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HIV and Obesity Comorbidity Increase Interleukin 6 but Not Soluble CD14 or D-Dimer

Taylor, Barbara S. MD, MS*; So-Armah, Kaku PhD; Tate, Janet P. ScD; Marconi, Vincent C. MD§; Koethe, John R. MD; Bedimo, Roger J. MD; Butt, Adeel A. MD, MS#; Gibert, Cynthia L. MD**; Goetz, Matthew B. MD††; Rodriguez-Barradas, Maria C. MD‡‡; Womack, Julie A. CNM, APRN, PhD§§; Gerschenson, Mariana PhD‖‖; Lo Re, Vincent III MD, MSCE¶¶; Rimland, David MD§; Yin, Michael T. MD, MS##; Leaf, David MD***; Tracy, Russell P. PhD†††; Justice, Amy C. MD, PhD; Freiberg, Matthew S. MD‡‡‡

JAIDS Journal of Acquired Immune Deficiency Syndromes: August 15, 2017 - Volume 75 - Issue 5 - p 500–508
doi: 10.1097/QAI.0000000000001444

Objectives: Obesity prevalence among people living with HIV (HIV+) is rising. HIV and obesity are proinflammatory states, but their combined effect on inflammation (measured by interleukin 6, IL-6), altered coagulation (D-dimer), and monocyte activation (soluble CD14, sCD14) is unknown. We hypothesized inflammation increases when obesity and HIV infection co-occur.

Methods: The Veterans Aging Cohort Study survey cohort is a prospective, observational study of predominantly male HIV+ veterans and veterans uninfected with HIV; a subset provided blood samples. Inclusion criteria for this analysis were body mass index ≥ 18.5 kg/m2 and biomarker measurement. Dependent variables were IL-6, sCD14, and D-dimer quartiles. Obesity/HIV status was the primary predictor. Unadjusted and adjusted logistic regression models were constructed.

Results: Data were analyzed for 1477 HIV+ and 823 uninfected participants. Unadjusted median IL-6 levels were significantly higher and sCD14 levels significantly lower in obese/HIV+ compared with nonobese/uninfected (P <0.01 for both). In adjusted analyses, the odds ratio for increased IL-6 in obese/HIV+ patients was 1.76 (95% confidence interval: 1.18 to 2.47) compared with nonobese/uninfected, and obesity/HIV+ remained associated with lower odds of elevated sCD14. We did not detect a synergistic association of co-occurring HIV and obesity on IL-6 or sCD14 elevation. D-dimer levels did not differ significantly between body mass index/HIV status groups.

Conclusions: HIVobesity comorbidity is associated with elevated IL-6, decreases in sCD14, and no significant difference in D-dimer. These findings are clinically significant, as previous studies associated these biomarkers with mortality. Future studies should assess whether other biomarkers show similar trends and potential mechanisms for unanticipated sCD14 and D-dimer findings.

*Medical Service/Infectious Diseases, South Texas Veterans Health Care System, San Antonio, TX; Department of Medicine, UT Health San Antonio, San Antonio, TX;

Department of Medicine, Boston University School of Medicine, Boston, MA;

Section of General Internal Medicine, VA Connecticut Healthcare System, West Haven, CT; Department of Internal Medicine, Yale University School of Medicine, New Haven, CT;

§Medical Service, VA Medical Center, Atlanta, GA; Medical Service, Emory University School of Medicine, Atlanta, GA;

Departments of Medicine and Biostatistics, Vanderbilt University School of Medicine, Nashville, TN;

Department of Medicine, Infectious Diseases Section, VA North Texas Health Care System; UT Southwestern Medical Center, Dallas, TX;

#Center for Health Equity Research and Promotion, VA Pittsburg Healthcare System, Pittsburgh, PA; Hamad Healthcare Quality Institute, Hamad Medical Corporation, Doha, Qatar; Department of Medicine, Weill Cornell Medical College, Doha, Qatar and New York, NY;

**Medical Service/Infectious Diseases, VA Medical Center, Washington, DC; Department of Medicine, George Washington University Medical Center, Washington, DC;

††Department of Medicine, VA Greater Los Angeles Healthcare System, Los Angeles, CA; David Geffen School of Medicine at UCLA, Los Angeles, CA;

