Abstract
Background
Metabolic dysfunction–associated steatotic liver disease (MASLD) is a major cause of liver-related morbidity and mortality among people with human immunodeficiency virus (PWH). We aimed to determine the prevalence of MASLD and clinically significant fibrosis among PWH and investigate if racial and ethnic differences exist after adjustment for clinical risk factors and PNPLA3 genotype.
Methods
This cross-sectional analysis included adult PWH prospectively enrolled in 2 US multicenter studies from 2018 to 2023. MASLD was defined as a controlled attenuation parameter (CAP) score ≥263 dB/m with at least 1 cardiometabolic risk factor and clinically significant fibrosis as a liver stiffness measurement ≥8 kPa upon vibration-controlled transient elastography. Multivariable logistic regression analysis was performed to examine the association of race/ethnicity with the presence of MASLD and clinically significant fibrosis, adjusting for clinical risk factors and PNPLA3 genotype.
Results
Of the 996 participants, the mean age was 53.9 years (standard deviation, 12 years) and 72% were male. The prevalence of MASLD and clinically significant fibrosis were 49% and 14%, respectively. Non-Hispanic Black (NHB) persons had the lowest prevalence of MASLD (43%) compared to non-Hispanic White (NHW) (53%) and Hispanic individuals (60%) (P < .001). Similarly, NHB persons had the lowest prevalence of clinically significant fibrosis (12%) compared to NHW (20%) and Hispanic individuals (13%) (P = .005). After adjusting for clinical risk factors and PNPLA3 genotype, NHB had a lower odds of MASLD (odds ratio [OR], 0.39 [95% confidence interval {CI}, .23–.66]) and clinically significant fibrosis (OR, 0.38 [95% CI, .20–.71]) compared to NHW persons.
Conclusions
NHB PWH have a lower risk of MASLD and clinically significant fibrosis compared to NHW and Hispanic individuals, even after controlling for clinical risk factors and PNPLA3 genotype.
Keywords: HIV, liver fibrosis, MASLD
Metabolic dysfunction–associated steatotic liver disease (MASLD) is currently the leading cause of liver disease in the aging human immunodeficiency virus (HIV) population and a major cause of liver-related morbidity and mortality among people with HIV (PWH) [1–4]. Nearly 50% of PWH without viral coinfections on suppressive antiretroviral therapy (ART) have steatotic liver disease, 90% of which is due to MASLD [5]. Black and Hispanic communities in the United States (US) are disproportionally affected by HIV compared to other racial and ethnic groups [6]. In addition, Black and Hispanic PWH have a higher prevalence of obesity and the greatest risk for significant weight gain on ART [7].
Racial and ethnic disparities in the prevalence of MASLD have been well described in the general population. Specifically, studies show that Hispanic persons have the highest and non-Hispanic Black (NHB) persons the lowest prevalence of MASLD compared to non-Hispanic White (NHW) individuals [8]. The risk of metabolic dysfunction–associated steatohepatitis (MASH) has also been shown to be higher in Hispanic and lower in NHB compared to NHW persons [8].
Differences in lifestyle, body fat distribution, and the prevalence of associated cardiometabolic risk factors (CMRFs) such as type 2 diabetes mellitus (T2DM), dyslipidemia, and hypertension that vary by race and ethnicity may partially account for these disparities [9]. In addition, variants in genes such as PNPLA3 (patatin-like phospholipase domain-containing protein 3), which regulates triglyceride metabolism, have been shown to contribute to differences in hepatic fat content and susceptibility to MASLD seen by race and ethnicity [10]. The GG genotype of PNPLA3 rs738409 is associated with a greater accumulation of hepatic steatosis and increased risk of fibrosis development compared to the CC genotype [11]. Prior studies have revealed that Hispanic persons have the highest prevalence of the GG genotype (25%) whereas NHB individuals have the lowest prevalence (2%) [10].
Racial and ethnic differences in the prevalence of MASLD and clinically significant fibrosis have not been adequately investigated in PWH. The primary aims of this study were to determine the prevalence of MASLD and clinically significant fibrosis among PWH and investigate if racial and ethnic differences exist after adjustment for clinical risk factors and PNPLA3 genotype. We examined these questions in a racially and ethnically diverse, multicenter cohort of PWH in the US.
METHODS
Study Design and Participants
The study population was comprised of participants from 2 multicenter National Institutes of Health–funded cohorts that prospectively enrolled adult PWH from outpatient clinics who provided written informed consent from 2018–2022 (first cohort) and 2021–2024 (second cohort). Inclusion criteria for the cohorts were age ≥18 years of age, documented HIV defined by a positive HIV antibody assay and/or detectable HIV-1 RNA, and stable ART regimen for at least 3 months prior to enrollment for those on ART at the time of study entry. Participants were excluded if they had evidence of hepatitis B (defined by positive hepatitis B surface antigen) or recent or current hepatitis C virus (HCV) coinfection (presence of anti-HCV antibody with detectable HCV RNA in serum within 3 years prior to enrollment) or any other form of chronic liver disease. Individuals were included in this cross-sectional analysis if they had an HIV RNA viral load <200 copies/mL, a self-reported racial/ethnic group of NHW, NHB, or Hispanic, and nonsignificant alcohol consumption. Persons who reported a race other than NHW, NHB, or Hispanic, or refused to report race were excluded from the analysis. Nonsignificant alcohol consumption was defined as alcohol consumption of ≤2 drinks/day and an Alcohol Use Disorders Identification Test (AUDIT) score <8. The first cohort enrolled participants at 3 clinical sites (Indiana University, Massachusetts General Hospital, and University of Texas Health–Houston) participating in National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK112293 [5]. The second cohort enrolled participants at 8 clinical sites (Duke University; Indiana University; Johns Hopkins University; University of Alabama at Birmingham; University of California, San Diego; University of California, San Francisco; University of Texas Health–Houston; and Virginia Commonwealth University) participating in NIDDK R01 DK121378 HIV NASH Clinical Research Network (ClinicalTrials.gov identifier NCT04795219) [12]. Duplicate data for participants who were enrolled in both cohorts were removed from the dataset. Each site's institutional review board (IRB) approved the study protocol for the first cohort. A single IRB approved the study protocol for the second cohort.
