Computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filament
Point mutations within sarcomeric proteins have been associated with altered function and cardiomyopathy development. Difficulties remain, however, in establishing the pathogenic potential of individual mutations, often limiting the use of genotype in management of affected families. To directly add...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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American Society for Clinical investigation
2021-12-01
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| Series: | JCI Insight |
| Subjects: | |
| Online Access: | https://doi.org/10.1172/jci.insight.154350 |
| _version_ | 1811227203597238272 |
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| author | Allison B. Mason Melissa L. Lynn Anthony P. Baldo Andrea E. Deranek Jil C. Tardiff Steven D. Schwartz |
| author_facet | Allison B. Mason Melissa L. Lynn Anthony P. Baldo Andrea E. Deranek Jil C. Tardiff Steven D. Schwartz |
| author_sort | Allison B. Mason |
| collection | DOAJ |
| description | Point mutations within sarcomeric proteins have been associated with altered function and cardiomyopathy development. Difficulties remain, however, in establishing the pathogenic potential of individual mutations, often limiting the use of genotype in management of affected families. To directly address this challenge, we utilized our all-atom computational model of the human full cardiac thin filament (CTF) to predict how sequence substitutions in CTF proteins might affect structure and dynamics on an atomistic level. Utilizing molecular dynamics calculations, we simulated 21 well-defined genetic pathogenic cardiac troponin T and tropomyosin variants to establish a baseline of pathogenic changes induced in computational observables. Computational results were verified via differential scanning calorimetry on a subset of variants to develop an experimental correlation. Calculations were performed on 9 independent variants of unknown significance (VUS), and results were compared with pathogenic variants to identify high-resolution pathogenic signatures. Results for VUS were compared with the baseline set to determine induced structural and dynamic changes, and potential variant reclassifications were proposed. This unbiased, high-resolution computational methodology can provide unique structural and dynamic information that can be incorporated into existing analyses to facilitate classification both for de novo variants and those where established approaches have provided conflicting information. |
| first_indexed | 2024-04-12T09:37:35Z |
| format | Article |
| id | doaj.art-1e3531e6706e4a88b2a0e19b2af033ed |
| institution | Directory Open Access Journal |
| issn | 2379-3708 |
| language | English |
| last_indexed | 2024-04-12T09:37:35Z |
| publishDate | 2021-12-01 |
| publisher | American Society for Clinical investigation |
| record_format | Article |
| series | JCI Insight |
| spelling | doaj.art-1e3531e6706e4a88b2a0e19b2af033ed2022-12-22T03:38:10ZengAmerican Society for Clinical investigationJCI Insight2379-37082021-12-01623Computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filamentAllison B. MasonMelissa L. LynnAnthony P. BaldoAndrea E. DeranekJil C. TardiffSteven D. SchwartzPoint mutations within sarcomeric proteins have been associated with altered function and cardiomyopathy development. Difficulties remain, however, in establishing the pathogenic potential of individual mutations, often limiting the use of genotype in management of affected families. To directly address this challenge, we utilized our all-atom computational model of the human full cardiac thin filament (CTF) to predict how sequence substitutions in CTF proteins might affect structure and dynamics on an atomistic level. Utilizing molecular dynamics calculations, we simulated 21 well-defined genetic pathogenic cardiac troponin T and tropomyosin variants to establish a baseline of pathogenic changes induced in computational observables. Computational results were verified via differential scanning calorimetry on a subset of variants to develop an experimental correlation. Calculations were performed on 9 independent variants of unknown significance (VUS), and results were compared with pathogenic variants to identify high-resolution pathogenic signatures. Results for VUS were compared with the baseline set to determine induced structural and dynamic changes, and potential variant reclassifications were proposed. This unbiased, high-resolution computational methodology can provide unique structural and dynamic information that can be incorporated into existing analyses to facilitate classification both for de novo variants and those where established approaches have provided conflicting information.https://doi.org/10.1172/jci.insight.154350Cardiology |
| spellingShingle | Allison B. Mason Melissa L. Lynn Anthony P. Baldo Andrea E. Deranek Jil C. Tardiff Steven D. Schwartz Computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filament JCI Insight Cardiology |
| title | Computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filament |
| title_full | Computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filament |
| title_fullStr | Computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filament |
| title_full_unstemmed | Computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filament |
| title_short | Computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filament |
| title_sort | computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filament |
| topic | Cardiology |
| url | https://doi.org/10.1172/jci.insight.154350 |
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