Inherited cardiovascular conditions: Phenotype-genotype data mining and sharing, and databases

J. Peter van Tintelen*, Paul A. van der Zwaag

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

With the advances of genetics in cardiovascular disease, increasingly more information on genetics and its associated phenotypes is becoming available, often online. The physician dealing with cardiovascular genetic disorders has to be able to interpret genetic test results and implement this in patient care including genetic counseling, risk assessment and, possibly personalized, treatment. To be able to navigate through the online resources available, we summarized some databases and online tools on the interpretation of genetic variants; i.e. databases that assess the pathogenicity using in silico computional models, databases with data on the presence of variants in control populations and disease or gene specific databases that summarize variants and its associated phenotypes. In addition to these variant-interpretation databases, databases to aid the clinician in making a diagnosis, predicting a positive genetic test or risk assessment are summarized. Finally websites that facilitate data-sharing are mentioned. Even though these tools are very useful, one has to be aware that online data are not always up-to-date and the interpretation of data that are used, especially in patient care, always need a critical review. This should be considered a multidisciplinary teams effort that involve amongst others cardiologists, clinical and molecular geneticists, and genetic counselors.

Original languageEnglish
Title of host publicationCardiovascular Genetics and Genomics
Subtitle of host publicationPrinciples and Clinical Practice
PublisherSpringer
Pages869-877
Number of pages9
ISBN (Electronic)9783319661148
ISBN (Print)9783319661124
DOIs
Publication statusPublished - 17 Jan 2018
Externally publishedYes

Keywords

  • Data-sharing
  • Database
  • Genetics
  • Mutation
  • On-line tools
  • Pathogenicity

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