Lipidomic and Multi-Omics Profiling of Fatty Liver Disease in People With and Without HIV

N/ANot Yet RecruitingNCT07640880

Yinzhong Shen120 enrolled

Overview

Metabolic dysfunction-associated steatotic liver disease (MASLD), commonly known as fatty liver disease, is increasingly prevalent worldwide. People living with HIV (PWH) face a higher risk of developing MASLD due to chronic immune activation and long-term antiretroviral therapy, yet whether the underlying biological changes differ from those in HIV-negative individuals with MASLD remains unknown. This prospective observational study will enroll three groups: PWH with MASLD, HIV-negative individuals with MASLD, and healthy controls without liver disease. A single fasting blood sample will be collected from each participant. Using targeted lipidomics, proteomics, and transcriptomics platforms, researchers will compare plasma molecular profiles across the three groups to identify MASLD-specific lipid signatures, characterize metabolic pathway dysregulation, and discover potential blood-based biomarkers for non-invasive diagnosis of MASLD. Findings from this study may help explain how HIV infection alters lipid metabolism in the context of MASLD and support the development of HIV-specific diagnostic tools for fatty 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.

Eligibility

Sex: ALLMin age: 18 YearsMax age: 80 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * Age 18-80 years * Able to provide written informed consent and cooperate with blood sample collection and clinical data recording For Group 1 (Treatment-naive people with HIV and MASLD): * Confirmed HIV infection with no prior antiretroviral therapy (treatment-naive) * Diagnosis of MASLD per the 2024 Chinese Guidelines: hepatic steatosis confirmed by imaging or histology (≥5% macrovesicular steatosis), exclusion of excessive alcohol consumption (\>210 g/week for men, \>140 g/week for women), and at least one metabolic cardiovascular risk factor For Group 2 (HIV-negative individuals with MASLD): * HIV-negative * Diagnosis of MASLD as defined above For Group 3 (Healthy Controls): * HIV-negative * Normal liver morphology on abdominal ultrasonography within the past year, with no evidence of hepatic steatosis * Matched to MASLD groups by age (within 5 years), sex, and BMI (within 3 kg/m²) Exclusion Criteria: * Chronic liver disease with decompensated cirrhosis, hepatic malignancy, or history of liver transplantation * Pregnancy or lactation * Active severe infectious disease (other than HIV for Group 1) * Severe critical illness or major organ failure

Outcomes

Primary Outcomes

Number of differentially abundant plasma lipid species identified by targeted lipidomics (UPLC-MS/MS)

Number of plasma lipid species showing statistically significant differential abundance among the three groups (treatment-naïve people with HIV and MASLD, HIV-negative people with MASLD, and healthy controls). Lipid species across core lipid classes (free fatty acids, ceramides, sphingomyelins, triglycerides, diacylglycerols, and phosphatidylcholines) are quantified by targeted lipidomics using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) in multiple reaction monitoring (MRM) mode, with quality-control samples and internal standards (e.g., TAG 17:0, Cer d18:1/17:0; RSD \<15%). A lipid species is counted as differentially abundant if it meets fold change ≥1.5 or ≤0.67, and FDR \<0.05.

Time frame: At enrollment (single time point, cross-sectional)

Secondary Outcomes

Number of differentially abundant plasma proteins identified by quantitative proteomics

Number of plasma proteins showing statistically significant differential abundance among the three groups (treatment-naïve people with HIV and MASLD, HIV-negative people with MASLD, and healthy controls), quantified by mass spectrometry-based (DIA) proteomics. A protein is counted as differentially abundant if it meets \|log2 fold change\| \>1 and adjusted p \<0.05.

Time frame: At enrollment

Number of differentially expressed genes in PBMCs identified by RNA sequencing

Number of genes showing statistically significant differential expression in peripheral blood mononuclear cells (PBMCs) among the three groups (treatment-naïve people with HIV and MASLD, HIV-negative people with MASLD, and healthy controls), quantified by RNA sequencing. A gene is counted as differentially expressed if it meets \|log2 fold change\| \>1 and FDR \<0.05.