ArticlemedRxiv : the preprint server for health sciences2024
Impact of disease-associated chromatin accessibility QTLs across immune cell types and contexts.
Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Updated by
Authors and funding
11 authors.
Funding
Abstract
Only a third of immune-associated loci from genome-wide association studies (GWAS) colocalize with expression quantitative trait loci (eQTLs). To learn about causal genes and mechanisms at the remaining loci, we created a unified single-cell chromatin accessibility (scATAC-seq) map in peripheral blood comprising a total of 282,424 cells from 48 individuals. Clustering and topic modeling of scATAC data identified discrete cell-types and continuous cell states, which helped reveal disease-relevant cellular contexts, and allowed mapping of genetic effects on chromatin accessibility across these contexts. We identified 37,390 chromatin accessibility QTLs (caQTL) at 10% FDR across eight cell groups and observed extensive sharing of caQTLs across immune cell contexts, finding that fewer than 20% of caQTLs are specific to a single cell type. Notably, caQTLs colocalized with ∼50% more GWAS loci compared to eQTLs, helping to nominate putative causal genes for many unexplained loci. However, most GWAS-caQTL colocalizations had no detectable downstream regulatory effects on gene expression levels in the same cell type. We find evidence that the higher rates of colocalization between caQTLs and GWAS signals reflect missing disease-relevant cellular contexts among existing eQTL studies. Thus, there remains a pressing need for identifying disease-causing cellular contexts and for mapping gene regulatory variation in these cells.
Identifiers
What OpenQuestion holds
Registered trials
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.