ArticleNature genetics2023
Modeling tissue co-regulation estimates tissue-specific contributions to disease.
Article in Nature genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Prioritizing context-specific genetic risk mechanisms in 11 solid cancers.Journal of the National Cancer Institute · 2026Article
- Identifying independent causal cell types for human diseases and risk variants.Cell genomics · 2026Article
- When can whole-genome SNP heritability be reliably estimated from summary statistics?bioRxiv : the preprint server for biology · 2026Article
- Functionally informed cis and trans proteome-wide association studies prioritize disease-critical genes.Research square · 2026Article
- Functionally informed cis and trans proteome-wide association studies prioritize disease-critical genes.medRxiv : the preprint server for health sciences · 2026Article
- Multi-ancestry genome-wide association study in all of Us for primary open-angle glaucoma.Scientific reports · 2026Article
- Prioritizing context-specific genetic risk mechanisms in 11 solid cancers.medRxiv : the preprint server for health sciences · 2025Article
- Multi-Ancestry Genome-Wide Association Study in All of Us for Primary Open- Angle Glaucoma.Research square · 2025Article
- GWAS-informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density.Genome biology · 2025Article
- Knockoff procedure improves susceptibility gene identifications in conditional transcriptome-wide association studies.American journal of human genetics · 2025Article
- Integrative Genomics Refines Tissues, Candidate Genes and Putative Regulatory Links Involved in the Humic Adaptation of Keystone Freshwater Fish.Molecular ecology · 2025Article
- Uncovering causal gene-tissue pairs and variants through a multivariate TWAS controlling for infinitesimal effects.Nature communications · 2025Article
- Distinct pathway-based effects of blood pressure and body mass index on cardiovascular traits: comparison of novel Mendelian randomization approaches.Genome medicine · 2025Article
- Variant-to-function approaches for adipose tissue: Insights into cardiometabolic disorders.Cell genomics · 2025Review
- Article
- Integrating genetics and transcriptomics to characterize shared mechanisms in digestive diseases and psychiatric disorders.Communications biology · 2025Article
- Fine-mapping causal tissues and genes at disease-associated loci.Nature genetics · 2025Article
- Integrating multi-layered biological priors to improve genomic prediction accuracy in beef cattle.Biology direct · 2024Article
- GWAS-Informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density.bioRxiv : the preprint server for biology · 2024Article
- Uncovering causal gene-tissue pairs and variants: A multivariable TWAS method controlling for infinitesimal effects.medRxiv : the preprint server for health sciences · 2024Article
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3 authors.
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Abstract
Integrative analyses of genome-wide association studies and gene expression data have implicated many disease-critical tissues. However, co-regulation of genetic effects on gene expression across tissues impedes distinguishing biologically causal tissues from tagging tissues. In the present study, we introduce tissue co-regulation score regression (TCSC), which disentangles causal tissues from tagging tissues by regressing gene-disease association statistics (from transcriptome-wide association studies) on tissue co-regulation scores, reflecting correlations of predicted gene expression across genes and tissues. We applied TCSC to 78 diseases/traits (average n = 302,000) and gene expression prediction models for 48 GTEx tissues. TCSC identified 21 causal tissue-trait pairs at a 5% false discovery rate (FDR), including well-established findings, biologically plausible new findings (for example, aorta artery and glaucoma) and increased specificity of known tissue-trait associations (for example, subcutaneous adipose, but not visceral adipose, and high-density lipoprotein). TCSC also identified 17 causal tissue-trait covariance pairs at 5% FDR. In conclusion, TCSC is a precise method for distinguishing causal tissues from tagging tissues.
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