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Identification of nine novel loci related to hematological traits in a Japanese population
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 cros...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Physiological Society
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6172615/ https://www.ncbi.nlm.nih.gov/pubmed/29958078 http://dx.doi.org/10.1152/physiolgenomics.00088.2017 |
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author | Yasukochi, Yoshiki Sakuma, Jun Takeuchi, Ichiro Kato, Kimihiko Oguri, Mitsutoshi Fujimaki, Tetsuo Horibe, Hideki Yamada, Yoshiji |
author_facet | Yasukochi, Yoshiki Sakuma, Jun Takeuchi, Ichiro Kato, Kimihiko Oguri, Mitsutoshi Fujimaki, Tetsuo Horibe, Hideki Yamada, Yoshiji |
author_sort | Yasukochi, Yoshiki |
collection | PubMed |
description | 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)). |
format | Online Article Text |
id | pubmed-6172615 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Physiological Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-61726152018-10-11 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 Physiol Genomics Research Article 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)). American Physiological Society 2018-09-01 2018-06-29 /pmc/articles/PMC6172615/ /pubmed/29958078 http://dx.doi.org/10.1152/physiolgenomics.00088.2017 Text en Copyright © 2018 the American Physiological Society http://creativecommons.org/licenses/by/4.0/deed.en_US Licensed under Creative Commons Attribution CC-BY 4.0 (http://creativecommons.org/licenses/by/4.0/deed.en_US) : © the American Physiological Society. |
spellingShingle | Research Article Yasukochi, Yoshiki Sakuma, Jun Takeuchi, Ichiro Kato, Kimihiko Oguri, Mitsutoshi Fujimaki, Tetsuo Horibe, Hideki Yamada, Yoshiji Identification of nine novel loci related to hematological traits in a Japanese population |
title | Identification of nine novel loci related to hematological traits in a Japanese population |
title_full | Identification of nine novel loci related to hematological traits in a Japanese population |
title_fullStr | Identification of nine novel loci related to hematological traits in a Japanese population |
title_full_unstemmed | Identification of nine novel loci related to hematological traits in a Japanese population |
title_short | Identification of nine novel loci related to hematological traits in a Japanese population |
title_sort | identification of nine novel loci related to hematological traits in a japanese population |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6172615/ https://www.ncbi.nlm.nih.gov/pubmed/29958078 http://dx.doi.org/10.1152/physiolgenomics.00088.2017 |
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