ArticleNature genetics2017
Estimating the causal tissues for complex traits and diseases.
Article in Nature genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 130 papers, 5 of them syntheses that pooled it.
What it found
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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.
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Who cites it
130 citing papers in PubMed, 5 syntheses or guidelines pooled it, 240 citations in OpenAlex.
- Analysis of genetically determined gene expression suggests role of inflammatory processes in exfoliation syndrome.BMC genomics · 2023Pooled it
- Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets.Nature communications · 2021Pooled it
- Prioritization of causal genes for coronary artery disease based on cumulative evidence from experimental and in silico studies.Scientific reports · 2020Pooled it
- A Review of Statistical Methods for Identifying Trait-Relevant Tissues and Cell Types.Frontiers in genetics · 2020Pooled it
- Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation.Nature genetics · 2018Pooled it
- Identifying independent causal cell types for human diseases and risk variants.Cell genomics · 2026Article
- A long-read human pangenome initiative for comprehensive interpretation of nuclear-embedded mitochondrial DNA.Nature communications · 2026Article
- Integrating genetically predicted transcriptomic signatures with longitudinal real-world data enables scalable drug repurposing for Alzheimer's disease.Research square · 2026Article
- Integrated mapping of human meniscus and cartilage eQTLs reveals shared and distinct osteoarthritis genetic drivers.medRxiv : the preprint server for health sciences · 2026Article
- The genetic basis for DNA methylation variation across tissues and development.Nature communications · 2026Article
- eQTL in diseased colon tissue identifies potential target genes associated with IBD.Nature communications · 2026Article
- Expanded chromatin accessibility mapping explains genetic variation associated with complex traits in liver.American journal of human genetics · 2026Article
- Farm animal evolution demonstrates hidden molecular basis of human traits.bioRxiv : the preprint server for biology · 2026Article
- L3MBTL2 as a novel therapeutic target for trigeminal neuralgia: evidence from integrated TWAS, multi-tissue MR, and experimental validation.The journal of headache and pain · 2025Article
- GWAS-informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density.Genome biology · 2025Article
- Expanded Chromatin Accessibility Mapping Explains Genetic Variation Associated with Complex Traits in Liver.medRxiv : the preprint server for health sciences · 2025Article
- Uncovering causal gene-tissue pairs and variants through a multivariate TWAS controlling for infinitesimal effects.Nature communications · 2025Article
- Integrating microbial GWAS and single-cell transcriptomics reveals associations between host cell populations and the gut microbiome.Nature microbiology · 2025Article
- Multi-INTACT: integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits.Genome biology · 2025Article
- Fine-mapping causal tissues and genes at disease-associated loci.Nature genetics · 2025Article
70 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
How to interpret the biological causes underlying the predisposing markers identified through genome-wide association studies (GWAS) remains an open question. One direct and powerful way to assess the genetic causality behind GWAS is through analysis of expression quantitative trait loci (eQTLs). Here we describe a new approach to estimate the tissues behind the genetic causality of a variety of GWAS traits, using the cis-eQTLs in 44 tissues from the Genotype-Tissue Expression (GTEx) Consortium. We have adapted the regulatory trait concordance (RTC) score to measure the probability of eQTLs being active in multiple tissues and to calculate the probability that a GWAS-associated variant and an eQTL tag the same functional effect. By normalizing the GWAS-eQTL probabilities by the tissue-sharing estimates for eQTLs, we generate relative tissue-causality profiles for GWAS traits. Our approach not only implicates the gene likely mediating individual GWAS signals, but also highlights tissues where the genetic causality for an individual trait is likely manifested.
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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.