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Article: Risk prediction of complex diseases from family history and known susceptibility loci, with applications for cancer screening

TitleRisk prediction of complex diseases from family history and known susceptibility loci, with applications for cancer screening
Authors
Issue Date2011
PublisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/
Citation
American Journal Of Human Genetics, 2011, v. 88 n. 5, p. 548-565 How to Cite?
AbstractRisk prediction based on genomic profiles has raised a lot of attention recently. However, family history is usually ignored in genetic risk prediction. In this study we proposed a statistical framework for risk prediction given an individual's genotype profile and family history. Genotype information about the relatives can also be incorporated. We allow risk prediction given the current age and follow-up period and consider competing risks of mortality. The framework allows easy extension to any family size and structure. In addition, the predicted risk at any percentile and the risk distribution graphs can be computed analytically. We applied the method to risk prediction for breast and prostate cancers by using known susceptibility loci from genome-wide association studies. For breast cancer, in the population the 10-year risk at age 50 ranged from 1.1% at the 5th percentile to 4.7% at the 95th percentile. If we consider the average 10-year risk at age 50 (2.39%) as the threshold for screening, the screening age ranged from 62 at the 20th percentile to 38 at the 95th percentile (and some never reach the threshold). For women with one affected first-degree relative, the 10-year risks ranged from 2.6% (at the 5th percentile) to 8.1% (at the 95th percentile). For prostate cancer, the corresponding 10-year risks at age 60 varied from 1.8% to 14.9% in the population and from 4.2% to 23.2% in those with an affected first-degree relative. We suggest that for some diseases genetic testing that incorporates family history can stratify people into diverse risk categories and might be useful in targeted prevention and screening. © 2011 The American Society of Human Genetics.
Persistent Identifierhttp://hdl.handle.net/10722/135396
ISSN
2015 Impact Factor: 10.794
2015 SCImago Journal Rankings: 8.769
PubMed Central ID
ISI Accession Number ID
Funding AgencyGrant Number
Hong Kong Research Grants CouncilHKU 766906M
HKU 774707M
European CommunityHEALTH-F2-2010-241909
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 (HKU 766906M and HKU 774707M), the European Community's Seventh Framework Programme under grant agreement No. HEALTH-F2-2010-241909 (Project EU-GEI), and the University of Hong Kong Strategic Research Theme of Genomics. H.-C.S. was supported by a Croucher Foundation Scholarship. The work was supported by the Hong Kong Research Grants Council General Research Fund.

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorSo, HCen_HK
dc.contributor.authorKwan, JSHen_HK
dc.contributor.authorCherny, SSen_HK
dc.contributor.authorSham, PCen_HK
dc.date.accessioned2011-07-27T01:34:43Z-
dc.date.available2011-07-27T01:34:43Z-
dc.date.issued2011en_HK
dc.identifier.citationAmerican Journal Of Human Genetics, 2011, v. 88 n. 5, p. 548-565en_HK
dc.identifier.issn0002-9297en_HK
dc.identifier.urihttp://hdl.handle.net/10722/135396-
dc.description.abstractRisk prediction based on genomic profiles has raised a lot of attention recently. However, family history is usually ignored in genetic risk prediction. In this study we proposed a statistical framework for risk prediction given an individual's genotype profile and family history. Genotype information about the relatives can also be incorporated. We allow risk prediction given the current age and follow-up period and consider competing risks of mortality. The framework allows easy extension to any family size and structure. In addition, the predicted risk at any percentile and the risk distribution graphs can be computed analytically. We applied the method to risk prediction for breast and prostate cancers by using known susceptibility loci from genome-wide association studies. For breast cancer, in the population the 10-year risk at age 50 ranged from 1.1% at the 5th percentile to 4.7% at the 95th percentile. If we consider the average 10-year risk at age 50 (2.39%) as the threshold for screening, the screening age ranged from 62 at the 20th percentile to 38 at the 95th percentile (and some never reach the threshold). For women with one affected first-degree relative, the 10-year risks ranged from 2.6% (at the 5th percentile) to 8.1% (at the 95th percentile). For prostate cancer, the corresponding 10-year risks at age 60 varied from 1.8% to 14.9% in the population and from 4.2% to 23.2% in those with an affected first-degree relative. We suggest that for some diseases genetic testing that incorporates family history can stratify people into diverse risk categories and might be useful in targeted prevention and screening. © 2011 The American Society of Human Genetics.en_HK
dc.languageengen_US
dc.publisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/en_HK
dc.relation.ispartofAmerican Journal of Human Geneticsen_HK
dc.subject.meshBreast Neoplasms - diagnosis - genetics-
dc.subject.meshEarly Detection of Cancer-
dc.subject.meshGenetic Association Studies-
dc.subject.meshGenetic Predisposition to Disease-
dc.subject.meshProstatic Neoplasms - diagnosis - genetics-
dc.titleRisk prediction of complex diseases from family history and known susceptibility loci, with applications for cancer screeningen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0002-9297&volume=88&issue=5&spage=548&epage=565&date=2011&atitle=Risk+prediction+of+complex+diseases+from+family+history+and+known+susceptibility+loci,+with+applications+for+cancer+screening+-
dc.identifier.emailCherny, SS: cherny@hku.hken_HK
dc.identifier.emailSham, PC: pcsham@hku.hken_HK
dc.identifier.authorityCherny, SS=rp00232en_HK
dc.identifier.authoritySham, PC=rp00459en_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1016/j.ajhg.2011.04.001en_HK
dc.identifier.pmid21529750-
dc.identifier.pmcidPMC3146722-
dc.identifier.scopuseid_2-s2.0-79955824808en_HK
dc.identifier.hkuros186060en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79955824808&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume88en_HK
dc.identifier.issue5en_HK
dc.identifier.spage548en_HK
dc.identifier.epage565en_HK
dc.identifier.eissn1537-6605-
dc.identifier.isiWOS:000290832100003-
dc.publisher.placeUnited Statesen_HK
dc.relation.projectGenome-wide association study of schizophrenia-
dc.identifier.scopusauthoridSo, HC=37031934700en_HK
dc.identifier.scopusauthoridKwan, JSH=37063349600en_HK
dc.identifier.scopusauthoridCherny, SS=7004670001en_HK
dc.identifier.scopusauthoridSham, PC=34573429300en_HK
dc.identifier.citeulike9253980-

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