Expressive

rs10107388 - PLEC

Magnitude 2.2 · 5 studies on file

Reported associations

  • 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 genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology - Unknown journal (n.d.) · Unknown authors · PubMed 37596262

    ABSTRACT: Blood cells contain functionally important intracellular structures, such as granules, critical to immunity and thrombosis. Quantitative variation in these structures has not been subjected previously to large-scale genetic analysis. We perform genome-wide association studies of 63 flow-cytometry derived cellular phenotypes-including cell-type specific measures of granularity, nucleic acid content and reactivity-in 41,515 participants in the INTERVAL study. We identify 2172 distinct variant-trait associations, including associations near genes coding for proteins in organelles implicated in inflammatory and thrombotic diseases. By integrating with epigenetic data we show that many intracellular structures are likely to be determined in immature precursor cells. By integrating

  • 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%

  • New role of fat-free mass in cancer risk linked with genetic predisposition - Unknown journal (n.d.) · Unknown authors · PubMed 38538606

    ABSTRACT: Cancer risk is associated with the widely debated measure body mass index (BMI). Fat mass and fat-free mass measurements from bioelectrical impedance may further clarify this association. The UK Biobank is a rare resource in which bioelectrical impedance and BMI data was collected on ~ 500,000 individuals. Using this dataset, a comprehensive analysis using regression, principal component and genome-wide genetic association, provided multiple levels of evidence that increasing whole body fat (WBFM) and fat-free mass (WBFFM) are both associated with increased post-menopausal breast cancer risk, and colorectal cancer risk in men. WBFM was inversely associated with prostate cancer. We also identified rs615029[T] and rs1485995[G] as associated in independent analyses with both PMB

  • Participation bias in the UK Biobank distorts genetic associations and downstream analyses - Unknown journal (n.d.) · Unknown authors · PubMed 37106081

    ABSTRACT: While volunteer-based studies such as the UK Biobank have become the cornerstone of genetic epidemiology, the participating individuals are rarely representative of their target population. To evaluate the impact of selective participation, here we derived UK Biobank participation probabilities on the basis of 14 variables harmonized across the UK Biobank and a representative sample. We then conducted weighted genome-wide association analyses on 19 traits. Comparing the output from weighted genome-wide association analyses (neffective = 94,643 to 102,215) with that from standard genome-wide association analyses (n = 263,464 to 283,749), we found that increasing representativeness led to changes in SNP effect sizes and identified novel SNP associations for 12 traits. While

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