HIV/hepatitis C virus coinfection ameliorates the atherogenic lipoprotein abnormalities of HIV infection
Wheeler, Amber L.a,b; Scherzer, Rebeccaa,b; Lee, Danielc; Delaney, Joseph A.C.d; Bacchetti, Petere; Shlipak, Michael G.a,b; Sidney, Stephenf; Grunfeld, Carla,b; Tien, Phyllis C.a,b; for the Study of Fat Redistribution and Metabolic Change in HIV Infection (FRAM)
aDepartment of Medicine, University of California San Francisco
bDivision of Endocrinology and Metabolism, Department of Veterans Affairs Medical Center San Francisco, San Francisco
cDepartment of Medicine, University of California, San Diego School of Medicine, San Diego, California
dDepartment of Epidemiology, University of Washington, Seattle, Washington
eDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco
fDivision of Research, Kaiser Permanente, Oakland, California, USA.
Correspondence to Phyllis Tien, MD, Infectious Disease Section, Veterans Affairs Medical Center, University of California San Francisco, 111W, 4150 Clement Street, San Francisco, CA 94121, USA. Tel: +1 415 221 4810x2577; e-mail: firstname.lastname@example.org
Received 8 July, 2013
Accepted 6 August, 2013
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 Website (http://www.AIDSonline.com).
Background: Higher levels of small low-density lipoprotein (LDL) and lower levels of high-density lipoprotein (HDL) subclasses have been associated with increased risk of cardiovascular disease. The extent to which HIV infection and HIV/hepatitis C virus (HCV) coinfection are associated with abnormalities of lipoprotein subclasses is unknown.
Methods: Lipoprotein subclasses were measured by nuclear magnetic resonance (NMR) spectroscopy in plasma samples from 569 HIV-infected and 5948 control participants in the Fat Redistribution and Metabolic Change in HIV Infection (FRAM), Coronary Artery Risk Development in Young Adults (CARDIA), and Multi-Ethnic Study of Atherosclerosis (MESA) studies. Multivariable regression was used to estimate the association of HIV and HIV/HCV coinfection with lipoprotein measures with adjustment for demographics, lifestyle factors, and waist-to-hip ratio.
Results: Relative to controls, small LDL levels were higher in HIV-monoinfected persons (+381 nmol/l, P <0.0001), with no increase seen in HIV/HCV coinfection (−16.6 nmol/l). Levels of large LDL levels were lower (−196 nmol/l, P <0.0001) and small HDL were higher (+8.2 μmol/l, P < 0.0001) in HIV monoinfection with intermediate values seen in HIV/HCV coinfection. Large HDL levels were higher in HIV/HCV-coinfected persons relative to controls (+1.70 μmol/l, P <0.0001), whereas little difference was seen in HIV-monoinfected persons (+0.33, P = 0.075). Within HIV-infected participants, HCV was associated independently with lower levels of small LDL (−329 nmol/l, P <0.0001) and small HDL (−4.6 μmol/l, P <0.0001), even after adjusting for demographic and traditional cardiovascular risk factors.
Conclusion: HIV-monoinfected participants had worse levels of atherogenic LDL lipoprotein subclasses compared with controls. HIV/HCV coinfection attenuates these changes, perhaps by altering hepatic factors affecting lipoprotein production and/or metabolism. The effect of HIV/HCV coinfection on atherosclerosis and the clinical consequences of low small subclasses remain to be determined.
Both HIV and hepatitis C virus (HCV) monoinfection are associated with an increased risk of cardiovascular disease (CVD) [1–4]. Some studies also report that HIV/HCV coinfection may confer an increased risk of CVD when compared with those with HIV monoinfection [5,6], whereas another study reported little association of HIV/HCV coinfection with subclinical atherosclerosis relative to those with HIV monoinfection .
