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Liver triglyceride content in HIV-1-infected patients
on combination antiretroviral therapy studied with
1
H-MR spectroscopy
Angel Moreno-Torres1*, Pere Domingo2, Jesus Pujol1,3, Francisco Blanco-Vaca4, Juan Antonio Arroyo2 and
Mª Antonia Sambeat2
1
Research Department, Centre Diagnòstic Pedralbes, Esplugues de Llobregat, Spain
Department of Internal Medicine, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
3
Institut d’Alta Tecnologia, CRC Corporació Sanitària, Barcelona, Spain
4
Department of Biochemistry, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
2
*Corresponding author: Tel: +34 935035434; Fax: +34 934737798; E-mail: [email protected]
Objective: To carry out an exploratory evaluation of liver
triglyceride content in HIV-1-infected patients receiving
highly active antiretroviral therapy (HAART) using
proton magnetic resonance spectroscopy and to study
how both the treatment itself and the biochemical and
physiological variables in which the treatment causes
alterations are related to liver fat content.
Methods: Intracellular hepatic triglyceride content was
determined in 29 HIV-1-infected patients on their first
HAART regime by means of localized water-unsuppressed
single voxel proton spectra. Other measurements were
body mass index, waist-to-hip ratio, lipodystrophy
assessment and a detailed blood biochemical analysis.
The relationship between intracellular hepatic triglycerides and relevant descriptive, treatment and
biochemical variables was studied by correlation and
regression analysis.
Results: Intrahepatic triglycerides were detected in 58.6%
of the patients and 13.8% showed a triglyceride content
compatible with liver steatosis. Many variables (body
mass index, waist-to-hip ratio, cumulative exposure to
PIs, lactate, insulin, insulin resistance measured by the
homeostasis model assessment method [HOMA-R index],
pH, total triglycerides, high density lipoprotein cholesterol
and very low density lipoprotein [VLDL] cholesterol) correlated individually with the amount of triglycerides.
Stepwise multiple regression analysis showed that the
combination of insulin or HOMA-R index and VLDL
cholesterol accounted for up to 50.2% of the triglyceride
liver variance. A positive relationship was found between
the concomitant presence of the metabolic syndrome
components (insulin resistance, dyslipidaemia and central
obesity) and intrahepatic triglyceride content.
Conclusions: The study showed that intrahepatic
triglyceride deposit appears to be a frequent feature of
HIV-1-infected patients receiving HAART. A coherent
multifactorial combination of biochemical and physiological factors associated with the deposit suggested
that cumulative exposure to PIs might be a possible
trigger event.
Introduction
Morbidity and mortality due to HIV-1 infection have
been considerably reduced since the introduction of
highly active antiretroviral therapy (HAART).
However, the antiretroviral drugs used in HAART can
give rise to a wide range of significantly adverse effects
[1,2]. Some of these effects, also present in non-treated
patients with a lower prevalence than in HAARTtreated patients, closely resemble the abnormalities
that are believed to cluster in the metabolic syndrome:
insulin resistance with dyslipidaemia and central
obesity [3]. A high prevalence of metabolic syndrome
features has been described in HIV-1-infected patients
© 2007 International Medical Press 1359-6535
treated with HAART [4] and hepatic steatosis is
common in such patients. Patients with the metabolic
syndrome are at increased risk of cardiovascular
disease [5] and diabetes [6]. Also, once developed,
hepatic steatosis might progress to steatohepatitis,
fibrosis and cirrhosis. Moreover, there is concern
regarding liver steatosis in the HIV-1-infected population following reports of severe hepatic steatosis and
lactic acidosis in patients exposed to nucleoside reverse
transcriptase inhibitors (NRTI) [7]. It is therefore
important to diagnose fatty infiltration of the liver
early in its course and to accurately evaluate its
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severity. However, few studies have focused on the
quantification of fatty liver in HAART patients [8] and
its relationship with the metabolic abnormalities
present in such patients.
