DiscoVari : A Web-Based Precision Medicine Tool for Predicting Variant Pathogenicity in Cardiomyopathy- and Channelopathy-Associated Genes
With genetic testing advancements, the burden of incidentally identified cardiac disease-associated gene variants is rising. These variants may carry a risk of sudden cardiac death, highlighting the need for accurate diagnostic interpretation. We sought to identify pathogenic hotspots in sudden card...
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| Vydáno v: | Circulation. Genomic and precision medicine Ročník 16; číslo 4; s. 317 |
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| Hlavní autoři: | , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
01.08.2023
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| ISSN: | 2574-8300, 2574-8300 |
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| Abstract | With genetic testing advancements, the burden of incidentally identified cardiac disease-associated gene variants is rising. These variants may carry a risk of sudden cardiac death, highlighting the need for accurate diagnostic interpretation. We sought to identify pathogenic hotspots in sudden cardiac death-associated genes using amino acid-level signal-to-noise (S:N) analysis and develop a web-based precision medicine tool,
, to improve variant evaluation.
The minor allele frequency of putatively pathogenic variants was derived from cohort-based cardiomyopathy and channelopathy studies in the literature. We normalized disease-associated minor allele frequencies to rare variants in an ostensibly healthy population (Genome Aggregation Database) to calculate amino acid-level S:N. Amino acids with S:N above the gene-specific threshold were defined as hotspots.
was built using JavaScript ES6 and using open-source JavaScript library ReactJS, web development framework Next.js, and JavaScript runtime NodeJS. We validated the ability of
to identify pathogenic variants using variants from ClinVar and individuals clinically evaluated at the Duke University Hospitals with cardiac genetic testing.
We developed
as an internet-based tool for S:N-based variant hotspots. Upon validation, a higher proportion of ClinVar likely pathogenic/pathogenic variants localized to
hotspots (43.1%) than likely benign/benign variants (17.8%;
0.0001). Further, 75.3% of ClinVar variants reclassified to likely pathogenic/pathogenic were in hotspots, compared with 41.3% of those reclassified as variants of uncertain significance (
0.0001) and 23.4% of those reclassified as likely benign/benign (
<0.0001). Of the clinical cohort variants, 73.1% of likely pathogenic/pathogenic were in hotspots, compared with 0.0% of likely benign/benign (
0.01).
reliably identifies disease-susceptible amino acid residues to evaluate variants by searching amino acid-specific S:N ratios. |
|---|---|
| AbstractList | With genetic testing advancements, the burden of incidentally identified cardiac disease-associated gene variants is rising. These variants may carry a risk of sudden cardiac death, highlighting the need for accurate diagnostic interpretation. We sought to identify pathogenic hotspots in sudden cardiac death-associated genes using amino acid-level signal-to-noise (S:N) analysis and develop a web-based precision medicine tool, DiscoVari, to improve variant evaluation.BACKGROUNDWith genetic testing advancements, the burden of incidentally identified cardiac disease-associated gene variants is rising. These variants may carry a risk of sudden cardiac death, highlighting the need for accurate diagnostic interpretation. We sought to identify pathogenic hotspots in sudden cardiac death-associated genes using amino acid-level signal-to-noise (S:N) analysis and develop a web-based precision medicine tool, DiscoVari, to improve variant evaluation.The minor allele frequency of putatively pathogenic variants was derived from cohort-based cardiomyopathy and channelopathy studies in the literature. We normalized disease-associated minor allele frequencies to rare variants in an ostensibly healthy population (Genome Aggregation Database) to calculate amino acid-level S:N. Amino acids with