The missing link between genetic association and regulatory function
- Harvard Medical School, United States
- Harvard TH Chan School of Public Health, United States
- Altius Institute for Biomedical Sciences, United States
- Boston Children's Hospital, United States
- Broad Institute, United States
- Brigham and Women's Hospital, United States
Abstract
The genetic basis of most traits is highly polygenic and dominated by non-coding alleles. It is widely assumed that such alleles exert small regulatory effects on the expression of cis-linked genes. However, despite the availability of gene expression and epigenomic data sets, few variant-to-gene links have emerged. It is unclear whether these sparse results are due to limitations in available data and methods, or to deficiencies in the underlying assumed model. To better distinguish between these possibilities, we identified 220 gene-trait pairs in which protein-coding variants influence a complex trait or its Mendelian cognate. Despite the presence of expression quantitative trait loci near most GWAS associations, by applying a gene-based approach we found limited evidence that the baseline expression of trait-related genes explains GWAS associations, whether using colocalization methods (8% of genes implicated), transcription-wide association (2% of genes implicated), or a combination of regulatory annotations and distance (4% of genes implicated). These results contradict the hypothesis that most complex trait-associated variants coincide with homeostatic eQTLs, suggesting that better models are needed. The field must confront this deficit, and pursue this 'missing regulation'.
Data availability
Numerical data for results is included in Source Data 1.The dataset generated (GWAS summary statistics conditioned on coding variants) can be found at doi:10.5061/dryad.612jm644q
-
GWAS results conditioned on coding variantsDryad Digital Repository, doi:10.5061/dryad.612jm644q.
-
NHLBI TOPMedhttps://www.nhlbiwgs.org/topmed-whole-genome-sequencing-project-freeze-5b-phases-1-and-2.
Article and author information
Author details
Noah James Connally
Funding
National Institutes of Health (R35GM127131)
- Shamil R Sunyaev
National Institutes of Health (R01HG010372)
- Shamil R Sunyaev
National Institutes of Health (R01MH101244)
- Shamil R Sunyaev
National Institutes of Health (U01HG012009)
- Chris Cotsapas
National Institutes of Health (T32GM74897)
- Shamil R Sunyaev
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Connally et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 7,180
- views
-
- 1,070
- downloads
-
- 102
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
The missing link between genetic association and regulatory function
eLife 11:e74970.
https://doi.org/10.7554/eLife.74970
