End-stage liver disease (ESLD) is a major source of morbidity and mortality among HIV-infected patients and is in large part attributable to chronic co-infection with hepatitis C virus (HCV) . However, only a subset of HIV/HCV patients will progress to ESLD  and the risk factors associated with disease progression are not fully understood.
Body composition is one potential risk factor for disease progression. Excess adiposity is closely associated with hepatic steatosis, which is common in HIV/HCV co-infected patients and correlates with hepatic fibrosis [3–5]. In HCV mono-infected patients, steatosis is a risk factor for liver disease progression , and higher body mass index (BMI) has also been associated with hepatic fibrosis . In addition, adiposity is related to a poorer response to hepatitis C therapy . Taken together, these findings suggest that reducing excess adiposity may reduce the risk of liver disease progression and improve HCV treatment response.
Many previous studies which have evaluated the relationship between body composition and histologic liver outcomes in HIV/HCV co-infected patients have used BMI as a measure of adiposity [3–5,7]. BMI, however, does not account for differences in regional adiposity. Because of central fat accumulation and subcutaneous fat wasting among HIV-infected patients receiving potent antiretroviral therapy (ART) , BMI may underestimate visceral adiposity in this population [10,11]. In addition, BMI does not reflect fat distribution, which may be an independent predictor of steatosis .
Sophisticated measurements of body composition can be used to address some of these limitations. Dual-energy X-ray absorptiometry (DXA) is a widely used technique that can accurately quantify regional adiposity, as well as provide a precise measurement of fat distribution.
Our previous studies in HIV/HCV co-infected individuals have shown that increased body weight was associated with steatosis  and that those with fibrosis progression tended to have a higher BMI compared to those with stable liver disease . In this analysis, we sought to expand upon these findings by using DXA to examine the relationship between regional body composition and the histologic presence of liver disease (i.e. steatosis or fibrosis).
Study participants were recruited from the Johns Hopkins University HIV Clinic or the Viral Hepatitis clinical practice into a prospective cohort whose primary aim is to characterize liver disease progression among HIV/HCV co-infected persons. Between February 2005 and November 2007, 173 individuals enrolled in the cohort underwent body composition analysis with DXA within 1 year of a liver biopsy. The median time between the liver biopsy and the DXA was −18 days [interquartile range (IQR) −139, 6 days].
For all patients, information on prescribed medications and laboratory parameters was obtained from clinical and laboratory databases. As described previously, data on patient demographics, social practices, clinical and laboratory parameters, and prescribed antiretroviral and other medications are abstracted from charts by trained personnel and transferred electronically from the laboratory database at enrollment and subsequent 6–12-month intervals . The designation of injection drug use and alcohol abuse was based on physician diagnosis and self-reports via orally administered questionnaires and audio computer-assisted self-interview. The presence of diabetes mellitus was self-reported. The study was approved by the Johns Hopkins Institutional Review Board and written informed consent was obtained for all participants.
Patients had standard laboratory assessments performed by licensed clinical laboratories, including a complete blood cell count, serum chemistry panels, aspartate aminotransferase (AST) levels, CD4 cell count, and plasma HIV-RNA level (reverse transcriptase polymerase chain reaction). HCV genotype testing was performed using reverse transcriptase polymerase chain reaction.
A transcutaneous liver biopsy was performed using an 18-gauge needle. Liver tissue was then fixed in 10% formalin, and paraffin-embedded sections were stained with hematoxylin–eosin and trichrome stains. Slides were evaluated by a single pathologist (M.T.). For fibrosis stage, biopsies were evaluated according to the METAVIR system [0 (no fibrosis) to 4 (cirrhosis)] . Hepatic steatosis was classified on a 5-point scale: 0, none; 1, steatosis involving less than 5% of hepatocytes; 2, 5–29%; 3, 30–60%; 4 greater than 60%. The median biopsy length was 13 mm (IQR 11, 15 mm).
