Development of Mathematical Model of hiPSC-CMs for Drug Discovery and Analysis of Genetic Diseases

• Project/Area Number: 19K17560
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 53020:Cardiology-related
• Research Institution: Kyoto University
• Principal Investigator: Kohjitani Hirohiko 京都大学, 医学研究科, 特定助教 (90823013)
• Project Period (FY): 2019-04-01 – 2023-03-31
• Project Status: Completed (Fiscal Year 2022)
• Budget Amount: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000); Fiscal Year 2020: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000); Fiscal Year 2019: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
• Keywords: コンピュータ・シミュレーション / 数理モデル / hiPSC-CMs / イオンチャネル / 数理最適化 / 機械学習 / 数理モデリング / パッチクランプ / ペースメーカー機転 / ヒトiPS細胞由来分化心筋 / 安全性薬理試験

Outline of Research at the Start

創薬において治療候補薬の心毒性を確認する試験として、動物や非心筋培養細胞を用いた実験が行われているが、ヒト心筋とは異なるため、より人体により近いヒトiPS細胞由来分化心筋を用いた研究が進んでいる。しかし、分化心筋は幼若で性質のばらつきが多いため臨床応用の妨げとなっている。
本研究では、正確にヒトiPS細胞由来分化心筋における電気生理学的動態を解析し、創薬や遺伝性不整脈疾患研究における研究応用を加速するため、性質のばらつきをAI技術の一部である数理最適化手法やディープラーニングを用いて解析・補正する数理システム（コンピュータ・シミュレーションシステム）の構築を行う。

Outline of Final Research Achievements

This research project achieved the development of a simulation model that reproduces action potential waveforms (APs) in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). By adjusting the ionic conductance (Gx), cell-specific models were constructed to generate APs that overlap with actual recorded data. A pattern search optimization method was employed, and by decreasing the mean square error (MSE), it was confirmed that the population of Gx values converged to the vicinity of the correct values for the cell-specific models.
We successfully constructed precise simulation models by optimizing parameters in electrophysiological biological simulation models, thereby contributing to groundbreaking advancements in the understanding and application of cellular electrophysiology and cardiac electrical phenomena.

Academic Significance and Societal Importance of the Research Achievements

本研究の学術的意義は、hiPSC-CMsの活動電位波形を再現する精密なシミュレーションモデルの開発に成功し、またこれまで困難とされていた電気生理学的生体シミュレーションモデルのパラメータ最適化による精密なシミュレーションモデルの実現可能性を示した点と考える。本モデル・手法を用いて創薬研究や個別化された治療法の開発が促進されることで、より効果的で安全な治療法の実現が可能となり、心臓病の診断や治療における新たなアプローチの提供が可能になること、心臓病による死亡率の低下や医療費の削減につながることが期待される点が社会的意義であると考えられる。

