Share this article on:

Detectable HIV Viral Load Is Associated With Metabolic Syndrome

Squillace, Nicola MD; Zona, Stefano MD; Stentarelli, Chiara MD; Orlando, Gabriella MD; Beghetto, Barbara PhD; Nardini, Giulia PhD; Esposito, Roberto MD; Guaraldi, Giovanni MD

JAIDS Journal of Acquired Immune Deficiency Syndromes: December 2009 - Volume 52 - Issue 4 - p 459-464
doi: 10.1097/QAI.0b013e3181b93a23
Clinical Science

Background: The aim of our study was to assess the association between HIV viral load (HIV-VL) and metabolic syndrome (MS) in a cohort of HIV-infected patients.

Methods: This is a cross-sectional study including 1324 consecutive HIV-infected patients on stable antiretroviral therapy regimens.

Results: Variables significantly associated with MS in univariate analysis were: age [mean ± SD: 47.04 ± 7.41 vs 44.07 ± 6.82, (P < 0.0001)]; male sex [224 (69.35%) vs 614 (61.34%) (P = 0.009)]; Apo B (mg/dL) [111.51 ± 29.64 vs 100.57 ± 31.22, (P < 0.0001)]; homeostasis model assessment equation [median (interquartile range), 5.14 (3.00-8.15) vs 2.95 (1.93-4.57), (P < 0.0001)]; body mass index [25.17 ± 4.40 vs 22.80 ± 3.38, (P < 0.0001)]; protease inhibitor current use (%) [199 (61.61) vs 529 (52.85), (P = 0.006)]; and log10 HIV-VL [2.17 ± 0.94 vs 2.02 ± 0.79, (P = 0.0048)]. MS associated variables in multivariable analysis were: log10 HIV-VL [odds ratio (OR): 1.25; P = 0.003], age (per 10-year increment) [OR: 1.60; P < 0.0001], homeostasis model assessment equation ≥3.8 [OR: 2.77; P < 0.0001].

Conclusions: Persistent viremia is a significant predictor for the development of MS. Viral control through effective antiretroviral therapy is paramount not only for the control of HIV disease progression but also for the prevention of MS and associated cardiovascular disease.

From the Department of Medicine and Medical Specialties, Infectious Diseases Clinic, University of Modena and Reggio Emilia, Modena, Italy. Nicola Squillace now moved to Division of Infectious Diseases, Department of Internal Medicine, “San Gerardo” Hospital, University Milano-Bicocca, Monza, Italy.

Received for publication January 24, 2009; accepted June 5, 2009.

Part of these data were presented as poster at the 10th International Workshop on Adverse Drug Reactions and Lipodystrophy in HIV, November 6-8, 2008, London, United Kingdom; and at the 9th International Congress on Drug Therapy in HIV Infection, November 9-13, 2008, Glasgow, United Kingdom.

None of the authors declared any possible conflict of interest.

Correspondence to: Nicola Squillace, MD, Division of Infectious Diseases, Department of Internal Medicine, “San Gerardo” Hospital, University Milano-Bicocca, Via Pergolesi 33, Monza, Italy (e-mail:

Back to Top | Article Outline


Metabolic syndrome (MS) has been identified as a constellation of abnormalities that lead to an increased risk of cardiovascular disease (CVD).1 MS is affecting the general population in epidemic proportion, for example, up to 26.5% in the National Health and Nutrition Examination Survey (NHANES) cohort.2 The prevalence of MS in HIV-infected individuals is comparable with that in the general population and varies from 15%3 to 25.5%.4 But the studies to-date have shown conflicting results with regard to the roles of both HIV and antiretroviral therapy (ART) on the diagnosis of MS.2-5 It has been established that HIV itself may produce lipid abnormalities both in ART-naive patients6 and experienced patients.7 It is well known that several of the diagnostic criteria of MS overlap with common features of metabolic and morphologic abnormalities frequently observed in ART-experienced HIV-infected individuals. In particular, increased abdominal waist circumference (WC), elevated triglycerides, low high-density lipoprotein (HDL) cholesterol, and glucose abnormalities are commonly observed in patients with HIV infection and have been associated with ART.8-11 A positive association of MS with lopinavir/ritonavir and stavudine was found by Jericò et al,12 lopinavir/ritonavir and didanosine by Jacobson et al,2 and stavudine alone by Sobieszczyk et al.13 Samaras et al14 confirmed the association of MS with the protease inhibitor (PI) class, whereas Sobieszczyk et al13 did not find a significant association with ritonavir-boosted PIs, but a protective role of the nonnucleoside reverse transcriptase inhibitor (NNRTI) nevirapine.