Body mass index was defined as weight (kilograms) divided by the height (meters) squared. A wall-mounted stadiometer was used to measure height. Each participant was weighed while wearing minimal clothing. Whole body DXA was performed to assess regional body composition (trunk fat, extremity fat). The ratio of trunk fat to lower extremity fat [i.e. trunk fat mass: lower extremity fat mass ratio (FMR)] was calculated as a measure of fat distribution . Procedures were done using a Hologic 4500A machine with QDA4500A software version 9.03 (Hologic Inc, Waltham, Massachusetts, USA).
Body composition measurements were compared between those with and without steatosis (steatosis grade >0) and those with and without significant fibrosis (METAVIR stage >1) using Wilcoxon rank-sum tests. Univariable and multivariable Poisson regression with robust variance was used to estimate prevalence ratios of steatosis or fibrosis by various body composition measurements . Logistic regression tends to overestimate the prevalence ratio when the outcome is not rare (>10%) as was the case in this analysis. By contrast, Poisson regression provides a direct estimate of the prevalence ratio . For multivariable models, variables that were associated with each histologic liver outcome in univariate analysis with a P value less than 0.10 were considered. Age, sex, and race were included in all multivariable models regardless of statistical significance. HIV RNA was analyzed as whether or not the concentration of HIV RNA was less than 400 copies/ml within 1 year of the DXA (median duration 13 days, IQR −8, 58 days). Two-sided P values less than 0.05 were considered statistically significant. Analysis was performed using SAS, version 9.1 (Cary, North Carolina, USA).
Description of study population
The demographic and clinical characteristics of the study population (n = 173) are presented in Table 1. The median age was 47.7 years; 61% were male; 84% were black; 71% had a history of injection drug use and 38% had a history of clinician-diagnosed alcohol abuse or alcoholism; 94% were infected with HCV genotype 1. The median CD4 cell count was 428 cells/μl with HIV RNA level less than or equal to 400 copies/ml in 70%. Of the 50 patients with uncontrolled HIV replication, 56% were receiving potent ART within a year of the DXA, 6% had previously received ART but not within a year of the DXA, and 38% had never received ART. For patients who were ART-experienced, cumulative ART exposure was 6.3 years, cumulative exposure to protease inhibitor (PI) was 4.1 years and stavudine exposure was minimal (median 0 years, IQR 0, 2.0).
Significant hepatic fibrosis (METAVIR stage >1) was observed in 24%, whereas hepatic steatosis was found in 45%. Of those with steatosis (n = 77), the majority (66%) had minimal steatosis (grade 1, fat in <5% of hepatocytes). Among all participants, the median BMI was 25.1 kg/m2 and 21% had BMI greater than 30 kg/m2 consistent with obesity. The median trunk: lower extremity FMR by whole body DXA was 1.5 (IQR 1.1, 2.2) and the median trunk fat was 8.5 kg (IQR 5.7, 13.6 kg).
Body composition stratified by steatosis and fibrosis on liver biopsy
Participants with steatosis (n = 77) had a higher median BMI, more trunk fat, and more extremity fat and tended to have a higher trunk/lower extremity FMR compared to those without steatosis (n = 96) (Table 2). The most significant differences were observed for trunk fat, which tended to increase with higher steatosis grade (Fig. 1). Participants with and without significant fibrosis were not significantly different with respect to BMI, trunk fat, and extremity fat.