‡‡Infectious Diseases Section, Michael E. DeBakey VA Medical Center, Houston, TX; Infectious Diseases Section, Baylor College of Medicine, Houston, TX;

§§VA Connecticut Healthcare System, West Haven, CT;

‖‖Cell and Molecular Biology Department, John A. Burns School of Medicine, University of Hawaii- Manoa, Honolulu, HI;

¶¶Philadelphia VA Medical Center, Philadelphia, PA; Perelman School of Medicine, University of Pennsylvania, Philadelphia, VA;

##Division of Infectious Diseases, Columbia University Medical Center, New York, NY;

***Infectious Diseases Section, VA Greater Los Angeles Healthcare System, Los Angeles, CA; Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA;

†††Departments of Pathology and Laboratory Medicine and Biochemistry, College of Medicine, University of Vermont, Burlington, VT; and

‡‡‡Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN; Geriatric Research, Education, and Clinical Center, VA Tennessee Valley Healthcare System, Nashville, TN.

Correspondence to: Barbara S. Taylor, MD, MS, Department of Medicine, Division of Infectious Diseases, University of Texas Health Science Center San Antonio, 7703 Floyd Curl Dr. MSC-7881 San Antonio, TX 78229-3900 (e-mail:

Supported by National Institute of Allergy and Infectious Diseases at the National Institutes of Health K23AI081538 (B.S.T.), American Heart Association, National Center Mentored Clinical and Population Research Award 14CRP20150023 (B.S.T.), National Institute on Alcohol Abuse and Alcoholism and National Heart Lung and Blood Institute at the National Institutes of Health R01HC095136-04 and 5R01HC095126-04 (M.S.F.), and National Institute on Alcohol Abuse and Alcoholism U10 AA 13566 (Veterans Aging Cohort Study).

Presented at 2016 Conference on Retroviruses and Opportunistic Infections. Poster Presentation; February 22–25, 2016; Boston, MA. B.S.T., K.S.-A., J.P.T., V.C.M., R.B., A.A.B., C.L.G, M.G., M.C.R.-B, M.S.F. “HIV & Obesity Synergistically Increase Interleukin 6 but not Soluble CD14 or D-dimer.”

The authors have no conflicts of interest to disclose.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (

Received December 09, 2016

Accepted March 30, 2017

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Obesity is a leading health threat in the United States1–3 and is more common in minorities and those with lower socioeconomic status.4–9 These same individuals are also most severely impacted by the HIV epidemic.10,11 Because potent antiretroviral therapy (ART) is now widely available, weight loss previously associated with untreated HIV infection has been supplanted by weight gain. Consequently, obesity is increasingly common in people living with HIV infection.12–17

Both obesity and HIV infection independently increase risk for cardiovascular disease (CVD).18–22 A hypothesized mechanism for the increased cardiovascular risk, common to both, is immune system alteration.23–29 Although obesity has well-established associations with traditional risk factors for CVD including hypertension, hyperlipidemia, and diabetes, both HIV and obesity are associated with immune system alterations that may independently impact risk.23–28 Although both HIV and obesity are associated with altered immunity, their combined effect on inflammation, altered coagulation, and monocyte activation is unclear.

We hypothesized that the combination of obesity and HIV infection (obesity/HIV) is associated with increased inflammation when compared with either condition alone or the absence of both conditions. In a subset of participants from the Veterans Aging Cohort Study (VACS) survey cohort, we examined the relationship between obesity/HIV and biomarkers of inflammation (interleukin 6), altered coagulation (D-dimer), and monocyte activation (soluble CD14, sCD14). These 3 biomarkers were chosen because they represent different inflammatory pathways and are altered in the context of HIV and obesity.23,30–33

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Study Design and Setting

This is a cross-sectional analysis of data from the VACS. The VACS survey cohort is a prospectively enrolled observational longitudinal study of veterans living with HIV (HIV+) and veterans who are uninfected with HIV (uninfected) matched (1:1) on age, sex, race/ethnicity, and geographic location.34 In 2005–2007, a subset of this cohort (1525 HIV+ and 843 uninfected) participants consented to provide blood samples as previously described.27 Those with body mass index (BMI) ≥18.5 kg/m2 (ie, not underweight) and with available measurements of IL-6, sCD14, or D-dimer were eligible for inclusion in the present analyses.