Currently, the histological assessment of fatty liver
through biopsy is considered the ‘gold standard’. Its use
is limited because of the risks involved and ultrasound,
computerized tomography and magnetic resonance
imaging (MRI) are used as non-invasive alternatives.
However, these techniques are non-specific, insensitive
to degrees of steatosis lower than 25% of liver fat and
do not provide quantitative information [9]. Localized
proton magnetic resonance spectroscopy (1H-MRS)
non-invasively provides a quantitative assessment of
hepatic triglycerides by directly measuring the MRS
signal of protons in the triglyceride fatty acids [10–14].
The method is highly specific, sensitive and has been
validated against direct determination of triglyceride
content of liver biopsies in animals [12] and in humans
[10,11]. In the present exploratory and cross-sectional
study we aimed to use 1H-MRS methodology to evaluate the deposit of hepatic triglycerides in a cohort of
HIV-1-infected patients who were receiving their first
HAART regime. In addition, we were interested in
studying the relation to liver fat content of both the
treatment itself and the biochemical and physiological
variables, mainly related to glucose metabolism, metabolism of lipids and redistribution of fat stores, in which
the HIV infection and treatment cause alterations. The
correlation with such variables could provide further
insight into the mechanisms involved in the pathogenesis of liver fat deposit in HIV-1-infected patients
receiving HAART. We hypothesize a higher percentage
of cases with hepatic deposits than would be observed
in comparable healthy subjects and strong associations
with the aforementioned variables, as described in other
conditions [8,14–19].
Methods
Subjects
The criteria for inclusion required patients to be biologically documented for HIV-1-infection, to have received
an antiretroviral regime including a combination of two
NRTIs and one or two protease inhibitors (PIs) for at
least the previous 6 months, to be undergoing active
follow up and to not be using any other drug known to
influence glucose or fat metabolism. Patients were
excluded if they had suffered active opportunistic infections, malignancy or fever (temperature >37.8ºC)
within the 3 months prior to entry or during the study.
Exposure to individual antiretroviral drugs was calculated by totalling the months, consecutive or otherwise,
of exposure to each. The patients’ daily alcohol
consumption was quantified as a continuous variable at
196
the time of selection and follow-up visits. A group of
healthy subjects was included in order to confirm that
non-hepatic lipids do not contaminate the liver spectra
acquired using the method adopted for this study.
Informed consent was obtained from all participants
prior to the study.
Anthropometric and plasma biochemical parametres
Anthropometric measurement included height, weight
and waist and hip circumferences. Body mass index
(BMI) was calculated by dividing the weight in kilograms by the square of the height in metres. Normal
was defined as BMI ≥18 kg/m2 but ≤27 kg/m2, overweight as BMI 27–30 kg/m2, and obese as BMI
>30 kg/m2. Central adiposity was defined by a waistto-hip ratio (WHR) of >0.95 in men, and >0.85 in
women [20]. Lipodystrophy was defined as selfreported (and investigator-confirmed) symptoms of
loss of subcutaneous fat with or without increased
abdominal girth, breast size or development of a
buffalo hump [21]. Blood plasma biochemical
measurements included the following blocks: glucose
metabolism (glucose, insulin and lactate levels);
acid–base status (pH, pCO2 and bicarbonate levels);
lipid metabolism and plasma protein transport (triglycerides, cholesterol, high density lipoprotein [HDL]
cholesterol, low density lipoprotein [LDL] cholesterol,
very low density lipoprotein [VLDL] cholesterol, total
protein and globulin fractions); and hepatic damage
markers (aspartate aminotransferase, alanine aminotransferase and γ-glutamyl transferase). Blood specimens were obtained after an overnight fast,
measurements were made with the routine assays and
the reference values of the hospital laboratory were
used. The homeostasis model assessment method
(HOMA-R) was used to obtain a measure of insulin
resistance as the product of the fasting concentrations
of plasma insulin (micro units/ml, in our case pmol/l
×0.1392) and plasma glucose (mmol/l) divided by 22.5
[22], and a cut-off point of 3.8 was used [23,24]. The
WHO criteria, modified by introducing this measurement of insulin resistance, were used for considering
the presence of the metabolic syndrome [25].
