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The Journal of Clinical Endocrinology & Metabolism 88(2):627– 636
Copyright © 2003 by The Endocrine Society
doi: 10.1210/jc.2002-020795
Hypoadiponectinemia Is Associated with Insulin
Resistance, Hypertriglyceridemia, and Fat
Redistribution in Human Immunodeficiency
Virus-Infected Patients Treated with Highly
Active Antiretroviral Therapy
CAROL L. ADDY, ALINA GAVRILA, SOTIRIOS TSIODRAS, KIMBERLY BRODOVICZ,
ADOLF W. KARCHMER, AND CHRISTOS S. MANTZOROS
Department of Internal Medicine (C.L.A.), Endocrinology-Hypertension Division, Brigham and Women’s Hospital, Boston,
Massachusetts 02115; Divisions of Endocrinology and Metabolism (C.L.A., A.G., C.S.M.) and Infectious Diseases (S.T.,
A.W.K.), Department of Internal Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215; and Merck
Research Laboratories (K.B.), Blue Bell, Pennsylvania 19422
(r ⴝ ⴚ0.32), and high-density lipoprotein (HDL) (r ⴝ 0.41) using
bivariate analysis (all P < 0.01). The association with HDL
weakened but remained significant on multivariate analysis
(standard ␤ ⴝ 0.29, P ⴝ 0.01). However, the association of
adiponectin with HOMA-IR became nonsignificant after adjusting for NRTI use (standard ␤ ⴝ ⴚ0.15, P ⴝ 0.12), suggesting
that changes in adiponectin levels may underlie the effect of
NRTI use on insulin resistance. The associations of adiponectin with triglycerides and HOMA-IR were also slightly weakened after adjusting for visceral and extremity fat, indicating
that adiponectin may, in part, mediate the effect of FR on
triglycerides and insulin resistance.
This study indicates that adiponectin is inversely correlated with abdominal visceral fat mass, serum triglycerides,
and insulin resistance and is directly correlated with HDL and
extremity fat in a sample of HIV-infected patients treated with
HAART. The results also indicate that NRTI use may worsen
insulin resistance by decreasing adiponectin levels. Thus, adiponectin replacement may be a potential treatment option to
ameliorate the metabolic changes observed in this patient
population. (J Clin Endocrinol Metab 88: 627– 636, 2003)
A lipodystrophic syndrome and metabolic abnormalities have
been observed in HIV-infected patients treated with highly
active antiretroviral therapy (HAART). A murine model of
lipodystrophy is associated with decreased levels of adiponectin, an adipocyte-secreted protein, the administration of
which improves the metabolic syndrome in these mice. To
investigate the association of adiponectin with metabolic
changes in human lipodystrophy, we conducted a crosssectional study of 112 HIV-infected patients treated with
HAART.
Mean adiponectin levels were higher in patients with no fat
redistribution (FR) vs. FR (4.8 ⴞ 5.0 vs. 2.2 ⴞ 2.7 ␮g/ml, P < 0.01),
but no significant differences in adiponectin levels were observed between FR subgroups. The difference in adiponectin
levels between subjects with and without FR remained significant after adjusting for age, gender, leptin, HIV medication use, and CD4 count using logistic regression (odds ratio,
0.54, P ⴝ 0.008). Adiponectin was significantly correlated with
triglycerides (r ⴝ ⴚ0.40), abdominal visceral fat (r ⴝ ⴚ0.35),
extremity fat (r ⴝ 0.37), insulin resistance (HOMA-IR) (r ⴝ
ⴚ0.28), nucleoside reverse transcriptase inhibitor (NRTI) use
H
IGHLY ACTIVE ANTIRETROVIRAL therapy
(HAART), which includes the use of protease inhibitors (PIs), has proven to be very effective in reducing
disease-associated mortality and morbidity in patients infected with HIV. However, use of HAART has been associated with the development of metabolic abnormalities. A
lipodystrophic syndrome characterized by body fat redistribution (FR) has been reported in HIV-infected patients
treated with HAART (1–3). FR in this syndrome includes fat
accumulation, fat wasting, or a combination of the two.
Similar to other congenital forms of lipodystrophy, HIV
lipodystrophy is associated with components of the metabolic syndrome: fasting hyperinsulinemia, hypertriglyceridemia, and hypercholesterolemia (1–3). Given the fat accumulation or fat wasting that occurs in this syndrome, it has
been hypothesized that adipocyte function may play a very
important role in the development of the associated metabolic abnormalities.
Adipocytes are metabolically and hormonally active, secreting proteins such as plasminogen activator inhibitor type
1, TNF␣, IL-6, and leptin (4 –9). An excess or deficiency of
these adipocytokines in the setting of obesity or lipoatrophy
is thought to play an important role in the development of
insulin resistance, positive energy balance, endothelial dysfunction, and abnormal fibrinolysis. These pathophysiological processes are commonly observed in the metabolic syndrome, which is characterized by hyperinsulinemia, type 2
diabetes mellitus, hypertension, hyperlipidemia, and coronary heart disease (CHD) (10, 11).
A new adipocytokine, adiponectin (acrp30, adipoQ), was
Abbreviations: BMI, Body mass index; CHD, coronary heart disease;
CT, computed tomography; DEXA, dual-energy x-ray absorptiometry;
DM, diabetes mellitus; FA, fat accumulation; FR, fat redistribution; FW,
fat wasting; HAART, highly active antiretroviral therapy; HDL, highdensity lipoprotein; HOMA, homeostasis model; IR, insulin resistance;
NRTI, nucleoside reverse transcriptase inhibitor; PI, protease inhibitor;
PPAR, peroxisome proliferator-activator receptor; VAT, visceral adipose
tissue; WHR, waist to hip ratio.
