Distinguishing pathogenic mutations from background genetic noise in cardiology: The use of large genome databases for genetic interpretation

Clin Genet. 2018 Mar;93(3):459-466. doi: 10.1111/cge.13066. Epub 2017 Sep 18.

Abstract

Advances in clinical genetic testing have led to increased insight into the human genome, including how challenging it is to interpret rare genetic variation. In some cases, the ability to detect genetic mutations exceeds the ability to understand their clinical impact, limiting the advantage of these technologies. Obstacles in genomic medicine are many and include: understanding the level of certainty/uncertainty behind pathogenicity determination, the numerous different variant interpretation-guidelines used by clinical laboratories, delivering the certain or uncertain result to the patient, helping patients evaluate medical decisions in light of uncertainty regarding the consequence of the findings. Through publication of large publicly available exome/genome databases, researchers and physicians are now able to highlight dubious variants previously associated with different cardiac traits. Also, continuous efforts through data sharing, international collaborative efforts to develop disease-gene-specific guidelines, and computational analyses using large data, will indubitably assist in better variant interpretation and classification. This article discusses the current, and quickly changing, state of variant interpretation resources within cardiovascular genetic research, e.g., publicly available databases and ways of how cardiovascular genetic counselors and geneticists can aid in improving variant interpretation in cardiology.

Keywords: ClinGen; false-positive; genetics; inherited cardiac disease; long QT syndrome; online databases.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Databases, Genetic
  • Ethnicity / genetics
  • Exome
  • Genetic Association Studies*
  • Genetic Background*
  • Genetic Predisposition to Disease*
  • Genetic Testing
  • Genome, Human
  • Genomics / methods
  • Heart Diseases / diagnosis*
  • Heart Diseases / genetics*
  • Humans
  • Mutation*
  • Web Browser