Three case-control studies have investigated the impact of HIV on MS diagnosis. In a cohort of 1243 patients compared with 1922 controls. Bonfanti et al5 observed an increased prevalence of MS in HIV-infected patients compared with HIV-negative controls. Sobieszczyk et al13 confimed these results. On the contrary, Mondy et al4 did not find an association of MS and HIV in a cohort of 471 HIV-infected patients compared with NHANES. However, HIV diagnosis was related to both elevated triglyceride levels and low HDL cholesterol.

It further remains unclear if HIV RNA levels may better discriminate the role of the virus in the development of MS. Mangili et al15 showed significantly higher HIV-VL in those defined as having MS in a cohort of 314 HIV-infected patients. Jacobson et al2 found a higher risk of MS in patients with clinically relevant increase in HIV-VL in the previous 6 months in a sample of 477 patients. Sobieszczyk et al13 showed that HIV-VL greater than 50,000 copies per milliliter conferred an increased risk of MS in a large sample of HIV-infected women.13 On the contrary, 5 other studies did not find a significant relationship between HIV-VL and MS diagnosis.3,4,12,16,17 In all these studies, patients who were both ART naive and ART experienced were included.

The objective of our study was to assess the association between detectable HIV-VL and MS prevalence in a cohort of HIV patients on stable ART regimen.

Back to Top | Article Outline



This was a cross-sectional study that included all consecutive HIV-infected patients seen at the metabolic clinic of the University of Modena and Reggio Emilia, Italy, between January 2006 and January 2008 (1 visit for patient) who had received ART for at least 2 years. Other inclusion criteria were serologically documented HIV infection, age >18 years, and, among persons with hyperlipidemia requiring treatment, on stable lipid lowering for at least 6 months. Patients naive to ART or undergoing treatment interruptions and those previously diagnosed with diabetes were excluded from participating.

5.7% of sample had a fasting blood glucose above 126 mg/dL in the absence of a known diabetes history. Given the observational cross-sectional nature of this study, we were unable to confirm these values and these patients were not excluded from the analysis.

Back to Top | Article Outline

Clinical Data and Measurements

Demographics and clinical data, including duration of HIV infection, prior opportunistic diseases (CDC classification), ART history, and lifestyle were obtained from medical files. Information regarding therapy with omega-3 fatty acids, fibrates, and statins was also collected from medical records.

Insulin resistance (IR) was calculated using the homeostasis model assessment equation {HOMA-IR = [fasting insulin (mU/mL) × fasting glucose (mmol/L)/22.5]}. IR was defined as HOMA-IR ≥3.8.18

CD4 cell counts (most recent value and nadir), plasma HIV-1 RNA levels, cumulative and current exposure to NNRTI and nucleoside reverse transcriptase inhibitors (NRTI), and PI. Total cholesterol (TChol), low-density lipoprotein, HDL, triglycerides, apolipoprotein B (Apo B), glucose, and insulin were assessed at entry after an overnight fast.

Lipodystrophy (LD) was defined using the HIV Outpatient Study definition, with anthropomorphic categorizations of lipoatrophy, lipohypertrophy, and mixed form.19 Obesity was defined as body mass index (BMI) >30.