Study Procedures
Clinical, Laboratory, and Vibration-Controlled Transient Elastography Assessments
The study procedures and data collection have been described in detail in earlier publications [5, 12]. Each participant underwent a history and physical examination by a study clinician and vibration-controlled transient elastography (VCTE) using FibroScan by trained study staff at each study site. Fibrosis was assessed by liver stiffness measurement (LSM) in kilopascals (kPa) and steatosis by controlled attenuation parameter (CAP) in decibels/meter (dB/m). We prospectively collected data on demographic information (including age, sex at birth, and self-reported race and ethnicity), anthropometrics (including body mass index [BMI, in kg/m2] and waist circumference [in centimeters]), comorbidities (prediabetes, T2DM, hypertension, hyperlipidemia), laboratory data (including aspartate aminotransferase [AST], alanine aminotransferase [ALT], total bilirubin, albumin, creatinine, fasting lipid panel), HIV-related factors (including HIV-1 RNA and CD4+ T-cell count), and ART regimen and class (protease inhibitors [PIs], nonnucleoside reverse transcriptase inhibitors [NNRTIs], integrase strand transfer inhibitors [INSTIs], nucleoside reverse transcriptase inhibitors [NRTIs], and entry inhibitors). FIB-4 was calculated using the established algorithm based on age, ALT, AST, and platelet count [13]. Each participant completed an AUDIT questionnaire to ascertain alcohol consumption in the past year. AUDIT is a validated instrument that allows categorization of alcohol consumption as never, 1–2 standard drinks/day, 3–4 standard drinks/day, or higher levels. A score of ≥8 indicates a strong likelihood of hazardous drinking [14, 15].
MASLD was defined as a CAP score ≥263 dB/m [5, 16], with at least 1 of the 5 CMRFs detailed in the multisociety Delphi consensus statement and no significant alcohol consumption [17]. The CMRFs include (1) BMI ≥25 kg/m2 or waist circumference >94 cm in men or 80 cm in women; (2) fasting serum glucose ≥100 mg/dL, 2-hour postload glucose level ≥140 mg/dL, hemoglobin A1C ≥5.7%, or T2DM or treatment for T2DM; (3) blood pressure ≥130/85 mm Hg or specific antihypertensive drug treatment; (4) plasma triglycerides ≥150 mg/dL or lipid-lowering treatment; and (5) plasma high-density lipoprotein cholesterol ≤40 mg/dL for males and ≤50 mg/dL for females or lipid-lowering agents. Clinically significant fibrosis was considered to be an LSM ≥8 kPa [5, 18, 19].
PNPLA3 rs738409 Genotyping
DNA samples were obtained from a subset of participants who provided informed written consent for genetic testing and were used to perform PNPLA3 rs738409 variant genotyping using a TaqMan genotyping assay [20]. The rs738409 in PNPLA3 gene is a missense coding variant (NM_025225.3: c.444C > G) and results in an Ile (ATC) to Met (ATG) substitution. TaqMan probes were used for allelic discrimination (Thermo Fisher, Waltham, Massachusetts) [20].
Statistical Methods
Descriptive statistics of participant demographics, comorbidities, and laboratory, anthropometric, and VCTE characteristics at baseline were assessed by the 3 self-reported racial/ethnic categories of NHW, NHB, or Hispanic. P values were derived from one-way analysis of variance for continuous measures (or Kruskal–Wallis test for continuous measures where normality assumptions were not met), χ2 or Fisher exact test for categorical measures, and Cochran–Armitage trend test for ordered alternatives.
We analyzed 2 primary outcomes: (1) MASLD and (2) clinically significant fibrosis. We used multivariable logistic regression analysis to determine the independent association of the 2 primary outcomes with race/ethnicity, with NHW as the reference group. Models were adjusted for age, sex, BMI, T2DM, hypertension, triglycerides, ALT, and platelets and, in a second model, PNPLA3 genotype. We also performed a sensitivity analysis adjusting for clinical site, entry date into study, and duration of HIV. Data analyses were performed using Stata release 15. Nominal P values are presented, with no adjustments for multiple comparisons. P values of <.05 were considered statistically significant.
RESULTS
Characteristics of Study Participants
Of 1314 participants, 318 participants were excluded from this analysis due to moderate or heavy alcohol consumption. 74 participants were excluded due to the following: 52 with a reported race/ethnicity other than NHW, NHB, or Hispanic or refusal to report race, and 22 with an HIV RNA load >200 copies/mL. The remaining 996 participants were included in this analysis. Table 1 shows the baseline clinical and laboratory characteristics of the entire cohort as well as stratified by racial/ethnic group. Among the entire cohort, the mean age was 53.9 years (standard deviation, 12 years). The majority (72%) were male at birth, and 2% were transgender females. NHB comprised 50.5% of the cohort, and 20.5% were Hispanic. More than half (56%) had an educational attainment level of college or higher. CMRFs were common, with 37% of the cohort being overweight (BMI, 25–29.9 kg/m2), 41% obese (BMI, ≥30 kg/m2), 61% with hypertension, 29% with prediabetes, 26% with T2DM, and 58% with hyperlipidemia. The majority (59%) were former or current smokers. HIV RNA levels <200 copies/mL were observed in 78% of the cohort.
