Opportunities and challenges for the integration of massively parallel genomic sequencing into clinical practice: lessons from the ClinSeq project

Genet Med. 2012 Apr;14(4):393-8. doi: 10.1038/gim.2011.78. Epub 2012 Feb 16.

Abstract

Purpose: The debate surrounding the return of results from high-throughput genomic interrogation encompasses many important issues including ethics, law, economics, and social policy. As well, the debate is also informed by the molecular, genetic, and clinical foundations of the emerging field of clinical genomics, which is based on this new technology. This article outlines the main biomedical considerations of sequencing technologies and demonstrates some of the early clinical experiences with the technology to enable the debate to stay focused on real-world practicalities.

Methods: These experiences are based on early data from the ClinSeq project, which is a project to pilot the use of massively parallel sequencing in a clinical research context with a major aim to develop modes of returning results to individual subjects.

Results: The study has enrolled >900 subjects and generated exome sequence data on 572 subjects. These data are beginning to be interpreted and returned to the subjects, which provides examples of the potential usefulness and pitfalls of clinical genomics.

Conclusion: There are numerous genetic results that can be readily derived from a genome including rare, high-penetrance traits, and carrier states. However, much work needs to be done to develop the tools and resources for genomic interpretation. The main lesson learned is that a genome sequence may be better considered as a health-care resource, rather than a test, one that can be interpreted and used over the lifetime of the patient.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, N.I.H., Intramural

MeSH terms

  • Biomedical Research / ethics
  • Biomedical Research / statistics & numerical data
  • Exome / genetics*
  • Genetics, Medical / ethics
  • Genetics, Medical / methods
  • Genetics, Medical / statistics & numerical data
  • Genome, Human / genetics*
  • Genomics / ethics
  • Genomics / statistics & numerical data*
  • Humans
  • Medical Informatics / ethics
  • Medical Informatics / methods
  • Medical Informatics / statistics & numerical data
  • Research Subjects
  • Researcher-Subject Relations / ethics
  • Sequence Analysis, DNA / ethics
  • Sequence Analysis, DNA / statistics & numerical data*
  • Truth Disclosure / ethics