627
628
J Clin Endocrinol Metab, February 2003, 88(2):627– 636
discovered through cDNA cloning techniques by four different groups in the mid-1990s (12–15). Adiponectin is the
protein product of the apM1 gene, which is expressed exclusively in adipocytes. In vitro and animal studies and crosssectional studies in humans have shown that adiponectin is
inversely correlated with features of the metabolic syndrome
including obesity, insulin resistance, type 2 diabetes, CHD,
and congenital and acquired lipodystrophies in non-HIV
infected subjects (16 –19). The association of adiponectin with
the metabolic syndrome is strengthened further, given that
this syndrome has recently been linked to a quantitative trait
locus on chromosome 3q27, the location of the apM1 gene
(20). Most recently, Yamauchi et al. (18) reported decreased
serum adiponectin and leptin levels in a murine model of
lipoatrophy. Administration of either adiponectin or leptin
alone could only partially correct the insulin resistance in
these mice. However, the administration of adiponectin and
leptin together was able to fully correct the associated insulin
resistance in this murine model of lipoatrophic diabetes.
It remains unknown, however, whether adiponectin is
associated with metabolic abnormalities in patients with
HIV-lipodystrophy. To study the association of adiponectin
with metabolic and anthropometric changes observed in a
sample of patients with lipodystrophy caused by HAART,
we performed a cross-sectional analysis of 112 consecutively
enrolled HIV-infected patients recruited through the Infectious Diseases Clinic of the Beth Israel Deaconess Medical
Center (BIDMC), Boston, Massachusetts, from August 2000
through March 2001.
Subjects and Methods
Study subjects
Subjects were 112 consecutively enrolled patients recruited from two
ambulatory HIV clinics at Beth Israel Deaconess Medical Center (Boston,
MA) from August 2000 through March 2001. Recruitment occurred by
means of contacting patients’ primary care physicians and through the
posting of study fliers in clinics. Eligibility for study enrollment included: age 16 yr or older, laboratory documentation of HIV infection,
and ability to give informed consent. The study consisted of one outpatient visit to the General Clinical Research Center at BIDMC.
Addy et al. • Hypoadiponectinemia in HAART
ence, and waist to hip ratio (WHR). Three measurements were obtained
at each site and recorded as the mean of the three values. Whole body
fat and lean masses and extremity fat mass were measured using dualenergy x-ray absorptiometry (DEXA) scans obtained with a QDR-2000
densitometer operating in an array mode (software version 5.73A; Hologic, Inc., Waltham, MA) (21, 22). A single-slice computed tomography
(CT) scan at the level of L4 was performed for each subject to assess
abdominal visceral and abdominal sc adipose tissue (23–26).
Assessment of body FR classification for each subject was conducted
independently by the Fat Redistribution Adjudication Committee. This
committee consisted of three clinical investigators who were not involved with subject interviews, data collection, or analysis or in the
clinical care of the study subjects. Committee members made a preliminary classification of each subject according to signs and symptoms
noted in individual medical charts, study questionnaires, and study
interviews. Subjects were then secondarily classified according to documented physical examination findings and digital photographs based
on the criteria specified in Table 1. Final classification of each subject was
verified according to the diagnostic test criteria specified in Table 1. Each
subject was classified as having no FR or the presence of FR, which
included fat accumulation (FA), fat wasting (FW), or mixed FR (FA and
FW). All committee members were provided with identical information
on which to base their decisions, and classifications were based on
supportive documentation and good clinical judgment. The final classification of each subject required the unanimous agreement of the
committee. Subjects whose classification was not unanimously agreed
on (n ⫽ 4) were not included in the analysis.
Blood was drawn from each subject after an overnight fast on the
morning of the study visit. Serum samples were immediately frozen at
⫺70 C, and hormonal analyses were performed simultaneously on a
subsequent day. Glucose levels were measured by the BIDMC Clinical
Laboratory (Roche/Hitachi, Indianapolis, IN). Insulin levels were measured using a commercially available RIA (DSL-1600; Diagnostic Systems Laboratories, Inc., Webster, TX) with a sensitivity of 1.3 ␮IU/ml
and inter- and intra-assay coefficients of variation between 4.7% and
12.2% and 4.5% and 8.3%, respectively. Insulin resistance was estimated
using the homeostasis model (HOMA) with the following formula:
Insulin resistance (IR) ⫽ (fasting insulin ⫻ fasting glucose)/22.5 (27, 28).
Fasting lipoprotein profile was measured as described previously (29).
Leptin was measured as described previously, and the sensitivity of this
assay was 0.5 ng/ml (30 –31). Adiponectin was measured by RIA with
a sensitivity of 2 ng/ml and inter- and intra-assay coefficients of variation between 1.78% and 6.21% and 6.9% and 9.3%, respectively. All
hormonal samples were measured in one run to minimize variability.
CD4 count was measured in the BIDMC Clinical Laboratory via flow
cytometry (three-color CD4 reagent from Becton Dickinson and Co.,
Franklin Lakes, NJ). HIV RNA was also measured in the BIDMC Clinical
Laboratory using ultrasensitive PCR (Amplicor HIV-1 monitor test, version 1.5; Roche-Cobas, Branchburg, NJ).
Materials and methods
Two study investigators obtained a detailed medical history for each
subject using a standardized questionnaire and interview. Information
provided by subjects was later confirmed by a review of available inpatient and outpatient medical records. Note was made of medical
conditions or medications that were known to affect glucose or lipid
metabolism and body composition. Information pertaining to alcohol
use (current or past use and number/quantity of alcoholic beverages per
week) and exercise habits (type of activity, such as aerobic training or
resistance training, and frequency/duration of exercise sessions) was
obtained by means of a questionnaire and interview. All previous and
ongoing antiretroviral therapies were noted, and exposure to each medication was recorded based on cumulative months of therapy.
Each subject received a complete physical examination with emphasis
given to body FR. A clinical diagnosis of FR was either evident to the
investigator during the physical examination or suggested based on
comparison to prior physical examination findings noted in the subject’s
medical record or through changes noted by the subjects themselves.
Standardized digital photographs of each body region were obtained to
document FR and used by the Fat Redistribution Adjudication Committee (described below) to support the classification of study subjects.