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Dependent and Independent Variables

IL-6, sCD14, and D-dimer were the dependent variables. They were analyzed as continuous variables for descriptive analyses and categorized into quartiles for regression analyses, as the relationships between BMI and all 3 biomarkers were nonlinear (Supplemental Digital Content Figure, IL-6 and D-dimer were log transformed to better approximate the normal distribution. Specimens used to measure these biomarkers were collected using serum separator and EDTA blood collection tubes and shipped to a central repository at the Massachusetts Veterans Epidemiology Research and Information Center in Boston, MA. Measurements of these biomarkers are further described in previous work.27

To construct the independent variable, we classified obesity (BMI) ≥ 30 kg/m2 by HIV status to create 4 mutually exclusive categories. We chose obesity as a threshold because overweight status (BMI ≥ 25 kg/m2 and <30 kg/m2) may not be associated with adverse outcomes in the general population or among people living with HIV.3,15,18 Underweight (BMI <18.5 kg/m2) was excluded because of the small number in the cohort (n = 48). People with BMI 18.5–30 kg/m2 who were HIV uninfected (nonobese/HIV) were defined as the referent group.

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Covariates were assessed closest to the time of blood specimen collection for IL-6, sCD14, and D-dimer measurements. Sociodemographic data included age, sex, and race/ethnicity. CVD was defined using previously validated diagnostic or procedural codes for myocardial infarction, unstable angina, congestive heart failure, coronary revascularization, or ischemic stroke.35,36 Hypertension was defined as receipt of antihypertensive therapy prescription or blood pressure ≥140/90 mm Hg based on the average of the last 3 outpatient measurements, as previously described.21,37,38 Diabetes was defined using a validated algorithm that includes glucose measurements, use of insulin or oral hypoglycemic agents, and/or International Classification of Diseases, Ninth Revision (ICD-9) codes.39 Smoking was self-reported using a standardized survey.40 Total cholesterol measurements were dichotomized at 200 mg/dL, low-density lipoprotein cholesterol at 160 mg/dL, high-density lipoprotein (HDL) cholesterol at 40 mg/dL, and triglycerides at 200 mg/dL.21,41 HMG CoA reductase inhibitor (statin) prescriptions were assessed using data from the VA Corporate Data Warehouse.

Using the Alcohol Use Disorders Identification Test (AUDIT-C) and alcohol abuse/dependence ICD-9 codes, we categorized alcohol use as follows: (1) no current drinking, (2) low-risk current drinking (AUDIT-C <4), (3) at risk or heavy drinking (AUDIT-C≥4), and (4) alcohol abuse or dependence diagnosis.42 History of cocaine use was defined by self-report. Hepatitis C virus (HCV) infection status was based on a positive HCV antibody test or at least 1 inpatient and/or 2 outpatient ICD-9 codes.43 Advanced liver fibrosis was estimated as a Fibrosis-4 index score >3.25 using participant age, platelet count, aspartate aminotransferase, and alanine aminotransferase levels.44,45 Anemia was defined as hemoglobin <12g/dL. Chronic kidney disease (stage 3–5) was defined as an estimated glomerular filtration rate of <60 mL·min−1·1.73 m−2.46 Any history of cancer up to time of biomarker assessment was determined using VA Central Cancer Registry data.47 For HIV-infected participants, we also assessed HIV-1 RNA level, dichotomized at 500 copies/mL as in previous VACS studies,21,38 CD4+ T-cell (CD4) count dichotomized at 500 cells/mm3, and ART regimen: nucleoside/nucleotide reverse transcriptase inhibitors plus protease inhibitors, nucleoside/nucleotide reverse transcriptase inhibitor plus nonnucleoside reverse transcriptase inhibitors, other, or no ART.21

