Expressive

rs12445804 - LITAF

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

  • Genetics of 35 blood and urine biomarkers in the UK Biobank - Unknown journal (n.d.) · Unknown authors · PubMed 33462484

    ABSTRACT: Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n=363,228 individuals). We identify 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations, and additional sets of large-effect (> 0.1 sd) protein-altering, HLA, and copy-number variant associations. Through Mendelian Randomization analysis, we discover 51 causal relationships, including previously known agonistic effects of urate on gout and cystatin C on stroke. Finally, we develop polygenic risk scores for each biomarker and built 'multi-PRS' models for diseases using 35 PRSs simultaneously, which improved chronic kidney disease, type 2 diabetes, gout, and alcoholic cirr

  • 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

  • Loss-of-function genomic variants highlight potential therapeutic targets for cardiovascular disease - Unknown journal (n.d.) · Unknown authors · PubMed 33339817

    ABSTRACT: Pharmaceutical drugs targeting dyslipidemia and cardiovascular disease (CVD) may increase the risk of fatty liver disease and other metabolic disorders. To identify potential novel CVD drug targets without these adverse effects, we perform genome-wide analyses of participants in the HUNT Study in Norway (n = 69,479) to search for protein-altering variants with beneficial impact on quantitative blood traits related to cardiovascular disease, but without detrimental impact on liver function. We identify 76 (11 previously unreported) presumed causal protein-altering variants associated with one or more CVD- or liver-related blood traits. Nine of the variants are predicted to result in loss-of-function of the protein. This includes ZNF529:p.K405X, which is associated with decreas

  • Polygenic Hyperlipidemias and Coronary Artery Disease Risk - Unknown journal (n.d.) · Unknown authors · PubMed 32154731

    ABSTRACT: Supplemental Digital Content is available in the text. Background: Hyperlipidemia is a highly heritable risk factor for coronary artery disease (CAD). While monogenic familial hypercholesterolemia associates with severely increased CAD risk, it remains less clear to what extent a high polygenic load of a large number of LDL (low-density lipoprotein) cholesterol (LDL-C) or triglyceride (TG)-increasing variants associates with increased CAD risk. Methods: We derived polygenic risk scores (PRSs) with ≈6M variants separately for LDL-C and TG with weights from a UK Biobank-based genome-wide association study with ≈324K samples. We evaluated the impact of polygenic hypercholesterolemia and hypertriglyceridemia to lipid levels in 27 039 individuals from the National FINRISK Study

  • The power of genetic diversity in genome-wide association studies of lipids - Unknown journal (n.d.) · Unknown authors · PubMed 34887591

    ABSTRACT: Elevated blood lipid levels are heritable risk factors of cardiovascular disease with varying prevalence worldwide due to differing dietary patterns and medication use. Despite advances in prevention and treatment, particularly through the lowering of low-density lipoprotein cholesterol levels, heart disease remains the leading cause of death worldwide. Genome-wide association studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS have been conducted in European ancestry populations and may have missed genetic variants contributing to lipid level variation in other ancestry groups due to differences in allele frequencies, effect sizes, and linkage-disequilibr

  • Phenotypic and Genetic Characterization of Lower LDL Cholesterol and Increased Type 2 Diabetes Risk in the UK Biobank - Unknown journal (n.d.) · Unknown authors · PubMed 32493714

    ABSTRACT: Although hyperlipidemia is traditionally considered a risk factor for type 2 diabetes (T2D), evidence has emerged from statin trials and candidate gene investigations suggesting that lower LDL cholesterol (LDL-C) increases T2D risk. We thus sought to more comprehensively examine the phenotypic and genotypic relationships of LDL-C with T2D. Using data from the UK Biobank, we found that levels of circulating LDL-C were negatively associated with T2D prevalence (odds ratio 0.41 [95% CI 0.39, 0.43] per mmol/L unit of LDL-C), despite positive associations of circulating LDL-C with HbA1c and BMI. We then performed the first genome-wide exploration of variants simultaneously associated with lower circulating LDL-C and increased T2D risk, using data on LDL-C from the UK Biobank (n = 431,

  • The contribution of common and rare genetic variants to variation in metabolic traits in 288,137 East Asians - Unknown journal (n.d.) · Unknown authors · PubMed 36333282

    ABSTRACT: Metabolic traits are heritable phenotypes widely-used in assessing the risk of various diseases. We conduct a genome-wide association analysis (GWAS) of nine metabolic traits (including glycemic, lipid, liver enzyme levels) in 125,872 Korean subjects genotyped with the Korea Biobank Array. Following meta-analysis with GWAS from Biobank Japan identify 144 novel signals (MAF ≥ 1%), of which 57.0% are replicated in UK Biobank. Additionally, we discover 66 rare (MAF < 1%) variants, 94.4% of them co-incident to common loci, adding to allelic series. Although rare variants have limited contribution to overall trait variance, these lead, in carriers, substantial loss of predictive accuracy from polygenic predictions of disease risk from common variant alone. We capture groups

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