On the same day of blood sample collection, the following anthropometric measurements were assessed: WC; BMI; total body fat mass and total lean cell mass by means of whole-body dual energy X-ray absorptiometry; abdominal visceral adipose tissue volume (VAT), subcutaneous adipose tissue volume, and total adipose tissue volume (TAT) by means of single-slice abdominal computed tomography (CT) scan at the level of the L4 vertebra. Lower extremity fat percentage to BMI ratio was the marker of lipoatrophy severity. VAT/TAT and VAT/TAT to BMI ratio calculations were the markers of central fat obesity.

The National Cholesterol Educational Program Adult Treatment Panel III MS definition was used to assess the primary outcome.20 Patients with at least 3 of the following abnormalities were defined as having MS: (1) abdominal obesity: WC >102 cm for men and >88 cm for women; (2) hypertriglyceridemia: >150 mg/dL; (3) low HDL cholesterol: <40 mg/dL for men and <50 mg/dL for women; (4) high blood pressure: ≥130/85 mm Hg; (5) high fasting glucose: ≥100 mg/dL according to 2004 definition.1

To assess the role of HIV-VL, the entire cohort was stratified as greater or equal and less than 400 copies per milliliter for HIV-VL: commonly used to define HIV-VL undetectability. Log HIV-VL was defined as the natural logarithm transformed concentration of HIV-viral load to achieve a normal distribution of the variable. “Current use”of PI, NNRTI, and NRTI was defined as actual use of these classes of drugs.

Back to Top | Article Outline

Statistical Analysis

Comparisons between continuous variables were performed using the t test or Mann-Whitney test when appropriate, whereas the χ2 test was used for qualitative variables. The P value of less than 0.05 was considered statistically significant. Univariate and multivariate logistic regression analyses were performed to identify variables associated with MS. A multivariable, backward stepwise model included variables significantly associated in the univariate model. Software package STATA (9.2 for windows, 2006) was used for statistical analysis.

Back to Top | Article Outline


One thousand three hundred twenty-four patients were analyzed. Eight hundred fifty (63%) were males, mean age was 45 (±7). Obesity was present in 78 patients (5.8%). HIV-VL <400 copies per milliliter was present in 84.8% patients. The prevalence of MS was of 24.4%.

Table 1 shows the distribution of demographic and clinical characteristics of HIV-infected patients with and without MS. Those with MS were significantly different from patients without MS with regard to the following: metabolic variables (glucose, HDL cholesterol, triglycerides, ApoB, TChol/HDL cholesterol ratio, HOMA-IR, blood pressure), anthropometric variables (BMI, WC, presence of LD, LD phenotype, VAT/TAT, % fat leg, % fat leg/BMI, trunk fat, total fat, total lean), and HIV variables (log HIV-VL, current PI use, current NNRTI use, NNRTI exposure).



MS was present in 139 patients (22.7%) with HIV-VL <400 copies per milliliter compared with 66 patients (32.2%) with VL ≥400 copies per milliliter (P = 0.005). Figure 1 describes the prevalence of MS components between patients with HIV-VL > or <400 copies per milliliter. Elevated blood pressure and low HDL and high triglycerides are significantly different between the 2 groups.



Table 2 compares variables by HIV-VL cutoffs in those patients with and without MS. Patients with MS and HIV-VL >400 copies per milliliter had significantly lower CD4 cell count than those with MS and HIV-VL <400 copies per milliliter (P < 0.01), more PI exposure (P = 0.05), and less NNRTI exposure and current use (P < 0.01 for both). Patients without MS and HIV-VL >400 copies per milliliter showed significantly lower CD4 cell count than those without MS and HIV-VL <400 copies per milliliter (P < 0.01) and higher TChol/HDL cholesterol ratio (P < 0.01).