Anthropometric evaluation of subjects involved skinfold thickness
(triceps and subscapular), upper arm circumference, waist circumfer-
Statistical analysis
SPSS version 8.0 for Windows software (SPSS, Inc., Chicago, IL) was
used for data analysis. Descriptive statistics are represented as mean ⫾
sd, and graphical displays of data are shown as mean ⫾ se. Independent
sample t test was used to compare normally distributed continuous
variables between groups with or without FR, and Wilcoxon rank sum
was used to compare variables that were not normally distributed. A ␹2
test was used to compare categorical variables between groups with or
without FR. Associations among adiponectin, leptin, anthropometric
variables, metabolic variables, cumulative HIV medication use, and
disease severity, as measured by CD4 count and HIV RNA, were determined using Spearman correlation coefficients. Multivariate linear
regression analyses were conducted to investigate predictors of insulin
resistance and lipids, and adjustments were made for potential confounders including age, gender, alcohol use, exercise, adiponectin, leptin, CD4 count, HIV RNA, HIV medication use, fat mass, presence or
absence of FR, and WHR. A logistic regression analysis was performed
to examine the association of adiponectin with FR while adjusting for
age, gender, leptin, CD4 count, HIV RNA, and HIV medication use. Data
were normalized via logarithmic or natural log transformation where
appropriate. A P value of 0.05 was used to test for statistical significance,
and all statistical tests were two tailed.
Addy et al. • Hypoadiponectinemia in HAART
TABLE 1. Fat redistribution adjudication guidelines
Fat accumulation
Physical examination criteria including one or more of the
following:a
Enlarged abdomen, neck/upper back, and/or breasts as
observed by the examining physician
Increase in abdominal girth, increase in neck size/mass in
upper back, and/or increase in breast size and/or change in
chest circumference compared to pre-HAART reference point
noted by patient
Increased abdominal girth, increased neck/upper back size,
and/or increase in breast size and/or change in chest
circumference compared to baseline value noted on chart
review
Single or multiple lipoma(s) in any body site
Diagnostic test criteria (one or more of the following)
Anthropometric measurement(s) suggestive of increased
visceral fat content and/or increased total body fat:b
1. Waist circumference ⬎102 cm in men and ⬎88 cm in
women
2. WHR ⬎0.95 in men and ⬎0.85 in women
3. Triceps skinfold thickness ⬎22 mm in men and ⬎36 mm
in women
4. Upper arm circumference ⬎37.5 cm in men and ⬎36.8 cm
in women
5. Subscapular skinfold thickness ⬎40 mm in men and ⬎39
mm in women
DEXA suggestive of increased total body fat, truncal fat, or fat
free mass
Total body fat ⬎29% in men and ⬎41% in women
Single slice CT indicating increased volume of sc and/or
visceral abdominal fat
1. VATc ⱖ200 cm2 in men, ⱖ157 cm2 in women, and ⱖ147
cm2 in blacks
2. TATd ⱖ628 cm2 in men, ⱖ697 cm2 in women, and ⱖ695
cm2 in blacks
Fat depletion
Physical examination criteria including one or more of the
following:a
Facial atrophy based on one or more of the following: sunken
cheeks, sunken temporal regions, and/or prominent
temporal veins observed by physician
Wasting of fat in periphery, limbs and/or buttocks (including
prominent veins)
Diagnostic test criteria (one or more of the following)
Anthropometric measurement(s) suggestive of decreased
subcutaneous fat:b
1. Triceps skinfold thickness ⬍4 mm in men and ⬍8 mm in
women
2. Upper arm circumference ⬍27.1 cm in men and ⬍23.3 cm
in women
3. Subscapular skinfold thickness ⬍7 mm in men and ⬍7
mm in women
DEXA suggestive of fat depletion
Total body fat ⱕ9% in men and ⱕ18% in women
Non-case
No evidence of fat accumulation and/or fat depletion on physical
examination
No evidence of fat accumulation and/or fat depletion based on
diagnostic test criteria
a
Takes into consideration photographic documentation.
More than 90th percentile or less than 5th percentile (49).
c
Visceral adipose tissue.
d
Total abdominal adipose tissue.
b
Results
Baseline characteristics were analyzed among the entire
study group (n ⫽ 112) and comparisons were made between
the FR (FA, FW, or presence of FA and FW) and non-FR
groups. Subjects whose FR subgroup classification could not
J Clin Endocrinol Metab, February 2003, 88(2):627– 636 629
be determined by the Fat Redistribution Adjudication Committee (n ⫽ 4) were excluded from the analysis. Subjects in
the FR group tended to be older, compared with the non-FR
group, and there were significantly more women in the FR
group, compared with the non-FR group (P ⬍ 0.05, data not
shown). WHR and abdominal visceral fat was significantly
higher (P ⬍ 0.01), and extremity fat was significantly lower
in the FR group (P ⬍ 0.05); however, the difference in abdominal sc fat was not significant between the FR and non-FR
groups (data not shown). Highly significant differences (P ⬍
0.01) among metabolic variables were also noted with serum
triglycerides, fasting insulin, and insulin resistance, as measured by HOMA-IR, being higher in the FR group (data not
shown). Fasting adiponectin (micrograms per milliliter) was
significantly lower in the FR, compared with the non-FR
group (2.2 ⫾ 2.7 vs. 4.8 ⫾ 5.0, P ⬍ 0.01), as was serum
high-density lipoprotein (HDL) cholesterol (P ⬍ 0.01, data
not shown). Comparison of HIV medication use between the
FR and non-FR groups was not significantly different with
the exception of cumulative months of nucleoside reverse
transcriptase inhibitor (NRTI) use, which was higher in the
FR group (P ⬍ 0.01, data not shown). Because diabetes mellitus (DM) is a potential confounder, the analyses between
the FR and non-FR groups were repeated with DM patients
excluded. These analyses gave very similar results, the only
difference being a significantly higher diastolic blood pressure (mm Hg) in the FR, compared with the non-FR group
(76.1 ⫾ 9.0 vs. 71.8 ⫾ 10.2, P ⫽ 0.03, data not shown).
