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Single-cell multi-omics profiling uncovers the immune heterogeneity in HIV-infected immunological non-responders

Xiaosheng Liu, Leidan Zhang, Xiaodi Li, Ling Chen, Lianfeng Lu, Yang Yang, Yuanni Wu, Liyuan Zheng, Jia Tang, Fada Wang, Yang Han, Xiaojing Song, Wei Cao, Taisheng Li

2025EBioMedicine18 citationsDOIOpen Access PDF

Abstract

BACKGROUND: T cells increase the risk of opportunistic infections and non-AIDS-related morbidity and mortality. Understanding the mechanisms driving this immune dysfunction is critical for developing targeted therapies. METHODS: We performed single-cell RNA sequencing (scRNA-seq) and single-cell VDJ sequencing (scVDJ-seq) on peripheral blood mononuclear cells (PBMCs) from INRs, immune responders (IRs), and healthy controls (HCs). We developed scGeneANOVA, a novel mixed model differential gene analysis tool, to detect differentially expressed genes and pathways. In addition, we developed the Viral Identification and Load Detection Analysis (VILDA) tool to quantify HIV-1 transcripts and investigate their relationship with interferon (IFN) pathway activation. FINDINGS: T cell exhaustion and immune recovery failure. The scGeneANOVA tool identified critical genes and pathways that were missed by traditional analysis methods, while VILDA showed higher levels of HIV-1 transcripts in INRs, which may drive the heightened IFN response. These findings support a potential contribution of IFN signalling in INR-related immune dysfunction. INTERPRETATION: T cell exhaustion. The identification of key genes and pathways offers potential biomarkers and therapeutic targets for improving immune recovery in this vulnerable population. FUNDING: This study was supported by the grants from Special Research Fund for the Central High-level Hospitals of Peking Union Medical College Hospital (Grant No. 2022-PUMCH-D-008), Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (Grant No. 2021-I2M-1-037), National Key Technologies R&D Program for the 13th Five-year Plan (Grant No. 2017ZX10202101-001). The funders played no role in the design, experiment conduction, data analysis and preparation of the manuscript of this work.

Topics & Concepts

BiologyImmune systemOmicsHuman immunodeficiency virus (HIV)Profiling (computer programming)Computational biologyVirologyImmunologyBioinformaticsComputer scienceOperating systemSingle-cell and spatial transcriptomicsHIV Research and Treatmentinterferon and immune responses
Single-cell multi-omics profiling uncovers the immune heterogeneity in HIV-infected immunological non-responders | Litcius