Table 1.
Baseline Clinical Characteristics of Study Participants, Stratified by Race and Ethnicity
| Characteristic | Non-Hispanic White | Non-Hispanic Black | Hispanic | Entire Cohort | P Valuea |
|---|---|---|---|---|---|
| No. of participants | 289 | 503 | 204 | 996 | |
| Demographics | |||||
| Age, y, mean ± SD | 55.6 ± 11.2 | 54.6 ± 12.1 | 49.7 ± 12.2 | 53.9 ± 12.0 | <.001 |
| Sex at birth (male) | 245 (85) | 308 (61) | 166 (81) | 719 (72) | <.001 |
| Transgender (female) | 3 (1) | 12 (2) | 8 (4) | 23 (2) | .11 |
| Educational attainment | <.001 | ||||
| Less than high school | 12 (4) | 84 (17) | 66 (32) | 162 (16) | |
| High school or GED | 51 (18) | 174 (35) | 51 (25) | 276 (28) | |
| College or above | 221 (78) | 243 (49) | 87 (43) | 551 (56) | |
| Food security | .09 | ||||
| High | 159 (72) | 277 (67) | 95 (64) | 531 (68) | |
| Low | 28 (13) | 72 (17) | 24 (16) | 124 (16) | |
| Very low | 33 (15) | 64 (15) | 30 (20) | 127 (16) | |
| Anthropometrics and comorbidities | |||||
| BMI, kg/m2, mean ± SD | 28.9 ± 6.5 | 30.4 ± 7.1 | 29.9 ± 5.5 | 29.9 ± 6.7 | .01 |
| Class | .001 | ||||
| <25 | 77 (27) | 106 (21) | 30 (15) | 213 (21) | |
| 25–29.9 | 114 (40) | 167 (33) | 88 (43) | 369 (37) | |
| ≥30 | 94 (33) | 229 (46) | 86 (42) | 409 (41) | |
| Waist circumference, cm, mean ± SD | 101.2 ± 15.6 | 99.2 ± 17.1 | 100.7 ± 12.7 | 100.1 ± 15.9 | .19 |
| Abdominal obesity | 131 (46) | 255 (51) | 91 (45) | 477 (48) | .26 |
| Hypertension | 167 (58) | 345 (69) | 92 (45) | 604 (61) | <.001 |
| Type 2 diabetes mellitus | 64 (22) | 146 (29) | 46 (23) | 256 (26) | .06 |
| Prediabetes | 70 (24) | 149 (30) | 73 (36) | 292 (29) | .02 |
| Hyperlipidemia | 181 (63) | 273 (54) | 124 (61) | 578 (58) | .05 |
| Low HDL-c | 116 (42) | 160 (35) | 88 (44) | 364 (39) | .06 |
| Smoking and alcohol consumption | |||||
| Smoking status | <.001 | ||||
| Never | 110 (38) | 188 (37) | 105 (51) | 403 (41) | |
| Former | 129 (45) | 169 (34) | 83 (41) | 381 (38) | |
| Current | 47 (16) | 145 (29) | 16 (8) | 208 (21) | |
| AUDIT score | .003 | ||||
| 0 | 134 (46) | 288 (57) | 111 (54) | 533 (54) | |
| 1–3 | 123 (43) | 191 (38) | 81 (40) | 395 (40) | |
| 4–7 | 32 (11) | 24 (5) | 12 (6) | 68 (7) | |
| HIV-related features | |||||
| History of AIDS | 47 (16) | 66 (13) | 44 (22) | 157 (16) | .02 |
| Time since HIV diagnosis, y, mean ± SD | 20.3 ± 10.5 | 20.5 ± 9.9 | 14.5 ± 9.7 | 19.2 ± 10.3 | <.001 |
| HIV medicationsb | |||||
| NRTI | 250 (87) | 443 (89) | 191 (94) | 884 (89) | .04 |
| NNRTI | 60 (21) | 84 (17) | 39 (19) | 183 (18) | .35 |
| INSTI | 260 (90) | 417 (84) | 168 (82) | 845 (85) | .02 |
| PI/cobicistat | 35 (12) | 111 (22) | 34 (17) | 180 (18) | .002 |
| PI/ritonavir | 35 (12) | 77 (15) | 22 (11) | 134 (14) | .19 |
| HIV RNA <200 copies/mL | 226 (78) | 395 (79) | 158 (77) | 779 (78) | .95 |
| HIV RNA copies/mL, median (IQR) | 22 (20–32) | 30 (20–45) | 23 (20–40) | 27 (20–40) | .01 |
| CD4+ count, cells/μL, median (IQR) | 725 (549–949) | 665 (508–911) | 632 (506–867) | 674 (518–913) | .03 |
| Laboratory features, median (IQR) | |||||
| Total cholesterol, mg/dL | 173 (145–198) | 170 (144–200) | 173 (147–200) | 171 (145–200) | .72 |
| Triglycerides, mg/dL | 139 (89–189) | 93 (71–136) | 139 (96–183) | 114 (79–170) | <.001 |
| HDL-c, mg/dL | 43 (37–52) | 48 (40–59) | 43 (36–50) | 45 (38–56) | <.001 |
| LDL-c, mg/dL | 100 (74–119) | 97 (75–124) | 102 (77–124) | 99 (75–122) | .79 |
| ALT, U/L | 25 (18–39) | 19 (13–26) | 26 (20–39) | 22 (16–33) | <.001 |
| AST, U/L | 24 (19–32) | 21 (17–27) | 22 (18–30) | 22 (18–29) | <.001 |
| Albumin, g/dL | 4.3 (4.1–4.6) | 4.3 (4.0–4.5) | 4.5 (4.3–4.7) | 4.3 (4.1–4.6) | <.001 |
| Total bilirubin, mg/dL | 0.6 (0.4–0.8) | 0.5 (0.3–0.6) | 0.5 (0.4–0.7) | 0.5 (0.4–0.7) | <.001 |
| Creatinine, mg/dL | 1.05 (0.90–1.20) | 1.10 (0.90–1.30) | 0.90 (0.80–1.10) | 1.00 (0.90–1.20) | <.001 |
| Alkaline phosphatase, U/L | 73 (58–90) | 76 (61–94) | 77 (64–92) | 75 (61–92) | .05 |
| Platelets, ×109/L | 233 (192–272) | 237 (197–280) | 243 (200–281) | 237 (195–278) | .26 |