Because the FR group included subjects with FA, mixed
FR, and FW and was therefore heterogeneous, comparisons
were made between these subgroups and the non-FR group
using one-way ANOVA with Bonferroni correction (Table 2).
Body mass index (BMI), sc abdominal fat, extremity fat, and
HDL were increased in the FA vs. mixed FR and FW groups
(P ⬍ 0.05), and abdominal visceral fat was significantly lower
in the FW, compared with the FA and mixed groups (P ⬍
0.05). The comparison of adiponectin levels between the FR
subgroups showed apparent differences: no FR (4.8 ⫾ 5.0
␮g/ml), fat accumulation (3.2 ⫾ 2.3 ␮g/ml), mixed FR (1.7
⫾ 2.8 ␮g/ml), and FW (2.0 ⫾ 2.6 ␮g/ml). However, these
differences were significant only between the no FR and
mixed FR groups (P ⬍ 0.05) and the no FR and FW groups
(P ⬍ 0.05). Differences in triglycerides (FA, compared with
mixed FR, P ⫽ 0.06), fasting glucose (FA, compared with FW,
P ⫽ 0.06), fasting insulin, and HOMA-IR among the three
different FR subgroups were noted, but these differences did
not reach statistical significance at the conventional level
(P ⬍ 0.05) except between non-FR and FR subgroups (Fig. 1).
Lack of significance may be due to small sample sizes (type
II error) in each of the FR subgroups (n ⫽ 16 for FA, n ⫽ 27
for mixed, and n ⫽ 20 for FW), although similarities in the
underlying pathophysiology among subgroups cannot be
ruled out. Subgroup analyses were repeated after DM patients were excluded and resulted in no change in the results
presented in Fig. 1.
We then studied the correlation of adiponectin with anthropometric and metabolic variables, HIV medication exposure, and disease duration and severity in the entire study
group using bivariate analysis (Table 3). Adiponectin was
significantly (P ⬍ 0.01) and inversely correlated with WHR,
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J Clin Endocrinol Metab, February 2003, 88(2):627– 636
Addy et al. • Hypoadiponectinemia in HAART
TABLE 2. Baseline characteristics of study group
Fat redistribution subgroupa
Baseline characteristics
Total cohort
(n ⫽ 112)
None (n ⫽ 45)
FA (n ⫽ 16)
Mixed (n ⫽ 27)
FW (n ⫽ 20)
Age (yr)
Gender (M/F)
Systolic BP (mm Hg)
Diastolic BP (mm Hg)
Weight (kg)
BMI (kg/m2)
WHR
Total body fat mass (kg)b
Abdominal visceral fat (cm2)c
Subcutaneous abdominal fat (cm2)c
Extremity fat (g)b
Triglycerides (mmol/liter)
Total cholesterol (mmol/liter)
HDL cholesterol (mmol/liter)
LDL cholesterol (mmol/liter)
Diabetes mellitus (n)
Fasting glucose (mmol/liter)
Fasting insulin (pmol/liter)
Insulin resistance (HOMA-IR)
Fasting adiponectin (␮g/ml)
Cumulative PI use (months)
Cumulative NRTI use (months)
Cumulative NNRTI use (months)
CD4 cell count (cells/␮liter)
HIV RNA levels (⫻103)
Duration HIV (months)
43.8 ⫾ 8.3
98/14
128.0 ⫾ 15.4
73.8 ⫾ 9.9
74.2 ⫾ 12.8
24.4 ⫾ 3.6
0.97 ⫾ 0.07
15.1 ⫾ 8.1
122.5 ⫾ 69.9
126.4 ⫾ 93.8
5342.8 ⫾ 3063.4
3.5 ⫾ 4.1
5.5 ⫾ 1.7
0.9 ⫾ 0.3
3.1 ⫾ 1.1
8 (7.1%)
5.2 ⫾ 1.8
138.0 ⫾ 144.0
109.0 ⫾ 151.7
3.3 ⫾ 4.0
37.9 ⫾ 25.1
121.2 ⫾ 58.0
12.8 ⫾ 12.4
473.7 ⫾ 283.2
12.6 ⫾ 43.9
112.2 ⫾ 47.4
41.6 ⫾ 7.7
42/3
125.1 ⫾ 14.3
71.8 ⫾ 10.2
73.7 ⫾ 10.3
24.0 ⫾ 2.5
0.94 ⫾ 0.06
14.4 ⫾ 5.5
98.5 ⫾ 43.3
121.8 ⫾ 68.1
5703.1 ⫾ 2575.0
2.3 ⫾ 1.7
5.4 ⫾ 1.5
1.0 ⫾ 0.3
3.2 ⫾ 1.2
0 (0%)
4.7 ⫾ 0.5
72.0 ⫾ 36.0
44.0 ⫾ 22.5
4.8 ⫾ 5.0
32.2 ⫾ 26.3
97.7 ⫾ 57.6
11.3 ⫾ 11.3
479.6 ⫾ 235.5
5.2 ⫾ 12.5
102.1 ⫾ 51.7
43.1 ⫾ 7.7
11/5d
126.6 ⫾ 13.3
72.8 ⫾ 12.0
84.3 ⫾ 16.0d
28.5 ⫾ 4.9d
0.99 ⫾ 0.07d
25.2 ⫾ 10.4d
181.3 ⫾ 81.1d
247.1 ⫾ 105.5d
8994.5 ⫾ 3555.9d
2.7 ⫾ 2.2
5.6 ⫾ 1.1
1.1 ⫾ 0.3
3.3 ⫾ 1.0
3 (18.8%)
6.5 ⫾ 3.0d
184.8 ⫾ 149.4d
187.8 ⫾ 198.9d
3.2 ⫾ 2.3
36.3 ⫾ 25.8
101.3 ⫾ 52.6
14.5 ⫾ 15.0
616.7 ⫾ 411.3
3.5 ⫾ 11.8
95.3 ⫾ 59.0
47.4 ⫾ 9.0d
24/3
130.6 ⫾ 15.7
76.0 ⫾ 8.6
75.2 ⫾ 13.5
24.6 ⫾ 3.0e
1.02 ⫾ 0.08d,f
15.0 ⫾ 6.9e,f
163.7 ⫾ 73.1d,f
112.5 ⫾ 86.5e,f
4234.8 ⫾ 2149.9d,e,f
6.0 ⫾ 7.1d
5.8 ⫾ 2.5
0.8 ⫾ 0.3d,e
2.7 ⫾ 1.2d
3 (11.1%)
5.5 ⫾ 2.5
196.2 ⫾ 174.6d
166.9 ⫾ 211.6d
1.7 ⫾ 2.8d
42.0 ⫾ 20.2
149.4 ⫾ 44.9d,e
13.8 ⫾ 13.0
399.4 ⫾ 246.5
17.3 ⫾ 52.6
125.7 ⫾ 35.3
44.6 ⫾ 7.6
19/1
135.0 ⫾ 17.7
76.1 ⫾ 8.3
68.3 ⫾ 10.2e
22.5 ⫾ 2.7e
0.94 ⫾ 0.04
8.1 ⫾ 3.7d,e
83.4 ⫾ 49.5e
48.3 ⫾ 33.9d,e
2863.0 ⫾ 1189.4d,e
3.8 ⫾ 2.7
5.4 ⫾ 1.4
0.8 ⫾ 0.2d,e
3.0 ⫾ 0.8
1 (5%)
4.8 ⫾ 0.9
159.0 ⫾ 193.8d
102.4 ⫾ 111.5d
2.0 ⫾ 2.6d
43.4 ⫾ 25.4
144.8 ⫾ 52.1d
12.8 ⫾ 11.6
483.0 ⫾ 301.6
33.7 ⫾ 80.9
127.5 ⫾ 36.1
