Multi-Omics Characterization of Lipid Metabolic Reprogramming in People With HIV Versus HIV-Negative Metabolic Dysfunction-Associated Steatotic Liver Disease

MASLD is characterized by hepatic lipid accumulation driven by metabolic dysfunction, and its pathophysiology involves extensive lipid metabolic reprogramming - including dysregulation of triglycerides, diacylglycerols, ceramides, and phosphatidylcholines. In people living with HIV (PWH), the metabolic burden imposed by chronic immune activation and long-term antiretroviral therapy (ART) further disrupts circulating lipid homeostasis, potentially creating a distinct pathophysiological profile compared to HIV-negative individuals with MASLD. However, the molecular differences between HIV-associated and HIV-negative MASLD have not been systematically characterized.

This prospective, observational, cross-sectional study enrolls three groups: (1) PWH with MASLD, (2) HIV-negative individuals with MASLD, and (3) healthy controls matched for age, sex, and BMI. All participants are recruited from Shanghai Public Health Clinical Center and affiliated health examination centers. A single fasting peripheral blood sample (10 mL) is collected from each participant, from which plasma is isolated and stored at -80°C until analysis.

Plasma samples will undergo multi-omics profiling including:

Targeted lipidomics: quantitative analysis of core lipid classes (free fatty acids, ceramides, sphingomyelins, triglycerides, diacylglycerols, phosphatidylcholines) using UPLC-MS/MS in multiple reaction monitoring (MRM) mode Proteomics: plasma protein profiling to identify disease-associated protein expression changes Transcriptomics: gene expression analysis to characterize transcriptional alterations associated with MASLD in the context of HIV infection Differential lipid features will be identified using multivariate analysis (PCA, OPLS-DA) and univariate filtering (VIP > 1, |FC| > 1.5, FDR < 0.05). KEGG and LipidMaps pathway enrichment analyses will reveal key metabolic pathways involved in lipid reprogramming. Correlations between lipid signatures and clinical parameters will be examined using Spearman correlation analysis. ROC curve analysis and logistic regression will be used to evaluate the diagnostic performance of candidate biomarkers.

This study aims to: (1) establish a comprehensive plasma lipidomic and multi-omics atlas of MASLD in PWH versus HIV-negative individuals; (2) identify HIV-specific lipid dysregulation patterns; and (3) discover novel, non-invasive biomarkers for MASLD diagnosis applicable to the HIV-infected population.