Liver triglyceride content (proton spectroscopy and MRI)
The magnetic resonance (MR) examinations were
performed using a 1.5 T whole body system (General
Electric Medical Systems, Milwaukee, WI, USA). Both
imaging and spectroscopy acquisitions were performed
using the quadrature body coil. T1-weighted breathhold in-phase and out-of-phase spoiled gradient-echo
MR images were acquired to define the pattern of
hepatic fat infiltration, and T1-weighed high resolution
MR images with respiratory compensation were
acquired to localize the voxel within the right lobe of
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Liver fat in HIV-infected patients receiving HAART
the liver. Subjects were free breathing in a supine position. Vascular structures and subcutaneous fat tissue
were avoided in the localization of the voxel (Figure
1A), which was placed at a sufficient distance (>2 cm)
to reach the abdominal subcutaneous fat [26]. Voxel
size was 7.2 ±0.6 cm3 (range: 5.9–7.3).
Quantitative assessment of intracellular triglycerides of the liver was performed using the MRS
signals of hepatic water and intracellular methylene
protons of triglyceride fatty acids, extrapolated to zero
echo time [10,11]. Localized water-unsuppressed
single-voxel proton spectra of the liver were recorded
using the stimulated-echo acquisition mode sequence
[27] as 16 individual frames (free induction decays).
Spectra were acquired at seven different echo times
(20, 30, 45, 70, 100, 200, and 400 ms) with a repetition time of 5,000 ms to calculate intensities at zero
echo time and T2 values. For T1 calculations, two
spectra were acquired with repetition times of
1,000 ms and 6,000 ms. Calculations for T1, T2 and
Figure 1. Experimental method for measuring intrahepatic triglyceride content by proton magnetic resonance spectroscopy
A
C
B
(A) Axial T1-weighted images showing the placement of the volume of interest in the liver. (B) Effect of the post-processing schema applied: lower trace, no correction applied; upper trace, correction of the individual spectral frames by phase and frequency prior to averaging. The spectral quality is improved by the narrowing
of the resonances (width at half maximum of the water resonance=12.44 ±1.60 Hz) and significant increase in intensity. (C) Representative spectra: lower trace,
intrahepatic triglycerides in the higher range of values (>5%); middle trace, intrahepatic triglycerides in the lower range of values; upper trace, spectrum with no
presence of intrahepatic triglycerides. Arrows indicate the IHT resonance. IHT, methylene protons of intrahepatic triglyceride fatty acids; W, water protons.
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intensities at zero echo time were performed as previously described [28]. No correction for partial T1 saturation effects was needed as the repetition time used
(>5×T1) guaranteed full relaxation for both water and
methylene protons (see Results). Other acquisition
parameters were four dummy scans, 2,048 data points
and 2,500-Hz spectral width. To evaluate the short
term reproducibility of our measurements and to rule
out aleatory fat contamination, three consecutive
spectra at echo time of 20 ms were acquired in the
same session for all subjects.
A post-processing frame-to-frame phase correction
and frequency registration method, slighty modified
from one previously demonstrated in the kidney [29],
was applied. The processing included zero-filling to
4,096 points prior to Fourier transform, zero-order
phase correction of the motion-induced phase shifts,
alignment of the spectra using the water signal as a
reference, spectrum averaging and inverse Fourier
transformation. The resulting averaged free-induction
decays were quantified in the time domain with a nonlinear least-square-fitting algorithm by using the variable projection method and prior knowledge [30].
Chemical shifts were measured relative to water at
4.70 ppm. The liver intracellular triglyceride content,
expressed as percentage by weight, was calculated from
the raw ratio of signal amplitudes at zero echo time
([methylene
protons/(water
protons+methylene
protons)]×100) using previously validated equations
[10] and experimentally determined factors [13]. Zero
intracellular triglyceride content was assumed when no
resonance of methylene protons could be detected and
was used for subsequent analysis.
