ABSTRACT
BACKGROUND: Torque teno virus (TTV) is part of the human virome. TTV load was related to the immune status in patients after organ transplantation. We hypothesize that TTV load could be an additional marker for immune function in people living with HIV (PLWH). METHODS: In this analysis, serum samples of PLWH from the RESINA multicenter cohort were reanalyzed for TTV. Investigated clinical and epidemiological parameters included human pegivirus load, patient age and sex, HIV load, CD4+ T-cell count (Centers for Disease Control and Prevention [CDC] stage 1, 2, or 3), and CDC clinical stage (1993 CDC classification system; stage A, B, or C) before initiation of antiretroviral therapy. Regression analysis was used to detect possible associations among parameters. RESULTS: Our analysis confirmed TTV as a strong predictor of CD4+ T-cell count and CDC class 3. This relationship was used to propose a first classification of TTV load with regard to clinical stage. We found no association with clinical CDC stages A-C. The human pegivirus load was inversely correlated with HIV load but not TTV load. CONCLUSIONS: TTV load was associated with immunodeficiency in PLWH. Neither TTV nor HIV load were predictive for the clinical categories of HIV infection.
Subject(s)
DNA Virus Infections , HIV Infections , Torque teno virus , Viral Load , Humans , Torque teno virus/isolation & purification , Male , Female , CD4 Lymphocyte Count , Adult , Middle Aged , HIV Infections/immunology , HIV Infections/virology , HIV Infections/drug therapy , HIV Infections/complications , DNA Virus Infections/virology , DNA Virus Infections/immunology , DNA Virus Infections/epidemiology , United States/epidemiology , Centers for Disease Control and Prevention, U.S. , Flaviviridae/immunology , Cohort Studies , Acquired Immunodeficiency Syndrome/immunology , Acquired Immunodeficiency Syndrome/virologyABSTRACT
OBJECTIVE: People with HIV (PWH) have high risk of liver fibrosis. We investigated the effect of weight gain and metabolic dysfunction-associated steatotic liver disease (MASLD) on liver fibrosis dynamics. DESIGN: Multicenter cohort study. METHODS: Fibrosis progression was defined as development of significant fibrosis [liver stiffness measurement (LSM) ≥8âkPa], or transition to cirrhosis (LSM ≥13âkPa), for those with significant fibrosis at baseline. Fibrosis regression was defined as transition to LSM less than 8âkPa, or to LSM less than 13âkPa for those with cirrhosis at baseline. MASLD was defined as hepatic steatosis (controlled attenuation parameter >248âdB/m) with at least one metabolic abnormality. A continuous-time multistate Markov model was used to describe transitions across fibrosis states. RESULTS: Among 1183 PWH included from three centers (25.2% with viral hepatitis coinfection), baseline prevalence of significant fibrosis and MASLD was 14.4 and 46.8%, respectively. During a median follow-up of 2.5âyears (interquartile range 1.9-3.5), the incidence rate of fibrosis progression and regression was 2.8 [95% confidence interval (CI) 2.3-3.4] and 2.2 (95% CI 1.9-2.6) per 100 person-years, respectively. In Markov model, weight gain increased the odds of fibrosis progression [odds ratio (OR) 3.11, 95% CI 1.59-6.08], whereas weight gain (OR 0.30, 95% CI 0.10-0.84) and male sex (OR 0.32, 95% CI 0.14-0.75) decreased the odds of fibrosis regression. On multivariable Cox regression analysis, predictors of fibrosis progression were weight gain [adjusted hazard ratio (aHR) 3.12, 95% CI 1.41-6.90] and MASLD (aHR 2.72, 95% CI 1.05-7.02). CONCLUSION: Fibrosis transitions are driven by metabolic health variables in PWH, independently of viral hepatitis coinfection and antiretroviral class therapy.