic requirements of T cells increase dramatically upon activation by shifting from
lipid oxidation to lipid synthesis for
creating membranes to enable cell
growth (22).
In addition, we found a positive correlation between insulin sensitivity and
the number of circulating monocytes in
type 1 diabetic patients. These data
confirm the recently published suggestion that decreased blood monocytes
and elevated neutrophils may be additional biomarkers of insulin resistance
in type 1 diabetes (38). Of note, while
that study assessed insulin resistance
from the surrogate markers waist-to-hip
ratio, hypertension, and HbA1c (38), the
present association is based on direct
measurement of insulin sensitivity using
the standard hyperinsulinemic-euglycemic
clamp test. Monocytes are progenitor
cells of macrophages, which, together
with CD8+ T cells, are the first cells found
Diabetes Care Volume 37, August 2014
in the inflamed pancreas tissue during
the development of the disease (39).
Upon activation, they secrete increased
levels of proinflammatory cytokines
(40). The correlation of innate immune
cell alterations with insulin resistance
may illustrate that not only metabolic
but also cellular factors play a role in
the pathogenesis of insulin resistance in
type 1 diabetes or vice versa.
Our study has strengths and limitations. We applied a flow cytometry protocol using fresh whole blood and
avoiding Ficoll separation or other in
vitro procedures, thereby minimizing
altered surface expression of phenotypic markers. The prospective set up
using fresh blood allowed measurements of ambient metabolic parameters and immune cells in extensively
metabolically characterized patients.
On the other hand, the cross-sectional
design of our study does not allow us to
draw conclusions regarding the longterm course of disease. Furthermore,
immune cells were not phenotyped
upon stimulation with islet antigens
or other functional stimuli of innate or
adaptive immune cells, and we did
not investigate infiltrating cells from
endocrine pancreas or adipose tissue.
In conclusion, this study demonstrates
that both type 1 and type 2 diabetes show
increased immune activation compared
with normoglycemic persons. However,
immune cell subtypes substantially differ
between type 1 and type 2 diabetic patients. In type 2 diabetes, higher WBC
counts are present in the face of lower
proportions of defensive NK cells of the
innate immune system and a generally
activated pattern of the adaptive immune
system. Hyperglycemia was the most
striking parameter modulating the pattern of immune cells. In type 1 diabetes,
WBC counts were not increased but
featured a general activation of adaptive
immunity and a correlation of monocyte
counts with insulin resistance.
Acknowledgments. The authors thank all
individuals for participating in this study and
Professor Boege from the Institute for Clinical
Chemistry and Laboratory Diagnostic for providing some of the routine laboratory analyses
at the University Hospital Düsseldorf.
Funding. This study was supported in part by
the German Center for Diabetes Research.
Duality of Interest. N.C.S. is currently on leave
of absence and employed by Lilly Deutschland
GmbH. No other potential conflicts of interest
relevant to this article were reported.
Author Contributions. B.M.-H. designed the
study, researched data, calculated statistics, created tables and graphs, wrote the manuscript,
and critically reviewed the manuscript. R.R.
designed the study, researched data, calculated
statistics, created tables and graphs, and critically reviewed the manuscript. B.N., C.K., S.K.,
M.-C.S., and J.S. performed the clinical characterization of volunteers and critically reviewed
the manuscript. J.R. provided advice for statistical analysis and critically reviewed the manuscript. N.C.S. and M.R. designed the study,
contributed to data analysis and discussion,
and wrote, edited, and critically reviewed the
manuscript. M.R. is the guarantor of this work
and, as such, had full access to all the data in the
study and takes responsibility for the integrity of the data and the accuracy of the data
analysis.
Prior Presentation. Parts of this study were
presented in abstract form at the 50th German
Diabetes Society Congress, Berlin, Germany,
28–31 May 2014.
Appendix
The GDS Group consists of H. Al-Hasani, J. Eckel,
G. Giani, C. Herder, A. Icks, J. Kotzka, K. Müssig,
B. Nowotny, P.J. Nowotny, W. Rathmann,
J. Rosenbauer, P. Schadewaldt, N.C. Schloot,
J. Szendroedi, D. Ziegler, and M. Roden (speaker).
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