Ontology highlight
ABSTRACT:
SUBMITTER: Hachiya T
PROVIDER: S-EPMC5266416 | biostudies-literature | 2017 Feb
REPOSITORIES: biostudies-literature
Hachiya Tsuyoshi T Kamatani Yoichiro Y Takahashi Atsushi A Hata Jun J Furukawa Ryohei R Shiwa Yuh Y Yamaji Taiki T Hara Megumi M Tanno Kozo K Ohmomo Hideki H Ono Kanako K Takashima Naoyuki N Matsuda Koichi K Wakai Kenji K Sawada Norie N Iwasaki Motoki M Yamagishi Kazumasa K Ago Tetsuro T Ninomiya Toshiharu T Fukushima Akimune A Hozawa Atsushi A Minegishi Naoko N Satoh Mamoru M Endo Ryujin R Sasaki Makoto M Sakata Kiyomi K Kobayashi Seiichiro S Ogasawara Kuniaki K Nakamura Motoyuki M Hitomi Jiro J Kita Yoshikuni Y Tanaka Keitaro K Iso Hiroyasu H Kitazono Takanari T Kubo Michiaki M Tanaka Hideo H Tsugane Shoichiro S Kiyohara Yutaka Y Yamamoto Masayuki M Sobue Kenji K Shimizu Atsushi A
Stroke 20161229 2
<h4>Background and purpose</h4>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 collectivel ...[more]