Liver Steatosis is Prevalent in Lean People With HIV and Associated With Exposure to Antiretroviral Treatment-A Cross-sectional Study

Abstract

Background: Steatotic liver disease is suggested to have a higher prevalence and severity in people with HIV (PHIV), including in those with a normal body mass index (BMI). In this study, we used data from the 2000HIV cohort to (1) assess the prevalence of liver steatosis and fibrosis in lean versus overweight/obese PHIV and (2) assess associations in these subgroups between steatosis and fibrosis with traditional risk factors and HIV-specific characteristics.

Methods: The 2000HIV study cohort comprises 1895 virally suppressed PHIV that were included between 2019 and 2021 in 4 HIV treatment centers in the Netherlands. The majority (58.5%) underwent vibration-controlled transient elastography for the assessment of liver steatosis and fibrosis. The prevalence of steatosis (controlled attenuation parameter ≥263 dB/m) and fibrosis (liver stiffness measurement ≥7.0 kPa) was estimated. Multiple factors including HIV characteristics and antiretroviral drugs were tested in a logistic regression model for association with steatosis and fibrosis. Analyses were performed separately for lean (Asian descent: BMI < 23 kg/m², other descent: BMI < 25 kg/m²) and overweight/obese (other BMI) participants.

Results: Of 1050 PHIV including 505 lean and 545 overweight/obese PHIV, liver steatosis was observed in 37.7% of the overall study population, 19.7% of lean, and 54% of overweight/obese PHIV, whereas fibrosis was observed in 9.0% of the overall study population, 5.9% of lean, and 12.0% of overweight/obese PHIV.All associations with fibrosis and most associations with steatosis concerned metabolic factors such as type 2 diabetes mellitus (overall population: adjusted odds ratio [aOR] for steatosis: 2.3 [1.21-4.4], P = .011; aOR for fibrosis: 3.7 [1.82-7.53], P < .001). Furthermore, in lean PLHIV, liver steatosis was associated with CD4 and CD8 counts at enrollment, dual therapy, and history of treatment with raltegravir (aOR: 3.6 [1.53-8.47], P = .003), stavudine (aOR: 3.73 [1.69-8.2], P = .001), and indinavir (aOR: 3.86 [1.59-9.37], P = .003). These associations were not observed in overweight/obese PHIV.

Conclusions: Liver steatosis was highly prevalent, affecting approximately one-fifth of lean PHIV and half of overweight/obese PHIV. Fibrosis was observed in a minority. Both steatosis and fibrosis were associated with traditional metabolic risk factors. In addition, (prior) exposure to specific antiretroviral drugs was associated liver steatosis in lean, but not in overweight/obese PHIV. Implementing increased screening protocols could enhance the identification of steatotic liver disease in lean PHIV.

Keywords: HIV; Lean; MASLD; Steatosis.

Figure 1.

Flow diagram of the study population. Abbreviations: CAP, controlled attenuation parameter; LSM, liver stiffness measurement.

Figure 2.

Stacked bar plots showing the prevalence of liver steatosis in the total study population (lowest bar), and the subgroups of lean (highest bar) and overweight or obese participants (middle bar). The legend shows the different steatosis grades.

Figure 3.

Associations between steatosis and demographics, comorbidities, laboratory measurements, HIV-specific characteristics, and ART exposure for the total population (purple), lean participants (green), and overweight and obese participants (orange). Effect estimates are presented as odds ratios with 95% confidence intervals. The odds ratios for demographics are not corrected for any confounders. The logistic regression with demographics identified 2 confounding variables: age, and fat layer thickness. Because of a strong association between BMI and fat layer thickness, only one of them was selected as a confounder for subsequent models. These confounding variables were added to the logistic regression models with comorbidities, HIV-specific characteristics, and ART exposure. In the models involving laboratory assessments, lipid-lowering therapy was also included as a confounder. Closed circles denote significant P values (<.05). For readability, few variables that did not show significant associations are not shown in this figure (ie, Native American ethnicity, Hispanic ethnicity, way of transmission: intravenous drugs, way of transmission: blood products, way of transmission: congenital, ever: zalcitabine, duration of untreated infection, current: no ART. Abbreviations: ALP, alkaline phosphatase; ALT, alanine transaminase; ART, antiretroviral therapy; AST, aspartate aminotransferase; BIC, bictegravir; CAP, controlled attenuation parameter; CMV, cytomegalovirus; D4T, stavudine; d-drugs, dideoxynucleoside analogs; DDI, didanosine; DTG, dolutegravir; EFV, efavirenz; EVG, elvitegravir; GGT, gamma-glutamyl transferase; HAV, hepatitis A virus; HBV, hepatitis B virus; HCV, hepatitis C virus; HDL, high-density lipoprotein; IDV, indinavir; INSTI, integrase strand transfer inhibitor; LDH, lactate dehydrogenase; LDL, low-density lipoprotein; LSM, liver stiffness measurement; MSM, men who have sex with men; NNRTI, nonnucleoside reverse transcriptase inhibitor; NRTI, nucleoside reverse transcriptase inhibitor; NtRTI, nucleotide reverse transcriptase inhibitor; RAL, raltegravir; PI, protease inhibitors; RTV, ritonavir; T2DM, type 2 diabetes mellitus; TAF, tenofovir alafenamide; TDF, tenofovir disoproxil fumarate; VLDL, very low-density lipoprotein; WOT, way of transmission; ZDV, zidovudine.