| FIB-4 | <.001 | ||||
| <1.30 | 160 (56) | 287 (59) | 154 (76) | 601 (62) | |
| 1.30–2.67 | 106 (37) | 182 (37) | 43 (21) | 331 (34) | |
| >2.67 | 18 (6) | 21 (4) | 5 (2) | 44 (5) | |
| VCTE features | |||||
| CAP, dB/m, mean ± SD | 265.0 ± 65.7 | 254.2 ± 63.0 | 276.4 ± 57.6 | 261.9 ± 63.3 | <.001 |
| Liver stiffness measurement, kPa | |||||
| Mean ± SD | 6.5 ± 5.5 | 5.9 ± 4.6 | 5.7 ± 2.9 | 6.0 ± 4.7 | .11 |
| Median (IQR) | 5.2 (4.1–7.2) | 5.1 (4.2–6.4) | 5.0 (4.0–6.5) | 5.1 (4.1–6.6) | .34 |
Data are presented as No. (%) unless otherwise indicated.
Abbreviations: ALT, alanine aminotransferase; AST, aspartate aminotransferase; AUDIT, Alcohol Use Disorders Identification Test; BMI, body mass index; CAP, controlled attenuation parameter; FIB-4, Fibrosis-4 Index for Liver Fibrosis; GED, General Educational Development; HDL-c, high-density lipoprotein cholesterol; HIV, human immunodeficiency virus; IQR, interquartile range; INSTI, integrase strand transfer inhibitor; LDL-c, low-density lipoprotein cholesterol; NNRTI, nonnucleoside reverse transcriptase inhibitor; NRTI, nucleoside reverse transcriptase inhibitor; PI, protease inhibitor; SD, standard deviation; VCTE, vibration-controlled transient elastography.
aContinuous variables were compared using one-way analysis of variance, and categorical variables were compared using the χ2 test or Fisher exact test. The Cochran–Armitage trend test was used for ordered alternatives, including education, BMI categories, and FIB-4.
bReflects prior or current exposure to antiretroviral therapy medication.
Prevalence of MASLD and Clinically Significant Fibrosis by Race/Ethnicity
Table 2 and Figure 1 show the prevalence of MASLD and clinically significant fibrosis in the entire cohort and stratified by racial/ethnic group. The prevalence of MASLD and clinically significant fibrosis was 49% and 14%, respectively, in the overall cohort. NHB had the lowest prevalence of MASLD at 43% compared to 60% for Hispanic and 53% for NHW persons (P < .001). NHB persons had the lowest prevalence of clinically significant fibrosis at 12% compared to 13% for Hispanic and 20% for NHW individuals (P = .005); 7.6% of NHB individuals had both MASLD and clinically significant fibrosis compared to 8.8% of Hispanic and 14.6% of NHW persons (P = .007) (Figure 1).
Table 2.
Prevalence of Metabolic Dysfunction–Associated Steatotic Liver Disease and Clinically Significant Fibrosis Among Study Participants, According to Racial/Ethnic Group
| Characteristic | Non-Hispanic White | Non-Hispanic Black | Hispanic | Entire Cohort | P Valuea |
|---|---|---|---|---|---|
| No. of participants | 289 | 503 | 204 | 996 | |
| MASLD | 152 (53) | 216 (43) | 122 (60) | 490 (49) | <.001 |
| Clinically significant fibrosis (LSM ≥8 kPa) | 57 (20) | 58 (12) | 26 (13) | 141 (14) | .005 |
Data are presented as No. (%).
Abbreviations: LSM, liver stiffness measurement; MASLD, metabolic dysfunction–associated steatotic liver disease.
aCategorical variables were compared using the χ2 test.
Figure 1.
Prevalence of MASLD and clinically significant fibrosis in the entire cohort and according to racial/ethnic group. A, The prevalence of MASLD by race/ethnicity. B, The prevalence of clinically significant fibrosis by race/ethnicity. C, The prevalence of MASLD and clinically significant fibrosis by race/ethnicity. Abbreviations: MASLD, metabolic dysfunction–associated steatotic liver disease; NHB, non-Hispanic Black; NHW, non-Hispanic White.
PNPLA3 Genetic Polymorphism
PNPLA3 genotyping was available for 627 (63%) individuals in the entire cohort (Table 3). The baseline characteristics between study participants with and without PNPLA3 genotype available were similar (data not shown). NHB persons had the lowest frequency of the risk allele G (28%) and high-risk GG genotype (1%) versus NHW (48% and 5%, respectively) and Hispanic persons, who had the highest frequencies (80% and 31%, respectively) (P < .001).
Table 3.