The results from multivariate logistic regression are shown in Table 3. In stepwise multivariable logistic regression analyses (Table 3), the following were independently associated with a diagnosis of MS: log10 HIV-VL [odds ratio (OR): 1.25; 95% confidence interval (CI): 1.08 to 1.46], age (per 10-year increment) (OR: 1.60; 95% CI: 1.35 to 1.90), and HOMA-IR≥ 3.8 (OR: 2.77; 95% CI: 2.02 to 3.8).



In particular, each Log10 increase in HIV-VL augmented the risk of MS diagnosis of 25%.

Back to Top | Article Outline


Our data suggest a strong association between detectable HIV-VL and MS. This association was previously shown by Mangili et al15 and Sobieszczyk et al13 but in a nonhomogeneous population of both naive and treatment-experienced patients. Our study attempted to reproduce this association in a more uniform cohort of HIV-infected patient on stable ART. We depict a cohort were 15.2% had detectable VL, lower than other large HIV cohorts.21

The clinical significance of HIV-VL >400 copies per milliliter is related both to suboptimal antiretroviral (ARV) therapy and/or drug failure. The availability of novel and more potent antiretroviral drugs has introduced a change to current HIV treatment guidelines. The current “virological goal” for long-term success of ARV therapy and control of progression of HIV disease is to achieve undetectable HIV-VL at any stage of HIV infection. We believe that the results of our study reinforces those guidelines' objective and additionally introduces a “metabolic goal”: an effective ART can control HIV and avoid MS and its related cardiovascular complications and diabetes risk.

MS prevalence in our population was 24.4%. This is higher than previously reported by Bonfanti et al5 (20.8%), who studied a population of similar ethnic origin, but with different clinical characteristics. Our patients were selected from an HIV Metabolic Clinic and the high prevalence of LD (present in 88.3%) may explain the higher prevalence of metabolic abnormalities in our cohort. However, LD was homogenously distributed in patients with detectable versus undetectable HIV-VL, thus not likely influencing the objective of our study. Moreover, we did not find any association between LD prevalence and HIV-VL >400 copies per milliliter.

This study provides 2 major comparisons. Patients with MS showed high prevalence of obesity and LD and biochemical patterns suggestive for increased cardiovascular risk. We confirmed the role of PI class for developing MS and the protective effect of NNRTI as recently described by Sobieszczyk et al.13 Insulin resistance is supposed to be the driving force of MS in the general population, and this association was found in our sample.

This cohort showed a higher risk of MS in males. A higher prevalence of MS in males is controversial in white ethnic group and much related to anthropometric characteristics of different populations. Interestingly, we found a low prevalence of obesity in our sample all together and a lower BMI in females with respect to males (data not shown).

As expected, HOMA-IR was higher in patients with MS, stressing the hypothesis of a possible common pathogenetic link between MS features. HOMA-IR was included in the regression analysis to provide clinicians a useful tool to predict MS. Given HOMA its collinear with glucose, to avoid overlap with glucose parameter, a component of MS definition, a high cutoff value was chosen (3.8). We also want to emphasize the importance of the association of ApoB with MS in our cohort. This lipid measurement has recently been proposed to be a better predictor of coronary heart disease than cholesterol and low-density lipoprotein cholesterol, moreover, it is not influenced by fasting status of the patient.22 We were not surprised to confirm that high BMI, VAT/TAT, trunk fat, and total fat in our HIV-infected patients were associated with MS. We hypothesize that higher total lean body mass was significantly associated with MS due to a higher proportion of fat tissue present in the muscles. This has previously been demonstrated in patients with LD.23

Of particular interest also is our observation of an association between cumulative and current ARV exposure and MS prevalence. Patients with MS seemed to be less exposed to NNRTI (both cumulative and current exposure), suggesting a protective role of this drug class as was previously shown by Sobieszczyk et al.13 We confirmed an association between current PI use and MS,2,12,14,16 but we did not find any association with NRTI exposure. We were unable to analyze the individual impact of thymidine analogues on MS due to the low number of patient on this class of drug among patients attending our metabolic clinic. Nevertheless, we believe it is necessary to stress that in observational cross-sectional studies, causation between drug exposure and MS can not be demonstrated and channelling bias may occur. For example, a NNRTI-based regimen may be the preferred treatment choice in patients with worse metabolic profiles.

