Partitioning heritability by functional annotation using genome-wide association summary statistics

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Abstract

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many cell-type-specific enrichments including significant enrichment of central nervous system cell types in body mass index, age at menarche, educational attainment, and smoking behavior.

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An Integrated Encyclopedia of DNA Elements in the Human Genome

Iakes Ezkurdia (2016)

Summary The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure, and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall the project provides new insights into the organization and regulation of our genes and genome, and an expansive resource of functional annotations for biomedical research.

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GCTA: a tool for genome-wide complex trait analysis.

Jian Yang, S. Lee, Michael E Goddard … (2011)

For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the "missing heritability" problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.

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The Human Genome Browser at UCSC

a. Haussler, W. J. Kent, C. Sugnet … (2002)

As vertebrate genome sequences near completion and research refocuses to their analysis, the issue of effective genome annotation display becomes critical. A mature web tool for rapid and reliable display of any requested portion of the genome at any scale, together with several dozen aligned annotation tracks, is provided at http://genome.ucsc.edu. This browser displays assembly contigs and gaps, mRNA and expressed sequence tag alignments, multiple gene predictions, cross-species homologies, single nucleotide polymorphisms, sequence-tagged sites, radiation hybrid data, transposon repeats, and more as a stack of coregistered tracks. Text and sequence-based searches provide quick and precise access to any region of specific interest. Secondary links from individual features lead to sequence details and supplementary off-site databases. One-half of the annotation tracks are computed at the University of California, Santa Cruz from publicly available sequence data; collaborators worldwide provide the rest. Users can stably add their own custom tracks to the browser for educational or research purposes. The conceptual and technical framework of the browser, its underlying MYSQL database, and overall use are described. The web site currently serves over 50,000 pages per day to over 3000 different users.

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Author and article information

Journal

Journal ID (nlm-journal-id): 9216904

Journal ID (pubmed-jr-id): 2419

Journal ID (nlm-ta): Nat Genet

Journal ID (iso-abbrev): Nat. Genet.

Title: Nature genetics

ISSN (Print): 1061-4036

ISSN (Electronic): 1546-1718

Publication date Nihms-submitted: 11 September 2015

Publication date (Electronic): 28 September 2015

Publication date (Print): November 2015

Publication date PMC-release: 01 May 2016

Volume: 47

Issue: 11

Pages: 1228-1235

Affiliations

[1 ]Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

[2 ]Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA

[3 ]Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

[4 ]Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

[5 ]Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA

[6 ]Division of Rheumatology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA

[7 ]Partners Center for Personalized Genetic Medicine, Boston, Massachusetts, USA

[8 ]Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

[9 ]Department of Computer Science, Harvard University, Massachusetts, USA

[10 ]Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA

[11 ]Epigenomics Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

[12 ]MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK

[14 ]The Department of Psychiatry at Mount Sinai School of Medicine, New York, New York, USA

[15 ]Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo 113-8510, Japan

[16 ]Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan

[17 ]Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK

[21 ]Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SA, UK

Author notes

[20 ]Correspondence should be addressed to H.K.F. ( hilaryf@ 123456mit.edu ) B.B.S. ( bulik@ 123456broadinstitute.org ), B.M.N. ( bneale@ 123456broadinstitute.org ) or A.L.P. ( aprice@ 123456hsph.harvard.edu )

[13]

A full list of consortium members appears in the Supplementary Note.

[18]

Co-first authors.

[19]

Co-last authors.

Article

Manuscript ID: NIHMS718020

DOI: 10.1038/ng.3404

PMC ID: 4626285

PubMed ID: 26414678

SO-VID: 676cba6b-68b3-4a2d-9c38-98b07372c79b

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Partitioning heritability by functional annotation using genome-wide association summary statistics

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Most cited references 54

An Integrated Encyclopedia of DNA Elements in the Human Genome

GCTA: a tool for genome-wide complex trait analysis.

The Human Genome Browser at UCSC

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