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DE-SC0025363: Genetic diversity of human heart responses to low-dose radiation

Award Status: Active
  • Institution: Board of Trustees of the Leland Stanford Junior University, Redwood City, CA
  • UEI: HJD6G4D6TJY5
  • DUNS: 009214214
  • Most Recent Award Date: 08/22/2024
  • Number of Support Periods: 1
  • PM: Kulkarni, Resham
  • Current Budget Period: 09/01/2024 - 08/31/2025
  • Current Project Period: 09/01/2024 - 08/31/2027
  • PI: Wu, Joseph
  • Supplement Budget Period: N/A
 

Public Abstract

                                                     Genetic Diversity of Human Heart Responses to Low-dose Radiation
Joseph C. Wu, MD, PhD, Professor, Stanford Cardiovascular Institute, Stanford University (Principal Investigator)
Adam J. Chicco, PhD, Professor, Department of Biomedical Sciences, Colorado State University (Co-Principal Investigator)
Michael M, Weil, PhD, Professor, Department of Environmental and Radiological Health Sciences, Colorado State University (Co-Principal Investigator)

The prediction and intervention of radiation-induced heart disease (RIHD) pose formidable challenges due to the multitude of individual-specific risk factors leading to diverse presentations. This study endeavors to overcome these challenges by generating comprehensive datasets aimed at unraveling the underlying genetic factors and identifying biomarkers associated with cardiac injury resulting from low-dose and low-dose-rate radiation exposures. Informed by previous investigations utilizing human induced pluripotent stem cell-derived engineered heart tissues (iPSC-EHTs) and animal models, our research focuses on oxidative stress, DNA damage, and mitochondrial dysfunction as pivotal contributors to radiogenic cardiac injury. Our approach entails the development of a "cell village" using an innovative computational methodology for parallel transcriptomic profiling in diverse patient populations of iPSC-derived cardiomyocytes (iPSC-CMs) following low-dose/dose-rate irradiation. Collectively, this study aims to establish a novel model system for systematic investigations into how human genetic diversity influences cellular responses to radiation exposure. Furthermore, the generated datasets and functional outcomes will contribute to elucidating the mechanisms of radiogenic cardiac injury and will be valuable for AI/ML analyses and sharing within the scientific community.


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