Dyslipidemia is an important risk factor for CVD, and both HIV and HCV monoinfection have been independently associated with alterations in lipid metabolism [3,8,9]. HIV monoinfection is known to be accompanied by an atherogenic lipoprotein phenotype (ALP) including increased triglycerides, and decreased high-density lipoprotein cholesterol (HDL-C), but also decreased low-density lipoprotein cholesterol (LDL-C) [8,10,11]. HCV monoinfection has been associated with decreased total cholesterol, triglycerides, and LDL-C when compared with those with neither HIV nor HCV infection . However, the relationship of HIV/HCV coinfection with lipoprotein levels is unclear.
Some studies have suggested that changes in lipoprotein subclass particle concentration may be a stronger predictor of CVD than the standard lipid panel [12,13]. The key lipoprotein classes, LDL-C and HDL-C, are composed of many subclasses based on size and density . Small LDL is believed to have atherogenic properties. In the general population, increased levels of small LDL often accompany other metabolic derangements including high triglycerides, low HDL-C, and insulin resistance [8,10,15] that are similar to changes found in HIV-monoinfected individuals. Increased relative number of LDL particles (LDL-P), total and small LDL-P concentration, and smaller LDL size have been directly associated with CVD in studies in the general population and can be independent of LDL-C [16–21].
HDL particle (HDL-P) concentrations have also been associated with subclinical atherosclerosis and incident CVD in the general population . Lower baseline total, large, and small HDL-P concentrations were associated with a higher risk of CVD in HIV-monoinfected participants . These findings are of concern because HIV infection is associated with lower HDL-P numbers with reductions in large and small HDL-P concentrations [23,24]. To date, no large, nationally representative multiethnic study has taken the effects of HCV infection into account when examining concentrations of lipoprotein subclasses in HIV-infected participants. Therefore, we evaluated lipoprotein levels measured in HIV/HCV-coinfected persons, HIV-monoinfected persons, and persons with neither infection from the Study of Fat Redistribution and Metabolic Change in HIV Infection (FRAM) and the Multi-Ethnic Study of Atherosclerosis (MESA).
Materials and methods
FRAM HIV-infected participants were initially recruited from 16 HIV or infectious disease clinics or cohorts, and were demographically nationally representative. The first FRAM examination enrolled 1183 HIV-infected and 297 HIV-uninfected controls from 2000 to 2002 . The second examination conducted approximately 5 years later, included lipoprotein measures and 581 HIV-infected and 246 HIV-uninfected controls who had been seen at the first examination. By the second examination, the FRAM HIV-infected participants were highly treated with 97% having received some form of antiretroviral therapy (ART).
Control participants were recruited from two centers of the Coronary Artery Risk Development in Young Adults (CARDIA) study. CARDIA participants were originally recruited in 1985–1986 as a population-based sample of healthy 18–30-year-old white and African–American women and men to longitudinally study cardiovascular risk factors. At the second FRAM examination, the CARDIA controls from the original FRAM study were 37–50 years old.
Controls from the MESA study who had lipoproteins measured and met inclusion criteria were also used for controls in this analysis as done previously . This additional pool of control participants was included to supplement the CARDIA control participant pool with individuals in the upper age range (45–78 years) of the HIV-infected FRAM participants. MESA was initiated in July 2000 to investigate the prevalence, correlates, and progression of CVD in a population-based sample of 6814 men and women aged 45–84 free of clinical CVD at enrollment, recruited from six US field centers. The baseline MESA visit was conducted from 2000 to 2002.
All three cohorts were nationally representative and the control groups were population-based. FRAM and MESA study protocols were approved by institutional review boards at all respective sites.
Analyses of HIV-infected participants alone included all 569 participants with nonmissing lipoprotein measures. To ensure comparability of the HIV-infected and control groups, participants included in analyses comparing HIV-infected and controls were restricted to white, African–American, and Hispanic men and women aged 37–78 years. All HIV-infected FRAM (n = 483), MESA control (n = 5712), and CARDIA control (n = 236) participants who met these criteria and had lipoprotein measurements available were included in the analysis. The linearity assumption was tested for continuous measures by adding quadratic terms to the models and by examining generalized additive models .
