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Article: Effect size measures in genetic association studies and age-conditional risk prediction

TitleEffect size measures in genetic association studies and age-conditional risk prediction
Authors
KeywordsAssociation study
Competing risks
Genetic counseling
Genetic risk prediction
Hazard ratio
Odds ratio
Relative risk
Issue Date2010
PublisherS Karger AG. The Journal's web site is located at http://www.karger.com/HHE
Citation
Human Heredity, 2010, v. 70 n. 3, p. 205-218 How to Cite?
AbstractThe interest in risk prediction using genomic profiles has surged recently. A proper interpretation of effect size measures in association studies is crucial to accurate risk prediction. In this study, we clarified the relationship between the odds ratio (OR), relative risk and incidence rate ratios in the context of genetic association studies. We demonstrated that under the common practice of sampling prevalent cases and controls, the resulting ORs approximate the incidence rate ratios. Based on this result, we presented a framework to compute the disease risk given the current age and follow-up period (including lifetime risk), with consideration of competing risks of mortality. We considered two extensions. One is correcting the incidence rate to reflect the person-years alive and disease-free, the other is converting prevalence to incidence estimates. The methodology was applied to an example of breast cancer prediction. We observed that simply multiplying the OR by the average lifetime risk estimates yielded a final estimate >100% (101%), while using our method that accounts for competing risks produces an estimate of 63% only. We also applied the method to risk prediction of Alzheimer's disease in Hong Kong. We recommend that companies offering direct-to-consumer genetic testing employ more rigorous prediction algorithms considering competing risks. © 2010 S. Karger AG, Basel.
Persistent Identifierhttp://hdl.handle.net/10722/137516
ISSN
2015 Impact Factor: 1.539
2015 SCImago Journal Rankings: 0.942
ISI Accession Number ID
Funding AgencyGrant Number
Hong Kong Research Grants CouncilHKU 766906M
HKU 774707M
University of Hong Kong Strategic Research Theme of Genomics
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. H.-C.S. was supported by a Croucher Foundation Scholarship.

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorSo, HCen_HK
dc.contributor.authorSham, PCen_HK
dc.date.accessioned2011-08-26T14:26:53Z-
dc.date.available2011-08-26T14:26:53Z-
dc.date.issued2010en_HK
dc.identifier.citationHuman Heredity, 2010, v. 70 n. 3, p. 205-218en_HK
dc.identifier.issn0001-5652en_HK
dc.identifier.urihttp://hdl.handle.net/10722/137516-
dc.description.abstractThe interest in risk prediction using genomic profiles has surged recently. A proper interpretation of effect size measures in association studies is crucial to accurate risk prediction. In this study, we clarified the relationship between the odds ratio (OR), relative risk and incidence rate ratios in the context of genetic association studies. We demonstrated that under the common practice of sampling prevalent cases and controls, the resulting ORs approximate the incidence rate ratios. Based on this result, we presented a framework to compute the disease risk given the current age and follow-up period (including lifetime risk), with consideration of competing risks of mortality. We considered two extensions. One is correcting the incidence rate to reflect the person-years alive and disease-free, the other is converting prevalence to incidence estimates. The methodology was applied to an example of breast cancer prediction. We observed that simply multiplying the OR by the average lifetime risk estimates yielded a final estimate >100% (101%), while using our method that accounts for competing risks produces an estimate of 63% only. We also applied the method to risk prediction of Alzheimer's disease in Hong Kong. We recommend that companies offering direct-to-consumer genetic testing employ more rigorous prediction algorithms considering competing risks. © 2010 S. Karger AG, Basel.en_HK
dc.languageengen_US
dc.publisherS Karger AG. The Journal's web site is located at http://www.karger.com/HHEen_HK
dc.relation.ispartofHuman Heredityen_HK
dc.rightsHuman Heredity. Copyright © S Karger AG.-
dc.subjectAssociation studyen_HK
dc.subjectCompeting risksen_HK
dc.subjectGenetic counselingen_HK
dc.subjectGenetic risk predictionen_HK
dc.subjectHazard ratioen_HK
dc.subjectOdds ratioen_HK
dc.subjectRelative risken_HK
dc.subject.meshGenetic Association Studies-
dc.subject.meshGenetic Counseling-
dc.subject.meshGenetic Testing-
dc.subject.meshOdds Ratio-
dc.subject.meshRisk Assessment - methods-
dc.titleEffect size measures in genetic association studies and age-conditional risk predictionen_HK
dc.typeArticleen_HK
dc.identifier.emailSham, PC: pcsham@hku.hken_HK
dc.identifier.authoritySham, PC=rp00459en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1159/000319192en_HK
dc.identifier.pmid20838054-
dc.identifier.scopuseid_2-s2.0-77956467624en_HK
dc.identifier.hkuros189824en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77956467624&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume70en_HK
dc.identifier.issue3en_HK
dc.identifier.spage205en_HK
dc.identifier.epage218en_HK
dc.identifier.isiWOS:000283613000005-
dc.publisher.placeSwitzerlanden_HK
dc.relation.projectGenome-wide association study of schizophrenia-
dc.identifier.scopusauthoridSo, HC=37031934700en_HK
dc.identifier.scopusauthoridSham, PC=34573429300en_HK
dc.identifier.citeulike8125509-

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