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Statistical Machine Learning in Population Genetics and Its Application to Infectious Disease Epidemiology

Research Project

Project/Area Number 23K21692
Project/Area Number (Other) 21H03490 (2021-2023)
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeMulti-year Fund (2024)
Single-year Grants (2021-2023)
Section一般
Review Section Basic Section 61030:Intelligent informatics-related
Research InstitutionHokkaido University

Principal Investigator

伊藤 公人  北海道大学, 人獣共通感染症国際共同研究所, 教授 (60396314)

Project Period (FY) 2021-04-01 – 2026-03-31
Project Status Granted (Fiscal Year 2024)
Budget Amount *help
¥16,770,000 (Direct Cost: ¥12,900,000、Indirect Cost: ¥3,870,000)
Fiscal Year 2025: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2024: ¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2023: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2022: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2021: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Keywords集団遺伝学 / 統計的機械学習 / 感染症疫学 / 感染症数理疫学 / SARS-CoV-2 / 機械学習 / インフルエンザ / 相対実効再生産数 / 変異株 / 流行予測 / 世代時間 / デルタ株 / オミクロン株 / COVID-19
Outline of Research at the Start

現在,新型コロナウイルスをはじめとする様々な感染症について,ウイルスのゲノム情報と感染者の疫学情報が急速に蓄積されている。集団遺伝学では,集団内の遺伝子の多様性により,集団内サイズの変化を推定する。一方,感染症疫学では,感染者数の時系列変化を基に再生産数を推定する。本研究では,集団遺伝学モデルと疫学モデルを融合し,変異ウイルスの集団に占める割合の時間変動をモデル化する。実際に観測される遺伝子データと疫学データを統計的機械学習により解析し,変異株の割合がどのように変化するかを予測する。予測した変異株の割合と観測データを比較し,予測の精度を検証する。

Outline of Annual Research Achievements

本研究では,遺伝子の多様性を表す集団遺伝学モデルに感染者数を表す疫学モデルを組み込み,ウイルスの多様性から感染者数や変異ウイルスの割合の時間変動を推定する手法を開発し,実際に観測される遺伝子データと疫学データを統計的機械学習により解析し,データ同化の手法を用いて感染者数や変異株の割合がどのように変化するかをリアルタイムに予測するとともに,予測の精度を検証することを目的としている。
2022年度までに変異株の従来株に対する相対実効再生産数を計算し,従来株から変異株への置き換わりを予測する手法を開発した。2023年度は,本手法をブラジルでのSARS-CoV-2変異株の置き換わりのデータに適用した。ブラジルでのガンマ株からデルタ株,デルタ株からオミクロンBA.1株への置き換わりを解析した結果,本手法により推定された相対実効再生産数は,Birth-Death-Skyline モデルで推定した実効再生産数の比とほぼ一致していることを明らかにした (Nat Comm, 2023)。また,同手法を用いて,ブラジルで流行するXBBの変異株を解析した結果, XBB+F486P株,XBB+F486P+F456L株,XBB+F486P+F456L+L455F株の他の流行株(主にBQ.1/BE株)に対する相対実効再生産数は,それぞれ1.24,1.33,1.48であることを明らかにした (Microbiol Spectr, 2024)。

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

SARS-CoV-2の変異株の割合がどのように変化するかをリアルタイムに予測する手法を確立し,各国のデータを用いて検証している。

Strategy for Future Research Activity

現在のモデルでは,変異株間の相対実効再生算数がすべて異なると仮定していた。この仮定を緩め,複数の株が同じ相対実効再生産数を持つことを許す数理モデルを構築し,効率的な最適モデルの探索アルゴリズムを開発する。

Report

(3 results)
  • 2023 Annual Research Report
  • 2022 Annual Research Report
  • 2021 Annual Research Report
  • Research Products

    (21 results)

All 2024 2023 2022 2021 Other

All Int'l Joint Research (4 results) Journal Article (14 results) (of which Int'l Joint Research: 6 results,  Peer Reviewed: 12 results,  Open Access: 13 results) Presentation (3 results) (of which Invited: 1 results)