Patients with detectable HIV-VL had a higher prevalence of MS than patients with undetectable HIV-VL (32.2% vs 22.7%, P < 0.001). Several epidemiological studies have previously shown this association in both naives and experienced HIV patients. More recently, Shrivastav et al24 demonstrated in vitro that HIV-1 viral protein R is a peroxisome proliferator-achieved receptor-γ (PPAR-γ) suppressor, which in turn induced insulin resistance, explaining a possible mechanism for the development of MS in HIV.

Sobieszczyk et al13 recently described dyslipidemia to be the principal component of MS diagnosis in a large sample of HIV-infected women. In our cohort, we describe a high prevalence of hypertension as an additional component of MS in HIV-infected patients. We therefore argue that MS diagnosis in HIV patients is not only the result of lipid abnormalities, but the complex resultant of multiple factors probably related to insulin resistance.

Our multivariate analysis confirmed that HIV-VL is an independent predictor of MS. This result could have important implications in clinical practices because HIV-VL, in addition to ARV, may contribute to the development of MS. Given the association between MS and CVD, our results further support the findings of the Strategies for Management of Antiretroviral Therapy (SMART) study where higher incidence of CVD was found in patients in the treatment interruption arm.25

Virologic failure can not be considered an acceptable condition in any HIV-infected patient, but in particular should be avoided those with concommitant metabolic abnormaltities, as it could further elevate the risk of CV morbitity and mortality. Prospective studies, with clinical endpoint, are needed to determine if the inclusion of detectable HIV-VL should be incorporated in the definition of MS in HIV-infected patients.

Our study has some limitations. It is a cross-sectional study not allowing the determination of causality between HIV-VL and MS. Further, we examined a highly treatment-experienced HIV-infected population (average period of exposure to ART was 100 months), which is not necessarily representative of all HIV-infected patients.

We were unable to verify the role of single drug agents on MS, in particular, the impact of thymidine analogues among NRTI; EFV among NNRTI; and the role of different PIs.

We conclude that based on our findings, an effective ART regimen is mandatory for both control of HIV disease progression and for prevention of MS-related disorders.

Back to Top | Article Outline


The authors wish to thank Dr. Alexandra Mangili for reviewing the article.

