Looking beyond the exome: a phenotype-first approach to molecular diagnostic resolution in rare and undiagnosed diseases

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Abstract

Purpose

To describe examples of missed pathogenic variants on whole exome sequencing (WES) and the importance of deep phenotyping for further diagnostic testing.

Methods

Guided by phenotypic information, three children with negative WES underwent targeted single gene testing.

Results

Individual 1 had a clinical diagnosis consistent with infantile systemic hyalinosis, although WES and an NGS-based ANTXR2 test were negative. Sanger sequencing of ANTXR2 revealed a homozygous single base pair insertion, previously missed by the WES variant caller software. Individual 2 had neurodevelopmental regression and cerebellar atrophy, with no diagnosis on WES. New clinical findings prompted Sanger sequencing and copy number testing of PLA2G6. A novel homozygous deletion of the non-coding exon 1 (not included in the WES capture kit) was detected, with extension into the promoter, confirming the clinical suspicion of infantile neuroaxonal dystrophy. Individual 3 had progressive ataxia, spasticity and MRI changes of vanishing white matter leukoencephalopathy. An NGS leukodystrophy gene panel and WES showed a heterozygous pathogenic variant in EIF2B5; no deletions/duplications were detected. Sanger sequencing of EIF2B5 showed a frameshift indel, likely missed due to failure of alignment.

Conclusions

These cases illustrate potential pitfalls of WES/NGS testing, and the importance of phenotype-guided molecular testing in yielding diagnoses.

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Most cited references 12

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Clinical application of exome sequencing in undiagnosed genetic conditions

Anna C Need, Vandana Shashi, Yuki Hitomi … (2012)

Background There is considerable interest in the use of next-generation sequencing to help diagnose unidentified genetic conditions, but it is difficult to predict the success rate in a clinical setting that includes patients with a broad range of phenotypic presentations. Methods The authors present a pilot programme of whole-exome sequencing on 12 patients with unexplained and apparent genetic conditions, along with their unaffected parents. Unlike many previous studies, the authors did not seek patients with similar phenotypes, but rather enrolled any undiagnosed proband with an apparent genetic condition when predetermined criteria were met. Results This undertaking resulted in a likely genetic diagnosis in 6 of the 12 probands, including the identification of apparently causal mutations in four genes known to cause Mendelian disease (TCF4, EFTUD2, SCN2A and SMAD4) and one gene related to known Mendelian disease genes (NGLY1). Of particular interest is that at the time of this study, EFTUD2 was not yet known as a Mendelian disease gene but was nominated as a likely cause based on the observation of de novo mutations in two unrelated probands. In a seventh case with multiple disparate clinical features, the authors were able to identify homozygous mutations in EFEMP1 as a likely cause for macular degeneration (though likely not for other features). Conclusions This study provides evidence that next-generation sequencing can have high success rates in a clinical setting, but also highlights key challenges. It further suggests that the presentation of known Mendelian conditions may be considerably broader than currently recognised.

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Variant detection sensitivity and biases in whole genome and exome sequencing

Alison M Meynert, Morad Ansari, David FitzPatrick … (2014)

Background Less than two percent of the human genome is protein coding, yet that small fraction harbours the majority of known disease causing mutations. Despite rapidly falling whole genome sequencing (WGS) costs, much research and increasingly the clinical use of sequence data is likely to remain focused on the protein coding exome. We set out to quantify and understand how WGS compares with the targeted capture and sequencing of the exome (exome-seq), for the specific purpose of identifying single nucleotide polymorphisms (SNPs) in exome targeted regions. Results We have compared polymorphism detection sensitivity and systematic biases using a set of tissue samples that have been subject to both deep exome and whole genome sequencing. The scoring of detection sensitivity was based on sequence down sampling and reference to a set of gold-standard SNP calls for each sample. Despite evidence of incremental improvements in exome capture technology over time, whole genome sequencing has greater uniformity of sequence read coverage and reduced biases in the detection of non-reference alleles than exome-seq. Exome-seq achieves 95% SNP detection sensitivity at a mean on-target depth of 40 reads, whereas WGS only requires a mean of 14 reads. Known disease causing mutations are not biased towards easy or hard to sequence areas of the genome for either exome-seq or WGS. Conclusions From an economic perspective, WGS is at parity with exome-seq for variant detection in the targeted coding regions. WGS offers benefits in uniformity of read coverage and more balanced allele ratio calls, both of which can in most cases be offset by deeper exome-seq, with the caveat that some exome-seq targets will never achieve sufficient mapped read depth for variant detection due to technical difficulties or probe failures. As WGS is intrinsically richer data that can provide insight into polymorphisms outside coding regions and reveal genomic rearrangements, it is likely to progressively replace exome-seq for many applications. Electronic supplementary material The online version of this article (doi:10.1186/1471-2105-15-247) contains supplementary material, which is available to authorized users.