  • [Int'l Joint Research] Oswaldo Cruz Foundation(ブラジル)

    • Related Report
      2023 Annual Research Report
  • [Int'l Joint Research] Iowa State University(米国)

    • Related Report
      2022 Annual Research Report
  • [Int'l Joint Research] Duke-NUS Medical School(シンガポール)

    • Related Report
      2022 Annual Research Report
  • [Int'l Joint Research] Instituto Oswaldo Cruz(ブラジル)

    • Related Report
      2022 Annual Research Report
  • [Journal Article] Extraction of the CDRH3 sequence of the mouse antibody repertoire selected upon influenza virus infection by subtraction of the background antibody repertoire2024

    • Author(s)
      Shingai Masashi、Iida Sayaka、Kawai Naoko、Kawahara Mamiko、Sekiya Toshiki、Ohno Marumi、Nomura Naoki、Handabile Chimuka、Kawakita Tomomi、Omori Ryosuke、Yamagishi Junya、Sano Kaori、Ainai Akira、Suzuki Tadaki、Ohnishi Kazuo、Ito Kimihito、Kida Hiroshi
    • Journal Title

      Journal of Virology

      Volume: 98 Issue: 3

    • DOI

      10.1128/jvi.01995-23

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Spatiotemporal dynamics and epidemiological impact of SARS-CoV-2 XBB lineage dissemination in Brazil in 20232024

    • Author(s)
      Arantes I, Gomes M, Ito K, Sarafim S, Graf T, Miyajima F, Khouri R, de Carvalho FC, de Almeida WAF, Siqueira MM, Resende PC, Naveca FG, Bello G; COVID-19 Fiocruz Genomic Surveillance Network
    • Journal Title

      Microbiology Spectrum

      Volume: 12 Issue: 3

    • DOI

      10.1128/spectrum.03831-23

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Link prediction on bipartite networks using matrix factorization with negative sample selection2023

    • Author(s)
      Peng S, Yamamoto A, Ito K
    • Journal Title

      PLOS ONE

      Volume: 18 Issue: 8 Pages: e0289568-e0289568

    • DOI

      10.1371/journal.pone.0289568

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Comparative epidemic expansion of SARS-CoV-2 variants Delta and Omicron in the Brazilian State of Amazonas2023

    • Author(s)
      Arantes I, Bello G, Nascimento V, Souza V, da Silva A, Silva D, Nascimento F, Mejia M, Brandao MJ, Goncalves L, Silva G, da Costa CF, Abdalla L, Santos JH, Ramos TCA, Piantham C, Ito K, Siqueira MM, Resende PC, Wallau GL, Delatorre E, Graf T, Naveca FG
    • Journal Title

      Nature Communications

      Volume: 14 Issue: 1

    • DOI

      10.1038/s41467-023-37541-6

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Predicting the Trajectory of Replacements of SARS-CoV-2 Variants Using Relative Reproduction Numbers2022

    • Author(s)
      Piantham C, Ito K.
    • Journal Title

      Viruses

      Volume: 14 Issue: 11 Pages: 2556-2556

    • DOI

      10.3390/v14112556

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Estimating relative generation times and reproduction numbers of Omicron BA.1 and BA.2 with respect to Delta variant in Denmark2022

    • Author(s)
      Ito Kimihito、Piantham Chayada、Nishiura Hiroshi
    • Journal Title

      Mathematical Biosciences and Engineering

      Volume: 19 Issue: 9 Pages: 9005-9017

    • DOI

      10.3934/mbe.2022418

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Targeted sampling reduces the uncertainty in force of infection estimates from serological surveillance2022

    • Author(s)
      Kim K, Ito K
    • Journal Title

      Frontiers in Veterinary Science

      Volume: 9 Pages: 754255-754255

    • DOI

      10.3389/fvets.2022.754255

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Inactivated whole influenza virus particle vaccines induce neutralizing antibodies with an increase in immunoglobulin gene subclones of B-lymphocytes in cynomolgus macaques2022

