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Integrated analysis of metabolomic profiling and exome data supplements sequence variant interpretation, classification, and diagnosis.

ABSTRACT: PURPOSE:A primary barrier to improving exome sequencing diagnostic rates is the interpretation of variants of uncertain clinical significance. We aimed to determine the contribution of integrated untargeted metabolomics in the analysis of exome sequencing data by retrospective analysis of patients evaluated by both exome sequencing and untargeted metabolomics within the same clinical laboratory. METHODS:Exome sequencing and untargeted metabolomic data were collected and analyzed for 170 patients. Pathogenic variants, likely pathogenic variants, and variants of uncertain significance in genes associated with a biochemical phenotype were extracted. Metabolomic data were evaluated to determine if these variants resulted in biochemical abnormalities that could be used to support their interpretation using current American College of Genetics and Genomics (ACMG) guidelines. RESULTS:Metabolomic data contributed to the interpretation of variants in 74 individuals (43.5%) over 73 different genes. The data allowed for the reclassification of 9 variants as likely benign, 15 variants as likely pathogenic, and 3 variants as pathogenic. Metabolomic data confirmed a clinical diagnosis in 21 cases, for a diagnostic rate of 12.3% in this population. CONCLUSION:Untargeted metabolomics can serve as a useful adjunct to exome sequencing by providing valuable functional data that may not otherwise be clinically available, resulting in improved variant classification.

SUBMITTER: Alaimo JT

PROVIDER: S-EPMC7483344 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Integrated analysis of metabolomic profiling and exome data supplements sequence variant interpretation, classification, and diagnosis.

Alaimo Joseph T JT Glinton Kevin E KE Liu Ning N Xiao Jing J Yang Yaping Y Reid Sutton V V Elsea Sarah H SH

Genetics in medicine : official journal of the American College of Medical Genetics 20200522 9

<h4>Purpose</h4>A primary barrier to improving exome sequencing diagnostic rates is the interpretation of variants of uncertain clinical significance. We aimed to determine the contribution of integrated untargeted metabolomics in the analysis of exome sequencing data by retrospective analysis of patients evaluated by both exome sequencing and untargeted metabolomics within the same clinical laboratory.<h4>Methods</h4>Exome sequencing and untargeted metabolomic data were collected and analyzed f ...[more]

PMID: 32439973

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Project description:AimsThe genetic cause of cardiac conduction system disease (CCSD) has not been fully elucidated. Whole-exome sequencing (WES) can detect various genetic variants; however, the identification of pathogenic variants remains a challenge. We aimed to identify pathogenic or likely pathogenic variants in CCSD patients by using WES and 2015 American College of Medical Genetics and Genomics (ACMG) standards and guidelines as well as evaluating the usefulness of functional studies for determining them.Methods and resultsWe performed WES of 23 probands diagnosed with early-onset (<65 years) CCSD and analysed 117 genes linked to arrhythmogenic diseases or cardiomyopathies. We focused on rare variants (minor allele frequency < 0.1%) that were absent from population databases. Five probands had protein truncating variants in EMD and LMNA which were classified as 'pathogenic' by 2015 ACMG standards and guidelines. To evaluate the functional changes brought about by these variants, we generated a knock-out zebrafish with CRISPR-mediated insertions or deletions of the EMD or LMNA homologs in zebrafish. The mean heart rate and conduction velocities in the CRISPR/Cas9-injected embryos and F2 generation embryos with homozygous deletions were significantly decreased. Twenty-one variants of uncertain significance were identified in 11 probands. Cellular electrophysiological study and in vivo zebrafish cardiac assay showed that two variants in KCNH2 and SCN5A, four variants in SCN10A, and one variant in MYH6 damaged each gene, which resulted in the change of the clinical significance of them from 'Uncertain significance' to 'Likely pathogenic' in six probands.ConclusionOf 23 CCSD probands, we successfully identified pathogenic or likely pathogenic variants in 11 probands (48%). Functional analyses of a cellular electrophysiological study and in vivo zebrafish cardiac assay might be useful for determining the pathogenicity of rare variants in patients with CCSD. SCN10A may be one of the major genes responsible for CCSD.

Dataset Information

Integrated analysis of metabolomic profiling and exome data supplements sequence variant interpretation, classification, and diagnosis.

Publications

Integrated analysis of metabolomic profiling and exome data supplements sequence variant interpretation, classification, and diagnosis.

Similar Datasets

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