Evidence map›Paper›PMID 39825011›Full record

ArticleScientific reports2025

Functionally-informed fine-mapping identifies genetic variants linking increased CHD1L expression and HIV restriction in monocytes.

Riley H Tough, Paul J McLaren, International Collaboration for the Genomics of HIV

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Riley H ToughSexually Transmitted and Bloodborne Infections Surveillance and Molecular Epidemiology, Sexually Transmitted and Bloodborne Infections Division at the JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratories, Public Health Agency of Canada, Winnipeg, MB, R3E 3L5, Canada.
Paul J McLarenSexually Transmitted and Bloodborne Infections Surveillance and Molecular Epidemiology, Sexually Transmitted and Bloodborne Infections Division at the JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratories, Public Health Agency of Canada, Winnipeg, MB, R3E 3L5, Canada. paul.mclaren@phac-aspc.gc.ca.
International Collaboration for the Genomics of HIV

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human Immunodeficiency Virus Type 1 (HIV) set-point viral load is a strong predictor of disease progression and transmission risk. A recent genome-wide association study in individuals of African ancestries identified a region on chromosome 1 significantly associated with decreased HIV set-point viral load. Knockout of the closest gene, CHD1L, enhanced HIV replication in vitro in myeloid cells. However, it remains unclear if HIV spVL associated variants are associated with CHD1L gene expression changes. Here we apply a heuristic fine-mapping approach to prioritize combinations of variants that explain the majority of set-point viral load variance and identify variants likely driving the association. We assess the combined impact of these variants on CHD1L regulation using publicly available sequencing studies, and test the relationship between CHD1L expression and set-point viral load using imputed CHD1L expression from monocytes. Taken together, this work characterizes genetically regulated CHD1L expression and further expands our knowledge of CHD1L-mediated HIV restriction in monocytes.

Indexed as

DNA-Binding ProteinsDNA HelicasesGenetic VariationHIV-1HIV InfectionsMonocytesChromosome MappingGene Expression RegulationGenome-Wide Association StudyHumansPolymorphism, Single NucleotideViral LoadVirus ReplicationDNA-Binding ProteinsDNA Helicases

Identifiers

PMID39825011
PMCPMC11748618

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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 OpenQuestion graph.