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Identification of nine novel loci related to hematological traits in a Japanese population
http://hdl.handle.net/2241/00153674
http://hdl.handle.net/2241/001536743c528f39-1636-4aea-8e2d-46424ded086d
名前 / ファイル | ライセンス | アクション |
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PR_50-9 (466.0 kB)
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Item type | Journal Article(1) | |||||
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公開日 | 2018-11-12 | |||||
タイトル | ||||||
タイトル | Identification of nine novel loci related to hematological traits in a Japanese population | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
Yasukochi, Yoshiki
× Yasukochi, Yoshiki× Sakuma, Jun× Takeuchi, Ichiro× Kato, Kimihiko× Oguri, Mitsutoshi× Fujimaki, Tetsuo× Horibe, Hideki× Yamada, Yoshiji |
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著者別名 |
佐久間, 淳
× 佐久間, 淳 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | 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). | |||||
書誌情報 |
Physiological Genomics 巻 50, 号 9, p. 758-769, 発行日 2018-09 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1094-8341 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA11704248 | |||||
PubMed番号 | ||||||
識別子タイプ | PMID | |||||
関連識別子 | 29958078 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1152/physiolgenomics.00088.2017 | |||||
権利 | ||||||
権利情報 | © 2018 American Physiological Society. All rights reserved. | |||||
権利 | ||||||
権利情報 | Licensed under Creative Commons Attribution CC-BY 4.0 | |||||
著者版フラグ | ||||||
値 | publisher | |||||
出版者 | ||||||
出版者 | American Physiological Society |