Genetic Predisposition to Ischemic Stroke: A Polygenic Risk Score

Tsuyoshi Hachiya, Yoichiro Kamatani, Atsushi Takahashi, Jun Hata, Ryohei Furukawa, Yuh Shiwa, Taiki Yamaji, Megumi Hara, Kozo Tanno, Hideki Ohmomo, Kanako Ono, Naoyuki Takashima, Koichi Matsuda, Kenji Wakai, Norie Sawada, Motoki Iwasaki, Kazumasa Yamagishi, Tetsuro Ago, Toshiharu Ninomiya, Akimune FukushimaAtsushi Hozawa, Naoko Minegishi, Mamoru Satoh, Ryujin Endo, Makoto Sasaki, Kiyomi Sakata, Seiichiro Kobayashi, Kuniaki Ogasawara, Motoyuki Nakamura, Jiro Hitomi, Yoshikuni Kita, Keitaro Tanaka, Hiroyasu Iso, Takanari Kitazono, Michiaki Kubo, Hideo Tanaka, Shoichiro Tsugane, Yutaka Kiyohara, Masayuki Yamamoto, Kenji Sobue, Atsushi Shimizu

研究成果: Article査読

33 被引用数 (Scopus)

抄録

Background and Purpose-The prediction of genetic predispositions to ischemic stroke (IS) may allow the identification of individuals at elevated risk and thereby prevent IS in clinical practice. Previously developed weighted multilocus genetic risk scores showed limited predictive ability for IS. Here, we investigated the predictive ability of a newer method, polygenic risk score (polyGRS), based on the idea that a few strong signals, as well as several weaker signals, can be collectively informative to determine IS risk. Methods-We genotyped 13 214 Japanese individuals with IS and 26 470 controls (derivation samples) and generated both multilocus genetic risk scores and polyGRS, using the same derivation data set. The predictive abilities of each scoring system were then assessed using 2 independent sets of Japanese samples (KyushuU and JPJM data sets). Results-In both validation data sets, polyGRS was shown to be significantly associated with IS, but weighted multilocus genetic risk scores was not. Comparing the highest with the lowest polyGRS quintile, the odds ratios for IS were 1.75 (95% confidence interval, 1.33-2.31) and 1.99 (95% confidence interval, 1.19-3.33) in the KyushuU and JPJM samples, respectively. Using the KyushuU samples, the addition of polyGRS to a nongenetic risk model resulted in a significant improvement of the predictive ability (net reclassification improvement=0.151; P<0.001). Conclusions-The polyGRS was shown to be superior to weighted multilocus genetic risk scores as an IS prediction model. Thus, together with the nongenetic risk factors, polyGRS will provide valuable information for individual risk assessment and management of modifiable risk factors.

本文言語English
ページ(範囲)253-258
ページ数6
ジャーナルStroke
48
2
DOI
出版ステータスPublished - 01-02-2017

All Science Journal Classification (ASJC) codes

  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine
  • Advanced and Specialised Nursing

フィンガープリント 「Genetic Predisposition to Ischemic Stroke: A Polygenic Risk Score」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル