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Identification of nine novel loci related to hematological traits in a Japanese population.
Yasukochi, Yoshiki; Sakuma, Jun; Takeuchi, Ichiro; Kato, Kimihiko; Oguri, Mitsutoshi; Fujimaki, Tetsuo; Horibe, Hideki; Yamada, Yoshiji.
Afiliação
  • Yasukochi Y; Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Mie , Japan.
  • Sakuma J; CREST, Japan Science and Technology Agency, Kawaguchi, Saitama , Japan.
  • Takeuchi I; CREST, Japan Science and Technology Agency, Kawaguchi, Saitama , Japan.
  • Kato K; Computer Science Department, College of Information Science, University of Tsukuba, Tsukuba, Ibaraki , Japan.
  • Oguri M; RIKEN Center for Advanced Intelligence Project , Tokyo , Japan.
  • Fujimaki T; CREST, Japan Science and Technology Agency, Kawaguchi, Saitama , Japan.
  • Horibe H; RIKEN Center for Advanced Intelligence Project , Tokyo , Japan.
  • Yamada Y; Department of Computer Science, Nagoya Institute of Technology, Nagoya, Aichi , Japan.
Physiol Genomics ; 50(9): 758-769, 2018 09 01.
Article em En | MEDLINE | ID: mdl-29958078
Recent genome-wide association studies have identified various genetic variants associated with hematological traits. Although it is possible that quantitative data of hematological traits are varied among the years examined, conventional genome-wide association studies have been conducted in a cross-sectional manner that measures traits at a single point in time. To address this issue, we have traced blood profiles in 4,884 Japanese individuals who underwent annual health check-ups for several years. In the present study, longitudinal exome-wide association studies were conducted to identify genetic variants related to 13 hematological phenotypes. The generalized estimating equation model showed that a total of 67 single nucleotide polymorphisms (SNPs) were significantly [false discovery rate (FDR) of <0.01] associated with hematological phenotypes. Of the 67 SNPs, nine SNPs were identified as novel hematological markers: rs4686683 of SENP2 for red blood cell count (FDR = 0.008, P = 5.5 × 10-6); rs3917688 of SELP for mean corpuscular volume (FDR = 0.005, P = 2.4 × 10-6); rs3133745 of C8orf37-AS1 for white blood cell count (FDR = 0.003, P = 1.3 × 10-6); rs13121954 at 4q31.2 for basophil count (FDR = 0.007, P = 3.1 × 10-5); rs7584099 at 2q22.3 (FDR = 2.6 × 10-5, P = 8.8 × 10-8), rs1579219 of HCG17 (FDR = 0.003, P = 2.0 × 10-5), and rs10757049 of DENND4C (FDR = 0.008, P = 5.6 × 10-5) for eosinophil count; rs12338 of CTSB for neutrophil count (FDR = 0.007, P = 2.9 × 10-5); and rs395967 of OSMR-AS1 for monocyte count (FDR = 0.008, P = 3.2 × 10-5).
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fenômenos Fisiológicos Sanguíneos / Característica Quantitativa Herdável / Povo Asiático / Loci Gênicos Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans / Male País/Região como assunto: Asia Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fenômenos Fisiológicos Sanguíneos / Característica Quantitativa Herdável / Povo Asiático / Loci Gênicos Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans / Male País/Região como assunto: Asia Idioma: En Ano de publicação: 2018 Tipo de documento: Article