Analyzing and Reanalyzing the Genome: Findings from the MedSeq Project

Am J Hum Genet. 2019 Jul 3;105(1):177-188. doi: 10.1016/j.ajhg.2019.05.017. Epub 2019 Jun 27.

Abstract

Although genome sequencing is increasingly available in clinical and research settings, many questions remain about the interpretation of sequencing data. In the MedSeq Project, we explored how much effort is required to evaluate and report on more than 4,500 genes reportedly associated with monogenic conditions, as well as pharmacogenomic (PGx) markers, blood antigen serotyping, and polygenic risk scores in 100 individuals (50 with cardiomyopathy and 50 healthy) randomized to the sequencing arm. We defined the quality thresholds for determining the need for Sanger confirmation. Finally, we examined the effort needed and new findings revealed by reanalyzing each genome (6-23 months after initial analysis; mean 13 months). Monogenic disease risk and carrier status were reported in 21% and 94% of participants, respectively. Only two participants had no monogenic disease risk or carrier status identified. For the PGx results (18 genotypes in six genes for five drugs), the identified diplotypes prompted recommendation for non-standard dosing of at least one of the analyzed drugs in 95% of participants. For blood antigen studies, we found that 31% of participants had a rare blood antigen genotype. In the cardiomyopathy cohort, an explanation for disease was identified in 48% of individuals. Over the course of the study, 14 variants were reclassified and, upon reanalysis, 18 new variants met criteria for reporting. These findings highlight the quantity of medically relevant findings from a broad analysis of genomic sequencing data as well as the need for periodic reinterpretation and reanalysis of data for both diagnostic indications and secondary findings.

Keywords: MedSeq; clinical genomes; genome; genomic interpretation; reanalysis; secondary findings; sequencing.

Publication types

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

MeSH terms

  • Cardiomyopathies / genetics*
  • Cardiomyopathies / pathology
  • Case-Control Studies
  • Computational Biology / methods*
  • Data Interpretation, Statistical*
  • Family
  • Female
  • Genetic Predisposition to Disease*
  • Genetic Variation*
  • Genome, Human*
  • Humans
  • Male
  • Multifactorial Inheritance
  • Randomized Controlled Trials as Topic
  • Sequence Analysis, DNA / statistics & numerical data*
  • Whole Genome Sequencing