Research Products

• [Journal Article] Disrupted CaV1.2 selectivity causes overlapping long QT and Brugada syndrome phenotypes in the CACNA1C-E1115K iPS cell model (2023)
  • Author(s): Kashiwa A、Makiyama T、Kohjitani H、Maurissen T L、Ishikawa T、Yamamoto Y、Wuriyanghai Y、Gao J、Huang H、Imamura T、Aizawa T、Nishikawa M、Chonabayashi K、Mishima H、Ohno S、Toyoda F、Sato S、Yoshiura K、Takahashi K、Yoshida Y、Woltjen K、Horie M、Makita N、Kimura T
  • Journal Title: Heart Rhythm Volume: 20 Issue: 1 Pages: 89-99
  • DOI: 10.1016/j.hrthm.2022.08.021
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Gradient-based parameter optimization method to determine membrane ionic current composition in human induced pluripotent stem cell-derived cardiomyocytes (2022)
  • Author(s): Kohjitani Hirohiko、Koda Shigeya、Himeno Yukiko、Makiyama Takeru、Yamamoto Yuta、Yoshinaga Daisuke、Wuriyanghai Yimin、Kashiwa Asami、Toyoda Futoshi、Zhang Yixin、Amano Akira、Noma Akinori、Kimura Takeshi
  • Journal Title: Scientific Reports Volume: 12 Issue: 1 Pages: 19110-19110
  • DOI: 10.1038/s41598-022-23398-0
  • Peer Reviewed / Open Access
• [Presentation] Development of a Genetic Prognostic Model for Hereditary Arrhythmia Disease Using Machine Learning (2022)
  • Author(s): Hirohiko Kohjitani, Takeshi Mitani, Takanori Aizawa, Takeru Makiyama, Asami Kashiwa, Tomohiko Imamura, Seiko Ohno, Minoru Horie, Satoshi Shizuta, Takeshi Kimura, Yasushi Okuno
  • Organizer: 第68回日本不整脈心電学会学術大会 パシフィコ横浜 2022/6/9
• [Presentation] Development of a Genetic Prognostic Model for Hereditary Arrhythmia Disease Using Machine Learning (2022)
  • Author(s): Hirohiko Kohjitani, Takeshi Mitani, Takanori Aizawa, Takeru Makiyama, Asami Kashiwa, Tomohiko Imamura, Seiko Ohno, Minoru Horie, Satoshi Shizuta, Takeshi Kimura, Yasushi Okuno
  • Organizer: 第86回日本循環器学会学術集会. 2022/3/11. Web
• [Presentation] Current Perspective on Precision Medicine of Inherited Arrhythmias Modeling Inherited Arrhythmias Associated with Ryanodine Receptor Dysfunction Using iPS Cells (2022)
  • Author(s): Makiyama Takeru, Gao Jingshan, Yamamoto Yuta, Kashiwa Asami, Aizawa Takanori, Imamura Tomohiko, Huang Hai, Kohjitani Hirohiko, Kato Kouichi, Ishikawa Taisuke, Aoki Hisaaki, Toyoda Futoshi, Wolten Knut, Yoshida Yoshinori, Ohno Seiko, Makita Naomasa, Kimura Takeshi
  • Organizer: 第85回日本循環器学会学術集会. 2022/3/26. Web
• [Presentation] Development of a Genetic Prognostic Model for Hereditary Arrhythmia Disease Using Machine Learning． (2022)
  • Author(s): Hirohiko Kohjitani, Takeshi Mitani, Takanori Aizawa, Takeru Makiyama, Asami Kashiwa, Tomohiko Imamura, Seiko Ohno, Minoru Horie, Satoshi Shizuta, Takeshi Kimura, Yasushi Okuno．
  • Organizer: 第86回日本循環器学会学術集会.
• [Presentation] sefulness of Collaboration Between Mathematical Models and Cell Engineering for Elucidating Complex Disease Mechanisms and Discover Effective Drugs． (2021)
  • Author(s): Hirohiko Kohjitani, Asami Kashiwa, Takeru Makiyama, Taisuke Ishikawa, Futoshi Toyoda, Seiko Ohno, Hai Huang, Jingshan Gao, Tomohiko Imamura, Takanori Aizawa, Satoshi Shizuta, Minoru Horie, Naomasa Makita, Takeshi Kimura
  • Organizer: 第67回日本不整脈心電学会学術集会．
• [Presentation] Usefulness of Collaboration Between Mathematical models and Cell Engineering. for Elucidating Complex Disease Mechanisms and Discover Effective Drugs. (2020)
  • Author(s): Hirohiko Kohjitani, Asami Kashiwa, Takeru Makiyama, Takeshi Kimura, et al.
  • Organizer: ESC Congress 2020
  • Int'l Joint Research
• [Presentation] Artificial Intelligence Based Optimization System of hiPSC-CMs Simulation and Prediction of Drug Testing. (2020)
  • Author(s): Kohjitani H, Koda S, Makiyama T, Noma A, Kimura T, el al.
  • Organizer: Heart Rhythm Scientific Sessions 2020
  • Int'l Joint Research
• [Presentation] Artificial Intelligence Based Optimization System for Cell-specific hiPSC-CMs Simulation and Prediction of Drug Testing. (2020)
  • Author(s): Hirohiko Kohjitani, Takeru Makiyama, Takeshi Kimura, et al.
  • Organizer: 第84回日本循環器学会学術集会
• [Presentation] Usefulness of Combination of Mathematical models and Cell Engineering Using Induced Pluripotent Stem Cell for Revealing Complex Disease Mechanisms. (2020)
  • Author(s): 糀谷泰彦, 柏麻美, 牧山武, 木村 剛
  • Organizer: 第84回日本循環器学会学術集会
• [Presentation] Modeling Overlap Syndrome Of Long QT And Brugada Syndrome Associated With CACNA1C-E1115K Which Alters Ion Selectivity With Induced Pluripotent Stem Cells. (2019)
  • Author(s): Asami Kashiwa, Hirohiko Kohjitani, Takeshi Kimura, et al.
  • Organizer: Heart Rhythm Scientific Sessions
  • Int'l Joint Research
• [Presentation] Autonomic Action Potential Analyzing System Enables Accurate Interpretation and Prediction of Result for Drug Testing Using hiPSC-CMs. (2019)
  • Author(s): Hirohiko Kohjitani, Yukiko Himeno, Takeru Makiyama, Akinori Noma, et al.
  • Organizer: Heart Rhythm Scientific Sessions
  • Int'l Joint Research
• [Presentation] Algorithmic Auto-Recreation System of hiPSC-CMs Simulation and Prediction of Drug Testing. (2019)
  • Author(s): Hirohiko Kohjitani, Yukiko Himeno, Takeru Makiyama, Akinori Noma, et al.
  • Organizer: 12th ASIA PACIFIC HEART RHYTHM SOCIETY SCIENTIFIC SESSION (APHRS 2019)
  • Int'l Joint Research
• [Presentation] Algorithmic Auto-Recreation System of hiPSC-CMs Simulation and Prediction of Drug Testing. (2019)
  • Author(s): Hirohiko Kohjitani, Yukiko Himeno, Takeru Makiyama, Akinori Noma, et al.
  • Organizer: 第 66 回 日本不整脈心電学会学術大会
• [Presentation] Modeling Overlapping Phenotypes of Long-QT and Brugada Syndrome with CACNA1C-E1115K which Alters Ion Selectivity of the Cardiac L-type Calcium Channel Using Induced Pluripotent Stem Cells. (2019)
  • Author(s): Asami Kashiwa, Hirohiko Kohjitani, Takeshi Kimura, et al.
  • Organizer: 第 66 回 日本不整脈心電学会学術大会