Evidence map›Paper›PMID 38645112›Full record

ArticlebioRxiv : the preprint server for biology2024

Multi-omic QTL mapping in early developmental tissues reveals phenotypic and temporal complexity of regulatory variants underlying GWAS loci.

Timothy D Arthur, Jennifer P Nguyen, Agnieszka D'Antonio-Chronowska, Jeffrey Jaureguy, Nayara Silva, Benjamin Henson, iPSCORE Consortium, Athanasia D Panopoulos, Juan Carlos Izpisua Belmonte, Matteo D'Antonio and 2 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

5 · Who and what money

Authors and funding

12 authors.

Timothy D Arthur
Jennifer P Nguyen
Agnieszka D'Antonio-Chronowska
Jeffrey Jaureguy
Nayara Silva
Benjamin Henson
iPSCORE Consortium
Athanasia D Panopoulos
Juan Carlos Izpisua Belmonte
Matteo D'Antonio
Graham McVicker
Kelly A Frazer

Funding

Predicting the effects of genetic variants on chromatin accessibility with a deep learning approachF31HG013262 · NHGRI · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI JAUREGUY, JEFF · 2024 to 2025
$89k
NHGRI NIH HHS F31 HG013262
6 · The paper itself

Abstract

Most GWAS loci are presumed to affect gene regulation, however, only ∼43% colocalize with expression quantitative trait loci (eQTLs). To address this colocalization gap, we identify eQTLs, chromatin accessibility QTLs (caQTLs), and histone acetylation QTLs (haQTLs) using molecular samples from three early developmental (EDev) tissues. Through colocalization, we annotate 586 GWAS loci for 17 traits by QTL complexity, QTL phenotype, and QTL temporal specificity. We show that GWAS loci are highly enriched for colocalization with complex QTL modules that affect multiple elements (genes and/or peaks). We also demonstrate that caQTLs and haQTLs capture regulatory variations not associated with eQTLs and explain ∼49% of the functionally annotated GWAS loci. Additionally, we show that EDev-unique QTLs are strongly depleted for colocalizing with GWAS loci. By conducting one of the largest multi-omic QTL studies to date, we demonstrate that many GWAS loci exhibit phenotypic complexity and therefore, are missed by traditional eQTL analyses.

Identifiers

PMID38645112
PMCPMC11030419

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.