Statistical analyses
All data are reported as mean ±SD. Statistical analyses
were performed using SPSS 8.0 statistical software
(SPSS Inc., Chicago, IL, USA). Spearman’s correlation
coefficient was used to detect individual correlations
between intracellular hepatic triglycerides and relevant
descriptive, treatment and biochemical variables, as
data for the majority of such variables (that is, hepatic
triglycerides) were not normally distributed, as
assessed with the Shapiro–Wilk test. A stepwise
multiple-regression analysis, including only the
biochemical variables related to glucose and lipid
metabolism with P≤0.1 by univariate analysis, was
used to further explore the combined contribution of
such variables to the variance of liver triglyceride
content. The relation between intracellular hepatic
triglycerides and the components of the metabolic
syndrome was analysed by the Spearman rank correlation test. Differences between paired and unpaired
data were tested by the Student t-test (significance
level P<0.01).
198
Results
Population studied
The study population consisted of 29 patients (23
males and 6 females). Table 1 shows the anthropometric, HIV-1-infection and antiretroviral-related
characteristics of the study group. The antiretroviral
regime at the time of study was based mainly on the
administration of the NRTI lamivudine (26 patients)
in combination with zidovudine (13 patients) or
stavudine (12 patients). The PIs co-administered were
indinavir (16 patients), saquinavir (8 patients), ritonavir (8 patients) and nelfinavir (4 patients). Twentyone patients were receiving one PI and eight patients
two PIs. Twelve of the subjects had also previously
undergone suboptimal antiretroviral therapy with
only NRTIs (Table 1) and no patient received nonnucleoside reverse transcriptase inhibitors. Alcohol
consumption was >30 g per day in two non-alcoholic
patients, <30 g per day in ten patients and 17 patients
did not consume any alcohol. Viral C hepatitis was
also present in five patients. The healthy group was
made up of five females (30.4 ±11.2 years old; range
20–46): four non-alcohol consumers and one
weekend drinker (60 g/weekend).
Anthropometric and biochemical results
No patient was obese and only five patients were overweight. Central obesity, however, was present in 12
patients and lipodystrophy in 16 patients. Table 1
shows the blood analysis results. Compared with our
laboratory reference values the most common findings
were lipid abnormalities in 25 patients (86.2% of
cases). Hypertriglyceridaemia was found in 12
patients, hypercholesterolaemia in 12 patients, low
HDL cholesterol in 20 patients, high LDL cholesterol
in five patients and high VLDL cholesterol in 20
patients. Hypertriglyceridaemia and/or low HDL
cholesterol were present in 21 patients. The overall
lipoprotein pattern was high VLDL cholesterol with
low HDL cholesterol in 18 cases. Other relevant plasmatic findings were: hyperlactataemia in four patients,
mild acidosis in 16 patients, hyperglycaemia in three
patients, hyperinsulinaemia in three patients, increased
aminotransferases in 13 patients and HOMA-R index
>3.8 in 13 patients.
Liver triglyceride content (proton spectroscopy and MRI)
Correction of the individual spectral frames by phase
and frequency prior to averaging resulted in a significant improvement in spectral quality (Figure 1B).
The resulting spectra showed, in addition to the
intense water resonance, a single resonance of methylene protons at 1.31 ±0.02 ppm in the livers of 17
patients (58.6%) (Figure 1C). The chemical shift of
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Liver fat in HIV-infected patients receiving HAART
Table 1. Descriptive data and Spearman correlation analysis with intrahepatic triglycerides
Mean ±SD
Out of range, n
Spearman C.C.
