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<p>While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we use artificial intelligence (AI) technologies to explore the predictive value of whole exome sequencing in forecasting clinical outcomes following surgery for congenital heart defects (CHD). We report results for a prospective observational cohort study of 2,253 CHD patients from the Pediatric Cardiac Genomics Consortium with a broad range of complex heart defects, pre- and post-operative clinical variables and exome sequencing. Damaging genotypes in chromatin-modifying and cilia-related genes are associated with an elevated risk of adverse post-operative outcomes, including mortality, cardiac arrest and prolonged mechanical ventilation. The impact of damaging genotypes is further amplified in the context of specific CHD phenotypes, surgical complexity and extra-cardiac anomalies. The absence of a damaging genotype in chromatin-modifying and cilia-related genes is also informative, reducing the risk for some adverse postoperative outcomes. Thus, genome sequencing enriches the ability to forecast outcomes following congenital cardiac surgery.</p>

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Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月10日

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  • W. Scott Watkins,
  • Edgar J. Hernandez,
  • Thomas A. Miller,
  • Nathan R. Blue,
  • Raquel Mae Zimmerman,
  • Eric R. Griffiths,
  • Erwin Frise,
  • Daniel Bernstein,
  • Marko T. Boskovski,
  • Martina Brueckner,
  • Wendy K. Chung,
  • J. William Gaynor,
  • Bruce D. Gelb,
  • Elizabeth Goldmuntz,
  • Peter J. Gruber,
  • Jane W. Newburger,
  • Amy E. Roberts,
  • Sarah U. Morton,
  • John E. Mayer Jr,
  • Christine E. Seidman,
  • Jonathan G. Seidman,
  • Yufeng Shen,
  • Michael Wagner,
  • H. Joseph Yost,
  • Mark Yandell,
  • Martin Tristani-Firouzi

摘要

While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we use artificial intelligence (AI) technologies to explore the predictive value of whole exome sequencing in forecasting clinical outcomes following surgery for congenital heart defects (CHD). We report results for a prospective observational cohort study of 2,253 CHD patients from the Pediatric Cardiac Genomics Consortium with a broad range of complex heart defects, pre- and post-operative clinical variables and exome sequencing. Damaging genotypes in chromatin-modifying and cilia-related genes are associated with an elevated risk of adverse post-operative outcomes, including mortality, cardiac arrest and prolonged mechanical ventilation. The impact of damaging genotypes is further amplified in the context of specific CHD phenotypes, surgical complexity and extra-cardiac anomalies. The absence of a damaging genotype in chromatin-modifying and cilia-related genes is also informative, reducing the risk for some adverse postoperative outcomes. Thus, genome sequencing enriches the ability to forecast outcomes following congenital cardiac surgery.