| Title: | Fine-mapping causal tissues and genes at disease-associated loci |
| Journal: | Nature Genetics |
| Published: | 2 Jan 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39747598/ |
| DOI: | https://doi.org/10.1038/s41588-024-01994-2 |
| URL: | https://doi.org/10.1101/2023.11.01.23297909 |
Publication 14575
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Abstract
Complex diseases often have distinct mechanisms spanning multiple tissues. We propose tissue-gene fine-mapping (TGFM), which infers the posterior inclusion probability (PIP) for each gene-tissue pair to mediate a disease locus by analyzing summary statistics and expression quantitative trait loci (eQTL) data; TGFM also assigns PIPs to non-mediated variants. TGFM accounts for co-regulation across genes and tissues and models uncertainty in cis-predicted expression models, enabling correct calibration. We applied TGFM to 45 UK Biobank diseases or traits using eQTL data from 38 Genotype-Tissue Expression (GTEx) tissues. TGFM identified an average of 147 PIP > 0.5 causal genetic elements per disease or trait, of which 11% were gene-tissue pairs. Causal gene-tissue pairs identified by TGFM reflected both known biology (for example, TPO-thyroid for hypothyroidism) and biologically plausible findings (for example, SLC20A2-artery aorta for diastolic blood pressure). Application of TGFM to single-cell eQTL data from nine cell types in peripheral blood mononuclear cells (PBMCs), analyzed jointly with GTEx tissues, identified 30 additional causal gene-PBMC cell type pairs.</p>
9 Keywords
- Chromosome Mapping
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Genotype
- Humans
- Leukocytes, Mononuclear
- Organ Specificity
- Polymorphism, Single Nucleotide
- Quantitative Trait Loci
5 Authors
- Benjamin J. Strober
- Martin Jinye Zhang
- Tiffany Amariuta
- Jordan Rossen
- Alkes L. Price
1 Application
| Application ID | Title |
|---|---|
| 16549 | Components of heritability in a UK Biobank cohort |
Enabling scientific discoveries that improve human health