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

Undiagnosed Diseases Network

Research output: Contribution to journalArticle

3 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)1-12
Number of pages12
JournalGenetics in Medicine
DOIs
StateAccepted/In press - Jun 15 2018

Fingerprint

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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title = "A comprehensive iterative approach is highly effective in diagnosing individuals who are exome negative",
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.",
keywords = "Exome sequencing, Genome sequencing, Phenotyping, Rare diseases, Undiagnosed diseases",
author = "{Undiagnosed Diseases Network} and Vandana Shashi and Kelly Schoch and Rebecca Spillmann and Heidi Cope and Tan, {Queenie K.G.} and Nicole Walley and Loren Pena and Allyn McConkie-Rosell and Jiang, {Yong Hui} and Nicholas Stong and Need, {Anna C.} and Goldstein, {David B.} and Adams, {David R.} and Alejandro, {Mercedes E.} and Patrick Allard and Ashley, {Euan A.} and Azamian, {Mahshid S.} and Bacino, {Carlos A.} and Ashok Balasubramanyam and Hayk Barseghyan and Batzli, {Gabriel F.} and Beggs, {Alan H.} and Babak Behnam and Bellen, {Hugo J.} and Bernstein, {Jonathan A.} and Anna Bican and Bick, {David P.} and Birch, {Camille L.} and Devon Bonner and Boone, {Braden E.} and Bostwick, {Bret L.} and Briere, {Lauren C.} and Brown, {Donna M.} and Matthew Brush and Burke, {Elizabeth A.} and Burrage, {Lindsay C.} and Butte, {Manish J.} and Shan Chen and Clark, {Gary D.} and Coakley, {Terra R.} and Cogan, {Joy D.} and Cooper, {Cynthia M.} and Heidi Cope and Craigen, {William J.} and Precilla D’Souza and Mariska Davids and Davidson, {Jean M.} and Dayal, {Jyoti G.} and Melissa Haendel and David Koeller",
year = "2018",
month = "6",
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language = "English (US)",
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T1 - A comprehensive iterative approach is highly effective in diagnosing individuals who are exome negative

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

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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U2 - 10.1038/s41436-018-0044-2

DO - 10.1038/s41436-018-0044-2

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JO - Genetics in Medicine

JF - Genetics in Medicine

SN - 1098-3600

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