Nuclear magnetic resonance lipoprotein measurements
Lipoprotein particle concentrations and size were measured on frozen plasma specimens (−70°C) by proton NMR spectroscopy (LipoScience Inc., Raleigh, North Carolina, USA). Lipoprotein subclass particle concentrations of different sizes were directly obtained from the measured amplitudes of their spectroscopically distinct lipid methyl group NMR signals . Weighted-average lipoprotein particle sizes are derived from the sum of the diameter of each subclass multiplied by its relative mass percentage based on the amplitude of its methyl NMR signal. As outlined in previous MESA papers , the concentrations in nanomoles of particles/liter (nmol/l) of the following subclasses were measured: small LDL (diameter of 18.0–21.2 nm), large LDL (21.2–23.0 nm), intermediate-density lipoprotein (IDL; 23.0–27.0 nm), large HDL (8.8–13.0 nm), medium HDL (8.2–8.8 nm), small HDL (7.3–8.2 nm), large very low-density lipoprotein (VLDL; >60 nm), medium VLDL (35.0–60.0 nm), and small VLDL (27.0–35.0 nm) [19,21]. Interassay reproducibility, determined from replicate analyses of plasma pools, is indicated by the following coefficients of variation: less than 2% for VLDL size and less than 0.5% for LDL and HDL size, less than 10% for VLDL-P subclasses, less than 4% for total LDL-P, less than 8% for large and small LDL-P, and less than 5% for large and small HDL-P, with higher variation (<30%) for medium HDL-P and IDL-P .
Height and weight were measured by standardized protocols. Standardized questionnaires determined demographic characteristics; medical history; HIV risk factors; and use of alcohol and tobacco. Research associates interviewed participants and reviewed medical charts regarding ART use. A diagnosis of AIDS was made by history of opportunistic infection or CD4+ cell count less than 200 cells/μl. We classified participants as having diabetes if they had a fasting blood glucose level of at least 126 mg/dl (7.0 mmol/l) or reported use of insulin or oral hypoglycemic medication.
HCV RNA testing was performed on frozen sera using the Bayer Versant 3.0 branched DNA assay (Leverkusen, Germany) in the entire FRAM cohort . CD4+ lymphocyte count and percentage, HIV RNA level (lower limit of detection: 400 copies/ml) in HIV-infected participants, and other blood specimens from FRAM participants were analyzed in a single centralized laboratory (Covance, Indianapolis, Indiana, USA).
Candidate covariates included demographic characteristics, lifestyle factors, and measures of body composition. Demographic characteristics included age, sex, and race. Lifestyle factors included smoking, alcohol use, and diabetes. Measures of body composition included waist-to-hip ratio (WHR), waist circumference, hip circumference, and BMI. HIV-related factors included HIV duration, HCV status, HIV RNA level, current and nadir CD4+ cell count, history of AIDS, and current ART use.
We compared demographic and clinical characteristics of HIV-infected and uninfected participants using the Mann–Whitney U-test for continuous variables and Fisher's exact test for categorical variables. Distributions of lipoprotein levels were examined using smoothed curves from kernel density estimates and were compared using Levene's test for homogeneity of variance. Tests of the residuals found violations of normality and homoscedasticity assumptions; therefore, we used quantile regression to compare median lipoprotein levels by HIV and HCV status .
To determine whether HIV and HCV infection were independently associated with lipoprotein levels, multivariable models were sequentially adjusted for demographics alone; and demographics, lifestyle factors, and body composition.
Separate models were constructed in HIV-infected individuals alone, adjusting for HIV-related factors as well as demographics, lifestyle factors, and body composition. Factors forced in the full model included age, gender, and race/ethnicity. We used stepwise backward selection with a significance level of α equal to 0.05 to remove candidate covariates that did not appear to be strongly associated with the outcome. All analyses were conducted using the SAS system, version 9.2 (SAS Institute Inc., Cary, North Carolina, USA).