    • Author(s)
      Shiohara M、Suzuki Saori、Shichinohe S、Ishigaki H、Nakayama M、Nomura N、Shingai M、Sekiya T、Ohno M、Iida S、Kawai N、Kawahara M、Yamagishi J、Ito K、Mitsumata R、Ikeda T、Motokawa K、Sobue T、Kida H、Ogasawara K、Itoh Y
    • Journal Title

      Vaccine

      Volume: 40 Issue: 30 Pages: 4026-4037

    • DOI

      10.1016/j.vaccine.2022.05.045

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Relative instantaneous reproduction number of Omicron SARS‐CoV‐2 variant with respect to the Delta variant in Denmark2022

    • Author(s)
      Ito Kimihito、Piantham Chayada、Nishiura Hiroshi
    • Journal Title

      Journal of Medical Virology

      Volume: 94 Issue: 5 Pages: 2265-2268

    • DOI

      10.1002/jmv.27560

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Estimating relative generation times and relative reproduction numbers of Omicron BA.1 and BA.2 with respect to Delta in Denmark2022

    • Author(s)
      Ito Kimihito、Piantham Chayada、Nishiura Hiroshi
    • Journal Title

      medRxiv

      Volume: -

    • DOI

      10.1101/2022.03.02.22271767

    • Related Report
      2021 Annual Research Report
    • Open Access
  • [Journal Article] Predicting the time course of replacements of SARS-CoV-2 variants using relative reproduction numbers2022

    • Author(s)
      Piantham Chayada、Ito Kimihito
    • Journal Title

      medRxiv

      Volume: -

    • DOI

      10.1101/2022.03.30.22273218

    • Related Report
      2021 Annual Research Report
    • Open Access
  • [Journal Article] Predicted dominance of variant Delta of SARS-CoV-2 before Tokyo Olympic Games, Japan, July 20212021

    • Author(s)
      Ito Kimihito、Piantham Chayada、Nishiura Hiroshi
    • Journal Title

      Eurosurveillance

      Volume: 26 Issue: 27 Pages: 2100570-2100570

    • DOI

      10.2807/1560-7917.es.2021.26.27.2100570

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Relative Reproduction Number of SARS-CoV-2 Omicron (B.1.1.529) Compared with Delta Variant in South Africa2021

    • Author(s)
      Nishiura Hiroshi、Ito Kimihito、Anzai Asami、Kobayashi Tetsuro、Piantham Chayada、Rodr?guez-Morales Alfonso J.
    • Journal Title

      Journal of Clinical Medicine

      Volume: 11 Issue: 1 Pages: 30-30

    • DOI

      10.3390/jcm11010030

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Modeling the selective advantage of new amino acids on the hemagglutinin of H1N1 influenza viruses using their patient age distributions2021

    • Author(s)
      Piantham Chayada、Ito Kimihito
    • Journal Title

      Virus Evolution

      Volume: 7 Issue: 1

    • DOI

      10.1093/ve/veab049

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access
  • [Presentation] 相対再生産数を用いた新型コロナウイルス変異株の置き換わり予測2023

    • Author(s)
      伊藤公人
    • Organizer
      2023 年度(第33 回)日本数理生物学会大会企画シンポジウム
    • Related Report
      2023 Annual Research Report
  • [Presentation] 集団遺伝学による新型コロナウイルス変異株の流行予測2022

    • Author(s)
      伊藤公人
    • Organizer
      日本遺伝学会公開市民講座
    • Related Report
      2022 Annual Research Report
    • Invited
  • [Presentation] 集団遺伝学による新型コロナウイルス変異株の流行予測2021

    • Author(s)
      伊藤公人
    • Organizer
      第24回情報論的学習理論ワークショップ (IBIS2021)
    • Related Report
      2021 Annual Research Report

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Published: 2021-04-28   Modified: 2024-12-25  

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