rs116927526 - SPATA33 - CDK10

Magnitude 4.5 · 3 studies on file

Reported associations

  • A generalized linear mixed model association tool for biobank-scale data. - Nature genetics (2021) · Jiang L, Zheng Z, Fang H, Yang J · PubMed 34737426

    Compared with linear mixed model-based genome-wide association (GWA) methods, generalized linear mixed model (GLMM)-based methods have better statistical properties when applied to binary traits but are computationally much slower. In the present study, leveraging efficient sparse matrix-based algorithms, we developed a GLMM-based GWA tool, fastGWA-GLMM, that is severalfold to orders of magnitude faster than the state-of-the-art tools when applied to the UK Biobank (UKB) data and scalable to cohorts with millions of individuals. We show by simulation that the fastGWA-GLMM test statistics of both common and rare variants are well calibrated under the null, even for traits with extreme case-control ratios. We applied fastGWA-GLMM to the UKB data of 456,348 individuals, 11,842,647 variants an

  • Genome-wide study of hair colour in UK Biobank explains most of the SNP heritability - Unknown journal (n.d.) · Unknown authors · PubMed 30531825

    ABSTRACT: Natural hair colour within European populations is a complex genetic trait. Previous work has established that MC1R variants are the principal genetic cause of red hair colour, but with variable penetrance. Here, we have extensively mapped the genes responsible for hair colour in the white, British ancestry, participants in UK Biobank. MC1R only explains 73% of the SNP heritability for red hair in UK Biobank, and in fact most individuals with two MC1R variants have blonde or light brown hair. We identify other genes contributing to red hair, the combined effect of which accounts for ~90% of the SNP heritability. Blonde hair is associated with over 200 genetic variants and we find a continuum from black through dark and light brown to blonde and account for 73% of the SNP heritabi

  • Genome-wide association meta-analyses combining multiple risk phenotypes provides insights into the genetic architecture of cutaneous melanoma susceptibility - Unknown journal (n.d.) · Unknown authors · PubMed 32341527

    ABSTRACT: Most genetic susceptibility to cutaneous melanoma remains to be discovered. Meta-analysis genome-wide association study (GWAS) of 36,760 melanoma cases (67% newly-genotyped) and 375,188 controls identified 54 significant loci with 68 independent SNPs. Analysis of risk estimates across geographical regions and host factors suggests the acral melanoma subtype is uniquely unrelated to pigmentation. Combining this meta-analysis with nevus count and hair color GWAS, and transcriptome association approaches, uncovered 31 potential secondary loci, for a total of 85 cutaneous melanoma susceptibility loci. These findings provide substantial insights into cutaneous melanoma genetic architecture, reinforcing the importance of nevogenesis, pigmentation, and telomere maintenance together with


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Lifestyle context

Concrete actions anchored to the cited research. We do not prescribe, we describe.

Screening

  • annual dermatological melanoma screening Moderate

    The T allele is associated with 1.7-fold increased cutaneous malignant melanoma risk.

    Annual full-body skin examination by dermatologist; baseline photography for reference.