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Statistical Analysis

We compared continuous variables (Kruskall–Wallis rank test) and categorical variables (χ2 test) by BMI categories overall and stratified by HIV status. We assessed correlations of obesity/HIV status with IL-6, sCD14, and D-dimer. We then constructed logistic regression models to estimate the association between obesity/HIV comorbidity and elevated (highest quartile vs lower 3 quartiles) IL-6, sCD14, or D-dimer. Logistic regression analyses were first adjusted for age and race/ethnicity and subsequently adjusted for diabetes, CVD, HCV infection, Fibrosis-4 index>3.25, estimated glomerular filtration rate<60, smoking, hypertension, HDL cholesterol and low-density lipoprotein cholesterol, triglycerides, statin prescription, cocaine use, and alcohol use. Adjustment covariates were selected based on previous work suggesting an association with BMI, and IL-6, sCD14, or D-dimer, but adjustment for sex was not possible because of the small number of obese HIV+ women in the cohort.27 Odds ratios (ORs) for the different categories of the BMI/HIV status variable were compared using Wald tests with a Bonferroni correction for multiple comparisons. We conducted 3 sensitivity analyses: (1) models subcategorizing HIV+ by HIV-1 RNA <500 copies/mL vs ≥500 copies/mL to determine the impact that uncontrolled HIV viremia may have on the association between the inflammatory parameters and BMI status; (2) models excluding those with hepatitis C infection because of its known association with increases in inflammatory biomarkers,48 and (3) models excluding those with prevalent diabetes, CVD, and cancer, all comorbidities likely to confound the relationship between obesity/HIV comorbidity and IL-6, sCD14, or D-dimer.

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Study Population

Of participants included in this cohort, 1477 HIV+ and 823 uninfected participants met the inclusion criteria for this analysis. Of the 68 who were excluded, most (70%) were for being underweight BMI (<18.5 kg/m2). Of 2300 participants overall, 95% were men; 68% were African American, 37% normal weight, 36% overweight, and 27% obese (Table 1).



Compared with nonobese participants, obese participants had higher prevalence of diabetes, statin prescription, and hypertension, and lower prevalence of alcohol use disorder and current smoking, regardless of HIV status (P < 0.05, Table 1). Obese/HIV+ participants had the highest prevalence of HDL <40 mg/dL and triglycerides ≥200 mg/dL (P < 0.05, Table 1).

HIV+ participants were less likely to be obese (39%) compared with uninfected participants (61%, P < 0.001) and were younger (mean 52 years, SD 8 years) than uninfected participants (54 years, SD 9 years, P < 0.001). Of the HIV+ participants, 43% had HIV-1 RNA <500 copies/mL, and 23% had CD4+ cell counts >500 cells/mm3 at baseline.

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Analysis of Inflammatory Biomarkers by Obesity/HIV Status

Median IL-6 levels were significantly higher in obese/HIV+ people (2.26 pg/mL; interquartile range 1.55–3.60) when compared with nonobese/uninfected (1.51 pg/mL; interquartile range: 0.99–2.79; P < 0.01; Fig. 1). In unadjusted logistic regression analyses, the odds of elevated IL-6 (ie, being in the highest quartile) were significantly greater in all 3 comparator groups (nonobese/HIV+, obese/uninfected, and obese/HIV+) when compared with the referent (nonobese/uninfected; Table 2). These associations persisted after adjustment for potential confounders: compared with nonobese/uninfected, there were 31% increased odds of elevated IL-6 with HIV infection (nonobese), 64% increased odds with obesity (uninfected), and 79% increased odds with both obesity and HIV (Table 2). Overall, adjusted differences in IL-6 elevation between other pairs of categories (ie, nonobese/HIV+ vs obese/HIV+; or nonobese/HIV+ vs obese/uninfected; or obese/uninfected vs obese/HIV+) were not statistically significant (omnibus P = 0.11).





Soluble CD14 levels were significantly lower in obese/HIV+ compared with nonobese/uninfected (P < 0.01, Fig. 1). This finding was confirmed in unadjusted and adjusted logistic regression models, where we observed significantly lower odds of elevated sCD14 in obese/HIV+ compared with nonobese/uninfected (both P < 0.01; Table 2). Overall differences in sCD14 elevation between other pairs of categories were statistically significant (omnibus P < 0.001). This was driven by differences in sCD14 elevation between nonobese/HIV+ vs obese/HIV+ (Bonferroni P < 0.001) and obese/uninfected vs obese/HIV+ (Bonferroni P = 0.02). Median D-dimer did not differ significantly between BMI/HIV status groups (Fig. 1). This result was reflected in fully adjusted models (Table 2).

