Evidence map›Paper›PMID 42310952›Full record

ArticleHGG advances2026

Genome-wide association study of untargeted plasma metabolomic profiles identifies host genetic regulation in people with HIV.

Mariam Ait Oumelloul, Adriaan van der Graaf, Simon Tang, Christian W Thorball, Marco Labarile, Ali Saadat, Valeriia Timonina, Isabella C Schöpf, Gilles Wandeler, Johannes Nemeth and 10 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in HGG advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Mariam Ait OumelloulSchool of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Adriaan van der GraafSwiss Institute of Bioinformatics, Lausanne, Switzerland; Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Simon TangSchool of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Christian W ThorballPrecision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Marco LabarileDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland; Institute of Medical Virology, University of Zurich, Zurich, Switzerland.
Ali SaadatSchool of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Valeriia TimoninaSchool of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Isabella C SchöpfUniversity Department of Medicine and Infectious Diseases Service, Kantonsspital Baselland, University of Basel, Bruderholz, Switzerland; Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Gilles WandelerInstitute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Department of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Johannes NemethDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland; Institute of Medical Virology, University of Zurich, Zurich, Switzerland.
Matthias CavassiniInfectious Diseases Service, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland.
Alexandra CalmyHIV/AIDS Unit, Division of Infectious Diseases, University Hospital Geneva, Geneva, Switzerland; Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Patrick SchmidDivision of Infectious Diseases, Cantonal Hospital St Gallen, St Gallen, Switzerland.
Marcel StöckleDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland.
Luigia ElziMalattie Infettive, Ospedale Regionale di Bellinzona e Valli, Bellinzona, Switzerland.
Nicola ZamboniInstitute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland; Swiss Multi-Omics Center, Zurich, Switzerland.
Roger D KouyosDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland; Institute of Medical Virology, University of Zurich, Zurich, Switzerland.
Philip E TarrUniversity Department of Medicine and Infectious Diseases Service, Kantonsspital Baselland, University of Basel, Bruderholz, Switzerland.
Jacques FellaySchool of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; Precision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland. Electronic address: jacques.fellay@epfl.ch.
Swiss HIV Cohort Study

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

People with human immunodeficiency virus (PWH) exhibit accelerated aging and a higher prevalence of aging-related conditions, despite effective antiretroviral therapy. The biological mechanisms involved remain incompletely understood. Integrating genomic and metabolomic profiling may help uncover genes and pathways contributing to aging-related disease in this population. Using a genome-wide association study framework and untargeted metabolomic profiling, we searched for associations between human genetic variants and the plasma concentrations of 1,930 putative metabolites in 1,244 individuals enrolled in the Swiss HIV Cohort Study. We performed an expression quantitative trait locus (eQTL) colocalization analysis to explore biological links between genetic variants and metabolites and used Mendelian randomization to search for causal relationships between metabolites and aging-related diseases. We identified 27 metabolites significantly associated with 12 genetic loci, including genes encoding the metabolic enzymes NAT8 and FUT2; 10 associations had been previously reported in general-population studies, of which eight were replicated in our analysis. The colocalization analyses provided evidence for a large overlap between genetic regulation of mRNA expression and metabolite levels, while Mendelian randomization suggested several causal effects. Our study uncovered genetic-metabolic associations observed in PWH and explored their biological relevance. These findings highlight the potential of integrated multi-omics profiling to deepen mechanistic understanding and inform future precision approaches to comorbidity management in this population.

Indexed as

aging-related comorbiditiescirculating metabolitesgenomicsGWASmetabolomicsmulti-omicspeople with HIV

Identifiers

PMID42310952
PMCPMC13355647

What Socratic holds

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Registered trials

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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 Socratic graph.