Recommendations and Guidelines for the Analytical Validation of Whole Genome Sequencing in Clinical Laboratories

BACKGROUND

Whole genome sequencing (WGS) is poised to become a first-tier diagnostic test for patients with rare genetic disorders. However, professional society guidelines and standards addressing the definition and deployment practice of a best-in-class test are lacking. 

To address these gaps, the Medical Genome Initiative (MGI), a consortium of leading healthcare and research organizations in the U.S. and Canada, was formed to expand access to high-quality clinical WGS by publishing best practices.2 The main goal and mission of MGI is to expand access to high-quality clinical whole genome sequencing (WGS) for the diagnosis of genetic diseases, through the publication of common laboratory and clinical best practices.

Recently, MGI members published detailed guidelines to address key issues encountered during the clinical validation of WGS. The article presents consensus recommendations on the analytical validation of clinical WGS for the diagnosis of individuals with suspected germline disease. In addition, the article has a focus on test development, upfront considerations for test design, test validation practices, and metrics to monitor test performance. This work also provides insight into the current state of WGS testing at each member’s institution, including the utilization of reference and other standards across sites. 

The focus of this manuscript is the primary and secondary analyses, which are the steps that directly relate to the evaluation of test performance for the analytical validation of clinical WGS. Elements critical to establishing analytical validity are described primarily in three sections:

  1. Test development and optimization
  2. Test validation
  3. Ongoing quality management of the test in clinical use

Major steps and activities in the analytical validation are shown in the figure to the right.1

SUMMARY

WGS has been gradually adopted as a mainstream technology to help diagnose individuals with a suspected genetic disease. In addition, WGS is capable of detecting most classes of clinically relevant genetic variations, including single nucleotide variants (SNV), small deletions, duplications, insertions (indels), structural variation (SV), copy number variations (CNV), balanced rearrangements, mitochondrial variants, and repeat expansions. While studies are still ongoing to determine detection accuracy of all these variant classes, MGI recommends SNVs, indels, and CNVs as a viable minimally appropriate set of variants for WGS. 

Furthermore, members of this initiative strongly believe that clinical WGS is an appropriate first-tier test for patients with rare genetic disorders. At minimum, members believe WGS is ready to replace chromosomal microarray analysis and whole exome sequencing. The recommendations presented by MGI should reduce the burden on laboratories introducing WGS into clinical practice, as well as support safe and effective WGS testing for diagnosis of germline disease.

BG’S CONTRIBUTION TO MGI

Dr. Shashikant Kulkarni, Chief Scientific Officer of Emerging Business and Innovation at Baylor Genetics; Professor and Vice Chairman of Research Affairs of Molecular and Human Genetics at Baylor College of Medicine, currently serves as a chairperson of MGI. Dr. Pengfei Liu, Associate Clinical Director at Baylor Genetics, has also contributed towards these guidelines. 

References
  1. Marshall, C.R., Bick, D., Belmont, J.W. et al. The Medical Genome Initiative: moving whole-genome sequencing for rare disease diagnosis to the clinic. Genome Med 12, 48 (2020). https://doi.org/10.1186/s13073-020-00748-z
  2. Marshall, C.R., Chowdhury, S., Taft, R.J. et al. Best practices for the analytical validation of clinical whole-genome sequencing intended for the diagnosis of germline disease. npj Genom. Med. 5, 47 (2020). https://doi.org/10.1038/s41525-020-00154-9
  3. Hayeems, R.Z., Dimmock, D., Bick, D. et al. Clinical utility of genomic sequencing: a measurement toolkit. npj Genom. Med. 5, 56 (2020). https://doi.org/10.1038/s41525-020-00164-7 

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