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Comparison of Exome and Genome Sequencing Technologies for the Complete Capture of Protein‐Coding Regions

Stefan Lelieveld, Malte Spielmann, Stefan Mundlos … (2015)

ABSTRACT For next‐generation sequencing technologies, sufficient base‐pair coverage is the foremost requirement for the reliable detection of genomic variants. We investigated whether whole‐genome sequencing (WGS) platforms offer improved coverage of coding regions compared with whole‐exome sequencing (WES) platforms, and compared single‐base coverage for a large set of exome and genome samples. We find that WES platforms have improved considerably in the last years, but at comparable sequencing depth, WGS outperforms WES in terms of covered coding regions. At higher sequencing depth (95x–160x), WES successfully captures 95% of the coding regions with a minimal coverage of 20x, compared with 98% for WGS at 87‐fold coverage. Three different assessments of sequence coverage bias showed consistent biases for WES but not for WGS. We found no clear differences for the technologies concerning their ability to achieve complete coverage of 2,759 clinically relevant genes. We show that WES performs comparable to WGS in terms of covered bases if sequenced at two to three times higher coverage. This does, however, go at the cost of substantially more sequencing biases in WES approaches. Our findings will guide laboratories to make an informed decision on which sequencing platform and coverage to choose.

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Author and article information

Journal

Journal ID (nlm-journal-id): 9815831

Journal ID (pubmed-jr-id): 22061

Journal ID (nlm-ta): Genet Med

Journal ID (iso-abbrev): Genet. Med.

Title: Genetics in medicine : official journal of the American College of Medical Genetics

ISSN (Print): 1098-3600

ISSN (Electronic): 1530-0366

Publication date Nihms-submitted: 13 July 2017

Publication date (Electronic): 14 September 2017

Publication date PMC-release: 15 March 2018

Electronic Location Identifier: 10.1038/gim.2017.128

Affiliations

[1 ]Division of Medical Genetics, Department of Pediatrics, Duke University Medical Center

[2 ]Institute of Genomic Medicine, Columbia University, New York, N.Y.

[3 ]Department of Pathology, Duke University Medical Center

[4 ]Division of Neurology, Department of Pediatrics, Duke University Medical Center

[5 ]Department of Ophthalmology, Duke University Medical Center

[6 ]Departments of Dermatology and Pediatrics, Duke University Medical Center

[7 ]Departments of Pediatrics and Surgery, Duke University Medical Center

[8 ]Division of Neuroradiology, Department of Radiology, Duke University Medical Center

[9 ]Division of Gastroenterology, Department of Pediatrics, Duke University Medical Center

[10 ]Division of Pediatric Nephrology, Department of Pediatrics, Duke University Medical Center

[11 ]Department of Orthopedic Surgery, Duke University Medical Center

[12 ]Division of Pediatric Hematology-Oncology, Department of Pediatrics, Duke University Medical Center

[13 ]Department of Human Genetics, University of Chicago, Chicago Ill

[14 ]Division of Maternal Fetal Medicine, University of Mississippi Medical Center, Jackson, Miss

[15 ]Division of Child Neurology, Department of Pediatrics, University of Mississippi Medical Center

[16 ]Division of Medical Genetics, Department of Pediatrics, University of Mississippi Medical Center

Author notes

[* ]Corresponding Author: Vandana Shashi, MD, Professor of Pediatrics, Division of Medical Genetics, Duke University Medical Center, Durham NC 27710, vandana.shashi@ 123456duke.edu , Fax: 919-668-0414, Tel: 919-681-2616

Article

Manuscript ID: NIHMS892188

DOI: 10.1038/gim.2017.128

PMC ID: 5851806

PubMed ID: 28914269

SO-VID: cf8856c3-1186-4d53-9393-44a38f1cc234

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Looking beyond the exome: a phenotype-first approach to molecular diagnostic resolution in rare and undiagnosed diseases

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Abstract

Purpose

Methods

Results

Conclusions

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Genes & Diseases

Most cited references 12

Clinical application of exome sequencing in undiagnosed genetic conditions

Variant detection sensitivity and biases in whole genome and exome sequencing

Comparison of Exome and Genome Sequencing Technologies for the Complete Capture of Protein‐Coding Regions

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