Evidence map›Paper›PMID 41084320›Full record

ArticleClinical and translational medicine2025

Immune cell subset profiling and metabolic dysregulation define the divergent immune microenvironments in HIV immunological non-responders.

Qingfei Chu, Ningye Fang, Huanhuan Chen, Abdur Rashid, Xia Luo, Jianjun Li, Kang Li

Erratum issuedAbstract read
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Article in Clinical and translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Qingfei ChuDepartment of Infectious Diseases, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.ORCID 0009-0008-4107-4336
Ningye FangGuangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China.
Huanhuan ChenGuangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China.
Abdur RashidNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Xia LuoGuangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.
Jianjun LiGuangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China.
Kang LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.ORCID 0009-0000-8910-2940

Funding

China Postdoctoral Science Foundation Project 2024MD763949First-class discipline innovation-driven talent program of Guangxi Medical University, and Guangxi Key Research and Development Program Guike AB25069025Guangxi Natural Science Foundation 2020GXNSFAA159020Guangxi Natural Science Foundation 2025GXNSFBA069245Youth Science Foundation of Guangxi Medical University GXMUYSF202504
6 · The paper itself

Abstract

backgroundA subset of people living with HIV (PLWH) exhibit poor immune recovery despite effective antiretroviral therapy (ART), remaining at risk of disease progression. The immunometabolic mechanisms underlying this immunological non-response remain unclear.

methodsWe integrated transcriptomic and immunophenotypic approaches to characterise immune differences between immunological responders (IRs) and non-responders (INRs). Public datasets were analysed to identify differentially expressed genes (DEGs), followed by enrichment analysis, predictive modelling, immune infiltration assessment, and regulatory network construction. In parallel, flow cytometry was performed to assess T and B cell subsets in an independent cohort including IRs, INRs, treatment-naïve patients (TNPs), and healthy controls (HCs).

resultsDEGs between IRs and INRs were enriched in mitochondrial and ribosomal pathways. INRs showed reduced Th1, Th17, and Tfh cells, alongside increased markers of immune activation and exhaustion. Predictive modelling identified five hub genes (ATP5O, PIGY, UQCRQ, COX7C, and BLVRB) associated with immune recovery, and clustering based on their expression defined two transcriptionally distinct subtypes. Flow cytometry further confirmed that INRs exhibited diminished CD4⁺ T cell counts, increased PD-1⁺ and HLA-DR⁺ expression, and reduced resting memory B cells, reflecting persistent immune dysfunction.

conclusionsThis study underscores the pivotal role of immunometabolic dysregulation in shaping heterogeneous immune responses to ART. By integrating computational and experimental data, we identified key biomarkers and regulatory pathways associated with immune recovery. Our findings highlight the central influence of metabolic processes on immune restoration outcomes and propose personalised metabolic interventions as a promising strategy to enhance therapeutic efficacy in HIV-infected individuals.

Indexed as

HIV InfectionsHumansacquired immunodeficiency syndromehub genesimmune cell infiltrationimmunological non‐respondersimmunological responderstherapeutic targets

Identifiers

PMID41084320
PMCPMC12518780

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.