Expressive

rs10513137 - ZBTB38

Magnitude 2.2 · 4 studies on file

Reported associations

  • Identification of 15 loci influencing height in a Korean population. - Journal of human genetics (2010) · Kim JJ, Lee HI, Park T, Kim K, Lee JE, Cho NH, Shin C, Cho YS, Lee JY, Han BG, Yoo HW, Lee JK · PubMed 19893584

    Height is a complex genetic trait that involves multiple genetic loci. Recently, 44 loci associated with height were identified in Caucasian individuals by large-scale genome-wide association (GWA) studies. To identify genetic variants influencing height in the Korean population, we analyzed GWA data from 8842 Korean individuals and identified 15 genomic regions with one or more sequence variants associated with height (P<1 x 10(-5)). Of these, eight loci were newly identified in Koreans (SUPT3H, EXT1, FREM1, PALM2-AKAP2, NUP37-PMCH, IGF1, KRT20 and ANKRD60). The 15 significant loci account for approximately 1.0% of height variation, with a 3.7-cm difference between individuals with < or =8 height-increasing alleles (5.1%) and > or =19 height-increasing alleles (4.2%). We also examined the

  • A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. - Nature genetics (2009) · Cho YS, Go MJ, Kim YJ, Heo JY, Oh JH, Ban HJ, Yoon D, Lee MH, Kim DJ, Park M, Cha SH, Kim JW, Han BG, Min H, Ahn Y, Park MS, Han HR, Jang HY, Cho EY, Lee JE, Cho NH, Shin C, Park T, Park JW, Lee JK, Cardon L, Clarke G, McCarthy MI, Lee JY, Lee JK, Oh B, Kim HL · PubMed 19396169

    To identify genetic factors influencing quantitative traits of biomedical importance, we conducted a genome-wide association study in 8,842 samples from population-based cohorts recruited in Korea. For height and body mass index, most variants detected overlapped those reported in European samples. For the other traits examined, replication of promising GWAS signals in 7,861 independent Korean samples identified six previously unknown loci. For pulse rate, signals reaching genome-wide significance mapped to chromosomes 1q32 (rs12731740, P = 2.9 x 10(-9)) and 6q22 (rs12110693, P = 1.6 x 10(-9)), with the latter approximately 400 kb from the coding sequence of GJA1. For systolic blood pressure, the most compelling association involved chromosome 12q21 and variants near the ATP2B1 gene (rs172

  • Progressive effects of single-nucleotide polymorphisms on 16 phenotypic traits based on longitudinal data - Unknown journal (n.d.) · Unknown authors · PubMed 31902109

    ABSTRACT: Background There are many research studies have estimated the heritability of phenotypic traits, but few have considered longitudinal changes in several phenotypic traits together. Objective To evaluate the progressive effect of single nucleotide polymorphisms (SNPs) on prominent health-related phenotypic traits by determining SNP-based heritability () using longitudinal data. Methods Sixteen phenotypic traits associated with major health indices were observed biennially for 6843 individuals with 10-year follow-up in a Korean community-based cohort. Average SNP heritability and longitudinal changes in the total period were estimated using a two-stage model. Average and periodic differences for each subject were considered responses to estimate SNP heritability. Furthermore, a ge

  • Your height affects your health: genetic determinants and health-related outcomes in Taiwan - Unknown journal (n.d.) · Unknown authors · PubMed 35831902

    ABSTRACT: Background Height is an important anthropometric measurement and is associated with many health-related outcomes. Genome-wide association studies (GWASs) have identified hundreds of genetic loci associated with height, mainly in individuals of European ancestry. Methods We performed genome-wide association analyses and replicated previously reported GWAS-determined single nucleotide polymorphisms (SNPs) in the Taiwanese Han population (Taiwan Biobank; n = 67,452). A genetic instrument composed of 251 SNPs was selected from our GWAS, based on height and replication results as the best-fit polygenic risk score (PRS), in accordance with the clumping and p-value threshold method. We also examined the association between genetically determined height (PRS251) and measured height (phen

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