The characteristics of the participants studied are presented in Table 1. For comparison of HIV-infected participants with controls, the age range was restricted to 38–79 years, wherein there was overlap between the HIV-infected and control participants. The median age was 49 years for HIV-infected participants and 61 years for controls. Among HIV-infected participants, 28% were women, 51% white, 42% African–American, and 6.4% Hispanic. Due to the design of the control cohorts, the controls were evenly divided by gender, and had a higher proportion of Hispanics than the HIV-infected cohort. Differences in smoking, diabetes, and other traditional CVD risk factors have been described previously . Of the FRAM participants, 11% of HIV/HCV-coinfected, 33% of HIV-monoinfected, and 16% of the controls were on lipid-lowering therapy.
Distributions of lipoprotein measures are shown in Fig. 1. HIV-monoinfected participants had lower levels of large LDL-P (Fig. 1a) compared with controls (median 310 vs. 593 nmol/l, P <0.0001), whereas the values for HIV/HCV-coinfected were intermediate (demographic-adjusted median 452, P = 0.0014 vs. controls). Analysis of the distribution found no strong evidence for a difference between the groups (P = 0.14, test for homogeneity of variance).
By contrast, HIV-monoinfected participants had higher levels of small LDL-P (Fig. 1b) compared with controls (1068 vs. 525 nmol/l, P <0.0001), whereas the values for HIV/HCV-coinfected were closer to controls (median 631, P = 0.56 vs. controls). The distribution of small LDL-P in the control participants was bimodal, showing separate populations of low and high levels of small LDL-P. The distributions of small LDL-P in the HIV-monoinfected and HIV/HCV-coinfected reflected a skewed distribution relative to the controls (P <0.0001, test for homogeneity of variance). The distribution in HIV-monoinfected participants was unimodal and was right-shifted relative to the high mode in the control group, whereas the distribution in HIV/HCV-coinfected participants was also unimodal but largely overlapped with the middle of the control group.
Large HDL-P levels (Fig. 1c) trended lower in HIV-monoinfected than control (4.1 vs. 5.3 μmol/l, P = 0.089), but were higher in HIV/HCV-coinfected (6.2, P <0.0001 vs. control). Variability in distribution of large HDL was greater in the two HIV-infected groups relative to controls (P = 0.0004).
Small HDL-P levels (Fig. 1d) were higher in HIV-monoinfected participants compared with control (23.3 vs. 14.4 μmol/l, P < 0.0001), whereas levels in HIV/HCV-coinfected were intermediate (18.2, P < 0.0001 vs. control). The test for homogeneity of variance showed a greater spread in the HIV/HCV-coinfected group (P = 0.017).
The association of lifestyle factors and waist-to-hip ratio with lipoprotein measures in HIV infection and HIV/hepatitis C virus coinfection
The demographic-adjusted median levels of NMR lipoprotein measurements from controls, HIV-monoinfected and HIV/HCV-coinfected participants are summarized in Supplemental Table 1, http://links.lww.com/QAD/A403. After multivariable adjustment for demographics, lifestyle factors, and body composition, HIV monoinfection remained associated with lower large LDL-P and with higher small LDL-P and small HDL-P relative to controls, although the difference was somewhat attenuated (Table 2). Additionally, HIV monoinfection remained associated with lower large LDL-P [−102, 95% confidence interval (CI): −132 to −71.6, P <0.0001] and higher small LDL-P (281, 95% CI: 236–325, P <0.0001) after further adjustment for triglycerides and HDL-C.
When adjusted for demographics in HIV/HCV-coinfected participants, there was a weak trend to an increase in small LDL-P when compared with controls; however, this trend disappeared after further adjustment for lifestyle factors and WHR. The differences between HIV/HCV coinfection and control remained significant for large LDL-P and large and small HDL-P even after adjustment in the final model.
Association of HIV-related factors with lipoprotein measures
Because HIV infection was associated with abnormal levels of lipoprotein measures even after multivariable adjustment, we constructed models to investigate the associated factors in HIV-infected participants alone. The association of HIV infection with all NMR lipoprotein measures is summarized in Supplemental Table 2, http://links.lww.com/QAD/A403. Female sex, increasing age, and African–American race were independently associated with higher median levels of large LDL-P (Table 3). By contrast, diabetes and WHR were associated with lower large LDL-P. Within all HIV-infected participants, HCV was also associated with higher large LDL-P in unadjusted analyses, but decreased in significance after full multivariable adjustment (77.1, 95% CI: −26.4 to 180.5, P = 0.14).