Data are mean values ⫾ SD. Mixed, Fat accumulation plus fat wasting; NNRTI, non-NRTI; M, male; F, female; BP, blood pressure; LDL,
low-density lipoprotein.
a
Four subjects (3.6%) could not be categorized according to fat redistribution based on available data.
b
Calculated from DEXA scan data.
c
Calculated from single slice CT scan at L4.
d
P ⬍ 0.05 compared with subgroup with no fat redistribution.
e
P ⬍ 0.05 compared with FA subgroup.
f
P ⬍ 0.05 compared with FW subgroup.
abdominal visceral fat, triglycerides, fasting insulin, HOMAIR, and cumulative NRTI exposure. Additionally, adiponectin showed significant direct correlation with abdominal sc
fat (r ⫽ 0.24), extremity fat (r ⫽ 0.37), and HDL cholesterol
(r ⫽ 0.41). Importantly, the correlation of adiponectin with
triglycerides, HOMA-IR, and abdominal visceral fat showed
a significant negative curvilinear relationship, but no significant association with total fat mass was observed (r ⫽ 0.15,
P ⫽ 0.12) (Fig. 2). Because of these apparent nonlinear relationships, additional models were run to better characterize
the nature of these associations (data not shown). An exponential model showed that adiponectin explained nearly
twice the variability of triglycerides in comparison with a
linear model. Additionally, a logarithmic model showed that
adiponectin explained nearly twice the variability of
HOMA-IR in comparison with a linear model. These models
suggest that Spearman correlation coefficients underestimate the association of adiponectin with both of these variables. Repeat correlation analyses after DM patients were
excluded resulted in weakening of the correlation of adiponectin with insulin resistance (r ⫽ ⫺0.25 vs. r ⫽ ⫺0.28, P ⫽
0.01 vs. P ⬍ 0.01), strengthening of the correlations of adiponectin with abdominal sc fat (r ⫽ 0.31 vs. r ⫽ 0.24, P ⬍ 0.01
vs. P ⫽ 0.01) and extremity fat (r ⫽ 0.40 vs. r ⫽ 0.37, both P ⬍
0.01), but no change in the association of adiponectin with
triglycerides, HDL, glucose, or fasting insulin.
We then performed multiple linear regression analyses for
the entire study group to study whether adiponectin is an
independent predictor of insulin resistance and serum lipid
levels and to adjust for potential confounding factors (Table
4). Regression models were run to adjust for each HAART
medication class separately. Adjustments for cumulative PI
or NNRTI use alone did not result in any significant improvement in the fit of the models and are therefore not
reported. We presented the model that adjusted for cumulative NRTI use because this resulted in the model that best
fit the data. Because the mixed FR subgroup was significantly
older that the non-FR group and there was a significant
correlation of age and abdominal visceral fat (r ⫽ 0.26, P ⬍
0.01), all models were adjusted for age. We presented visceral
adipose tissue (VAT) in all models as a correlate of central
adiposity and extremity fat as a marker of peripheral fat
wasting. We also ran similar models substituting WHR or
waist circumference for VAT and models that substituted hip
circumference or abdominal sc fat for extremity fat. The
strong inverse correlation between adiponectin and serum
triglycerides was essentially unaltered after adjusting for
potential confounders such as age, gender, leptin, cumulative NRTI use, cumulative use of all HIV medications, CD4
count, or viral load (P ⫽ 0.01) (Table 4). The significance of
this correlation was slightly decreased but remained statistically significant when the model was further adjusted for
HOMA-IR (data not shown, P ⫽ 0.01). The association between serum triglycerides and adiponectin was slightly
Addy et al. • Hypoadiponectinemia in HAART
J Clin Endocrinol Metab, February 2003, 88(2):627– 636 631
FIG. 1. Adiponectin, triglycerides, abdominal visceral fat, and IR in association with FR class. Group 0 ⫽ no FR (n ⫽ 45), group 1 ⫽ FA (n ⫽
16), group 2 ⫽ mixed FR (n ⫽ 27), group 3 ⫽ FW (n ⫽ 20). Data are means ⫾ SE. a, P ⱕ 0.02 for comparison adiponectin between group 0 and
groups 2 and 3. b, P ⫽ 0.001 for comparison of triglycerides between group 0 and group 2. c, P ⬍ 0.001 for comparison of abdominal visceral
fat area between group 0 and groups 1 and 2 and between groups 1 and 2 and group 3. d, P ⬍ 0.03 for comparison of IR between group 0 and
groups 1, 2, and 3.
