CardioClassifier: disease- and gene-specific computational decision support for clinical genome interpretation
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Purpose
Internationally adopted variant interpretation guidelines from the American College of Medical Genetics and Genomics (ACMG) are generic and require disease-specific refinement. Here we developed CardioClassifier (http://www.cardioclassifier.org), a semiautomated decision-support tool for inherited cardiac conditions (ICCs).
Methods
CardioClassifier integrates data retrieved from multiple sources with user-input case-specific information, through an interactive interface, to support variant interpretation. Combining disease- and gene-specific knowledge with variant observations in large cohorts of cases and controls, we refined 14 computational ACMG criteria and created three ICC-specific rules.
Results
We benchmarked CardioClassifier on 57 expertly curated variants and show full retrieval of all computational data, concordantly activating 87.3% of rules. A generic annotation tool identified fewer than half as many clinically actionable variants (64/219 vs. 156/219, Fisher’s P = 1.1 × 10−18), with important false positives, illustrating the critical importance of disease and gene-specific annotations. CardioClassifier identified putatively disease-causing variants in 33.7% of 327 cardiomyopathy cases, comparable with leading ICC laboratories. Through addition of manually curated data, variants found in over 40% of cardiomyopathy cases are fully annotated, without requiring additional user-input data.
Conclusion
CardioClassifier is an ICC-specific decision-support tool that integrates expertly curated computational annotations with case-specific data to generate fast, reproducible, and interactive variant pathogenicity reports, according to best practice guidelines.
Internationally adopted variant interpretation guidelines from the American College of Medical Genetics and Genomics (ACMG) are generic and require disease-specific refinement. Here we developed CardioClassifier (http://www.cardioclassifier.org), a semiautomated decision-support tool for inherited cardiac conditions (ICCs).
Methods
CardioClassifier integrates data retrieved from multiple sources with user-input case-specific information, through an interactive interface, to support variant interpretation. Combining disease- and gene-specific knowledge with variant observations in large cohorts of cases and controls, we refined 14 computational ACMG criteria and created three ICC-specific rules.
Results
We benchmarked CardioClassifier on 57 expertly curated variants and show full retrieval of all computational data, concordantly activating 87.3% of rules. A generic annotation tool identified fewer than half as many clinically actionable variants (64/219 vs. 156/219, Fisher’s P = 1.1 × 10−18), with important false positives, illustrating the critical importance of disease and gene-specific annotations. CardioClassifier identified putatively disease-causing variants in 33.7% of 327 cardiomyopathy cases, comparable with leading ICC laboratories. Through addition of manually curated data, variants found in over 40% of cardiomyopathy cases are fully annotated, without requiring additional user-input data.
Conclusion
CardioClassifier is an ICC-specific decision-support tool that integrates expertly curated computational annotations with case-specific data to generate fast, reproducible, and interactive variant pathogenicity reports, according to best practice guidelines.
Date Issued
2018-01-25
Date Acceptance
2017-11-28
Citation
Genetics in Medicine, 2018, 20, pp.1246-1254
ISSN
1098-3600
Publisher
Nature Publishing Group
Start Page
1246
End Page
1254
Journal / Book Title
Genetics in Medicine
Volume
20
Copyright Statement
© The Author(s) 2018. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
License URL
Sponsor
British Heart Foundation
Fondation Leducq
Fondation Leducq
Wellcome Trust
Department of Health
Royal Brompton & Harefield NHS Foundation Trust
Wellcome Trust
Royal Brompton & Harefield NHS Foundation Trust
British Heart Foundation
Imperial College Healthcare NHS Trust- BRC Funding
Grant Number
SP/10/10/28431
11 CVD-01
11 CVD-01
100134/Z/12/Z
HICF-R6-373
infoed 59322
107469/Z/15/Z
N/A
FS/15/81/31817
RDB02
Subjects
Science & Technology
Life Sciences & Biomedicine
Genetics & Heredity
bioinformatics
clinical genomics
inherited cardiac conditions
next-generation sequencing
variant interpretation
SEQUENCE VARIANTS
GUIDELINES
CARDIOMYOPATHY
STANDARDS
MUTATIONS
CLINVAR
CHANNEL
0604 Genetics
1103 Clinical Sciences
Publication Status
Published