Correlates of hepatic steatosis and fibrosis
The presence of steatosis was associated with BMI and trunk fat in univariate analysis (Table 3). Other variables associated with steatosis included diabetes mellitus, hepatic fibrosis, and uncontrolled HIV replication (HIV RNA level >400 copies/ml). Notably, age, sex, race, current or nadir CD4 cell count, clinical diagnosis of alcohol abuse, or ART use, including current, ever, or cumulative exposure to PIs, non-nucleoside reverse transcriptase inhibitors (NNRTIs), stavudine, or zidovudine (data not shown), was not associated with steatosis. Because of their close correlations (r > 0.8), we chose only one of the body composition variables, trunk fat, to be carried forward in the multivariable analysis, since it had the strongest association with steatosis. In the multivariable analysis (model 1), independent predictors of steatosis included uncontrolled HIV replication, fibrosis, and higher trunk fat. Similar results were obtained when steatosis was defined as liver fat greater than 5% (i.e. ≥ grade 2 vs. grade 0) (data not shown). In a second multivariable analysis (model 2), we further assessed the relationship between steatosis and relative fat distribution, using trunk/lower extremity FMR which has been proposed as a measure of mixed lipodystrophy . Trunk fat was, therefore, removed from model 1 and replaced with BMI and trunk/lower extremity FMR. Both BMI and the trunk/lower extremity FMR were independently associated with steatosis (Table 2, model 2).
In univariable analysis, the presence of significant fibrosis (METAVIR stage >1) was not associated with BMI [prevalence ratio 1.01; 95% confidence interval (CI) 0.97, 1.06, P = 0.7], extremity fat (prevalence ratio 0.99, 95% CI 0.94, 1.05, P = 0.79), trunk fat (prevalence ratio 1.00; 95% CI 0.96, 1.04, P = 0.97), or trunk/lower extremity FMR (prevalence ratio 1.75; 95% CI 0.90, 3.41, P = 0.10). The association between fibrosis and trunk/lower extremity FMR was not statistically significant after adjustment for other confounders including age, sex, race, PI use at DXA, steatosis, and AST (data not shown). Similar results were obtained for both models 1 and 2 when the sample was restricted to the 145 African-American participants (data not shown).
In this cohort of HIV/HCV co-infected patients who underwent DXA and histologic evaluation of contemporaneous liver biopsy specimens, hepatic steatosis was significantly associated with increased central fat, whether measured in absolute or relative terms, whereas hepatic fibrosis was not correlated with any measure of body composition. We also found that steatosis was associated with uncontrolled HIV replication rather than the use of ART or specific antiretroviral drugs. These findings confirm the importance of central adiposity and central fat distribution as a potentially modifiable risk factor for hepatic steatosis and suggest that current antiretroviral regimens, without stavudine, may attenuate rather than promote liver fat accumulation.
To our knowledge, this is one of the only studies in HIV/HCV co-infected patients which employs the best available measures of both body composition and steatosis. Most previous studies have relied on BMI or body weight as a measure of adiposity [3–5,18] or have used noninvasive surrogate measures for steatosis (e.g. magnetic resonance imaging or ultrasound techniques) . Using DXA, we also quantified the regional distribution of adipose tissue and found the expected association between central fat and hepatic steatosis.
There are important physiologic differences in various adipose tissue depots. Central fat has a major role in the pathogenesis of steatosis, likely through increased insulin resistance , elaboration of free fatty acids , and adipocytokine production . In contrast, subcutaneous fat of the lower extremities may protect against metabolic derangement, including steatosis, by serving as a triglyceride storage depot . In the FRAM cohort, for example, hypertriglyceridemia and elevated alanine aminotransferase (ALT), suggestive of steatosis, were associated with both increased visceral fat and lower amounts of subcutaneous fat [19,23]. As a result, in HIV-infected patients, measures of fat distribution, such as the ratio of central fat to lower extremity fat may be particularly relevant in identifying those at increased risk of metabolic abnormalities . Similarly, we found that this DXA-derived measure of fat distribution was associated with steatosis, independent of BMI.
Another important finding in our study was that uncontrolled HIV replication was independently related to the presence of hepatic steatosis. This observation is similar to that from a recent large case–control study which observed that a higher plasma HIV viral load was associated with severe hepatic steatosis as determined by ultrasonography . Although it is not possible to determine a causal relationship from cross-sectional data, uncontrolled HIV replication may contribute to the pathogenesis of steatosis through increased insulin resistance and inflammation. In the Multicenter AIDS Cohort Study, all groups of HIV-infected men, including those not receiving ART, were more insulin-resistant compared to HIV-uninfected men . Moreover, in a large cohort of ART-naive patients, insulin resistance was associated with higher viral load and lower CD4 cell count , which may be mediated by the increased expression of proinflammatory cytokines, including TNF-α [27,28] and IL-6 , thereby promoting steatosis. The extent to which effective antiretroviral therapy can decrease the risk of steatosis deserves further investigation.
