Re-annotation of large-scale human genome data by integration of statistical genetics and operations research

• Project/Area Number: 20K21834
• Research Category: Grant-in-Aid for Challenging Research (Exploratory)
• Allocation Type: Multi-year Fund
• Review Section: Medium-sized Section 62:Applied informatics and related fields
• Research Institution: Osaka University
• Principal Investigator: Okada Yukinori 大阪大学, 医学系研究科, 教授 (70727411)
• Co-Investigator(Kenkyū-buntansha): 垣村 尚徳 慶應義塾大学, 理工学部(矢上), 准教授 (30508180)
• Project Period (FY): 2020-07-30 – 2022-03-31
• Project Status: Completed (Fiscal Year 2021)
• Budget Amount: ¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000); Fiscal Year 2021: ¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000); Fiscal Year 2020: ¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
• Keywords: 遺伝統計学 / 最適化理論 / poygenic risk score / ハプロタイプ / ゲノムデータ

Outline of Research at the Start

大規模ゲノム情報は、①：長大なゲノム配列の中で一部の遺伝子変異のみが関与する「スパース性」、②：遺伝子変異数がサンプル数と比べて著しく大きい「P>>N問題」、が特徴である。遺伝統計学で扱われるヒト集団ゲノム情報は単純なグラフ構造として記述でき、即ち組合せ最適化問題として解釈可能である。本研究は、遺伝統計学と最適化理論の学際連携を通じて、大規模ヒトゲノム・臨床情報の組合せ最適化問題としての再定義を目指すものである。

Outline of Final Research Achievements

Large-scale human genome data has two major characteristics; (i) limited fractions of the human genome variations only affects human disease risk, (ii) numbers of the human genome variations are much larger than those of samples (i.e., P>>N problem). Statistical genetics handles human population genome data as input, which can be described as simple graphs. We considered that these graphs can be solved by operations researches. This project aims re-annotation of large-scale human genome data by integration of statistical genetics and operations research through iterdisciplinary cooperative studies.

Academic Significance and Societal Importance of the Research Achievements

遺伝統計学と最適化理論は共通した理論的背景を有するも、異なる学問分野として捉えられてきた。本研究は、大規模疾患ゲノム情報をシンプルな行列・グラフ情報として捉えることにより、る数理理論の応用研究の題材となることを示し、学際連携の新たな可能性を切り拓いたものとして学術的な意義を有すると考えられる。今後、解析アルゴリズムのスケーラビリティーの獲得と高速計算化を進めることで、より汎用性の高い情報解析ツールとしての実装が可能になると期待される。

Research Products

• [Journal Article] Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores (2022)
  • Author(s): Weissbrod Omer、Kanai Masahiro、...、、Koretsune Yukihiro、Martin Alicia R.、Finucane Hilary K.、Price Alkes L.
  • Journal Title: Nature Genetics Volume: 54 Issue: 4 Pages: 450-458
  • DOI: 10.1038/s41588-022-01036-9
  • Peer Reviewed / Int'l Joint Research
• [Journal Article] An evolving hypothesis in autoimmune disease genetics (2022)
  • Author(s): Okada Yukinori
  • Journal Title: Nature Reviews Genetics Volume: - Issue: 8 Pages: 458-459
  • DOI: 10.1038/s41576-022-00482-9
  • Peer Reviewed / Open Access
• [Journal Article] Decoding the diversity of killer immunoglobulin-like receptors by deep sequencing and a high-resolution imputation method (2022)
  • Author(s): Sakaue S, Hosomichi K, Hirata J, Nakaoka H, Yamazaki K, Yawata M, Yawata N, Naito T, Umeno J, Kawaguchi T, Matsui T, Motoya S, Suzuki Y, Inoko H, Tajima A, Morisaki T, Matsuda K, Kamatani Y, Yamamoto K, Inoue I, Okada Y
  • Journal Title: Cell Genomics Volume: 2 Issue: 3 Pages: 100101-100101
  • DOI: 10.1016/j.xgen.2022.100101
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps (2021)
  • Author(s): Polygenic Risk Score Task Force of the International Common Disease Alliance
  • Journal Title: Nature Medicine Volume: 27 Issue: 11 Pages: 1876-1884
  • DOI: 10.1038/s41591-021-01549-6
  • Peer Reviewed / Int'l Joint Research
• [Journal Article] A high-resolution HLA reference panel capturing global population diversity enables multi-ancestry fine-mapping in HIV host response (2021)
  • Author(s): Luo Yang、Kanai Masahiro、...、Okada Yukinori、Han Buhm、McLaren Paul J.、Raychaudhuri Soumya
  • Journal Title: Nature Genetics Volume: 53 Issue: 10 Pages: 1504-1516
  • DOI: 10.1038/s41588-021-00935-7
  • Peer Reviewed / Int'l Joint Research
• [Journal Article] A deep learning method for HLA imputation and trans-ethnic MHC fine-mapping of type 1 diabetes (2021)
  • Author(s): Naito Tatsuhiko、Suzuki Ken、Hirata Jun、Kamatani Yoichiro、Matsuda Koichi、Toda Tatsushi、Okada Yukinori
  • Journal Title: Nature Communications Volume: 12 Issue: 1 Pages: 1639-1639
  • DOI: 10.1038/s41467-021-21975-x
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Trans‐Ethnic Fine‐Mapping of the Major Histocompatibility Complex Region Linked to Parkinson's Disease (2021)
  • Author(s): Naito Tatsuhiko、Satake Wataru、Ogawa Kotaro、Suzuki Ken、Hirata Jun、Foo Jia Nee、Tan Eng‐King、Toda Tatsushi、Okada Yukinori
  • Journal Title: Movement Disorders Volume: 36 Issue: 8 Pages: 1805-1814
  • DOI: 10.1002/mds.28583
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Population-specific causal disease effect sizes in functionally important regions impacted by selection (2021)
  • Author(s): Shi Huwenbo、Gazal Steven、Kanai Masahiro、Koch Evan M.、Schoech Armin P.、Siewert Katherine M.、Kim Samuel S.、Luo Yang、Amariuta Tiffany、Huang Hailiang、Okada Yukinori、Raychaudhuri Soumya、Sunyaev Shamil R.、Price Alkes L.
  • Journal Title: Nature Communications Volume: 12 Issue: 1 Pages: 1098-1098
  • DOI: 10.1038/s41467-021-21286-1
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power (2021)
  • Author(s): Atkinson Elizabeth G.、Maihofer Adam X.、Kanai Masahiro、Martin Alicia R.、Karczewski Konrad J.、Santoro Marcos L.、Ulirsch Jacob C.、Kamatani Yoichiro、Okada Yukinori、Finucane Hilary K.、Koenen Karestan C.、Nievergelt Caroline M.、Daly Mark J.、Neale Benjamin M.
  • Journal Title: Nature Genetics Volume: 53 Issue: 2 Pages: 195-204
  • DOI: 10.1038/s41588-020-00766-y
  • Peer Reviewed / Open Access / Int'l Joint Research