Development of a high-performance system for disease risk prediction on GWAS summary statistics

• Project/Area Number: 21K10439
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 58030:Hygiene and public health-related: excluding laboratory approach
• Research Institution: Tohoku University
• Principal Investigator: Narita Akira 東北大学, 東北メディカル・メガバンク機構, 助教 (50459468)
• Co-Investigator(Kenkyū-buntansha): 田宮 元 国立研究開発法人理化学研究所, 革新知能統合研究センター, チームリーダー (10317745)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Project Status: Completed (Fiscal Year 2023)
• Budget Amount: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000); Fiscal Year 2023: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000); Fiscal Year 2022: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000); Fiscal Year 2021: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
• Keywords: ゲノムワイド関連解析 / ポリジェニックリスクスコア

Outline of Research at the Start

GWAS（genome-wide association study; 全ゲノム関連解析）などのアプローチによって、これまで疾患を含む様々な形質と関連するSNP（single nucleotide polymorphism; 一塩基多型）などのDNA多型が数多く同定されてきた。
それに伴い、それらの多型情報から算出されるPRS（polygenic risk score; ポリジェニックリスクスコア）が、個人ごとの疾患発症リスクの新たな指標として提唱されている。
本研究は、GWAS要約統計量をもとに、PRSに基づく疾患発症リスク予測システムの基盤を確立することを目的とする。

Outline of Final Research Achievements

The aim of the study is to establish the basis for a high-performance disease risk prediction system, based on summary statistics of genome-wide association analysis (GWAS).
GWAS is a statistical genetic approach in which genetic variants are tested for association with a health-related trait to detect disease-causing variants. In the study, we conducted GWAS on a range of traits/diseases using the data from the Tohoku Medical Megabank Project Community-Based Cohort Study and in collaboration with other (both domestic and international) research institutions, and assessed the predictive ability of polygenic risk scores, which were calculated from the GWAS summary statistics, for various diseases.

Academic Significance and Societal Importance of the Research Achievements

本研究を通じて、国内外のゲノムコホート/バイオバンクで実施されたGWASの結果を幅広く収集し、より大規模、より多様な民族集団のデータを統合することが、疾患原因遺伝子多型の探索や疾患リスク予測の精度向上に重要であることが示された。
さらに、多様な民族集団を対象としたゲノム医学研究は、医療アクセスに関する、民族集団間の不平等な状況を是正し、次世代医療システムの恩恵を広くもたらすと考えられ、本研究はその先進的な取組みの一つと位置付けられる。

Research Products

• [Int'l Joint Research] University of Michigan(米国)
• [Int'l Joint Research] Eurac Research(イタリア)
• [Int'l Joint Research] University of Michigan(米国)
• [Int'l Joint Research] Helmholtz Zentrum Munchen(ドイツ)
• [Journal Article] A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids (2022)
  • Author(s): Ramdas Shweta、Judd Jonathan、Graham Sarah E.、Kanoni Stavroula、Wang Yuxuan、...、Narita Akira、...、Tamiya Gen、...、Brown Christopher D.
  • Journal Title: The American Journal of Human Genetics Volume: 109 Issue: 8 Pages: 1366
  • DOI: 10.1016/j.ajhg.2022.06.012
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Genome-wide association study of the risk of chronic kidney disease and kidney-related traits in the Japanese population: J-Kidney-Biobank (2022)
  • Author(s): Sugawara Yuka、Hirakawa Yosuke、Nagasu Hajime、Narita Akira、Katayama Akihiro、Wada Jun、Shimizu Miho、Wada Takashi、Kitamura Hiromasa、Nakano Toshiaki、Yokoi Hideki、Yanagita Motoko、Goto Shin、Narita Ichiei、Koshiba Seizo、Tamiya Gen、Nangaku Masaomi、Yamamoto Masayuki、Kashihara Naoki
  • Journal Title: Journal of Human Genetics Volume: 68 Issue: 2 Pages: 55-64
  • DOI: 10.1038/s10038-022-01094-1
  • Peer Reviewed / Open Access
• [Journal Article] Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis (2022)
  • Author(s): Kanoni Stavroula、Graham Sarah E.、Wang Yuxuan、Surakka Ida、Ramdas Shweta、...、Narita Akira、...、Tamiya Gen、...、Peloso Gina M.
  • Journal Title: Genome Biology Volume: 23 Issue: 1 Pages: 268-268
  • DOI: 10.1186/s13059-022-02837-1
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] A cross-population atlas of genetic associations for 220 human phenotypes (2021)
  • Author(s): Sakaue S, Kanai M, Tanigawa Y, Karjalainen J, Kurki M, Koshiba S, Narita A, Konuma T, Yamamoto K, Akiyama M, Ishigaki K, Suzuki A, Suzuki K, Obara W, Yamaji K, Takahashi K, Asai S, Takahashi Y, Suzuki T, Shinozaki N, Yamaguchi H, Minami S, Murayama S, Yoshimori K, Nagayama S, Obata D, Higashiyama M, Masumoto A, et al.
  • Journal Title: Nature Genetics Volume: 53 Issue: 10 Pages: 1415-1424
  • DOI: 10.1038/s41588-021-00931-x
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] The power of genetic diversity in genome-wide association studies of lipids (2021)
  • Author(s): Graham SE, et al. (Tamiya G; 513th in 530 authors)
  • Journal Title: Nature Volume: 600 Issue: 7890 Pages: 675-679
  • DOI: 10.1038/s41586-021-04064-3
  • Peer Reviewed / Int'l Joint Research
• [Presentation] 大規模ゲノムデータを用いた疾患リスク予測におけるSTMGPの有効性の検証 (2023)
  • Author(s): 田端佑介, 成田 暁, 三宅顕光, 船山貴光, 田宮 元
  • Organizer: 第5回日本メディカルAI学会学術集会