Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals (CROSBI ID 318011)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Okbay, Aysu ; Wu, Yeda ; Wang, Nancy ; Jayashankar, Hariharan ; Bennett, Michael ; Nehzati, Seyed Moeen ; ... ; Kolčić, Ivana ; ... ; Polašek, Ozren ; [et al.]
23andMe Research Team ; Social Science Genetic Association Consortium
engleski
Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals
We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of similar to 3 million individuals and identify 3, 952 approximately uncorrelated genome-wide- significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.
HUMAN COMPLEX TRAITS ; COHORT PROFILE ; BIOBANK ; GENETICS ; MODELS ; HEALTH ; LOCI ; GWAS
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o izdanju
Povezanost rada
Temeljne medicinske znanosti