Comprehensive use of extended exome analysis improves diagnostic yield in rare disease: a retrospective survey in 1,059 cases

Abstract Background Whole-exome sequencing (WES) has become an efficient diagnostic test for patients with likely monogenic conditions such as rare idiopathic diseases or sudden unexplained death. Yet, many cases remain undiagnosed. Here, we report the added diagnostic yield achieved for 101 WES cases re-analyzed 1 to 7 years after initial analysis. Methods Of the 101 WES cases, 51 were rare idiopathic disease cases and 50 were postmortem “molecular autopsy” cases of early sudden unexplained death. Variants considered for reporting were prioritized and classified into three groups: (1) diagnostic variants, pathogenic and likely pathogenic variants in genes known to cause the phenotype of interest; (2) possibly diagnostic variants, possibly pathogenic variants in genes known to cause the phenotype of interest or pathogenic variants in genes possibly causing the phenotype of interest; and (3) variants of uncertain diagnostic significance, potentially deleterious variants in genes possibly causing the phenotype of interest. Results Initial analysis revealed diagnostic variants in 13 rare disease cases (25.4%) and 5 sudden death cases (10%). Re-analysis resulted in the identification of additional diagnostic variants in 3 rare disease cases (5.9%) and 1 sudden unexplained death case (2%), which increased our molecular diagnostic yield to 31.4% and 12%, respectively. Conclusions The basis of new findings ranged from improvement in variant classification tools, updated genetic databases, and updated clinical phenotypes. Our findings highlight the potential for re-analysis to reveal diagnostic variants in cases that remain undiagnosed after initial WES.

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Increasing diagnostic yield by RNA-Sequencing in rare disease—bypass hurdles of interpreting intronic or splice-altering variants

Annals of Translational Medicine ◽

10.21037/atm.2018.01.14 ◽

2018 ◽

Vol 6 (7) ◽

pp. 126-126 ◽

Cited By ~ 4

Author(s):

Dong Li ◽

Lifeng Tian ◽

Hakon Hakonarson

Keyword(s):

Rare Disease ◽

Rna Sequencing ◽

Diagnostic Yield

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Robust diagnostic yield and candidate gene discovery through paired exome analysis in vascular malformation and overgrowth

Molecular Genetics and Metabolism ◽

10.1016/s1096-7192(21)00441-8 ◽

2021 ◽

Vol 132 ◽

pp. S232

Author(s):

Catherine Cottrell ◽

Bhuvana Setty ◽

Anna Lillis ◽

Ibrahim Khansa ◽

Gregory Pearson ◽

...

Keyword(s):

Candidate Gene ◽

Vascular Malformation ◽

Diagnostic Yield ◽

Gene Discovery ◽

Exome Analysis

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Beyond Panel-Based Testing: Exome Analysis Increases Sensitivity for Diagnosis of Genetic Kidney Disease

Kidney360 ◽

10.34067/kid.0001342020 ◽

2020 ◽

Vol 1 (8) ◽

pp. 772-780 ◽

Cited By ~ 2

Author(s):

Parker C. Wilson ◽

Latisha Love-Gregory ◽

Meagan Corliss ◽

Samantha McNulty ◽

Jonathan W. Heusel ◽

...

Keyword(s):

Kidney Disease ◽

Diagnostic Yield ◽

Pathogenic Variant ◽

Gene Panel ◽

Cystic Kidney Disease ◽

Cystic Kidney ◽

Genetic Kidney Disease ◽

Exome Analysis ◽

Clinically Significant ◽

Gene Panels

BackgroundNext-generation sequencing (NGS) is a useful tool for evaluating patients with suspected genetic kidney disease. Clinical practice relies on the use of targeted gene panels that are ordered based on patient presentation. We compare the diagnostic yield of clinical panel-based testing to exome analysis.MethodsIn total, 324 consecutive patients underwent physician-ordered, panel-based NGS testing between December 2014 and October 2018. Gene panels were available for four clinical phenotypes, including atypical hemolytic uremic syndrome (n=224), nephrotic syndrome (n=56), cystic kidney disease (n=26), and Alport syndrome (n=13). Variants were analyzed and clinical reports were signed out by a pathologist or clinical geneticist at the time of testing. Subsequently, all patients underwent retrospective exome analysis to detect additional clinically significant variants in kidney disease genes that were not analyzed as part of the initial clinical gene panel. Resulting variants were classified according to the American College of Medical Genetics and Genomics 2015 guidelines.ResultsIn the initial physician-ordered gene panels, we identified clinically significant pathogenic or likely pathogenic variants in 13% of patients (n=42/324). CFHR3-CFHR1 homozygous deletion was detected in an additional 13 patients with aHUS without a pathogenic or likely pathogenic variant. Diagnostic yield of the initial physician-ordered gene panel was 20% and varied between groups. Retrospective exome analysis identified 18 patients with a previously unknown pathogenic or likely pathogenic variant in a kidney disease gene and eight patients with a high-risk APOL1 genotype. Overall, retrospective exome analysis increased the diagnostic yield of panel-based testing from 20% to 30%.ConclusionsThese results highlight the importance of a broad and collaborative approach between the clinical laboratory and their physician clients that employs additional analysis when a targeted panel of kidney disease–causing genes does not return a clinically meaningful result.

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Automated application of novel gene-disease associations to scale reanalysis of undiagnosed patients

10.1101/2020.10.16.20212852 ◽

2020 ◽

Author(s):

Nana E. Mensah ◽

Ataf H. Sabir ◽

Andrew Bond ◽

Wendy Roworth ◽

Melita Irving ◽

...

Keyword(s):

Rare Disease ◽

Diagnostic Yield ◽

Genomic Medicine ◽

Molecular Testing ◽

Clinical Services ◽

The Public ◽

Novel Gene ◽

Spondylometaphyseal Dysplasia ◽

Disease Associations ◽

New Gene

AbstractA pressing challenge for genomic medicine services is to increase the diagnostic rate of molecular testing. Reanalysis of genomic data can increase the diagnostic yield of molecular testing for rare diseases by 5.9-47% and novel gene-disease associations are often cited as the catalyst for significant findings. However, clinical services lack adequate resources to conduct routine reanalysis for unresolved cases. To determine whether an automated application could lead to new diagnoses and streamline routine reanalysis, we developed TierUp. TierUp identifies new gene-disease associations with implications for unresolved rare disease cases recruited to the 100,000 Genomes Project. TierUp streams data from the public PanelApp database to enable routine, up-to-date reanalyses. When applied to 948 undiagnosed rare disease cases, TierUp highlighted 410 high and moderate impact variants in under 77 minutes, reducing the burden of variants for review with this reanalysis strategy by 99%. Ongoing variant interpretation has produced five follow-up clinical reports, including a molecular diagnosis of a rare form of spondylometaphyseal dysplasia. We recommend that clinical services leverage bioinformatics expertise to develop automated reanalysis tools. Additionally, we highlight the need for studies focused on the ethical, legal and health economics considerations raised by automated reanalysis tools.

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