In contrast to previous studies, including our own [5,30], we did not observe a relationship between specific antiretroviral agents and steatosis. In older studies, stavudine exposure has been most closely associated with steatosis, through its effect on mitochondrial function [30,31]. However, stavudine usage is now very uncommon in our cohort and, in those who were previously exposed, the effects of stavudine on hepatic steatosis may have reversed with discontinuation.
In this study, most patients did not have more than 5% steatosis. Nonetheless, as in previous studies of HIV/HCV co-infected patients [3–5,18,30], hepatic steatosis was associated with concomitant liver fibrosis. Ectopic fat accumulation in the liver can lead to hepatic necrosis and apoptosis through the generation of oxidative stress and inflammation . In a previous longitudinal study , we did not find an association between baseline steatosis and fibrosis progression, but this important issue deserves further attention.
In contrast to findings in HCV mono-infected patients , we did not find an association between adiposity and the presence of hepatic fibrosis. This lack of association was also observed in another cohort of HCV/HIV co-infected patients and, in that study, was attributed to the relatively low BMI (mean ∼25 kg/m2) and the presence of other contributing factors, such as low CD4 cell count . We did observe a nonsignificant trend towards a higher trunk/extremity fat mass ratio in those with fibrosis. Longitudinal studies are required to assess the contribution of central fat distribution to fibrosis progression.
Our study had several limitations. First, 94% of our cohort was infected with genotype 1 and most are African-American; thus, it is unclear whether our findings are generalizable to populations with other genotypes or different racial composition. Genotype 3 virus, in particular, is thought to cause steatosis through direct viral mechanisms, and steatosis is likely a more important problem in countries, such as Spain, with higher genotype 3 HCV prevalence . Second, although well correlated with other measurement techniques, such as magnetic resonance imaging , DXA does not distinguish subcutaneous from visceral fat, which would be helpful in understanding the contributions of various fat depots to steatosis risk. It is also impossible to ascertain whether the association between unsuppressed HIV RNA and steatosis reflects HIV replication or other factors like unacknowledged alcohol use that might be associated with both steatosis and incomplete antiretroviral adherence.
In conclusion, the relative and absolute amount of central fat was correlated with hepatic steatosis. These findings underscore the potential of weight loss to improve hepatic outcomes in HIV/HCV co-infected patients. In addition, the independent association of uncontrolled HIV infection and hepatic steatosis suggests that effective HIV therapy may be an important tool to reduce the burden of liver disease in HIV-infected patients.
Financial support for this study came from K24 DA00432, DA-11602, DA-16065 and DA-13806 from the National Institute on Drug Abuse, AA016893 from the National Institute on Alcohol Abuse and Alcoholism, K23 AT002862 (TTB) from the National Center for Complementary and Alternative Medicine, grant HS 07-809 from the Agency for Healthcare Policy and Research and the Clinical Research Unit at the Johns Hopkins Medical Institutions, M01RR-02719
1. Weber R, Sabin CA, Friis-Moller N, Reiss P, El Sadr WM, Kirk O, et al
. Liver-related deaths in persons infected with the human immunodeficiency virus: the D:A:D study. Arch Intern Med 2006; 166:1632–1641.
2. Graham CS, Baden LR, Yu E, Mrus JM, Carnie J, Heeren T, et al
. Influence of human immunodeficiency virus infection on the course of hepatitis C
virus infection: a meta-analysis. Clin Infect Dis 2001; 33:562–569.
3. Marks KM, Petrovic LM, Talal AH, Murray MP, Gulick RM, Glesby MJ. Histological findings and clinical characteristics associated with hepatic steatosis
in patients coinfected with HIV
and hepatitis C
virus. J Infect Dis 2005; 192:1943–1949.
