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Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation
- Source :
- Nature Genetics, Vol. 50, No 7 (2018) pp. 956-967, PMC, Nature genetics
- Publication Year :
- 2018
-
Abstract
- We apply integrative approaches to expression quantitative loci (eQTLs) from 44 tissues from the Genotype-Tissue Expression project and genome-wide association study data. About 60% of known trait-associated loci are in linkage disequilibrium with a cis-eQTL, over half of which were not found in previous large-scale whole blood studies. Applying polygenic analyses to metabolic, cardiovascular, anthropometric, autoimmune, and neurodegenerative traits, we find that eQTLs are significantly enriched for trait associations in relevant pathogenic tissues and explain a substantial proportion of the heritability (40-80%). For most traits, tissue-shared eQTLs underlie a greater proportion of trait associations, although tissue-specific eQTLs have a greater contribution to some traits, such as blood pressure. By integrating information from biological pathways with eQTL target genes and applying a gene-based approach, we validate previously implicated causal genes and pathways, and propose new variant and gene associations for several complex traits, which we replicate in the UK BioBank and BioVU.<br />National Institutes of Health (U.S.) (Contract HHSN268201000029C)
- Subjects :
- 0301 basic medicine
Linkage disequilibrium
Genotype
ddc:025.063/570
Quantitative Trait Loci
Gene Expression
Genome-wide association study
Biology
Quantitative trait locus
Polymorphism, Single Nucleotide
Article
03 medical and health sciences
Quantitative Trait, Heritable
ddc:590
Genetics
Humans
Disease
ddc:576.5
Regulation of gene expression
Gene Expression Profiling
Heritability
3. Good health
Phenotype
030104 developmental biology
Gene Expression Regulation
Expression quantitative trait loci
Trait
Functional genomics
Genome-Wide Association Study
Subjects
Details
- Language :
- English
- ISSN :
- 15461718 and 10614036
- Volume :
- 50
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- Nature Genetics
- Accession number :
- edsair.doi.dedup.....8a81614cea735accd1872429b0e0ca84