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Genetic Structures of Population Cohorts Change with Increasing Age: Implications for Genetic Analyses of Human aging and Life Span.

dc.contributor.author Akushevich, Igor
dc.contributor.author Arbeev, Konstantin
dc.contributor.author Arbeeva, LS
dc.contributor.author Culminskaya, IV
dc.contributor.author Kulminski, Alexander
dc.contributor.author Stallard, Eric
dc.contributor.author Ukraintseva, Svetlana
dc.contributor.author Wu, D
dc.contributor.author Yashin, Anatoli I
dc.coverage.spatial United States
dc.date.accessioned 2017-06-02T18:22:14Z
dc.date.available 2017-06-02T18:22:14Z
dc.date.issued 2017-06-02
dc.identifier https://www.ncbi.nlm.nih.gov/pubmed/25893220
dc.identifier.uri http://hdl.handle.net/10161/14761
dc.description.abstract BACKGROUND: Correcting for the potential effects of population stratification is an important issue in genome wide association studies (GWAS) of complex traits. Principal component analysis (PCA) of the genetic structure of the population under study with subsequent incorporation of the first several principal components (PCs) in the GWAS regression model is often used for this purpose. PROBLEM: For longevity related traits such a correction may negatively affect the accuracy of genetic analyses. This is because PCs may capture genetic structure induced by mortality selection processes in genetically heterogeneous populations. DATA AND METHODS: We used the Framingham Heart Study data on life span and on individual genetic background to construct two sets of PCs. One was constructed to separate population stratification due to differences in ancestry from that induced by mortality selection. The other was constructed using genetic data on individuals of different ages without attempting to separate the ancestry effects from the mortality selection effects. The GWASs of human life span were performed using the first 20 PCs from each of the selected sets to control for possible population stratification. RESULTS: The results indicated that the GWAS that used the PC set separating population stratification induced by mortality selection from differences in ancestry produced stronger genetic signals than the GWAS that used PCs without such separation. CONCLUSION: The quality of genetic estimates in GWAS can be improved when changes in genetic structure caused by mortality selection are taken into account in controlling for possible effects of population stratification.
dc.language eng
dc.relation.ispartof Ann Gerontol Geriatr Res
dc.subject Genetic associations
dc.subject Genetic structure
dc.subject Genetics of aging
dc.subject Heterogeneous population
dc.subject Longevity
dc.subject Mortality selection
dc.subject Principal component analysis
dc.title Genetic Structures of Population Cohorts Change with Increasing Age: Implications for Genetic Analyses of Human aging and Life Span.
dc.type Journal article
pubs.author-url https://www.ncbi.nlm.nih.gov/pubmed/25893220
pubs.issue 4
pubs.organisational-group Center for Population Health & Aging
pubs.organisational-group Duke
pubs.organisational-group Duke Population Research Institute
pubs.organisational-group Sanford School of Public Policy
pubs.organisational-group Staff
pubs.publication-status Published
pubs.volume 1


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