Factors independently associated with higher levels of small LDL-P included diabetes, WHR, and current NRTI use (Table 3). In contrast, female sex and HCV infection were independently associated with lower levels of small LDL-P. When we examined the association of specific NRTIs with small LDL-P, we found that nearly all were positively associated, including tenofovir, although not as strong as for the class itself. Current protease inhibitor and lopinavir/ritonavir use were initially associated with higher levels of small LDL-P in unadjusted analyses (127.4, 95% CI: 13.0–241.8, P = 0.029; 184.0, 95% CI: 12.6–355.5, P = 0.036), but decreased in significance after adjustment (24.6, 95% CI: −86.1 to 135.3, P = 0.66; 9.3, 95% CI: −140.5 to 159.2, P = 0.90).
Factors associated with higher levels of large HDL (Table 4) included female sex, age, African–American race, alcohol use, HCV infection, and the use of the nonnucleoside reverse transcriptase inhibitors (NNRTIs) nevirapine and efavirenz. Factors independently associated with lower levels of small HDL (Table 4) included greater HIV RNA, HCV, and lopinavir/ritonavir use. Abacavir use was associated with higher levels of small HDL.
Our study is the first, to our knowledge, to directly examine lipoprotein subclass concentrations and distributions in HIV/HCV-coinfected participants. Persons with HIV/HCV coinfection are thought to be at higher risk of CVD compared with those with HIV monoinfection or those with neither infection [5,6]. However, our findings suggest that HIV/HCV coinfection attenuates the atherogenic changes in lipoprotein subclass concentrations observed in HIV monoinfection. We found that HIV monoinfection was associated with higher levels of small LDL-P compared with controls, but HIV/HCV coinfection blunted this increase in small LDL-P such that the levels were similar to those found in controls after multivariable adjustment. HIV-monoinfected individuals had the highest levels of small HDL-P, whereas levels in HIV/HCV-coinfected individuals were intermediate to HIV-monoinfected individuals and controls. Compared with controls, HIV-monoinfected had lower concentrations of large LDL-P, whereas HIV/HCV-coinfected individuals had levels that were also lower than controls but intermediate when compared with HIV monoinfection. In contrast, there was little change in large HDL-P in HIV monoinfection, whereas HIV/HCV coinfection was associated with substantially higher levels of large HDL-P relative to HIV monoinfection and controls, even after adjusting for demographic and other risk factors. These results add to the growing evidence that HIV/HCV coinfection has a direct effect on lipid profiles and lipoprotein concentrations [30–33] and suggest that HCV status should be considered when evaluating CVD risk factors such as lipoprotein subclasses in HIV-infected persons.
The observed association of HIV monoinfection with higher levels of small LDL-P and triglycerides, with decreased large LDL-P compared with controls is consistent with an ALP  described in HIV-monoinfected men on ART. Additionally, HIV monoinfection remained associated with higher levels of small LDL-P and decreased large LDL-P even after adjustment for triglycerides and HDL-C. Thus, alteration in small LDL-P and large LDL-P levels were independent of hypertriglyceridemia and low HDL-C seen in HIV monoinfection. Results from the Swiss HIV Cohort Study suggest that in HIV-infected patients treated with ART, small LDL-Ps were associated with coronary events . The consequences of the attenuation by HIV/HCV coinfection are unknown.
Our findings showed that small HDL-P levels were higher in HIV-monoinfected participants compared with control with intermediate levels seen in HIV/HCV coinfection. A previous study found that HIV infection was associated with lower small HDL-P in women even after adjustment for standard lipids and ART use  and lower small HDL-P concentrations were associated with a higher risk of CVD in HIV-monoinfected participants . Small HDL-P may play a role in mitigating the risk of CVD given their preference over larger HDL-P as initial acceptors of cholesterol from peripheral cells in reverse cholesterol transport and their anti-inflammatory properties [34,35]. However, in studies of the general population, the clinical consequences of low levels of small HDL-P on CVD risk have been inconsistent [17,36,37].