PNPLA3 Genotype for Individuals With Genotyping Available, According to Racial/Ethnic Group
| Genotype | Non-Hispanic White | Non-Hispanic Black | Hispanic | Entire Cohort | P Valuea |
|---|---|---|---|---|---|
| No. with PNPLA3 Rs738409 available | 185 | 315 | 127 | 627 | |
| GG | 9 (5) | 3 (1) | 40 (31) | 52 (8) | <.001 |
| CG | 79 (43) | 85 (27) | 61 (48) | 225 (36) | |
| CC | 97 (52) | 227 (72) | 26 (20) | 350 (56) | |
| CG or GG | 88 (48) | 88 (28) | 101 (80) | 277 (44) | <.001 |
Data are presented as No. (%).
aCompared using the χ2 test.
Associations Between Race/Ethnicity and MASLD and Clinically Significant Fibrosis
Table 4 shows the multivariable logistic regression models assessing the independent association of race and ethnicity with MASLD and clinically significant fibrosis. After adjusting for clinically relevant variables, which included age, sex at birth, BMI, T2DM, hypertension, ALT, triglycerides, and platelet count, NHB had a significantly lower odds of both MASLD (adjusted odds ratio [aOR], 0.54 [95% confidence interval {CI}, .36–.81]) and clinically significant fibrosis (aOR, 0.50 [95% CI, .31–.81]) compared to NHW persons. There were no differences in the risk of MASLD and clinically significant fibrosis between Hispanic and NHW persons after adjusting for clinical risk factors. ART class was not significantly associated with MASLD or clinically significant fibrosis in univariate or multivariate analysis (data not shown).
Table 4.
Independent Association of Metabolic Dysfunction–Associated Steatotic Liver Disease and Clinically Significant Fibrosis With Participants’ Race/Ethnicity, From Multivariate Logistic Regression
| Characteristic | MASLDa | Clinically Significant Fibrosis (LSM ≥8 kPa)b | ||
|---|---|---|---|---|
| OR (95% CI) | P Value | OR (95% CI) | P Value | |
| Race/ethnicity, adjusted for age, sex, BMI, T2DM, hypertension, ALT, triglycerides, and platelets | ||||
| Non-Hispanic White | Ref. (1) | Ref. (1) | ||
| Non-Hispanic Black | 0.54 (.36–.81) | .003 | 0.50 (.31–.81) | .005 |
| Hispanic | 1.19 (.77–1.86) | .44 | 0.63 (.36–1.09) | .10 |
| Race/ethnicity, adjusted for age, sex, BMI, T2DM, hypertension, ALT, triglycerides, platelets, and PNPLA3 genotypec | ||||
| Non-Hispanic White | Ref. (1) | Ref. (1) | ||
| Non-Hispanic Black | 0.39 (.23–.66) | .001 | 0.38 (.20–.71) | .003 |
| Hispanic | 0.96 (.53–1.74) | .89 | 0.50 (.24–1.05) | .07 |
Abbreviations: ALT, alanine aminotransferase; BMI, body mass index; CI, confidence interval; LSM, liver stiffness measurement; MASLD, metabolic dysfunction–associated steatotic liver disease; OR, odds ratio; T2DM, type 2 diabetes mellitus.
aOutcome was MASLD vs controlled attenuation parameter <263 dB/m. n = 903 for the MASLD model due to the exclusion of significant alcohol use and missingness in covariates.
bOutcome was LSM ≥8 kPa vs LSM <8 kPa with nonsignificant alcohol consumption. n = 905 owing to the exclusion of significant alcohol use and missingness in the covariates.
cn = 569 for the MASLD model and n = 570 for the clinically significant fibrosis model due to the missing PNPLA3 genotype.
After controlling for PNPLA3 genotype in addition to clinical risk factors, there was an even greater reduction in the risk of MASLD (aOR, 0.39 [95% CI, .23–.66]) and clinically significant fibrosis (aOR, 0.38 [95% CI, .20–.71]) for NHB compared to NHW persons (Table 4). There were still no differences in the risk of MASLD and clinically significant fibrosis for Hispanic versus NHW participants after adjusting for PNPLA3 genotype. We also performed a sensitivity analysis adjusting for clinical site, entry date into study, and duration of HIV. This showed that addition of these factors made the inverse association of MASLD and clinically significant fibrosis with Black race even stronger (aOR, 0.34 [95% CI, .19–.62] for MASLD and aOR, 0.24 [95% CI, .12–.50] for clinically significant fibrosis) (Supplementary Table 1).
DISCUSSION
In this large, multiethnic cohort of persons with well-controlled HIV and no significant alcohol consumption, we found a substantial burden of MASLD, with a 49% and 14% prevalence of MASLD and clinically significant fibrosis, respectively. We determined that NHB individuals had greater than 60% lower odds of having MASLD and clinically significant fibrosis compared to NHW after controlling for clinically relevant risk factors and PNPLA3 genotype. We found no differences in the risk of MASLD and clinically significant fibrosis between Hispanic and NHW persons after adjusting for clinical risk factors and PNPLA3 genotype. Despite the lower risk of MASLD, NHB PWH had a disproportionate burden of CMRF with higher prevalences of obesity, prediabetes/T2DM, and hypertension compared to NHW participants.
Our findings highlight the significant burden of MASLD and clinically significant fibrosis in PWH, as we found a prevalence significantly higher than that in the general population, which is estimated to be around 38% for MASLD [21] and 7% for clinically significant fibrosis [22]. Furthermore, the high prevalence of CMRFs including obesity, prediabetes/T2DM, and hypertension among PWH emphasizes the need for additional studies to investigate cardiovascular disease risk and the association with MASLD in this population. This is important as cardiovascular disease is the leading cause of mortality in patients with MASLD [23], and PWH already have an increased cardiovascular disease risk compared to the general population [24], which may be compounded by the presence of MASLD. A recent study found that MASLD in PWH is independently associated with altered advanced lipoprotein and targeted metabolic profiles, indicative of higher cardiovascular disease risk, with no differences between those with or without clinically significant fibrosis [25].
