One in seven pathogenic variants can be challenging to detect by NGS: an analysis of 450,000 patients with implications for clinical sensitivity and genetic test implementation

Stephen E Lincoln,Marc Salit,Shimul Chowdhury,Shazia Mahamdallie,Matthew J Ferber,Chen Huang ,Russell Garlick ,Kathryn E Hatchell ,Swaroop Aradhya,Sara L Bristow,Wasanthi Desilva,Tina Hambuch,Andrew Fellowes,Michael Kennemer,Rebecca Truty,Nazneen Rahman,Sheila Seal,Peter M Vallone,Farol L Tomson,Eric W Klee,Justin M Zook,Brian H Shirts,Megan H Cleveland,Yan Ding,Stephen F Kingsmore,Robert L Nussbaum

doi:10.1038/s41436-021-01187-w

Abstract

PurposeTo evaluate the impact of technically challenging variants on the implementation, validation, and diagnostic yield of commonly used clinical genetic tests. Such variants include large indels, small copy-number variants (CNVs), complex alterations, and variants in low-complexity or segmentally duplicated regions. MethodsAn interlaboratory pilot study used synthetic specimens to assess detection of challenging variant types by various next-generation sequencing (NGS)–based workflows. One well-performing workflow was further validated and used in clinician-ordered testing of more than 450,000 patients. ResultsIn the interlaboratory study, only 2 of 13 challenging variants were detected by all 10 workflows, and just 3 workflows detected all 13. Limitations were also observed among 11 less-challenging indels. In clinical testing, 21.6% of patients carried one or more pathogenic variants, of which 13.8% (17,561) were classified as technically challenging. These variants were of diverse types, affecting 556 of 1,217 genes across hereditary cancer, cardiovascular, neurological, pediatric, reproductive carrier screening, and other indicated tests. ConclusionThe analytic and clinical sensitivity of NGS workflows can vary considerably, particularly for prevalent, technically challenging variants. This can have important implications for the design and validation of tests (by laboratories) and the selection of tests (by clinicians) for a wide range of clinical indications.

Highlights

Clinical genetic tests based on next-generation sequencing (NGS) are increasingly used to aid diagnosis and inform patient care.[1]
An interlaboratory study was conducted both to reinforce our understanding of the impact of different NGS methodologies on challenging variant types, and to evaluate whether synthetic positive controls are a useful tool for the development and validation of methods to detect such variants
Manual review using Integrative Genomics Viewer (IGV) demonstrated that evidence of the missed variants was visible in most of the raw data sets, indicating that the sensitivity limitations were largely bioinformatic in nature

Summary

Introduction

Clinical genetic tests based on next-generation sequencing (NGS) are increasingly used to aid diagnosis and inform patient care.[1]. Conventional short-read NGS methods have wellknown limitations that can allow certain technically challenging variants—such as large indels, small CNVs, and complex alterations—to remain undetected, at least without the application of specialized bioinformatic and biochemical methodologies.[9,10,11]. Even simple SNVs and indels in segmentally duplicated (segdup) or low-complexity genomic regions can present substantial challenges.[12,13,14,15]. The impact of such technically challenging variants on the implementation, validation, and diagnostic yield of commonly used clinical genetic tests has not yet been thoroughly described

Methods

Results

Conclusion