Back to Top | Article Outline


1. Grundy SM, Brewer HB Jr, Cleeman JI, et al. Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation. 2004;109:433-438.
2. Jacobson DL, Tang AM, Spiegelman D, et al. Incidence of metabolic syndrome in a cohort of HIV-infected adults and prevalence relative to the US population (National Health and Nutrition Examination Survey). J Acquir Immune Defic Syndr. 2006;43:458-466.
3. Estrada V, Martinez-Larrad MT, Gonzalez-Sanchez JL, et al. Lipodystrophy and metabolic syndrome in HIV-infected patients treated with antiretroviral therapy. Metabolism. 2006;55:940-945.
4. Mondy K, Overton ET, Grubb J, et al. Metabolic syndrome in HIV-infected patients from an urban, midwestern US outpatient population. Clin Infect Dis. 2007;44:726-734.
5. Bonfanti P, Giannattasio C, Ricci E, et al. HIV and metabolic syndrome: a comparison with the general population. J Acquir Immune Defic Syndr. 2007;45:426-431.
6. El-Sadr WM, Mullin CM, Carr A, et al. Effects of HIV disease on lipid, glucose and insulin levels: results from a large antiretroviral-naive cohort. HIV Med. 2005;6:114-121.
7. Riddler SA, Smit E, Cole SR, et al. Impact of HIV infection and HAART on serum lipids in men. JAMA. 2003;289:2978-2982.
8. Brown TT, Chu H, Wang Z, et al. Longitudinal increases in waist circumference are associated with HIV-serostatus, independent of antiretroviral therapy. AIDS. 2007;21:1731-1738.
9. Justman JE, Hoover DR, Shi Q, et al. Longitudinal anthropometric patterns among HIV-infected and HIV-uninfected women. J Acquir Immune Defic Syndr. 2008;47:312-319.
10. Howard AA, Floris-Moore M, Lo Y, et al. Abnormal glucose metabolism among older men with or at risk of HIV infection. HIV Med. 2006;7:389-396.
11. Brown TT, Cole SR, Li X, et al. Antiretroviral therapy and the prevalence and incidence of diabetes mellitus in the multicenter AIDS cohort study. Arch Intern Med. 2005;165:1179-1184.
12. Jerico C, Knobel H, Montero M, et al. Metabolic syndrome among HIV-infected patients: prevalence, characteristics, and related factors. Diabetes Care. 2005;28:132-137.
13. Sobieszczyk ME, Hoover DR, Anastos K, et al. Prevalence and predictors of metabolic syndrome among HIV-infected and HIV-uninfected women in the Women's Interagency HIV Study. J Acquir Immune Defic Syndr. 2008;48:272-280.
14. Samaras K, Wand H, Law M, et al. Prevalence of metabolic syndrome in HIV-infected patients receiving highly active antiretroviral therapy using International Diabetes Foundation and Adult Treatment Panel III criteria: associations with insulin resistance, disturbed body fat compartmentalization, elevated C-reactive protein, and [corrected] hypoadiponectinemia. Diabetes Care. 2007;30:113-119.
15. Mangili A, Jacobson DL, Gerrior J, et al. Metabolic syndrome and subclinical atherosclerosis in patients infected with HIV. Clin Infect Dis. 2007;44:1368-1374.
16. Wand H, Calmy A, Carey DL, et al. Metabolic syndrome, cardiovascular disease and type 2 diabetes mellitus after initiation of antiretroviral therapy in HIV infection. AIDS. 2007;21:2445-2453.
17. Bergersen BM, Schumacher A, Sandvik L, et al. Important differences in components of the metabolic syndrome between HIV-patients with and without highly active antiretroviral therapy and healthy controls. Scand J Infect Dis. 2006;38:682-689.
18. Ascaso JF, Romero P, Real JT, et al. Abdominal obesity, insulin resistance, and metabolic syndrome in a southern European population. Eur J Intern Med. 2003;14:101-106.
19. Lichtenstein KA, Ward DJ, Moorman AC, et al. Clinical assessment of HIV-associated lipodystrophy in an ambulatory population. AIDS. 2001;15:1389-1398.
20. Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA. 2001;285:2486-2497.
21. von Wyl V, Yerly S, Boni J, et al. Emergence of HIV-1 drug resistance in previously untreated patients initiating combination antiretroviral treatment: a comparison of different regimen types. Arch Intern Med. 2007;167:1782-1790.
22. Sniderman AD. Apolipoprotein B versus non-high-density lipoprotein cholesterol: and the winner is. Circulation. 2005;112:3366-3367.
23. Torriani M, Hadigan C, Jensen ME, et al. Psoas muscle attenuation measurement with computed tomography indicates intramuscular fat accumulation in patients with the HIV-lipodystrophy syndrome. J Appl Physiol. 2003;95:1005-1010.
24. Shrivastav S, Kino T, Cunningham T, et al. Human immunodeficiency virus (HIV)-1 viral protein R suppresses transcriptional activity of peroxisome proliferator-activated receptor {gamma} and inhibits adipocyte differentiation: implications for HIV-associated lipodystrophy. Mol Endocrinol. 2008;22:234-247.
25. El-Sadr WM, Lundgren JD, Neaton JD, et al. CD4+ count-guided interruption of antiretroviral treatment. N Engl J Med. 2006;355:2283-2296.

HIV; metabolic syndrome;

© 2009 Lippincott Williams & Wilkins, Inc.