A comprehensive iterative approach is highly effective in diagnosing individuals who are exome negative

Undiagnosed Diseases Network, Vandana Shashi, Kelly Schoch, Rebecca Spillmann, Heidi Cope, Queenie K.G. Tan, Nicole Walley, Loren Pena, Allyn McConkie-Rosell, Yong Hui Jiang, Nicholas Stong, Anna C. Need, David B. Goldstein, David R. Adams, Mercedes E. Alejandro, Patrick Allard, Euan A. Ashley, Mahshid S. Azamian, Carlos A. Bacino, Ashok Balasubramanyam & 31 others Hayk Barseghyan, Gabriel F. Batzli, Alan H. Beggs, Babak Behnam, Hugo J. Bellen, Jonathan A. Bernstein, Anna Bican, David P. Bick, Camille L. Birch, Devon Bonner, Braden E. Boone, Bret L. Bostwick, Lauren C. Briere, Donna M. Brown, Matthew Brush, Elizabeth A. Burke, Lindsay C. Burrage, Manish J. Butte, Shan Chen, Gary D. Clark, Terra R. Coakley, Joy D. Cogan, Cynthia M. Cooper, Heidi Cope, William J. Craigen, Precilla D’Souza, Mariska Davids, Jean M. Davidson, Jyoti G. Dayal, Melissa Haendel, David M. Koeller

Research output: Contribution to journalArticle

Abstract

Purpose: Sixty to seventy-five percent of individuals with rare and undiagnosed phenotypes remain undiagnosed after exome sequencing (ES). With standard ES reanalysis resolving 10–15% of the ES negatives, further approaches are necessary to maximize diagnoses in these individuals. Methods: In 38 ES negative patients an individualized genomic–phenotypic approach was employed utilizing (1) phenotyping; (2) reanalyses of FASTQ files, with innovative bioinformatics; (3) targeted molecular testing; (4) genome sequencing (GS); and (5) conferring of clinical diagnoses when pathognomonic clinical findings occurred. Results: Certain and highly likely diagnoses were made in 18/38 (47%) individuals, including identifying two new developmental disorders. The majority of diagnoses (>70%) were due to our bioinformatics, phenotyping, and targeted testing identifying variants that were undetected or not prioritized on prior ES. GS diagnosed 3/18 individuals with structural variants not amenable to ES. Additionally, tentative diagnoses were made in 3 (8%), and in 5 individuals (13%) candidate genes were identified. Overall, diagnoses/potential leads were identified in 26/38 (68%). Conclusions: Our comprehensive approach to ES negatives maximizes the ES and clinical data for both diagnoses and candidate gene identification, without GS in the majority. This iterative approach is cost-effective and is pertinent to the current conundrum of ES negatives.

LanguageEnglish (US)
Pages1-12
Number of pages12
JournalGenetics in Medicine
DOIs
StateAccepted/In press - Jun 15 2018

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Exome
Genome
Computational Biology
Genetic Association Studies
Phenotype
Costs and Cost Analysis

Keywords

  • Exome sequencing
  • Genome sequencing
  • Phenotyping
  • Rare diseases
  • Undiagnosed diseases

ASJC Scopus subject areas

  • Genetics(clinical)

Cite this

A comprehensive iterative approach is highly effective in diagnosing individuals who are exome negative. / Undiagnosed Diseases Network.

In: Genetics in Medicine, 15.06.2018, p. 1-12.

Research output: Contribution to journalArticle

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abstract = "Purpose: Sixty to seventy-five percent of individuals with rare and undiagnosed phenotypes remain undiagnosed after exome sequencing (ES). With standard ES reanalysis resolving 10–15{\%} of the ES negatives, further approaches are necessary to maximize diagnoses in these individuals. Methods: In 38 ES negative patients an individualized genomic–phenotypic approach was employed utilizing (1) phenotyping; (2) reanalyses of FASTQ files, with innovative bioinformatics; (3) targeted molecular testing; (4) genome sequencing (GS); and (5) conferring of clinical diagnoses when pathognomonic clinical findings occurred. Results: Certain and highly likely diagnoses were made in 18/38 (47{\%}) individuals, including identifying two new developmental disorders. The majority of diagnoses (>70{\%}) were due to our bioinformatics, phenotyping, and targeted testing identifying variants that were undetected or not prioritized on prior ES. GS diagnosed 3/18 individuals with structural variants not amenable to ES. Additionally, tentative diagnoses were made in 3 (8{\%}), and in 5 individuals (13{\%}) candidate genes were identified. Overall, diagnoses/potential leads were identified in 26/38 (68{\%}). Conclusions: Our comprehensive approach to ES negatives maximizes the ES and clinical data for both diagnoses and candidate gene identification, without GS in the majority. This iterative approach is cost-effective and is pertinent to the current conundrum of ES negatives.",
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AU - Undiagnosed Diseases Network

AU - Shashi, Vandana

AU - Schoch, Kelly

AU - Spillmann, Rebecca

AU - Cope, Heidi

AU - Tan, Queenie K.G.