Several traditional risk factors for CVD can be impacted by HIV infection and its treatment. However, there are limited data regarding the extent to which ART induced abnormalities in the lipoprotein subclass concentrations. We examined the association of ART class with lipoprotein concentration in all HIV-infected participants. We found that NRTI use was associated with higher small LDL-P. The association of NRTI use with higher levels of small LDL-P appeared to be specific to this class as there was little association when other classes or ART use in general were examined in the model.
Although protease inhibitor use was initially associated with higher small LDL-P, after adjustment, the association was attenuated and no longer reached statistical significance. These findings are similar to results from Tien et al.  that showed that ART use, mainly protease inhibitor-based, was associated with greater small LDL-P but after adjustment for standard lipids, ART use was no longer associated.
Among the individual antiretroviral drugs, we found that the NNRTIs nevirapine and efavirenz were associated with higher large HDL-P perhaps reflecting the increase in HDL-C that has been previously described . Lopinavir/ritonavir was associated with lower small HDL-P similar to the trend of decreased HDL-C observed in some studies of ritonavir-boosted protease inhibitors . Interestingly, abacavir use was associated with higher small HDL-P, which might suggest lower risk. The effect of specific ART and alterations in lipoprotein particles on CVD needs further study.
These findings have potential clinical implications for the management of both HIV/HCV-coinfected and HIV-monoinfected participants. First, HIV/HCV-coinfected participants appear to have attenuated abnormalities in lipoprotein subclass levels that have a reported association with CVD in HIV-monoinfected and healthy patients – in particular, HIV/HCV-coinfected have lower levels of small dense LDL-P vs. HIV-monoinfected. This seems to imply that HIV/HCV-coinfected participants have less atherogenic lipid profiles and would have less CVD risk. However, previous studies have found that HIV/HCV coinfection is associated with an increased risk of CVD events [5,6]. Thus, these changes in lipoprotein particles do not appear to protect against CVD and suggest that they should not be used clinically. These results imply that factors other than lipid and lipoprotein perturbations likely account for the increased reports of CVD in the HIV/HCV-coinfected population.
Also, because lipid profiles and lipoprotein subclass particle concentrations appear to be less atherogenic in HIV/HCV-coinfected compared with HIV-monoinfected persons, it may be that clinicians underutilize lipid-lowering medications in such patients. Indeed, in our study, HIV/HCV-coinfected participants were only one-third as likely as HIV-monoinfected participants to be treated with statins. Prospective studies on CVD outcomes are needed to guide treatment targets in the HIV/HCV-coinfected population.
One possible explanation for the observed difference in lipid profiles between the HIV-monoinfected and HIV/HCV-coinfected groups is the direct effect of HCV on modulation of lipoprotein production in hepatocytes . HCV infection increases intrahepatocyte lipid deposition and utilizes lipids to promote HCV viral replication and secretion of lipoviroparticles. HCV-apoE containing lipoprotein particles span the range of VLDL to HDL. Clearance of VLDL and LDL containing HCV and apoE has been shown to be jointly mediated by both the LDL receptor and another receptor, such as the scavenger receptor SR-B1 [39–42], with these receptors playing a role in HCV infectivity by serving as a potential entry factor  as well as a modulator of replication of the HCV genome . The role of HCV containing lipoprotein particles in atherogenesis needs further study.
The strengths of our study are direct assessment of HCV infection and the inclusion of a large control group with extensive data on CVD risk factors that enabled us to adjust for relevant traditional CVD risk factors, including age, which was our major aim. Limitations of our study include its cross-sectional design, which complicates the evaluation of the potential causality of the reported associations. We did not use matched controls, but used a large population-based cohort, adjusting for multiple determinants of lipoprotein levels; however, we cannot exclude the possibility of residual confounding. Injection drug use status was not available in MESA, so we are unable to determine whether this variable may influence the association of HCV status with lipoprotein levels. We do not have data on adequate numbers of HCV-monoinfected individuals, which should be the focus of future studies. Finally, our study lacks cardiovascular events to correlate with alterations in lipoproteins.
