Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enri...

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Bibliographic Details
Published in:Nature genetics Vol. 50; no. 4; pp. 621 - 629
Main Authors: Finucane, Hilary K., Reshef, Yakir A., Anttila, Verneri, Slowikowski, Kamil, Gusev, Alexander, Byrnes, Andrea, Gazal, Steven, Loh, Po-Ru, Lareau, Caleb, Shoresh, Noam, Genovese, Giulio, Saunders, Arpiar, Macosko, Evan, Pollack, Samuela, Perry, John R. B., Buenrostro, Jason D., Bernstein, Bradley E., Raychaudhuri, Soumya, McCarroll, Steven, Neale, Benjamin M., Price, Alkes L.
Format: Journal Article
Language:English
Published: New York Nature Publishing Group US 01.04.2018
Nature Publishing Group
Subjects:
631/114
631/208/199
631/208/205/2138
Agriculture
Alzheimer's disease
Analysis
Animal Genetics and Genomics
Annotations
Biochemistry
Biomedical and Life Sciences
Biomedicine
Bipolar disorder
Bipolar Disorder - genetics
Body Mass Index
Body size
Brain
Brain - metabolism
Cancer Research
Chromatin - genetics
Datasets
Enrichment
Epigenesis, Genetic
Gene Expression
Gene Expression Profiling - statistics & numerical data
Gene Function
Genes
Genetic Predisposition to Disease
Genome-wide association studies
Genome-Wide Association Study - statistics & numerical data
Genomes
Genomics
Heritability
Human Genetics
Humans
Immune System Diseases - genetics
Linkage Disequilibrium
Mental disorders
Metabolism
Models, Genetic
Multifactorial Inheritance
Neurons
Neurons - metabolism
Polygenic inheritance
Regression analysis
Schizophrenia
Schizophrenia - genetics
Statistical analysis
Statistical tests
Statistics
Tissue Distribution - genetics
Tissues
Tourette syndrome
Type 2 diabetes
ISSN:1061-4036, 1546-1718, 1546-1718
Online Access:Get full text
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Summary:We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We applied our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N  = 169,331) and found significant tissue-specific enrichments (false discovery rate (FDR) < 5%) for 34 traits. In our analysis of multiple tissues, we detected a broad range of enrichments that recapitulated known biology. In our brain-specific analysis, significant enrichments included an enrichment of inhibitory over excitatory neurons for bipolar disorder, and excitatory over inhibitory neurons for schizophrenia and body mass index. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signals. A new method tests whether disease heritability is enriched near genes with high tissue-specific expression. The authors use gene expression data together with GWAS summary statistics for 48 diseases and traits to identify disease-relevant tissues.
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ISSN:1061-4036
1546-1718
1546-1718
DOI:10.1038/s41588-018-0081-4