Expressive

rs121918166 - OCA2

Magnitude 4.5 · 6 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

  • Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program - Unknown journal (n.d.) · Unknown authors · PubMed 39024449

    ABSTRACT: INTRODUCTION: Findings from genome-wide association studies (GWASs) have provided foundational knowledge of the genetic basis of disease, facilitating precision approaches for prevention and treatment. Current GWAS results are limited by underrepresentation of individuals from diverse populations, leading to concerns with generalizability regarding our knowledge of the relationships between genes, traits, and disease. The Department of Veterans Affairs (VA) Million Veteran Program (MVP), one of the largest US-based biobanks, addresses this need; 29% of MVP comprises individuals genetically similar to African (AFR), Admixed American (AMR), and East Asian (EAS) reference populations. With over 635,000 participants and more than 44.3M genotyped variants linked with detailed phenotyp

  • A scalable variational inference approach for increased mixed-model association power - Unknown journal (n.d.) · Unknown authors · PubMed 39789286

    ABSTRACT: The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71%

  • 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

  • Multi-omic spatial effects on high-resolution AI-derived retinal thickness - Unknown journal (n.d.) · Unknown authors · PubMed 39904976

    ABSTRACT: Retinal thickness is a marker of retinal health and more broadly, is seen as a promising biomarker for many systemic diseases. Retinal thickness measurements are procured from optical coherence tomography (OCT) as part of routine clinical eyecare. We processed the UK Biobank OCT images using a convolutional neural network to produce fine-scale retinal thickness measurements across > 29,000 points in the macula, the part of the retina responsible for human central vision. The macula is disproportionately affected by high disease burden retinal disorders such as age-related macular degeneration and diabetic retinopathy, which both involve metabolic dysregulation. Analysis of common genomic variants, metabolomic, blood and immune biomarkers, disease PheCodes and genetic scores a

  • Genome-wide association study identifies novel loci associated with skin autofluorescence in individuals without diabetes - Unknown journal (n.d.) · Unknown authors · PubMed 36536295

    ABSTRACT: Background Skin autofluorescence (SAF) is a non-invasive measure reflecting accumulation of advanced glycation endproducts (AGEs) in the skin. Higher SAF levels are associated with an increased risk of developing type 2 diabetes and cardiovascular disease. An earlier genome-wide association study (GWAS) revealed a strong association between NAT2 variants and SAF. The aim of this study was to calculate SAF heritability and to identify additional genetic variants associated with SAF through genome-wide association studies (GWAS). Results In 27,534 participants without diabetes the heritability estimate of lnSAF was 33% ± 2.0% (SE) in a model adjusted for covariates. In meta-GWAS for lnSAF five SNPs, on chromosomes 8, 11, 15 and 16 were associated with lnSAF (P < 5 × 1

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