The PNPLA3 gene codes for adiponutrin, a protein that plays a key role in the export of fat from hepatocytes. A specific genetic variant in the PNPLA3 gene (PNPLA3 I148M or rs738409 variant) is a strong risk factor for MASLD due to reduced enzyme function that promotes fat accumulation in the liver and increased oxidative and endoplasmic reticulum stress that can lead to inflammation and fibrosis progression [26]. Although the relationship between PNPLA3 rs738409 variant (G allele) and MASLD has been well described in general population [10], only a few studies to date have assessed the prevalence of PNPLA3 variants and its association with MASLD in persons with HIV monoinfection [27–29]. In our current study, we had PNPLA3 genotyping data available for 627 participants, which represented 63% of the total cohort. 44% of the entire cohort was found to carry at least one G allele, which has been associated with more progressive liver disease in the general population [11]. We found significant differences in G allele frequency by race and ethnicity, with 80% of Hispanic persons having at least one G allele compared to only 28% of NHB and 48% of NHW persons.
Our results are similar to the findings of studies of primary MASLD, which show that despite the higher prevalence of CMRFs such as obesity, diabetes, and hypertension among Black persons, Black race is associated with a lower prevalence of MASLD and less severe disease [8]. Despite differences in the prevalence of underlying CMRFs and PNPLA3 genetic polymorphisms by race and ethnicity, we found that the lower risk of MASLD and clinically significant fibrosis among Black individuals persisted even after adjusting for clinical risk factors and PNPLA3 genotype. A recent study published by the NASH Clinical Research Network showed similar results in the general population, with NHB persons with nonalcoholic fatty liver disease (NAFLD) having lower rates of advanced fibrosis and cirrhosis despite controlling for clinical risk factors and PNPLA3 genotype [30]. This raises intriguing questions about what protective factors could explain why Black persons have a lower risk of MASLD in terms of both prevalence and severity, and whether the same factors in the general population account for the similar observations seen in PWH. Studies have shown that polymorphisms of other genes coding for enzymes involved in hepatic fatty acid metabolism, such as TM6SF2 and MBOAT7-TMC4 genes, are associated with MASLD severity in the general population [31, 32]. A study of 65 PWH with persistently elevated aminotransferase levels and suspected NAFLD who underwent liver biopsy found that the MBOAT7-TMC4 A allele variant was associated with steatohepatitis [27]. Thus genetic variants in genes other than the PNPLA3 gene, which also have different distributions across racial and ethnic groups, may explain part of the observed differences seen and need to be further investigated in PWH.
In addition to genetic factors, there is increasing evidence of the role that alterations in the gut microbiota may play in the pathogenesis and progression of MASLD [33]. A study investigating a gut microbiome signature for HIV and MASLD found that MASLD had a greater influence on the overall structure of the gut microbiota than HIV status alone [34]. Studies have shown that there are significant differences in gut microbiota composition among self-identified racial and ethnic groups in the US [35]. Whether differences in gut microbiota contribute to racial and ethnic disparities in MASLD in PWH has not yet been studied and warrants further investigation.
Despite studies showing that the use of INSTIs, which are recommended as first-line ART, are associated with greater weight gain and incident insulin resistance in PWH, especially in persons of African descent [36–38], we did not find an association with ART class and the risk of MASLD or clinically significant fibrosis in this study.
Our study results, similar to studies of MASLD in the general population [39], highlight that Hispanic PWH are at a disproportionate risk of MASLD, which is largely due to the higher prevalence of the PNPLA3 I148M genetic variant as well CMRFs including overweight/obesity and insulin resistance.
One of the major strengths of this study is its multicenter design. This allowed for recruitment of a large number of participants from 9 clinical centers across the US, which resulted in a racially and ethnically diverse cohort in which 50.5% of individuals were NHB and 20.5% were Hispanic. This is similar to the racial and ethnic breakdown of the population living with HIV in the US, with an estimated 38% comprised of Black and 32% Hispanic persons [40]. Our study population thus reflects the reality that HIV disproportionately affects Black and Hispanic persons and increases the generalizability of our results to the general population of PWH in the US. The prospective data collection allowed for the collection of high-quality, accurate data on demographic and clinical variables that were used in the analysis.
There were several limitations of our study. This was a cross-sectional study, so we did not have information on the development of liver-related complications, mortality, or other clinical outcomes. We also could not assess for differences in the progression of fibrosis over time by race/ethnicity. We relied on self-reported race and ethnicity when studies have shown that genetically determined ancestry is more informative and accurate [41]. Although we acknowledge that race and ethnicity are social and political constructs, we used these simplified categories for our analysis due to the absence of genetic ancestry data. We also did not analyze the social determinants of health, which can contribute to racial and ethnical disparities in disease prevalence and severity for this study. We only included participants with viral suppression in our cohort, which limits our ability to study the direct effect of the HIV virus itself on steatotic liver disease. Finally, we recruited participants attending clinical sites at large academic centers, which limits the generalizability of our findings as this was not a community-based cohort.
