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Article: Risk prediction of complex diseases from family history and known susceptibility loci, with applications for cancer screening
Title | Risk prediction of complex diseases from family history and known susceptibility loci, with applications for cancer screening | ||||||||||
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Authors | |||||||||||
Issue Date | 2011 | ||||||||||
Publisher | Cell 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? | ||||||||||
Abstract | Risk 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 Identifier | http://hdl.handle.net/10722/135396 | ||||||||||
ISSN | 2023 Impact Factor: 8.1 2023 SCImago Journal Rankings: 4.516 | ||||||||||
PubMed Central ID | |||||||||||
ISI Accession Number ID |
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 Field | Value | Language |
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dc.contributor.author | So, HC | en_HK |
dc.contributor.author | Kwan, JSH | en_HK |
dc.contributor.author | Cherny, SS | en_HK |
dc.contributor.author | Sham, PC | en_HK |
dc.date.accessioned | 2011-07-27T01:34:43Z | - |
dc.date.available | 2011-07-27T01:34:43Z | - |
dc.date.issued | 2011 | en_HK |
dc.identifier.citation | American Journal Of Human Genetics, 2011, v. 88 n. 5, p. 548-565 | en_HK |
dc.identifier.issn | 0002-9297 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/135396 | - |
dc.description.abstract | Risk 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.language | eng | en_US |
dc.publisher | Cell Press. The Journal's web site is located at http://www.cell.com/AJHG/ | en_HK |
dc.relation.ispartof | American Journal of Human Genetics | en_HK |
dc.subject.mesh | Breast Neoplasms - diagnosis - genetics | - |
dc.subject.mesh | Early Detection of Cancer | - |
dc.subject.mesh | Genetic Association Studies | - |
dc.subject.mesh | Genetic Predisposition to Disease | - |
dc.subject.mesh | Prostatic Neoplasms - diagnosis - genetics | - |
dc.title | Risk prediction of complex diseases from family history and known susceptibility loci, with applications for cancer screening | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://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.email | Cherny, SS: cherny@hku.hk | en_HK |
dc.identifier.email | Sham, PC: pcsham@hku.hk | en_HK |
dc.identifier.authority | Cherny, SS=rp00232 | en_HK |
dc.identifier.authority | Sham, PC=rp00459 | en_HK |
dc.description.nature | link_to_OA_fulltext | - |
dc.identifier.doi | 10.1016/j.ajhg.2011.04.001 | en_HK |
dc.identifier.pmid | 21529750 | - |
dc.identifier.pmcid | PMC3146722 | - |
dc.identifier.scopus | eid_2-s2.0-79955824808 | en_HK |
dc.identifier.hkuros | 186060 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-79955824808&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 88 | en_HK |
dc.identifier.issue | 5 | en_HK |
dc.identifier.spage | 548 | en_HK |
dc.identifier.epage | 565 | en_HK |
dc.identifier.eissn | 1537-6605 | - |
dc.identifier.isi | WOS:000290832100003 | - |
dc.publisher.place | United States | en_HK |
dc.relation.project | Genome-wide association study of schizophrenia | - |
dc.identifier.scopusauthorid | So, HC=37031934700 | en_HK |
dc.identifier.scopusauthorid | Kwan, JSH=37063349600 | en_HK |
dc.identifier.scopusauthorid | Cherny, SS=7004670001 | en_HK |
dc.identifier.scopusauthorid | Sham, PC=34573429300 | en_HK |
dc.identifier.citeulike | 9253980 | - |
dc.identifier.issnl | 0002-9297 | - |