In summary, after adjusting for traditional CVD risk factors, HIV infection is associated with abnormal lipoprotein levels. This risk appears to be attenuated partially by the presence of HIV/HCV coinfection. Although HIV/HCV coinfection is associated with a less atherogenic lipid profile than HIV monoinfection, the long-term effects of HIV/HCV coinfection on vascular disease are unclear with limited studies suggesting an increased risk of CVD. Additional studies are needed to determine whether HIV/HCV coinfection is associated with increased CVD events beyond that of HIV infection. In the interim, lack of elevated small LDL in a patient with HIV/HCV coinfection should be interpreted cautiously with regard to lowering risk. Also, given that lipoprotein alterations secondary to coinfection may not be protective, other novel markers of CVD risk in HIV/HCV-coinfected persons should be investigated. Our findings emphasize the importance of determining HCV status when assessing CVD risk factors in HIV-infected patients.
Sites and investigators are as follows: University Hospitals of Cleveland (Barbara Gripshover, MD); Tufts University (Abby Shevitz, MD (deceased) and Christine Wanke, MD); Stanford University (Andrew Zolopa, MD); University of Alabama at Birmingham (Michael Saag, MD); Johns Hopkins University (Joseph Cofrancesco Jr., MD and Adrian Dobs, MD); University of Colorado Health Sciences Center (Lisa Kosmiski, MD and Constance Benson, MD); University of North Carolina at Chapel Hill (David Wohl, MD and Charles van der Horst, MD*); University of California at San Diego (Daniel Lee, MD and W. Christopher Mathews, MD*); Washington University (E. Turner Overton, MD and William Powderly, MD); VA Medical Center, Atlanta (David Rimland, MD); University of California at Los Angeles (Judith Currier, MD); VA Medical Center, New York (Michael Simberkoff, MD); VA Medical Center, Washington DC (Cynthia Gibert, MD); St Luke's-Roosevelt Hospital Center (Donald Kotler, MD and Ellen Engelson, PhD); Kaiser Permanente, Oakland (Stephen Sidney, MD); University of Alabama at Birmingham (Cora E. Lewis, MD).
FRAM 2 Data Coordinating Center: University of Washington, Seattle (Richard A. Kronmal, PhD, Mary Louise Biggs, PhD, J. A. Christopher Delaney, PhD and John Pearce).
Image reading centers: St Luke's-Roosevelt Hospital Center: (Steven Heymsfield, MD, Jack Wang, MS and Mark Punyanitya). Tufts Medical Center, Boston: (Daniel H. O’Leary, MD, Joseph F. Polak MD MPH, Anita P. Harrington).
Office of the principal investigator: University of California, San Francisco, Veterans Affairs Medical Center and the Northern California Institute for Research and Development: (Carl Grunfeld, MD, PhD, Phyllis Tien, MD, Peter Bacchetti, PhD, Michael Shlipak, MD, Rebecca Scherzer, PhD, Mae Pang, RN, MSN, Heather Southwell, MS, RD).
Clinicaltrials.gov ID: NCT00331448.
This study is supported by NIH grants RO1- DK57508, HL74814, and HL 53359, and NIH GCRC grants M01- RR00036, RR00051, RR00052, RR00054, RR00083, RR0636, RR00865, UL1 RR024131, P30 DK 026687-269012, and NHLBI contracts N01-HC-95095, N01-HC-48047, and N01-HC-48050, the Albert L. and Janet A. Schultz Supporting Foundation; and with resources and the use of facilities of the Veterans Affairs Medical Centers of, Atlanta, District of Columbia, New York and San Francisco. The funding agency had no role in the collection or analysis of the data.
This study is also supported by R01-HL071739 and contracts N01-HC-95159 through N01-HC-95165 and N01-HC-95169 from the National Heart, Lung, and Blood Institute. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org.
The funder played no role in the conduct of the study, collection of the data, management of the study, analysis of data, interpretation of the data or preparation of the article. A representative of the funding agent participated in planning the protocol.
All authors received funding from some of the supporting grants.
Conflicts of interest
There are no conflicts of interest.
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