CONCLUSIONS
In this racially and ethnically diverse cohort of nearly 1000 persons with well-controlled HIV, we found a substantial burden of liver disease, with a prevalence of MASLD of 49% and clinically significant fibrosis of 14%, as well as a high prevalence of CMRFs. After controlling for clinically relevant risk factors and PNPLA3 genotype, NHB had a decreased risk of MASLD and clinically significant fibrosis compared to NHW persons, while Hispanic persons did not have increased risk. Thus, the higher prevalence of MASLD in Hispanic PWH can be explained by clinical risk factors and the PNPLA3 G allele, whereas the lower prevalence of MASLD and clinically significant fibrosis in NHB persons appears to be due to factors beyond PNPLA3 genotype. Additional studies are needed to determine the underlying protective factors for MASLD and clinically significant fibrosis in NHB PWH, including testing for polymorphisms of other genes involved in hepatic fatty acid metabolism and gut microbiome analysis. In addition, due to the high prevalence of CMRFs, additional studies are warranted to investigate cardiovascular disease risk in this population and association with liver disease. Longitudinal studies to assess changes in fibrosis over time and correlation with clinical outcomes are also needed and currently in progress.
Supplementary Material
Notes
Financial support. This work was supported by the National Institutes of Health (grant number R01DK121378).
Contributor Information
Tinsay A Woreta, Division of Gastroenterology and Hepatology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Samer Gawrieh, Division of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Laura A Wilson, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Yuchen Xin, Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.
Eduardo Vilar-Gomez, Division of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Kathleen E Corey, Division of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts, USA.
Richard K Sterling, Division of Gastroenterology, Hepatology and Nutrition, Virginia Commonwealth University, Richmond, Virginia, USA.
Jordan E Lake, Division of Infectious Diseases, Department of Medicine, UTHealth, Houston, Texas, USA.
Susanna Naggie, Division of Infectious Diseases, Duke University School of Medicine, Durham, North Carolina, USA.
Sonya Heath, Division of Infectious Diseases, University of Alabama, Birmingham, Alabama, USA.
Holly Crandall, Division of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Jennifer C Price, Division of Gastroenterology and Hepatology, University of California, San Francisco, San Francisco, California, USA.
Rohit Loomba, Division of Gastroenterology and Hepatology, University of California, San Diego, La Jolla, California, USA.
Naga Chalasani, Division of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Mark S Sulkowski, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Supplementary Data
Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
References
- 1. Crum-Cianflone NF. Elevated aminotransferase levels among HIV-infected persons: what's lurking under the surface? Clin Infect Dis 2015; 60:1579–81. [DOI] [PubMed] [Google Scholar]
- 2. Maurice JB, Patel A, Scott AJ, Patel K, Thursz M, Lemoine M. Prevalence and risk factors of nonalcoholic fatty liver disease in HIV-monoinfection. AIDS 2017; 31:1621–32. [DOI] [PubMed] [Google Scholar]
- 3. Verna EC. Non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in patients with HIV. Lancet Gastroenterol Hepatol 2017; 2:211–23. [DOI] [PubMed] [Google Scholar]
- 4. Lake JE, Overton T, Naggie S, et al. Expert panel review on nonalcoholic fatty liver disease in persons with human immunodeficiency virus. Clin Gastroenterol Hepatol 2022; 20:256–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Gawrieh S, Lake JE, Debroy P, et al. Burden of fatty liver and hepatic fibrosis in persons with HIV: a diverse cross-sectional US multicenter study. Hepatology 2023; 78:578–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Centers for Disease Control and Prevention . Estimated HIV incidence and prevalence in the United States, 2015–2019. HIV Surveillance Supplemental Report 2021. Available at: https://stacks.cdc.gov/view/cdc/149257. Accessed 12 January 2026.
- 7. Erlandson KM, Zhang L, Lake JE, et al. Changes in weight and weight distribution across the lifespan among HIV-infected and -uninfected men and women. Medicine (Baltimore) 2016; 95:e5399. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Rich NE, Oji S, Mufti AR, et al. Racial and ethnic disparities in nonalcoholic fatty liver disease prevalence, severity, and outcomes in the United States: a systematic review and meta-analysis. Clin Gastroenterol Hepatol 2018; 16:198–210.e192. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Soti S, Corey KE, Lake JE, Erlandson KM. NAFLD and HIV: do sex, race, and ethnicity explain HIV-related risk? Curr HIV/AIDS Rep 2018; 15:212–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Romeo S, Kozlitina J, Xing C, et al. Genetic variation in PNPLA3 confers susceptibility to nonalcoholic fatty liver disease. Nat Genet 2008; 40:1461–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Sookoian S, Pirola CJ. Meta-analysis of the influence of I148M variant of patatin-like phospholipase domain containing 3 gene (PNPLA3) on the susceptibility and histological severity of nonalcoholic fatty liver disease. Hepatology 2011; 53:1883–94. [DOI] [PubMed] [Google Scholar]
- 12. Gawrieh S, Vilar-Gomez E, Woreta TA, et al. Prevalence of steatotic liver disease, MASLD, MetALD and significant fibrosis in people with HIV in the United States. Aliment Pharmacol Ther 2024; 59:666–79. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Sterling RK, Lissen E, Clumeck N, et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology 2006; 43:1317–25. [DOI] [PubMed] [Google Scholar]
- 14. Frank D, DeBenedetti AF, Volk RJ, Williams EC, Kivlahan DR, Bradley KA. Effectiveness of the AUDIT-C as a screening test for alcohol misuse in three race/ethnic groups. J Gen Intern Med 2008; 23:781–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Knight JR, Sherritt L, Harris SK, Gates EC, Chang G. Validity of brief alcohol screening tests among adolescents: a comparison of the AUDIT, POSIT, CAGE, and CRAFFT. Alcohol Clin Exp Res 2003; 27:67–73. [DOI] [PubMed] [Google Scholar]