AU - Walley, Nicole

AU - Pena, Loren

AU - McConkie-Rosell, Allyn

AU - Jiang, Yong Hui

AU - Stong, Nicholas

AU - Need, Anna C.

AU - Goldstein, David B.

AU - Adams, David R.

AU - Alejandro, Mercedes E.

AU - Allard, Patrick

AU - Ashley, Euan A.

AU - Azamian, Mahshid S.

AU - Bacino, Carlos A.

AU - Balasubramanyam, Ashok

AU - Barseghyan, Hayk

AU - Batzli, Gabriel F.

AU - Beggs, Alan H.

AU - Behnam, Babak

AU - Bellen, Hugo J.

AU - Bernstein, Jonathan A.

AU - Bican, Anna

AU - Bick, David P.

AU - Birch, Camille L.

AU - Bonner, Devon

AU - Boone, Braden E.

AU - Bostwick, Bret L.

AU - Briere, Lauren C.

AU - Brown, Donna M.

AU - Brush, Matthew

AU - Burke, Elizabeth A.

AU - Burrage, Lindsay C.

AU - Butte, Manish J.

AU - Chen, Shan

AU - Clark, Gary D.

AU - Coakley, Terra R.

AU - Cogan, Joy D.

AU - Cooper, Cynthia M.

AU - Cope, Heidi

AU - Craigen, William J.

AU - D’Souza, Precilla

AU - Davids, Mariska

AU - Davidson, Jean M.

AU - Dayal, Jyoti G.

AU - Haendel, Melissa

AU - Koeller, David M.

PY - 2018/6/15

Y1 - 2018/6/15

N2 - Purpose: Sixty to seventy-five percent of individuals with rare and undiagnosed phenotypes remain undiagnosed after exome sequencing (ES). With standard ES reanalysis resolving 10–15% of the ES negatives, further approaches are necessary to maximize diagnoses in these individuals. Methods: In 38 ES negative patients an individualized genomic–phenotypic approach was employed utilizing (1) phenotyping; (2) reanalyses of FASTQ files, with innovative bioinformatics; (3) targeted molecular testing; (4) genome sequencing (GS); and (5) conferring of clinical diagnoses when pathognomonic clinical findings occurred. Results: Certain and highly likely diagnoses were made in 18/38 (47%) individuals, including identifying two new developmental disorders. The majority of diagnoses (>70%) were due to our bioinformatics, phenotyping, and targeted testing identifying variants that were undetected or not prioritized on prior ES. GS diagnosed 3/18 individuals with structural variants not amenable to ES. Additionally, tentative diagnoses were made in 3 (8%), and in 5 individuals (13%) candidate genes were identified. Overall, diagnoses/potential leads were identified in 26/38 (68%). Conclusions: Our comprehensive approach to ES negatives maximizes the ES and clinical data for both diagnoses and candidate gene identification, without GS in the majority. This iterative approach is cost-effective and is pertinent to the current conundrum of ES negatives.

AB - Purpose: Sixty to seventy-five percent of individuals with rare and undiagnosed phenotypes remain undiagnosed after exome sequencing (ES). With standard ES reanalysis resolving 10–15% of the ES negatives, further approaches are necessary to maximize diagnoses in these individuals. Methods: In 38 ES negative patients an individualized genomic–phenotypic approach was employed utilizing (1) phenotyping; (2) reanalyses of FASTQ files, with innovative bioinformatics; (3) targeted molecular testing; (4) genome sequencing (GS); and (5) conferring of clinical diagnoses when pathognomonic clinical findings occurred. Results: Certain and highly likely diagnoses were made in 18/38 (47%) individuals, including identifying two new developmental disorders. The majority of diagnoses (>70%) were due to our bioinformatics, phenotyping, and targeted testing identifying variants that were undetected or not prioritized on prior ES. GS diagnosed 3/18 individuals with structural variants not amenable to ES. Additionally, tentative diagnoses were made in 3 (8%), and in 5 individuals (13%) candidate genes were identified. Overall, diagnoses/potential leads were identified in 26/38 (68%). Conclusions: Our comprehensive approach to ES negatives maximizes the ES and clinical data for both diagnoses and candidate gene identification, without GS in the majority. This iterative approach is cost-effective and is pertinent to the current conundrum of ES negatives.

KW - Exome sequencing

KW - Genome sequencing

KW - Phenotyping

KW - Rare diseases

KW - Undiagnosed diseases

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