weakened but remained significant when the model was
further adjusted for VAT (P ⫽ 0.03) and extremity fat (P ⫽
0.04), indicating that the association between adiponectin
and triglycerides is in part influenced by FR. A strong direct
correlation was noted between adiponectin and HDL cholesterol, and this correlation remained significant when the
model was adjusted for potential confounders (␤ ⫽ 0.29, P ⫽
0.007) (Table 4). In addition, adiponectin was inversely correlated with HOMA-IR after adjusting for age, gender, and
leptin (␤ ⫽ ⫺0.21, P ⫽ 0.03) (Table 4). This correlation was
weakened significantly after adjusting for cumulative NRTI
but not other HIV medication use (P ⫽ 0.12) (Table 4). The
association of adiponectin with insulin resistance was further
weakened when the model was adjusted for CD4 count and
HIV viral load (P ⫽ 0.20), suggesting that disease severity
and NRTI use may modulate insulin resistance by altering
adiponectin levels. The association between adiponectin and
insulin resistance was further weakened when the model
was adjusted for VAT and extremity fat (P ⫽ 0.40), suggest-
ing that FR may modulate insulin resistance through changes
in adiponectin (Table 4).
Multivariate linear regression models adjusting for the use
of alcohol, exercise and activity level, duration of HIV infection, extremity fat, and abdominal sc fat did not alter the
significance of the correlations between adiponectin and
HOMA-IR, triglycerides, and HDL (data not shown). The
associations of adiponectin with insulin resistance and serum
lipids were essentially unchanged after WHR or waist circumference was substituted for VAT and hip circumference
or abdominal sc fat was substituted for extremity fat in the
models (data not shown).
The exclusion of DM cases from the analyses (data not
shown) showed weakening of the association of adiponectin
with triglycerides (␤7 ⫽ ⫺0.17, P ⫽ 0.16) and a weakened but
still significant direct association with HDL (␤ ⫽ 0.24, P ⫽
0.02). The association of adiponectin with insulin resistance
became of borderline significance after adjusting for potential confounders (␤2 ⫽ ⫺0.18, P ⫽ 0.08).
632
J Clin Endocrinol Metab, February 2003, 88(2):627– 636
Addy et al. • Hypoadiponectinemia in HAART
TABLE 3. Spearman correlation of adiponectin with metabolic
factors, anthropometric factors, HIV medication use, and disease
severity and duration
Variable
Age
BMI
WHR
Total body fat mass
Abdominal visceral fat
Abdominal sc fat
Extremity fat
Total cholesterol
LDL cholesterol
HDL cholesterol
Triglycerides
Fasting glucose
Fasting insulin
Insulin resistance (HOMA-IR)
Fasting leptin
Cumulative PI exposure
Cumulative NRTI exposure
Cumulative NNRTI exposure
CD4 count
HIV RNA
Duration of HIV infection
Adiponectin
r
P
⫺0.36
⫺0.16
⫺0.43
0.15
⫺0.35
0.24
0.37
⫺0.16
0.04
0.41
⫺0.40
⫺0.09
⫺0.31
⫺0.28
0.15
⫺0.09
⫺0.32
⫺0.003
⫺0.06
⫺0.07
⫺0.12
⬍0.01
0.09
⬍0.01
0.12
⬍0.01
0.01
⬍0.01
0.09
0.72
⬍0.01
⬍0.01
0.34
⬍0.01
⬍0.01
0.13
0.35
⬍0.01
0.97
0.57
0.49
0.20
LDL, Low-density lipoprotein; NNRTI, non-NRTI.
We performed a multiple logistic regression analysis to
examine the relationship of adiponectin with FR (Table 5).
We observed adiponectin to be inversely associated with FR
even when adjusting for age, gender, leptin, CD4 count, HIV
RNA, and HIV medication use (odds ratio, 0.54, P ⫽ 0.008).
Repeat analyses adjusting for duration of HIV infection and
after excluding subjects with DM resulted in no change in
this association.
Finally, to determine whether the FR subgroups individually affected the results of linear regression and logistic
regression models, we repeated these analyses after separately excluding each of the subgroups. Exclusion of the FA
or FW subgroups did not essentially change the results. Exclusion of the mixed FR subgroup resulted in relatively more
substantial weakening of all linear regression models as well
as the logistic regression model (odds ratio 6, 0.64 vs. 0.54),
compared with the exclusion of the other two subgroups.
This finding suggests that the combined effect of peripheral
FW and central FA may be of relatively more importance
than either of the two alone in giving rise to the metabolic
abnormalities and decreased adiponectin levels that are associated with HAART/HIV-associated lipodystrophy.
Given recent data demonstrating that adiponectin administered to lipodystrophic mice led to improvement in metabolic parameters and insulin sensitivity, we explored the
bivariate association between adiponectin and insulin resistance, metabolic outcomes, and anthropometric variables by
means of Spearman correlation in the FW subgroup only (n ⫽
20, data not shown). Significant associations were noted between adiponectin and HDL (r ⫽ 0.61, P ⫽ 0.005), abdominal
visceral fat (r ⫽ ⫺0.69, P ⫽ 0.007), total body fat mass on CT
(r ⫽ ⫺0.51, P ⫽ 0.02), and body weight (r ⫽ ⫺0.46, P ⫽ 0.04).