S:N above the gene-specific threshold were defined as hotspots. DiscoVari was built using JavaScript ES6 and using open-source JavaScript library ReactJS, web development framework Next.js, and JavaScript runtime NodeJS. We validated the ability of DiscoVari to identify pathogenic variants using variants from ClinVar and individuals clinically evaluated at the Duke University Hospitals with cardiac genetic testing.METHODSThe minor allele frequency of putatively pathogenic variants was derived from cohort-based cardiomyopathy and channelopathy studies in the literature. We normalized disease-associated minor allele frequencies to rare variants in an ostensibly healthy population (Genome Aggregation Database) to calculate amino acid-level S:N. Amino acids with S:N above the gene-specific threshold were defined as hotspots. DiscoVari was built using JavaScript ES6 and using open-source JavaScript library ReactJS, web development framework Next.js, and JavaScript runtime NodeJS. We validated the ability of DiscoVari to identify pathogenic variants using variants from ClinVar and individuals clinically evaluated at the Duke University Hospitals with cardiac genetic testing.We developed DiscoVari as an internet-based tool for S:N-based variant hotspots. Upon validation, a higher proportion of ClinVar likely pathogenic/pathogenic variants localized to DiscoVari hotspots (43.1%) than likely benign/benign variants (17.8%; P<0.0001). Further, 75.3% of ClinVar variants reclassified to likely pathogenic/pathogenic were in hotspots, compared with 41.3% of those reclassified as variants of uncertain significance (P<0.0001) and 23.4% of those reclassified as likely benign/benign (P<0.0001). Of the clinical cohort variants, 73.1% of likely pathogenic/pathogenic were in hotspots, compared with 0.0% of likely benign/benign (P<0.01).RESULTSWe developed DiscoVari as an internet-based tool for S:N-based variant hotspots. Upon validation, a higher proportion of ClinVar likely pathogenic/pathogenic variants localized to DiscoVari hotspots (43.1%) than likely benign/benign variants (17.8%; P<0.0001). Further, 75.3% of ClinVar variants reclassified to likely pathogenic/pathogenic were in hotspots, compared with 41.3% of those reclassified as variants of uncertain significance (P<0.0001) and 23.4% of those reclassified as likely benign/benign (P<0.0001). Of the clinical cohort variants, 73.1% of likely pathogenic/pathogenic were in hotspots, compared with 0.0% of likely benign/benign (P<0.01).DiscoVari reliably identifies disease-susceptible amino acid residues to evaluate variants by searching amino acid-specific S:N ratios.CONCLUSIONSDiscoVari reliably identifies disease-susceptible amino acid residues to evaluate variants by searching amino acid-specific S:N ratios. With genetic testing advancements, the burden of incidentally identified cardiac disease-associated gene variants is rising. These variants may carry a risk of sudden cardiac death, highlighting the need for accurate diagnostic interpretation. We sought to identify pathogenic hotspots in sudden cardiac death-associated genes using amino acid-level signal-to-noise (S:N) analysis and develop a web-based precision medicine tool, , to improve variant evaluation. The minor allele frequency of putatively pathogenic variants was derived from cohort-based cardiomyopathy and channelopathy studies in the literature. We normalized disease-associated minor allele frequencies to rare variants in an ostensibly healthy population (Genome Aggregation Database) to calculate amino acid-level S:N. Amino acids with S:N above the gene-specific threshold were defined as hotspots. was built using JavaScript ES6 and using open-source JavaScript library ReactJS, web development framework Next.js, and JavaScript runtime NodeJS. We validated the ability of to identify pathogenic variants using variants from ClinVar and individuals clinically evaluated at the Duke University Hospitals with cardiac genetic testing. We developed as an internet-based tool for S:N-based variant hotspots. Upon validation, a higher proportion of ClinVar likely pathogenic/pathogenic variants localized to hotspots (43.1%) than likely benign/benign variants (17.8%; 0.0001). Further, 75.3% of ClinVar variants reclassified to likely pathogenic/pathogenic were in hotspots, compared with 41.3% of those reclassified as variants of uncertain significance ( 0.0001) and 23.4% of those reclassified as likely benign/benign ( <0.0001). Of the clinical cohort variants, 73.1% of likely pathogenic/pathogenic were in hotspots, compared with 0.0% of likely benign/benign ( 0.01). reliably identifies disease-susceptible amino acid residues to evaluate variants by searching amino acid-specific S:N ratios. |
