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Original Investigation |

Clinical Interpretation and Implications of Whole-Genome Sequencing

Frederick E. Dewey, MD1,2,3,4; Megan E. Grove, MS1,2,3,4; Cuiping Pan, PhD4,5; Benjamin A. Goldstein, PhD6; Jonathan A. Bernstein, MD, PhD7; Hassan Chaib, PhD4,5; Jason D. Merker, MD, PhD8; Rachel L. Goldfeder, BS9; Gregory M. Enns, MB, ChB7; Sean P. David, MD, DPhil6; Neda Pakdaman, MD6; Kelly E. Ormond, MS5,10; Colleen Caleshu, MS1,2,3,7; Kerry Kingham, MS11; Teri E. Klein, PhD5; Michelle Whirl-Carrillo, PhD5; Kenneth Sakamoto, MD3,6; Matthew T. Wheeler, MD, PhD1,2,3,4; Atul J. Butte, MD, PhD7,12; James M. Ford, MD, PhD11; Linda Boxer, MD6; John P. A. Ioannidis, MD, PhD6,12,14,15; Alan C. Yeung, MD2,3; Russ B. Altman, MD, PhD5,6,16; Themistocles L. Assimes, MD, PhD2,3; Michael Snyder, PhD2,4,5; Euan A. Ashley, MRCP, DPhil1,2,3,4,5; Thomas Quertermous, MD1,2,3,4
[+] Author Affiliations
1Stanford Center for Inherited Cardiovascular Disease, Stanford, California
2Stanford Cardiovascular Institute, Stanford, California
3Division of Cardiovascular Medicine, Stanford University, Stanford, California
4Stanford Center for Genomics and Personalized Medicine, Stanford, California
5Department of Genetics, Stanford University, Stanford, California
6Department of Medicine, Stanford University, Stanford, California
7Department of Pediatrics, Stanford University, Stanford, California
8Department of Pathology, Stanford University, Stanford, California
9Biomedical Informatics Training Program, Stanford University, Stanford, California
10Stanford Center for Biomedical Ethics, Stanford, California
11Division of Medical Oncology, Stanford University, Stanford, California
12Division of Systems Medicine, Stanford University, Stanford, California
14Stanford Prevention Research Center, Stanford, California
15Department of Health Research and Policy, Stanford University, Stanford, California
16Department of Bioengineering, Stanford University, Stanford, California
JAMA. 2014;311(10):1035-1045. doi:10.1001/jama.2014.1717.
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Importance  Whole-genome sequencing (WGS) is increasingly applied in clinical medicine and is expected to uncover clinically significant findings regardless of sequencing indication.

Objectives  To examine coverage and concordance of clinically relevant genetic variation provided by WGS technologies; to quantitate inherited disease risk and pharmacogenomic findings in WGS data and resources required for their discovery and interpretation; and to evaluate clinical action prompted by WGS findings.

Design, Setting, and Participants  An exploratory study of 12 adult participants recruited at Stanford University Medical Center who underwent WGS between November 2011 and March 2012. A multidisciplinary team reviewed all potentially reportable genetic findings. Five physicians proposed initial clinical follow-up based on the genetic findings.

Main Outcomes and Measures  Genome coverage and sequencing platform concordance in different categories of genetic disease risk, person-hours spent curating candidate disease-risk variants, interpretation agreement between trained curators and disease genetics databases, burden of inherited disease risk and pharmacogenomic findings, and burden and interrater agreement of proposed clinical follow-up.

Results  Depending on sequencing platform, 10% to 19% of inherited disease genes were not covered to accepted standards for single nucleotide variant discovery. Genotype concordance was high for previously described single nucleotide genetic variants (99%-100%) but low for small insertion/deletion variants (53%-59%). Curation of 90 to 127 genetic variants in each participant required a median of 54 minutes (range, 5-223 minutes) per genetic variant, resulted in moderate classification agreement between professionals (Gross κ, 0.52; 95% CI, 0.40-0.64), and reclassified 69% of genetic variants cataloged as disease causing in mutation databases to variants of uncertain or lesser significance. Two to 6 personal disease-risk findings were discovered in each participant, including 1 frameshift deletion in the BRCA1 gene implicated in hereditary breast and ovarian cancer. Physician review of sequencing findings prompted consideration of a median of 1 to 3 initial diagnostic tests and referrals per participant, with fair interrater agreement about the suitability of WGS findings for clinical follow-up (Fleiss κ, 0.24; P < 001).

Conclusions and Relevance  In this exploratory study of 12 volunteer adults, the use of WGS was associated with incomplete coverage of inherited disease genes, low reproducibility of detection of genetic variation with the highest potential clinical effects, and uncertainty about clinically reportable findings. In certain cases, WGS will identify clinically actionable genetic variants warranting early medical intervention. These issues should be considered when determining the role of WGS in clinical medicine.

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Figure 1.
Overview of Whole-Genome Sequence Analysis Workflow for the Genomic Medicine Application Pilot Project (GMAPP)

Rare genetic variants were defined as alleles with frequency <0.01 in an ethnically matched population genetic survey. Inherited disease risk candidate identification and genetic drug response prediction are outlined in the Supplement. Abbreviations: ACMG, American College of Medical Genetics and Genomics; GMAPP, Genomic Medicine Application Pilot Project; SNV, single nucleotide variant; SV, structural variant.

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Figure 2.
Missing Coverage of 56 Genes the ACMG Recommends for Pathogenic Variant Discovery, Review, and Reporting in WGS

The percentage of exonic bases of genes for pathogenic variant discovery and reporting in genome and exome sequencing that were not covered by 10 or more reads. ACMG indicates American College of Medical Genetics and Genomics; WGS, whole-genome sequencing.

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Figure 3.
Genotype Concordance Between Whole-Genome Sequencing Platforms in 12 Participants Sequenced in the Genomic Medicine Application Pilot Project

A, Genotype concordance for all variant positions. B, Genotype concordance for variants in protein-coding regions. C, Genotype concordance for candidate inherited disease risk variants. Concordant refers to sequence variants with the same alleles and zygosity (ie, homozygous calls in both platforms) called by both platforms; discordant, refers to sequence variants called by both platforms but with different alleles or zygosity; and not called, sequence variants identified using the Illumina platform for which no variant genotype call was made by the Complete Genomics platform.

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