Expressive

rs117159862 - Metazoa_SRP - KNL1

Magnitude 2.2 · 3 studies on file

Reported associations

  • Combining cross-sectional and longitudinal genomic approaches to identify determinants of cognitive and physical decline - Unknown journal (n.d.) · Unknown authors · PubMed 40374629

    ABSTRACT: Large-scale genomic studies focusing on the genetic contribution to human aging have mostly relied on cross-sectional data. With the release of longitudinally curated aging phenotypes by the UK Biobank (UKBB), it is now possible to study aging over time at genome-wide scale. In this work, we evaluated the suitability of competing models of change in realistic simulation settings, performed genome-wide association scans on simulation-validated measures of age-related deweekcline, and followed up with LD-score regression and Mendelian Randomization (MR) analyses. Focusing on global cognitive and physical function, we observed marked differences between baseline function (θ) and accelerated decline (Δ). Both outcomes showed distinct heritability levels (e.g., 31.38% versus 3.15%

  • Investigating the genetic architecture of non-cognitive skills using GWAS-by-subtraction - Unknown journal (n.d.) · Unknown authors · PubMed 33414549

    ABSTRACT: Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used Genomic Structural Equation Modeling and prior genome-wide association studies (GWAS) of educational attainment (n = 1,131,881) and cognitive test performance (n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability.We identified 157 genome-wide significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Non-cognitive genetics were enriched in the same brain tissues and cell types as cognitive performance but showed different associations with gray-matter brain volumes. Non-cognitive genetics were further distinguished by associations with

  • Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals - Unknown journal (n.d.) · Unknown authors · PubMed 35361970

    ABSTRACT: We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~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-significan

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