Adiponectin showed nonsignificant correlation with triglycerides (r ⫽ ⫺0.30, P ⫽ 0.20) and HOMA-IR (r ⫽ ⫺0.17, P ⫽
0.48). The lack of significance of these correlations may be
due to small sample size (n ⫽ 20) or the fact that the relationships between adiponectin and both triglycerides and
HOMA-IR are not linear (as shown in Fig. 2 for the entire
cohort). Thus, we repeated our analyses using nonlinear
models and found that in the FW subgroup, an exponential
model explained more than twice the variability of that explained by a linear model in describing the association of
adiponectin with triglycerides. Similarly, a logarithmic
model explained nearly twice as much of the variability of
that explained by a linear model in the association of
HOMA-IR and adiponectin. These models suggest that use
of linear models underestimates the correlation because of a
nonlinear relationship with adiponectin and both of these
variables.
Discussion
Our study demonstrates that adiponectin levels are significantly lower in a sample of HIV-infected subjects with FR
caused by HAART, compared with those subjects without
FR. Although evident in both the FA and FW groups, the
decline in adiponectin appeared to be most significant in
those subjects with mixed FR (FA plus FW) as seen in Fig. 1.
The difference in adiponectin levels between subjects with
and without FR remained essentially unchanged after adjusting for age, gender, leptin, HIV medications, and disease
severity using logistic regression analysis. Because of the
significant association of adiponectin with both abdominal
visceral fat and extremity fat, the distinct possibility exists
that increased visceral adiposity coupled with peripheral FW
best explains the decreased adiponectin levels in patients
with mixed FR, especially in those with increased central,
compared with peripheral, fat distribution.
Because the possibility exists that visceral fat may also
influence, in part, the relationship between adiponectin and
metabolic factors, we examined whether adiponectin was
related to several components of the metabolic syndrome
and whether such associations were mediated by body fat
distribution as well as disease severity or medication use.
Our results demonstrate that adiponectin is significantly correlated with IR, triglycerides, and HDL in HIV-infected patients treated with HAART. The strong direct correlation of
adiponectin with HDL was most pronounced in the entire
study group and was even significant in the FW group,
despite the small number of subjects in this subgroup. The
associations of adiponectin with IR, HDL, and triglycerides
persisted on multivariate analyses when adjusting for age,
gender, leptin, DM, alcohol use, and exercise. Adjusting for
central obesity, expressed as VAT, and extremity fat weakened the association of adiponectin with insulin resistance
and slightly weakened its association with serum triglycerides, indicating that body FR may, in part, underlie the association between adiponectin and IR and serum triglycerides. The inverse association of adiponectin with HOMA-IR
was also weakened significantly with adjustment for cumulative NRTI use, CD4 count, and HIV viral load, indicating
that disease severity and HIV medication use may play a role
in mediating the effect of adiponectin on IR. However, the
association of adiponectin with HDL weakened but remained significant despite adjustments for potential con-
Addy et al. • Hypoadiponectinemia in HAART
J Clin Endocrinol Metab, February 2003, 88(2):627– 636 633
FIG. 2. Correlation of adiponectin with triglycerides, IR, abdominal visceral fat, and total body fat mass.
founders, including central obesity. Importantly, in our
study adiponectin was inversely associated with abdominal
visceral fat and positively associated with sc fat, which is
consistent with the role of visceral adiposity in the development of IR and lipid abnormalities associated with the
metabolic syndrome (32–34).
Features of the metabolic syndrome such as obesity and IR
have been associated with increased levels of TNF␣. An in
vitro study demonstrated that TNF␣ decreased the expression of the apM1 gene and the secretion of its gene product,
adiponectin, from 3T3-L1-adipocytes (35). The effect of
HAART on TNF␣ remains largely unknown. Although one
study has suggested that circulating TNF␣ levels decrease,
but do not normalize, in patients receiving HAART, another
study has suggested that HAART may be partly responsible
for increased synthesis of TNF␣ by T cells (36 –37). We found
that adiponectin was inversely associated with cumulative
months of NRTI use but not other classes of antiretroviral
therapies, including PI use. The lack of association with the
latter is potentially a type II error and may be explained by
the fact that the vast majority of the study subjects had used
PI therapy for some time period during their treatment for
634
J Clin Endocrinol Metab, February 2003, 88(2):627– 636
Addy et al. • Hypoadiponectinemia in HAART
TABLE 4. Multivariate linear regression models showing association of adiponectin with insulin resistance and serum lipids while
adjusting for age, gender, leptin, HIV medication use, disease severity, and fat distribution
a
Triglycerides
P value
HDL cholesterola
P value
Insulin resistanceb,c
P value
Total cholesterola
P value
LDL cholesterol
P value
␤1
␤2
␤3
␤4
␤5
␤6
␤7
⫺0.32
0.001
0.36
⬍0.001
⫺0.24
0.01
⫺0.13
0.19
⫺0.02
0.84
⫺0.31
0.001
0.33
0.001
⫺0.20
0.03
⫺0.12
0.22
0.0
0.97
⫺0.31
0.001
0.31
0.001
⫺0.21
0.03
⫺0.13
0.19
0.0
0.99
⫺0.29
0.005
0.29
0.003
⫺0.15
0.12
⫺0.13
0.21
⫺0.05
0.61
⫺0.29
0.005
0.30
0.002
⫺0.15
0.11
⫺0.13
0.21
⫺0.05
0.62
⫺0.28
0.01
0.33
0.001
⫺0.14
0.20
⫺0.10
0.38
⫺0.02
0.87
⫺0.25
0.03
0.33
0.002
⫺0.07
0.53
⫺0.09
0.44
⫺0.04
0.73
␤8
⫺0.24
0.04
0.29
0.007
⫺0.10
0.40
⫺0.10
0.41
⫺0.04
0.75
␤1, Bivariate analysis; ␤2, adjusted for age, gender; ␤3, adjusted for age, gender, leptin; ␤4, adjusted for age, gender, leptin, NRTI use; ␤5,
adjusted for age, gender, leptin, all HIV medication use; ␤6, adjusted for age, gender, leptin, all HIV medication use, CD4 count, HIV RNA;
␤7, adjusted for age, gender, leptin, all HIV medication use, CD4 count, HIV RNA, visceral adipose tissue (VAT); ␤8, adjusted for age, gender,
leptin, all HIV medication use, CD4 count, HIV RNA, VAT, extremity fat.
a
Data natural log transformed prior to analysis.
b
As measured by HOMA-IR.
c
Data log10 transformed prior to analysis.