Descriptive data
Age, years
Body mass index, kg/m2
Waist-to-hip ratio
41.6 ±9.8
23.3 ±3.13
0.94 ±0.07
–
0
12
–
0.62, P<0.001*
0.52, P=0.004*
Clinical data
Time since diagnosis of HIV, months
Most recent CD4+ T-cell count, x106/l
Most recent CD8+ T-cell count, x106/l
CD4+ T-cell count nadir, x106/l
80.2 ±48.2
580 ±295
951 ±391
225 ±180
–
–
–
–
0.09, P=0.635
0.07, P=0.733
0.47, P=0.011
-0.35, P=0.070
Cumulative antiretroviral exposure†
PIs, months
NRTIs, months
53.1 ±17.1
111.2 ±52.7
–
–
0.50, P=0.005*
0.18, P=0.338
Individual antiretroviral exposure
ZDV, months
3TC , months
d4T, months
ddC, months
ddI, months
IDV, months
RTV, months
NFV, months
SQV, months
28.6 ±32.5
43.0 ±23.4
27.2 ±26.6
5.2 ±16.0
7.1 ±13.4
30.0 ±25.4
7.9 ±14.0
4.6 ±11.4
10.5 ±19.9
–
–
–
–
–
–
–
–
–
-0.02, P=0.913
0.35, P=0.062
0.30, P=0.115
0.27, P=0.161
-0.19, P=0.325
0.05, P=0.814
0.10, P=0.599
-0.06, P=0.760
0.16, P=0.408
Blood analysis
Glucose metabolism
Glucose, mM
Lactate, mM
Insulin, pM
HOMA-R index
5.32 ±1.27
1.44 ±0.71
112.45 ±79.96
3.77 ±2.75
3
4
3
13
0.33, P=0.080
0.70, P<0.001*
0.62, P<0.001*
0.62, P<0.001*
Lipid metabolism
Triglycerides, mM
Cholesterol, mM
HDL cholesterol, mM
LDL cholesterol, mM
VLDL cholesterol, mM
2.46 ±1.86
5.65 ±1.22
1.10 ±0.28
3.35 ±0.85
1.00 ±0.64
12
12
20
5
20
0.56, P=0.002*
0.22, P=0.247
-0.50, P=0.006*
-0.11, P=0.586
0.60, P<0.001*
Protein
Total, g/l
Albumin, g/l
α1-Globulin, g/l
α2-Globulin, g/l
β-Globulin, g/l
75.03 ±4.94
43.88 ±3.07
2.42 ±0.43
6.20 ±1.47
8.47 ±1.32
1
2
1
8
5
-0.11, P=0.561
0.14, P=0.459
-0.27, P=0.158
-0.17, P=0.392
0.38, P=0.042
Acid–base status
pH
pCO2, mm Hg
CO3H, nM
7.34 ±0.03
46.20 ±5.27
23.54 ±1.26
16
15
5
-0.53, P=0.005*
0.32, P=0,115
-0.25, P=0,186
Liver damage
AST, u/l
ALT, u/l
GGT, u/l
26.69 ±15.05
34.24 ±31.52
40.72 ±31.40
7
8
11
0.01, P=0.969
0.29, P=0.129
0.01, P=0.949
Data were available for all 29 patients, except data for pH and pCO2, which were only available in 26 patients. *Correlations showing P≤0.01, two-tailed; †12
patients had received prior suboptimal antiretroviral therapy with nucleoside reverse transcriptase inhibitors for a mean duration of 37.1 ±36.9 months. 3TC,
lamivudine; ALT, alanine aminotransferase; AST, aspartate aminotransferase; C.C., correlation coefficient; d4T, stavudine; ddC, zalcitabine; ddI, didanosine; GGT,
γ-glutamyl transferase; HDL, high density lipoprotein; HOMA-R index, insulin resistance by homeostasis model assessment method; IDV, indinavir; LDL, low
density lipoprotein; NFV, nelfinavir; out of range, number of patients outside the laboratory reference range; RTV, ritonavir; SQV, saquinavir; VLDL, very low
density lipoprotein; ZDV, zidovudine.
