rs10254101 - PRKAG2

Magnitude 2.2 · 8 studies on file

Reported associations

  • A cross-population atlas of genetic associations for 220 human phenotypes. - Nature genetics (2021) · Sakaue S, Kanai M, Tanigawa Y, Karjalainen J, Kurki M, Koshiba S, Narita A, Konuma T, Yamamoto K, Akiyama M, Ishigaki K, Suzuki A, Suzuki K, Obara W, Yamaji K, Takahashi K, Asai S, Takahashi Y, Suzuki T, Shinozaki N, Yamaguchi H, Minami S, Murayama S, Yoshimori K, Nagayama S, Obata D, Higashiyama M, Masumoto A, Koretsune Y, Ito K, Terao C, Yamauchi T, Komuro I, Kadowaki T, Tamiya G, Yamamoto M, Nakamura Y, Kubo M, Murakami Y, Yamamoto K, Kamatani Y, Palotie A, Rivas MA, Daly MJ, Matsuda K, Okada Y · PubMed 34594039

    Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (n = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wid

  • 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

  • Genome-wide association study of medication-use and associated disease in the UK Biobank - Unknown journal (n.d.) · Unknown authors · PubMed 31015401

    ABSTRACT: Genome-wide association studies (GWASs) of medication use may contribute to understanding of disease etiology, could generate new leads relevant for drug discovery and can be used to quantify future risk of medication taking. Here, we conduct GWASs of self-reported medication use from 23 medication categories in approximately 320,000 individuals from the UK Biobank. A total of 505 independent genetic loci that meet stringent criteria (P < 10−8/23) for statistical significance are identified. We investigate the implications of these GWAS findings in relation to biological mechanism, potential drug target identification and genetic risk stratification of disease. Amongst the medication-associated genes are 16 known therapeutic-effect target genes for medications from 9 cat

  • 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function - Unknown journal (n.d.) · Unknown authors · PubMed 28452372

    ABSTRACT: HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10−8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SN

  • 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 association studies in a large Korean cohort identify quantitative trait loci for 36 traits and illuminate their genetic architectures - Unknown journal (n.d.) · Unknown authors · PubMed 40436827

    ABSTRACT: Genome-wide association studies (GWAS) have predominantly focused on European ancestry populations, limiting biological discoveries across diverse populations. Here we report GWAS findings from 153,950 individuals across 36 quantitative traits in the Korean Cancer Prevention Study-II (KCPS2) Biobank. We discovered 301 previously unreported genetic loci in KCPS2, including an association between thyroid-stimulating hormone and CD36. Meta-analysis with the Korean Genome and Epidemiology Study, Biobank Japan, Taiwan Biobank, and UK Biobank identified 4588 loci that were not significant in any contributing GWAS. We describe differences in genetic architectures across these East Asian and European samples. We also highlight East Asian specific associations, including a known pleiotrop

  • Trans-ethnic association study of blood pressure determinants in over 750,000 individuals - Unknown journal (n.d.) · Unknown authors · PubMed 30578418

    ABSTRACT: In this trans-ethnic multi-omic study we reinterpret the genetic architecture of blood pressure to identify genes, tissues, phenome, and medication contexts of blood pressure homeostasis. We discovered 208 novel common blood pressure SNPs and 53 rare variants in GWASs of systolic, diastolic and pulse pressure in up to 776,078 participants from the Million Veteran Program (MVP) and collaborating studies, with analysis of the blood pressure clinical phenome in MVP. Our transcriptome-wide association study detected 4,043 blood pressure associations with genetically-predicted gene expression of 840 genes in 45 tissues, and murine renal single-cell RNA sequencing identified upregulated blood pressure genes in kidney tubule cells. Editorial summary: Analysis of blood pressure data from

  • Blood metabolic biomarkers and colorectal cancer risk: results from large prospective cohort and Mendelian randomisation analyses - Unknown journal (n.d.) · Unknown authors · PubMed 40307439

    ABSTRACT: Background Emerging evidence suggests metabolic dysregulation may contribute to colorectal cancer (CRC) aetiology. We aimed to identify pre-diagnostic metabolic biomarkers for CRC risk in 230,420 UK Biobank participants. Methods Nuclear magnetic resonance spectroscopy was used to quantify 249 metabolic biomarkers in plasma samples collected at baseline. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals (CIs) for associations of metabolic biomarkers with CRC risk after adjusting for potential confounders. To infer the potential causality of biomarkers that were associated with CRC independent of the others, we performed genome-wide association analyses among 199,732 UK Biobank participants of European ancestry to identify biomarker-as


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