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Article: Uncovering the total heritability explained by all true susceptibility variants in a genome-wide association study

TitleUncovering the total heritability explained by all true susceptibility variants in a genome-wide association study
Authors
KeywordsAssociation study
Common variants
Genetic architecture
Issue Date2011
PublisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841
Citation
Genetic Epidemiology, 2011, v. 35 n. 6, p. 447-456 How to Cite?
AbstractGenome-wide association studies (GWAS) have become increasingly popular recently and contributed to the discovery of many susceptibility variants. However, a large proportion of the heritability still remained unexplained. This observation raises queries regarding the ability of GWAS to uncover the genetic basis of complex diseases. In this study, we propose a simple and fast statistical framework to estimate the total heritability explained by all true susceptibility variants in a GWAS. It is expected that many true risk variants will not be detected in a GWAS due to limited power. The proposed framework aims at recovering the "hidden" heritability. Importantly, only the summary z-statistics are required as input and no raw genotype data are needed. The strategy is to recover the true effect sizes from the observed z-statistics. The methodology does not rely on any distributional assumptions of the effect sizes of variants. Both binary and quantitative traits can be handled and covariates may be included. Population-based or family-based designs are allowed as long as the summary statistics are available. Simulations were conducted and showed satisfactory performance of the proposed approach. Application to real data (Crohn's disease, HDL, LDL, and triglycerides) reveals that at least around 10-20% of variance in liability or phenotype can be explained by GWAS panels. This translates to around 10-40% of the total heritability for the studied traits. © 2011 Wiley-Liss, Inc.
Persistent Identifierhttp://hdl.handle.net/10722/135398
ISSN
2015 Impact Factor: 2.553
2015 SCImago Journal Rankings: 2.101
ISI Accession Number ID
Funding AgencyGrant Number
Hong Kong Research Grants CouncilHKU 766906M
HKU 774707M
University of Hong Kong
Croucher Foundation
Funding Information:

The work was supported by the Hong Kong Research Grants Council General Research Fund grants HKU 766906M and HKU 774707M and the University of Hong Kong Strategic Research Theme of Genomics. HCS was supported by a Croucher Foundation Scholarship.

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorSo, HCen_HK
dc.contributor.authorLi, Men_HK
dc.contributor.authorSham, PCen_HK
dc.date.accessioned2011-07-27T01:34:44Z-
dc.date.available2011-07-27T01:34:44Z-
dc.date.issued2011en_HK
dc.identifier.citationGenetic Epidemiology, 2011, v. 35 n. 6, p. 447-456en_HK
dc.identifier.issn0741-0395en_HK
dc.identifier.urihttp://hdl.handle.net/10722/135398-
dc.description.abstractGenome-wide association studies (GWAS) have become increasingly popular recently and contributed to the discovery of many susceptibility variants. However, a large proportion of the heritability still remained unexplained. This observation raises queries regarding the ability of GWAS to uncover the genetic basis of complex diseases. In this study, we propose a simple and fast statistical framework to estimate the total heritability explained by all true susceptibility variants in a GWAS. It is expected that many true risk variants will not be detected in a GWAS due to limited power. The proposed framework aims at recovering the "hidden" heritability. Importantly, only the summary z-statistics are required as input and no raw genotype data are needed. The strategy is to recover the true effect sizes from the observed z-statistics. The methodology does not rely on any distributional assumptions of the effect sizes of variants. Both binary and quantitative traits can be handled and covariates may be included. Population-based or family-based designs are allowed as long as the summary statistics are available. Simulations were conducted and showed satisfactory performance of the proposed approach. Application to real data (Crohn's disease, HDL, LDL, and triglycerides) reveals that at least around 10-20% of variance in liability or phenotype can be explained by GWAS panels. This translates to around 10-40% of the total heritability for the studied traits. © 2011 Wiley-Liss, Inc.en_HK
dc.languageengen_US
dc.publisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841en_HK
dc.relation.ispartofGenetic Epidemiologyen_HK
dc.rightsGenetic Epidemiology. Copyright © John Wiley & Sons, Inc.-
dc.subjectAssociation studyen_HK
dc.subjectCommon variantsen_HK
dc.subjectGenetic architectureen_HK
dc.subject.meshComputer Simulation-
dc.subject.meshCrohn Disease - genetics-
dc.subject.meshGenetic Predisposition to Disease-
dc.subject.meshGenetic Variation-
dc.subject.meshGenome-Wide Association Study-
dc.titleUncovering the total heritability explained by all true susceptibility variants in a genome-wide association studyen_HK
dc.typeArticleen_HK
dc.identifier.emailLi, M: mxli@hku.hken_HK
dc.identifier.emailSham, PC: pcsham@hku.hken_HK
dc.identifier.authorityLi, M=rp01722en_HK
dc.identifier.authoritySham, PC=rp00459en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/gepi.20593en_HK
dc.identifier.pmid21618601-
dc.identifier.scopuseid_2-s2.0-80051807776en_HK
dc.identifier.hkuros186076en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80051807776&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume35en_HK
dc.identifier.issue6en_HK
dc.identifier.spage447en_HK
dc.identifier.epage456en_HK
dc.identifier.isiWOS:000294177900003-
dc.publisher.placeUnited Statesen_HK
dc.relation.projectGenome-wide association study of schizophrenia-
dc.identifier.scopusauthoridSo, HC=37031934700en_HK
dc.identifier.scopusauthoridLi, M=17135391100en_HK
dc.identifier.scopusauthoridSham, PC=34573429300en_HK
dc.identifier.citeulike9351147-

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