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this resonance confirmed its assignation to intracellular methylene protons of triglyceride hepatic fatty
acids [12]. The calculated hepatic intracellular
triglyceride content in such patients was 3.4 ±2.5 g of
triglycerides per 100 g of liver wet weight (range:
0.91–10.05 g/100 g), with four (13.8%) showing an
intrahepatic triglyceride content exceeding 5% of
liver weight, the level above which steatosis is generally defined [31]. The sensitivity limit of our methodology is 0.46 g of triglycerides per 100 g of liver
weight, which corresponds to the smallest triglyceride resonance detected in the spectra of the healthy
female weekend drinker (methylene/[methylene+
water]×100=0.60). Repeated measurements showed
an excellent reproducibility: 12 of the patients and
the four healthy non-alcohol consumers showed no
methylene resonances and this as the case in all three
repeated spectra for each individual; when present,
the mean ±SD coefficients of variation of the water
and methylene resonances were 0.60 ±0.38% and
2.64 ±1.76%, respectively. Relaxation times were as
follows: T 2(water, methylene)=(36.30 ±4.36 ms,
64.59 ±10.96 ms; P<0.001) and T1(water, methylene)=(741 ±65 ms, 368 ±100 ms; P<0.001).
Analysis of T1-weighted in-phase and out-of-phase
MR images showed no cases of focal fatty infiltration
of the liver.
Correlations
Individual strong correlations were found between
intrahepatic triglycerides and the following variables:
BMI, waist-to-hip ratio, most recent CD8+ T-cell
count, cumulative exposure to PIs, plasmatic variables related to glucose (lactate, insulin, HOMA-R
index), pH and lipid metabolism (triglycerides, HDL
cholesterol and VLDL cholesterol). No correlation
was found with aminotransferases (Table 1). All
correlations were positive with the exception of pH
and HDL cholesterol. No correlation was found with
alcohol consumption, lipodystrophy, individual drugs
administered, total time since diagnosis or other
biochemical data (not shown). Stepwise multiple
regression analysis with MRS liver triglyceride
percentage as the dependent variable and glucose,
lactate, insulin, pH, triglycerides, HDL cholesterol
and VLDL cholesterol as independent variables
showed that blood levels of VLDL cholesterol and
insulin accounted for 50.2% of the intrahepatic
triglyceride variance (Table 2). Similar results were
obtained when removing glucose and insulin blood
levels and adding the calculated HOMA-R index to
the analysis (49.8% of variance accounted for).
Although all five patients coinfected with hepatitis C
virus (HCV) showed intrahepatic triglycerides, they
did not reach the level for steatosis (range:
0.91–3.91 g/100 g). After removing such patients
from our calculations, the percentages of cases with
detectable intrahepatic triglycerides and steatosis in
the non-coinfected patients were 50% and 16.7%
respectively. All in all, 29.4% of patients showing
intrahepatic triglycerides were coinfected with HCV.
Six patients fulfilled the conditions set for the metabolic syndrome: insulin resistance (HOMA-R index
>3.8), dyslipidaemia with hypertriglyceridaemia
and/or low HDL cholesterol, and central obesity [25].
Among the remaining patients, 11 presented two of
these conditions (six with dyslipidaemia+insulin resistance, four with dyslipidaemia+central obesity and one
with insulin resistance+central obesity), seven
presented only one condition (six with dyslipidaemia
and one with central obesity) and five patients showed
no condition. Blood pressure and albumin urinary
excretion were within the normal range in all patients
(data not shown). A positive correlation was found
between the number of components of the metabolic
syndrome and the intrahepatic triglyceride content
(Figure 2).
Comparison between groups with or without intrahepatic triglycerides
Subjects with intrahepatic triglycerides had a longer PI
exposure (60.1 ±13.0 vs 43.3 ±17.8 months; P=0.006)
and showed higher BMIs (24.5 ±3.2 vs
21.6 ±2.1 kg/m2; P=0.006), insulin levels (143.3 ±89.8
Table 2. Stepwise multiple-regression analysis
Step
Adjusted R2
F-change
Correlation
Zero-order
Partial
F-test
P-value
VLDL cholesterol
Insulin
1
2
0.372
0.502
15.83
7.27
0.630
0.618
0.630
0.490
15.83
13.62
0.001
0.0001
VLDL cholesterol
HOMA-R
1
2
0.372
0.498
15.83
7.02
0.630
0.601
0.630
0.484
15.83
13.41
0.001
0.0001
The dependent variable is liver triglyceride percentage determined by magnetic resonance spectroscopy. HOMA-R, insulin resistance by homeostasis model assessment
method; VLDL, very low density lipoprotein.