TABLE 5. Logistic regression model to assess association of fat redistribution with adiponectin, leptin, disease severity, and HIV
medication use
Adiponectina
P value
OR1
OR2
OR3
OR4
OR5
OR6
0.53
⬍0.001
0.51
⬍0.001
0.50
⬍0.001
0.51
0.002
0.57
0.002
0.54
0.008
OR1, Univariate analysis; OR2, adjusted for age, gender; OR3, adjusted for age, gender, leptin; OR4, adjusted for age, gender, leptin, CD4
count, HIV RNA; OR5, adjusted for age, gender, leptin, CD4 count, HIV RNA, cumulative NRTI use; OR6, adjusted for age, gender, leptin, CD4
count, HIV RNA, all HIV medication use.
a
Natural log transformed prior to analysis.
HIV infection. The strong association between adiponectin
and IR on multivariate linear regression analysis became
statistically insignificant when the model was adjusted for
cumulative NRTI use. These observations support the hypothesis that adiponectin secretion may be down-regulated
with use of medications such as NRTIs. Whether this effect
is mediated by NRTI-induced changes in TNF␣ levels or it
is due to a direct effect of NRTIs to decrease adipocyte differentiation and thus decrease adiponectin secretion remains
to be shown. Carr et al. (38) proposed that antiretroviral
medications may directly decrease adipocyte differentiation
by inhibiting the activation of the retinoid X receptorperoxisome proliferator-activator receptor (PPAR)-␥ heterodimer, a nuclear receptor involved in adipocyte differentiation. Agonists of PPAR-␥ have been associated with
improvement in insulin sensitivity and increased adipocyte
differentiation and have been shown in in vitro, animal, and
human models to increase adiponectin secretion (18, 39, 40).
Most recently, Bastard et al. (41) showed that a decrease in
sterol-regulatory-element-binding-protein-1c was associated with decreased expression of PPAR-␥ and decreased
adipocyte differentiation in a sample of patients with
HAART-induced lipoatrophy. TNF␣ was found to be increased and leptin was found to be decreased in these
patients as would be expected in the setting of abnormal
adipocyte differentiation. Although adiponectin was not
measured specifically, one could hypothesize that based on
increased TNF␣ and decreased adipocyte differentiation,
adiponectin levels would be decreased as seen in our study.
The results from our study highlight a significant inverse
association of adiponectin with IR and serum triglyceride
levels as well as a strong direct correlation of adiponectin
with HDL cholesterol. Our findings are in keeping with prior
association studies in humans with type 2 DM, obesity, CHD,
and congenital and acquired lipodystrophies in non-HIV
infected subjects/populations and mirror those from a prospective longitudinal study that reported declining adiponectin levels in parallel with the development of obesity
and type 2 DM in Rhesus monkeys (14, 16, 17, 19, 42, 43).
This is the first study to show that hypoadiponectinemia
is associated with HIV-induced lipodystrophy. Although our
entire study was adequately powered, our subgroup analysis
was limited by relatively small numbers of subjects in each
of the three FR subgroups. The factors contributing to these
differences in body fat distribution in HAART-induced
lipodystrophy are currently unknown but may include the
effects of specific antiretroviral medications on the sterolregulatory-element-binding-protein-1c and adipocyte differentiation (44). In all likelihood, the etiology of this disorder
is multifactorial and influenced by genetics, diet, race, gender, and viral factors. Future studies are needed to better
characterize the potential differences among subgroups
with regard to the underlying pathophysiology of FR and
the associated metabolic consequences such as hypoadiponectinemia, hyperlipidemia, and IR.
In a murine model of lipoatrophic diabetes mellitus and
hypoadiponectinemia, administration of adiponectin decreased IR (18). Adiponectin increases free fatty acid transport, oxidation, and dissipation in skeletal muscle; reduces
the levels of intramyocellular lipids; and thus improves insulin signaling (45, 46). In addition, adiponectin suppresses
hepatic glucose output and increases the sensitivity of hepa-
Addy et al. • Hypoadiponectinemia in HAART
tocytes to insulin either through a direct action or indirectly
by lowering circulating lipids because of its action in muscle
(18, 45– 47). Taken together, these data suggest that administration of adiponectin results in improved insulin sensitivity and glucose tolerance and decreased hyperglycemia.
Oral et al. (48) recently demonstrated partial but significant
improvement in insulin sensitivity and a decline in serum
triglycerides after leptin administration in patients with
leptin-deficient lipodystrophy. Interestingly, leptin or
adiponectin administration alone can only partially restore
insulin sensitivity in lipoatrophic mice, whereas the coadministration of both leptin and adiponectin can fully normalize insulin sensitivity (18). It remains to be seen whether
leptin and/or adiponectin replacement in patients with
HIV-lipodystrophy would lead to similar metabolic
improvements.
J Clin Endocrinol Metab, February 2003, 88(2):627– 636 635
16.
17.
18.
19.
20.
Acknowledgments
Received May 23, 2002. Accepted November 4, 2002.
Address all correspondence and requests for reprints to: Christos S.
Mantzoros, M.D., Division of Endocrinology and Metabolism, Beth Israel Deaconess Medical Center, 99 Brookline Avenue, RN 325A, Boston,
Massachusetts 02215. E-mail: [email protected].
This work was supported by an American Diabetes Association Clinical Research Grant and NIH Grant DK-58785-R01 (to C.S.M.), NIH
Grant M01-RR 01032 (to BIDMC General Clinical Research Center), NIH
Grant K30-HL04095 (to Harvard Medical School), and Merck Research
Laboratories.
21.
22.
23.
24.
25.
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