4. Bani-Sadr F, Carrat F, Bedossa P, Piroth L, Cacoub P, Perronne C, et al
. Hepatic steatosis
-HCV coinfected patients: analysis of risk factors. AIDS 2006; 20:525–531.
5. Sulkowski MS, Mehta SH, Torbenson M, Afdhal NH, Mirel L, Moore RD, et al
. Hepatic steatosis
and antiretroviral drug use among adults coinfected with HIV
and hepatitis C
virus. AIDS 2005; 19:585–592.
6. Adinolfi LE, Gambardella M, Andreana A, Tripodi MF, Utili R, Ruggiero G. Steatosis
accelerates the progression of liver damage of chronic hepatitis C
patients and correlates with specific HCV genotype and visceral obesity. Hepatology 2001; 33:1358–1364.
7. Monto A, Kakar S, Dove LM, Bostrom A, Miller EL, Wright TL. Contributions to hepatic fibrosis
-HCV coinfected and HCV monoinfected patients. Am J Gastroenterol 2006; 101:1509–1515.
8. Dore GJ, Torriani FJ, Rodriguez-Torres M, Brau N, Sulkowski M, Lamoglia RS, et al
. Baseline factors prognostic of sustained virological response in patients with HIV
virus co-infection. AIDS 2007; 21:1555–1559.
9. Grinspoon S, Carr A. Cardiovascular risk and body-fat abnormalities in HIV
-infected adults. N Engl J Med 2005; 352:48–62.
10. Joy T, Keogh HM, Hadigan C, Dolan SE, Fitch K, Liebau J, et al
. Relation of body composition
to body mass index in HIV
-infected patients with metabolic abnormalities. J Acquir Immune Defic Syndr 2008; 47:174–184.
11. Brown TT, Xu X, John M, Singh J, Kingsley LA, Palella FJ, et al
. Fat distribution and longitudinal anthropometric changes in HIV
-infected men with and without clinical evidence of lipodystrophy and HIV
-uninfected controls: a substudy of the Multicenter AIDS Cohort Study. AIDS Res Ther 2009; 6:8.
12. Sulkowski MS, Mehta SH, Torbenson MS, Higgins Y, Brinkley SC, de Oca RM, et al
. Rapid fibrosis progression among HIV
virus-co-infected adults. AIDS 2007; 21:2209–2216.
13. Moore RD. Understanding the clinical and economic outcomes of HIV
therapy: the Johns Hopkins HIV
clinical practice cohort. J Acquir Immune Defic Syndr Hum Retrovirol 1998; 17(Suppl 1):S38–S41. S38–S41.
14. Bedossa P, Poynard T. An algorithm for the grading of activity in chronic hepatitis C
. The METAVIR Cooperative Study Group. Hepatology 1996; 24:289–293.
15. Bonnet E, Delpierre C, Sommet A, Marion-Latard F, Herve R, Aquilina C, et al
. Total body composition
by DXA of 241 HIV
-negative men and 162 HIV
-infected men: proposal of reference values for defining lipodystrophy. J Clin Densitom 2005; 8:287–292.
16. Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol 2004; 159:702–706.
17. Thompson ML, Myers JE, Kriebel D. Prevalence odds ratio or prevalence ratio in the analysis of cross sectional data: what is to be done? Occup Environ Med 1998; 55:272–277.
18. Neau D, Winnock M, Castera L, Bail BL, Loko MA, Geraut L, et al
. Prevalence of and factors associated with hepatic steatosis
in patients coinfected with hepatitis C
virus and HIV
: Agence Nationale pour la Recherche contre le SIDA et les hepatites virales CO3 Aquitaine Cohort. J Acquir Immune Defic Syndr 2007; 45:168–173.