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vs 68.8 ±31.5 pM; P=0.005) and HOMA-R index
values (4.9 ±3.0 vs 2.2 ±1.1; P=0.009).
Discussion
The results described in this paper showed a total of
58.6% of the patients with detectable intrahepatic
triglycerides and 13.8% with triglyceride content
consistent with clinical steatosis [31]. Frequent metabolic abnormalities found were dyslipidaemia, mild
acidosis, increased aminotransferases, insulin resistance, central obesity and lipodystrophy. Less
frequently observed were hyperlactataemia, hyperglycaemia and hyperinsulinaemia. In the univariate
analysis BMI, WHR, cumulative PI exposure, lactate,
insulin, HOMA-R index, triglycerides and VLDL
cholesterol correlated positively with intrahepatic
triglyceride content, whereas pH and HDL cholesterol
correlated negatively. In the multivariate analysis of
plasmatic variables, up to 50.2% of the variance in
hepatic triglycerides was explained by the combined
effect of VLDL cholesterol and insulin or HOMA-R
index. A total of 20.7% of the patients showed the
metabolic syndrome and a positive relationship
between the number of syndrome components and
triglyceride content was found.
The data concerning intrahepatic triglyceride
accumulation described in this study are relevant
because the history and prevalence of this process
among HIV-1-patients taking HAART have not been
fully studied [32]. The percentage of cases with
hepatic steatosis in our study is within a reasonable
Figure 2. Relationship between the intrahepatic triglyceride
content and the number of components of the metabolic
syndrome concomitantly present in patients
Box-and-whisker plots are shown for each group. Spearman’s rank correlation
coefficient ρ=0.692; P=0.00003. MS, metabolic syndrome (insulin resistance
and two other components); TAG, triglyceride.
Antiviral Therapy 12:2
range when compared with the available references.
It is higher than the described prevalence of 8.8% in
a similar healthy and non-obese group studied in the
Barcelona area [33] and lower than the value
described in HIV/HCV-coinfected patients receiving
HAART, which ranged between 18 and 40% [34,35].
However, such comparisons should be made with
caution because of the absence of a control group in
our study and the controversy over the real prevalence in the general population of the condition
known as non-alcoholic fatty liver disease (NAFLD)
[9], in which fatty liver is detected in apparently
healthy subjects and is not related to alcohol abuse.
In our study exclusion of coinfected patients showed
that the proportion of the remaining non-infected
patients with steatosis was greater, 16.7%. However,
this is probably due to the small sample size.
It is now accepted that NAFLD has a multifactorial
nature [9] and among the most relevant risk factors
associated with hepatic fat deposit are obesity [36],
central adiposity [37], hyperlipaemia [36], insulin
resistance [17] and the metabolic syndrome [18]. Our
results show a similar multifactorial picture with
strong positive correlations of intrahepatic
tryglicerides with BMI, visceral adiposity, insulin resistance, plasma tryglicerides and the number of metabolic syndrome components simultaneously present
(insulin resistance, dyslipidaemia and central obesity).
There is also agreement with similar associations
found in other conditions where hepatic steatosis is
present, such as diabetes [19], familial hypobetalipoproteinaemia [15] and others. This is not
surprising because, although specific or different
trigger events might be responsible for the final fat
deposit, both the biochemical mechanisms involved
and the cytosolic lipid-body cycle in mammalian hepatocytes (with steatosis as an up-regulation of the cycle
[38]) are common pathways.