| Author | Landstrom, Andrew P Patel, Viraj Rosamilia, Michael B Parker, Lauren E Tadros, Hanna J Kurzlechner, Leonie M Kishnani, Sujata Pace, Leslie A Moya-Mendez, Mary E Chowdhury, Shawon Atkins, Sage L Chahal, C Anwar A |
| Author_xml | – sequence: 1 givenname: Leonie M orcidid: 0000-0002-9305-0669 surname: Kurzlechner fullname: Kurzlechner, Leonie M organization: Department of Pediatrics, Division of Pediatric Cardiology (LMK, SK, SC, SLA, MEM-M, LEP, MBR, LAP, APL), Duke University School of Medicine, Durham, NC – sequence: 2 givenname: Sujata surname: Kishnani fullname: Kishnani, Sujata organization: Department of Pediatrics, Division of Pediatric Cardiology (LMK, SK, SC, SLA, MEM-M, LEP, MBR, LAP, APL), Duke University School of Medicine, Durham, NC – sequence: 3 givenname: Shawon surname: Chowdhury fullname: Chowdhury, Shawon organization: Department of Pediatrics, Division of Pediatric Cardiology (LMK, SK, SC, SLA, MEM-M, LEP, MBR, LAP, APL), Duke University School of Medicine, Durham, NC – sequence: 4 givenname: Sage L surname: Atkins fullname: Atkins, Sage L organization: Department of Pediatrics, Division of Pediatric Cardiology (LMK, SK, SC, SLA, MEM-M, LEP, MBR, LAP, APL), Duke University School of Medicine, Durham, NC – sequence: 5 givenname: Mary E orcidid: 0000-0003-0845-6750 surname: Moya-Mendez fullname: Moya-Mendez, Mary E organization: Department of Pediatrics, Division of Pediatric Cardiology (LMK, SK, SC, SLA, MEM-M, LEP, MBR, LAP, APL), Duke University School of Medicine, Durham, NC – sequence: 6 givenname: Lauren E surname: Parker fullname: Parker, Lauren E organization: Department of Pediatrics, Division of Pediatric Cardiology (LMK, SK, SC, SLA, MEM-M, LEP, MBR, LAP, APL), Duke University School of Medicine, Durham, NC – sequence: 7 givenname: Michael B orcidid: 0000-0003-1927-7176 surname: Rosamilia fullname: Rosamilia, Michael B organization: Department of Pediatrics, Division of Pediatric Cardiology (LMK, SK, SC, SLA, MEM-M, LEP, MBR, LAP, APL), Duke University School of Medicine, Durham, NC – sequence: 8 givenname: Hanna J orcidid: 0000-0002-2348-9262 surname: Tadros fullname: Tadros, Hanna J organization: Department of Pediatrics, Section of Pediatric Cardiology, Baylor College of Medicine, Houston, TX (H.J.T.) – sequence: 9 givenname: Leslie A surname: Pace fullname: Pace, Leslie A organization: Department of Pediatrics, Division of Pediatric Cardiology (LMK, SK, SC, SLA, MEM-M, LEP, MBR, LAP, APL), Duke University School of Medicine, Durham, NC – sequence: 10 givenname: Viraj orcidid: 0000-0003-4041-0971 surname: Patel fullname: Patel, Viraj organization: North West Thames Regional Genetics Service, St Mark's Hospital, London, United Kingdom (V.P.) – sequence: 11 givenname: C Anwar A orcidid: 0000-0001-7825-8827 surname: Chahal fullname: Chahal, C Anwar A organization: Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN (C.A.A.C.) – sequence: 12 givenname: Andrew P orcidid: 0000-0002-1878-9631 surname: Landstrom fullname: Landstrom, Andrew P organization: Department of Cell Biology (A.P.L.), Duke University School of Medicine, Durham, NC |
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| SubjectTerms | Amino Acids Cardiomyopathies - genetics Channelopathies - genetics Death, Sudden, Cardiac - pathology Genetic Variation Humans Precision Medicine Virulence |
| Title | DiscoVari : A Web-Based Precision Medicine Tool for Predicting Variant Pathogenicity in Cardiomyopathy- and Channelopathy-Associated Genes |
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