Sensitivity analyses that further classified HIV status by HIV-1 RNA < or ≥500 copies/mL demonstrated results consistent with the primary analyses for IL-6 and sCD14 (Table 3). IL-6 and sCD14 levels in nonobese/HIV+ with HIV-1 RNA <500 copies/mL did not differ from those for nonobese/uninfected people, although sample sizes in the subgroups were small (Table 3 footnote). Nonobese/HIV+ people with HIV-1 RNA ≥500 copies/mL had elevated D-dimer relative to nonobese/uninfected people (OR = 1.79; 95% confidence interval = 1.28 to 2.49; Table 3). The same was true for obese/HIV+ people with HIV-1 RNA ≥500 copies/mL, although this association did not reach statistical significance (OR: 1.32; 95% confidence interval = 0.76 to 2.31); Table 3. Two additional sensitivity analyses excluding those with HCV and those with prevalent diabetes, CVD, and cancer yielded results that were directionally consistent with the primary analyses (Supplemental Digital Content,



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In this cross-sectional examination of inflammatory biomarkers in HIV+ and uninfected participants, we found that obesity/HIV comorbidity is associated with elevated IL-6 and decreased sCD14, particularly in the setting of uncontrolled viral replication. Obese/HIV+ participants, when compared with nonobese/uninfected participants, had statistically significant elevations in IL-6, a biomarker of inflammation, and decreases in sCD14, a biomarker of monocyte activation. We did not detect a significant association between obesity/HIV status and D-dimer, a biomarker of altered coagulation.

To our knowledge, this is the largest study comparing IL-6, sCD14, and D-dimer by BMI and HIV status in a cohort including HIV+ and uninfected participants. A recent investigation compared 35 HIV+ with 30 matched, uninfected, obese participants, and found that IL-6 did not significantly differ according to HIV status. They also found sCD14 was increased in obese/HIV+ when compared with obese/uninfected participants, the opposite of the association seen in our study. The characteristics of this smaller cohort differed from those in our cohort in terms of age and gender distributions, and D-dimer levels were not measured.30

Multiple prior studies investigated the association between these biomarkers and obesity in HIV+ participants without comparison with an uninfected population. IL-6 did not have a consistent association with adipose tissue mass in HIV+ participants in 1 investigation,49 whereas in other reports, IL-6 was associated with increases in BMI, particularly for HIV+ men.31,50 sCD14 was found to increase with weight gain in virologically suppressed, predominately normal weight HIV+ participants between 0 and 48 weeks after antiretroviral initiation across 9 countries.29 In the Strategies for Management of Antiretroviral Therapy (SMART) Study, investigators did not detect an association between obesity and D-dimer in HIV+ participants,32 similar to our findings. Likewise, D-dimer was not associated with obesity in a cohort of uninfected participants.33 These studies, which did not compare HIV+ with uninfected participants in the same cohort, have limited ability to comment on the differential impact of obesity on these biomarkers in those living with HIV versus without HIV infection.

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Interleukin 6

We found that obesity and HIV infection contributed to elevations in IL-6, an inflammatory cytokine strongly associated with morbidity and mortality in HIV+ cohorts.51–55 Median IL-6 levels were significantly higher in obese/HIV+, when compared with nonobese/uninfected, but there was no statistical difference between IL-6 levels in obese/HIV+ and those with either condition alone (nonobese/HIV+ or obese/uninfected, Fig. 1). Thus, we did not find evidence for a synergistic effect of HIV/obesity comorbidity on IL-6 elevations.

Obesity without HIV and HIV viremia without obesity were each associated with IL-6 elevation, and obese/uninfected individuals were more likely to have elevated IL-6 levels than nonobese/uninfected in all 3 logistic regression models. Interestingly, nonobese/HIV+ individuals with HIV-1 RNA <500 copies/mL had similar IL-6 levels to nonobese/uninfected (Table 3), implying that controlled HIV disease alone, without obesity, is not associated with significant elevations in IL-6 in this cohort. Although obese/HIV+ participants with HIV-1 RNA ≥500 copies/mL had a higher prevalence of elevated IL-6 than nonobese/uninfected, this association did not reach statistical significance. The anticipated elevation of IL-6 derived from uncontrolled viral replication may have been present, but the small sample size of only 83 obese/HIV+ participants with HIV-1 RNA ≥500 copies/mL may have limited our ability to detect an association.