19. Tien PC, Kotler DP, Overton ET, Lewis CE, Rimland D, Bacchetti P, et al
. Regional adipose tissue and elevations in serum aminotransferases in HIV
-infected individuals. J Acquir Immune Defic Syndr 2008; 48:169–176.
20. Grunfeld C, Rimland D, Gibert CL, Powderly WG, Sidney S, Shlipak MG, et al
. Association of upper trunk and visceral adipose tissue volume with insulin resistance in control and HIV
-infected subjects in the FRAM study. J Acquir Immune Defic Syndr 2007; 46:283–290.
21. Jensen MD. Role of body fat distribution and the metabolic complications of obesity. J Clin Endocrinol Metab 2008; 93(Suppl 1):S57–S63.
22. Qureshi K, Abrams GA. Metabolic liver disease of obesity and role of adipose tissue in the pathogenesis of nonalcoholic fatty liver disease. World J Gastroenterol 2007; 13:3540–3553.
23. Wohl D, Scherzer R, Heymsfield S, Simberkoff M, Sidney S, Bacchetti P, et al
. The associations of regional adipose tissue with lipid and lipoprotein levels in HIV
-infected men. J Acquir Immune Defic Syndr 2008; 48:44–52.
24. Ryan P, Blanco F, Garcia-Gasco P, Garcia-Merchan J, Vispo E, Barreiro P, et al
. Predictors of severe hepatic steatosis
using abdominal ultrasound in HIV
-infected patients. HIV
Med 2009; 10:53–59.
25. Brown TT, Li X, Cole SR, Kingsley LA, Palella FJ, Riddler SA, et al
. Cumulative exposure to nucleoside analogue reverse transcriptase inhibitors is associated with insulin resistance markers in the Multicenter AIDS Cohort Study. AIDS 2005; 19:1375–1383.
26. El Sadr WM, Mullin CM, Carr A, Gibert C, Rappoport C, Visnegarwala F, 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.
27. Bastard JP, Caron M, Vidal H, Jan V, Auclair M, Vigouroux C, et al
. Association between altered expression of adipogenic factor SREBP1 in lipoatrophic adipose tissue from HIV
-1-infected patients and abnormal adipocyte differentiation and insulin resistance. Lancet 2002; 359:1026–1031.
28. Mynarcik DC, McNurlan MA, Steigbigel RT, Fuhrer J, Gelato MC. Association of severe insulin resistance with both loss of limb fat and elevated serum tumor necrosis factor receptor levels in HIV
lipodystrophy. J Acquir Immune Defic Syndr 2000; 25:312–321.
29. Vigouroux C, Maachi M, Nguyen TH, Coussieu C, Gharakhanian S, Funahashi T, et al
. Serum adipocytokines are related to lipodystrophy and metabolic disorders in HIV
-infected men under antiretroviral therapy. AIDS 2003; 17:1503–1511.
30. McGovern BH, Ditelberg JS, Taylor LE, Gandhi RT, Christopoulos KA, Chapman S, et al
. Hepatic steatosis
is associated with fibrosis, nucleoside analogue use, and hepatitis C
virus genotype 3 infection in HIV
-seropositive patients. Clin Infect Dis 2006; 43:365–372.
31. Miller KD, Cameron M, Wood LV, Dalakas MC, Kovacs JA. Lactic acidosis and hepatic steatosis
associated with use of stavudine: report of four cases. Ann Intern Med 2000; 133:192–196.
32. Marra F, Gastaldelli A, Svegliati BG, Tell G, Tiribelli C. Molecular basis and mechanisms of progression of nonalcoholic steatohepatitis. Trends Mol Med 2008; 14:72–81.
33. Ramalho F. Hepatitis C
virus infection and liver steatosis
. Antiviral Res 2003; 60:125–127.
34. Scherzer R, Shen W, Bacchetti P, Kotler D, Lewis CE, Shlipak MG, et al
. Comparison of dual-energy X-ray absorptiometry and magnetic resonance imaging-measured adipose tissue depots in HIV
-infected and control subjects. Am J Clin Nutr 2008; 88:1088–1096.