Figure 4.

Associations between fibrosis and demographics, comorbidities, laboratory measurements, HIV-specific characteristics, and ART exposure for the total population (purple), lean participants (green), and overweight and obese participants (orange). Effect estimates are presented as odds ratios with 95% confidence intervals. The odds ratios for demographics are not corrected for any confounders. The logistic regression with demographics identified 2 confounding variables: age and fat layer thickness (BMI and fat layer thickness are strongly associated so we choose 1 of them to add as confounder in subsequent models). These confounding variables were added to the logistic regression models with comorbidities, HIV-specific characteristics, and ART exposure. For the models with laboratory assessments, we also added lipid-lowering therapy as a confounder. Closed circles denote significant P values (<.05). For readability, few variables that did not show significant associations are not shown in this figure (ie, Native American ethnicity, Hispanic ethnicity, way of transmission: intravenous drugs, way of transmission: blood products, way of transmission: congenital, ever: zalcitabine, duration of untreated infection, current: no ART). Abbreviations: ALT, alanine transaminase; ALP, alkaline phosphatase; ART, antiretroviral therapy; AST, aspartate aminotransferase; BIC, bictegravir; BMI, body mass index; CAP, controlled attenuation parameter; CMV, cytomegalovirus; D4T, stavudine; d-drugs, dideoxynucleoside analogs; DDI, didanosine; DTG, dolutegravir; EFV, efavirenz; EVG, elvitegravir; GGT, gamma-glutamyl transferase; HAV, hepatitis A virus; HBV, hepatitis B virus; HCV, hepatitis C virus; HDL, high-density lipoprotein; IDV, indinavir; INSTI, integrase strand transfer inhibitor; LDH, lactate dehydrogenase; LDL, low-density lipoprotein; LSM, liver stiffness measurement; MSM, men who have sex with men; NNRTI, nonnucleoside reverse transcriptase inhibitor; NRTI, nucleoside reverse transcriptase inhibitor; NtRTI, nucleotide reverse transcriptase inhibitor; PI, protease inhibitors; RAL, raltegravir; RTV, ritonavir; T2DM, type 2 diabetes mellitus; TAF, tenofovir alafenamide; TDF, tenofovir disoproxil fumarate; VLDL, very low-density lipoprotein; WOT, way of transmission; ZDV, zidovudine.

Figure 5.

Correlations between HIV characteristics and duration of exposure to selected antiretrovirals with metabolic factors for lean (left) and overweight and obese PHIV (right). This correlation plot shows the correlations between HIV characteristics and ART exposure, with metabolic comorbidities and lipid measurements. Spearman's rho correlation coefficients were calculated for associations between continuous variables and Phi coefficients for associations between 2 binary variables (accompanied with the P value from Chi-square test). The color of the tiles shows the direction (red for positive, blue for negative) and strength of the association, the asterisks depict the level of significance of the FDR-corrected P values: *P values .01–.05; **P values .001–.01; and ***P values < .001. Abbreviations: ART, antiretroviral therapy; D4T, stavudine; HDL, high density lipoprotein; IDV, indinavir; INSTI, integrase strand transfer inhibitor; LDL, low-density lipoprotein; RAL, raltegravir; T2DM, type 2 diabetes mellitus; VLDL, very low-density lipoprotein; ZDV, zidovudine.