The source of IL-6 in obesity/HIV comorbidity may be an important consideration in defining the implications of and future hypotheses generated from our findings. IL-6 can be derived from activated macrophages in tissues, such as blood vessels, or it can be produced by adipocytes, where levels increase in association with adipocyte diameter.56–58 In obesity, IL-6 is predominately adipose tissue derived, which may differ from chronic HIV infection, where it is likely induced by immune cell activation. Whether (1) adipocyte-derived IL-6 has more local effects on tissues while IL-6 production from immune cell activation has more systemic effects and whether (2) the distribution of local versus systemic effects has impact on morbidity or mortality are important questions for future research.

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Soluble CD14

We observed lower sCD14 levels in obese/HIV+ participants compared with nonobese/HIV+ participants, which is in line with results from some previous studies.45,47,58 Other studies have focused on the association between HIV status and sCD14 elevation in normal weight participants and found increased sCD14 in HIV+ participants.59–61 A possible explanation for these discordant findings is that hepatic steatosis in obesity leads to lower sCD14 levels because of decreases in hepatocyte-derived sCD14.62 When HIV and obesity co-occur, sCD14 levels may be influenced by multiple factors including monocyte activation within adipose tissue, other co-occurring inflammatory conditions (eg, diabetes, hepatitis C), and the presence of hepatic steatosis.63,64 The etiology of the unanticipated findings that sCD14 decreases in the setting of obesity/HIV comorbidity deserve further exploration, and other biomarkers of monocyte activation, such as soluble CD163 or macrophage inflammatory protein-1α, should be examined to determine whether they follow a similar trend.45 Other illustrative lines of research would repeat this study accounting for differences in hepatic steatosis between groups.

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In fully adjusted models, obesity/HIV comorbidity was not associated with D-dimer except when HIV status was stratified by viral suppression (ie, HIV-1 RNA less or greater than 500 copies/mL). Unsuppressed HIV viremia was associated with increased D-dimer, although this was only statistically significant among nonobese people. The positive association between obesity and D-dimer among HIV-uninfected people did not reach statistical significance. Overall, we did not detect a synergistic effect of obesity/HIV comorbidity on D-dimer elevations.

There are limitations to this analysis. This is an observational, cross-sectional study, preventing us from examining trends over time in inflammatory parameters. It would be useful to examine trends in relation to the duration of virologic suppression or in the setting of weight change or aging. BMI is used as a measure of adiposity rather than a measurement of waist circumference or visceral adipose tissue, known to be more strongly correlated with cardiovascular outcomes. The population is overwhelmingly male and older, limiting generalizability to women and younger HIV+ people. The individual biomarkers measured may not capture the full complexity of the immune processes they represent, although all 3 are well studied in both HIV+ and uninfected cohorts. Data on diet and physical activity, which can confound associations of obesity with inflammatory biomarkers, were not included in this analysis. As with any observational study, there is the possibility of unmeasured confounding from drug use, multiple comorbidities, or other factors.

In summary, obesity/HIV comorbidity is associated with elevated IL-6 and decreased sCD14. However, we did not detect a synergistic effect of obesity/HIV comorbidity on IL-6, sCD14, or D-dimer. This may suggest overlap in the mechanisms by which obesity and HIV contribute to alterations in these biomarkers and the immune processes they represent. The clinical implications of these findings deserve further exploration, as the impact of obesity on morbidity and mortality in HIV+ individuals remains unclear. Recent studies from the North American AIDS Cohort Collaboration on Research and Design suggest that weight gain and obesity are associated with improved CD4+ cell recovery and decreased incidence of noncommunicable diseases.65,66 However, data from the Data Collection on Adverse Events of Anti-HIV Drugs cohort study show that short-term weight gain after ART initiation, particularly in those with a normal baseline BMI, was associated with increased risk of incident CVD and diabetes.67

Despite uncertainty surrounding the impact of rising BMI in this population, the difference in median IL-6 levels between obese/HIV+ and nonobese/uninfected participants our analysis is similar to or greater than differences associated with increased mortality risk in other prospective studies.53,54 As obesity prevalence among people living with HIV rises,17 further investigation into the long-term implications of this weight gain is needed. Future prospective studies should assess whether intentional weight loss or similar interventions affect inflammatory processes similarly in HIV-infected and uninfected people.68–70

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HIV; obesity; inflammation; monocyte activation; coagulation; VACS

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