The causal factor for intrahepatic triglyceride
deposit in our study series cannot be ascertained with
certainty owing to the design of the study and its
exploratory nature. However the cumulative exposure to PIs is a likely candidate, in addition to a
possible effect of the HIV infection itself. PI exposure
correlated with intrahepatic triglycerides, although
this does not imply a cause-and-effect relationship,
and subjects with detectable intrahepatic triglycerides
had had a longer exposure. This interpretation of our
data would be consistent with the described development of insulin resistance associated with PI administration [39], and the strong relationship of insulin
resistance with fatty liver [16,17], which was also
found in the present study, both in the univariate and
multivariate analyses. Moreover, insulin resistance
results in increased rates of triglyceride lipolysis in
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A Moreno-Torres et al.
adipocytes [40] and PIs also stimulate triglyceride and
cholesterol synthesis in hepatocytes and adipocytes
[41]. This results in hyperlipidaemia that can increase
the input sources of free fatty acids to the liver and be
part of a bottom-level mechanism by which PIs might
be associated with hepatic triglyceride accumulation.
No correlation was found in our study between liver
triglyceride accumulation and plasmatic levels of
hepatic aminotransferases, which suggests that hepatic
damage in the studied group is not the primary process
leading to hepatic triglyceride accumulation and that it
might occur at a later stage, perhaps as a result of
oxidative mechanisms inducing inflammation [42].
However, a positive correlation was found between
liver triglyceride accumulation and blood lactate levels.
Interestingly, increased lactate levels have been noted as
a marker of hepatic mitochondrial toxicity in HIV
patients receiving NRTIs and considered a consequence
of an impaired oxidative phosphorylation, which in
turn is postulated to produce triglyceride accumulation
through impairment of fatty acid β-oxidation [43].
A limitation in our study is the use of the HOMA-R
index for defining insulin resistance, as this is an indirect
estimation. However, a strong correlation does exist
between clamp-measured total glucose disposal and
HOMA-estimated insulin sensitivity [44], and the cut-off
point used in the present study corresponds to the 90th
percentile of southern European subjects without clinical
or biological insulin resistance parameters [23,24]. We
are also aware of the recent controversy concerning the
definition, pathogenesis and clinical usefulness of metabolic syndrome [45,46]. However, a detailed discussion
of such issues is beyond the scope of the present study.
Finally, and as a result of patient free-breathing, possible
technical criticisms of our method are spatial misregistration and possible voxel contamination by outer lipids.
Our imaging data revealed no focal liver changes and
spectra were acquired from the hepatic parenchyma so
spatial misregistration is not a problem. Lipid contamination was avoided effectively by the voxel placement, as
demonstrated by our experimental results showing no
additional signal of non-intrahepatic triglycerides, excellent reproducibility and agreement of intrahepatic
triglycerides and water relaxation times with previously
reported values [10,11]. Despite its limitations, our
study illustrated the power of 1H-MRS as a tool for the
recognition, diagnosis and management of steatosis in
HIV-1-infected population by the ability of the methodology to detect not only steatosis but also intrahepatic
triglyceride accumulation at a substeatotic level, and to
quantify such accumulations.
In summary, the present study used 1H-MRS for the
analysis of intrahepatic triglyceride deposits in a cohort
of HIV-1-infected patients receiving HAART and
showed that such a deposit is a frequent consequence
202
of the therapy. Our results also showed a coherent
multifactorial picture of known biochemical and physiological factors associated with the deposit. Although
arguable, the cumulative exposure to PIs is suggested as
a possible trigger event for the deposit. Our study also
shows the potential of 1H-MRS as a tool for the recognition, diagnosis and management of steatosis in the
HIV-1-infected population.
Acknowledgements
This work was supported by the Fundación para la
Investigación de la SIDA en España (FIPSE) (grant
3161/00), the Fundació la Marató de TV3 (grant
020631) and the Instituto de Salud Carlos III,
Ministerio de Sanidad y Consumo (grants C03/08 and
PI052255). The authors thank Gerald-Patrick Fannon,
PhD, for revising the manuscript.
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Accepted for publication 19 September 2006
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