- 16. Siddiqui MS, Vuppalanchi R, Van Natta ML, et al. Vibration-controlled transient elastography to assess fibrosis and steatosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol 2019; 17:156–63.e152. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Rinella ME, Lazarus JV, Ratziu V, et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. Hepatology 2023; 78:1966–86. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Rinella ME, Neuschwander-Tetri BA, Siddiqui MS, et al. AASLD practice guidance on the clinical assessment and management of nonalcoholic fatty liver disease. Hepatology 2023; 77:1797–835. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Kanwal F, Shubrook JH, Adams LA, et al. Clinical care pathway for the risk stratification and management of patients with nonalcoholic fatty liver disease. Gastroenterology 2021; 161:1657–69. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Vilar-Gomez E, Pirola CJ, Sookoian S, et al. Impact of the association between PNPLA3 genetic variation and dietary intake on the risk of significant fibrosis in patients with NAFLD. Am J Gastroenterol 2021; 116:994–1006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Younossi ZM, Kalligeros M, Henry L. Epidemiology of metabolic dysfunction–associated steatotic liver disease. Clin Mol Hepatol 2025; 31:S32–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Kim HY, Yu JH, Chon YE, et al. Prevalence of clinically significant liver fibrosis in the general population: a systematic review and meta-analysis. Clin Mol Hepatol 2024; 30:S199–213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Targher G, Byrne CD, Tilg H. NAFLD and increased risk of cardiovascular disease: clinical associations, pathophysiological mechanisms and pharmacological implications. Gut 2020; 69:1691–705. [DOI] [PubMed] [Google Scholar]
- 24. Zhu S, Wang W, He J, et al. Higher cardiovascular disease risks in people living with HIV: a systematic review and meta-analysis. J Glob Health 2024; 14:04078. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Lin KH, Vilar-Gomez E, Corey KE, et al. MASLD in persons with HIV is associated with high cardiometabolic risk as evidenced by altered advanced lipoprotein profiles and targeted metabolomics. Lipids Health Dis 2024; 23:339. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Petta S, Armandi A, Bugianesi E. Impact of PNPLA3 I148M on clinical outcomes in patients with MASLD. Liver Int 2025; 45:e16133. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Busca C, Arias P, Sanchez-Conde M, et al. Genetic variants associated with steatohepatitis and liver fibrosis in HIV-infected patients with NAFLD. Front Pharmacol 2022; 13:905126. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Sherman KE, Rouster SD, Meeds H, et al. PNPLA3 single nucleotide polymorphism prevalence and association with liver disease in a diverse cohort of persons living with HIV. Biology (Basel) 2021; 10:242. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Price JC, Seaberg EC, Latanich R, et al. Risk factors for fatty liver in the Multicenter AIDS Cohort Study. Am J Gastroenterol 2014; 109:695–704. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Samala N, Xin Y, Wilson LA, et al. Non-Hispanic Black persons with nonalcoholic fatty liver disease have lower rates of advanced fibrosis, cirrhosis, and liver-related events even after controlling for clinical risk factors and PNPLA3 genotype. Am J Gastroenterol 2024; 119(9):1857–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Mancina RM, Dongiovanni P, Petta S, et al. The MBOAT7-TMC4 variant rs641738 increases risk of nonalcoholic fatty liver disease in individuals of European descent. Gastroenterology 2016; 150:1219–30.e1216. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Liu YL, Reeves HL, Burt AD, et al. TM6SF2 rs58542926 influences hepatic fibrosis progression in patients with non-alcoholic fatty liver disease. Nat Commun 2014; 5:4309. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Ha S, Wong VW, Zhang X, Yu J. Interplay between gut microbiome, host genetic and epigenetic modifications in MASLD and MASLD-related hepatocellular carcinoma. Gut 2024; 74:141–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Martinez-Sanz J, Talavera-Rodriguez A, Diaz-Alvarez J, et al. A gut microbiome signature for HIV and metabolic dysfunction–associated steatotic liver disease. Front Immunol 2023; 14:1297378. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Brooks AW, Priya S, Blekhman R, Bordenstein SR. Gut microbiota diversity across ethnicities in the United States. PLoS Biol 2018; 16:e2006842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. O’Halloran JA, Sahrmann J, Parra-Rodriguez L, et al. Integrase strand transfer inhibitors are associated with incident diabetes mellitus in people with human immunodeficiency virus. Clin Infect Dis 2022; 75:2060–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Savinelli S, Newman E, Mallon PWG. Metabolic complications associated with use of integrase strand transfer inhibitors (InSTI) for the treatment of HIV-1 infection: focus on weight changes, lipids, glucose and bone metabolism. Curr HIV/AIDS Rep 2024; 21:293–308. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Mulindwa F, Kamal H, Castelnuovo B, et al. Association between integrase strand transfer inhibitor use with insulin resistance and incident diabetes mellitus in persons living with HIV: a systematic review and meta-analysis. BMJ Open Diabetes Res Care 2023; 11:e003136. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Tesfai K, Pace J, El-Newihi N, Martinez ME, Tincopa MA, Loomba R. Disparities for Hispanic adults with metabolic dysfunction–associated steatotic liver disease in the United States: a systematic review and meta-analysis. Clin Gastroenterol Hepatol 2025; 23:236–49. [DOI] [PubMed] [Google Scholar]
- 40. Centers for Disease Control and Prevention . HIV surveillance report: diagnoses, deaths, and prevalence of HIV in the United States and 6 territories and freely associated states, 2022. 2024. Available at: https://stacks.cdc.gov/view/cdc/156509. Accessed 25 September 2024.
- 41. Spector SA, Brummel SS, Nievergelt CM, et al. Genetically determined ancestry is more informative than self-reported race in HIV-infected and -exposed children. Medicine (Baltimore) 2016; 95:e4733. [DOI] [PMC free article] [PubMed] [Google Scholar]
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