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J-GLOBAL ID：201902271306353200   整理番号：19A1052228

血漿蛋白質と骨粗鬆症の間の遺伝的相関の評価:多遺伝子リスクスコア分析【JST・京大機械翻訳】

Assessing the Genetic Correlations Between Blood Plasma Proteins and Osteoporosis: A Polygenic Risk Score Analysis

著者 (16件)： Liang Xiao (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Du Yanan (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Wen Yan (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Liu Li (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Li Ping (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Zhao Yan (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Ding Miao (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Cheng Bolun (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Cheng Shiqiang (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Ma Mei (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Zhang Lu (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Shen Hui (Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, USA) ,  Tian Qing (Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, USA) ,  Guo Xiong (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Zhang Feng (Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Collaborative Innovation Center of Endemic Diseases and Population Health Promotion in Sick Road Region, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China) ,  Deng Hong-Wen (School of Basic Medical Sciences, Central South University, Changsha, People’s Republic of China)
資料名： Calcified Tissue International  (Calcified Tissue International)
巻： 104  号： 2  ページ： 171-181  発行年： 2019年 
JST資料番号： W4130A  ISSN： 1432-0827  資料種別： 逐次刊行物 (A)
記事区分： 原著論文  発行国： ドイツ (DEU)  言語： 英語 (EN)

抄録/ポイント： 骨粗鬆症は一般的な代謝性骨疾患である。骨粗しょう症のリスクに対する全体的な血漿蛋白質の影響は,現在,不明のままである。著者らは,558人の男性と1728人の女性を含む2286人の白人における骨粗鬆症の発症に対する血しょう蛋白質の潜在的影響を評価するために大規模多遺伝子リスクスコア(PRS)分析を行った。骨密度(BMD)および尺骨と橈骨,股関節および脊椎における骨領域を,Hology4500W DXAを用いて測定した。BMD/骨領域値は,年齢,性別,身長,体重に対して共変量として調整した。2286人の白人被験者の全ゲノムSNP遺伝子タイピングを,AffymetrixヒトSNPアレイ6.0を用いて行った。267の血しょう蛋白質関連SNP遺伝子座とそれらの遺伝的効果を,高度に多重化されたアプタマーに基づく親和性プロテオミクスプラットフォームを用いて,最近発表されたゲノムワイド関連研究(GWAS)から得た。各血しょう蛋白質に対する研究対象者の多遺伝子リスクスコア(PRS)を,PLINKソフトウェアにより2286人の白人被験者の遺伝子型データから計算した。個々のPRS値とBMD/骨面積値のピアソン相関分析をRを用いて行った。さらに,性別特異的分析もピアソン相関分析により行った。本研究では267の血しょう蛋白質を分析した。BMDについては,41の蛋白質とBMDの間の関連シグナルを観察し,主に全BMD対因子H(p値=9.00×10~3),全BMD対BGH3(p値=1.40×10-2),脊椎総BMDに対する脊椎総BMD(p値=3.90×10-2)を認めた。骨領域に関しては,フェリチン対脊椎領域(p値=1.90×10-2),C4対股関節面積(p値=1.25×10-2),およびヘモグロビン対右尺骨と半径領域(p値=2.70×10-2)のような45の血しょう蛋白質と骨領域の間に関連証拠が観察された。著者らの研究結果は,BMD/骨領域の変化に及ぼす血漿蛋白質の中程度の影響を示唆し,骨粗鬆症に対するいくつかの候補血しょう蛋白質を同定する。Copyright 2018 Springer Science+Business Media, LLC, part of Springer Nature Translated from English into Japanese by JST.【JST・京大機械翻訳】

シソーラス用語： *遺伝子 ,  ゲノムワイド関連解析 ,  女性 ,  ヘモグロビン ,  ヒト ,  遺伝子型 ,  ソフトウェア ,  体重 ,  脊柱 ,  男性 ,  *骨粗鬆症 ,  骨密度
準シソーラス用語： p値 ,  被験者 ,  性別 , 【Automatic Indexing@JST】

著者キーワード (4件)： ゲノムワイド関連研究 ,  血しょう蛋白質 ,  骨粗鬆症 ,  多遺伝子リスクスコア分析

分類 (4件)： 運動器系の疾患  (GG03000T) ,  分子遺伝学一般  (EC02010J) ,  運動器系の診断  (GG02000M) ,  運動器系の臨床医学一般  (GG01030M)

タイトルに関連する用語 (6件)： 血漿蛋白質 ,  骨粗鬆症 ,  相関 ,  評価 ,  多遺伝子リスクスコア ,  分析