Assessing the Utility of ColabFold and AlphaMissense in Determining Missense Variant Pathogenicity for Congenital Myasthenic Syndromes
Background/Objectives: Congenital myasthenic syndromes (CMSs) are caused by variants in >30 genes with increasing numbers of variants of unknown significance (VUS) discovered by next-generation sequencing. Establishing VUS pathogenicity requires in vitro studies that slow diagnosis and treatment...
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2024-11-01
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| author | Finlay Ryan-Phillips Leighann Henehan Sithara Ramdas Jacqueline Palace David Beeson Yin Yao Dong |
| author_facet | Finlay Ryan-Phillips Leighann Henehan Sithara Ramdas Jacqueline Palace David Beeson Yin Yao Dong |
| author_sort | Finlay Ryan-Phillips |
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| description | Background/Objectives: Congenital myasthenic syndromes (CMSs) are caused by variants in >30 genes with increasing numbers of variants of unknown significance (VUS) discovered by next-generation sequencing. Establishing VUS pathogenicity requires in vitro studies that slow diagnosis and treatment initiation. The recently developed protein structure prediction software AlphaFold2/ColabFold has revolutionized structural biology; such predictions have also been leveraged in AlphaMissense, which predicts ClinVar variant pathogenicity with 90% accuracy. Few reports, however, have tested these tools on rigorously characterized clinical data. We therefore assessed ColabFold and AlphaMissense as diagnostic aids for CMSs, using variants of the CHRN genes that encode the nicotinic acetylcholine receptor (nAChR). Methods: Utilizing a dataset of 61 clinically validated CHRN variants, (1) we evaluated the possibility of a ColabFold metric (either predicted structural disruption, prediction confidence, or prediction quality) that distinguishes variant pathogenicity; (2) we assessed AlphaMissense’s ability to differentiate variant pathogenicity; and (3) we compared AlphaMissense to the existing pathogenicity prediction programs AlamutVP and EVE. Results: Analyzing the variant effects on ColabFold CHRN structure prediction, prediction confidence, and prediction quality did not yield any reliable pathogenicity indicative metric. However, AlphaMissense predicted variant pathogenicity with 63.93% accuracy in our dataset—a much greater proportion than AlamutVP (27.87%) and EVE (28.33%). Conclusions: Emerging in silico tools can revolutionize genetic disease diagnosis—however, improvement, refinement, and clinical validation are imperative prior to practical acquisition. |
| format | Article |
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| institution | Kabale University |
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| language | English |
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| series | Biomedicines |
| spelling | doaj-art-165e2ec6b1cd4076996f63eba6eaf57e2024-11-26T17:53:11ZengMDPI AGBiomedicines2227-90592024-11-011211254910.3390/biomedicines12112549Assessing the Utility of ColabFold and AlphaMissense in Determining Missense Variant Pathogenicity for Congenital Myasthenic SyndromesFinlay Ryan-Phillips0Leighann Henehan1Sithara Ramdas2Jacqueline Palace3David Beeson4Yin Yao Dong5Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DS, UKNeurology Department, John Radcliffe Hospital, Oxford OX3 9DU, UKDepartment of Paediatric Neurology, John Radcliffe Hospital, Oxford OX3 9DU, UKNuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DS, UKNuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DS, UKNuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DS, UKBackground/Objectives: Congenital myasthenic syndromes (CMSs) are caused by variants in >30 genes with increasing numbers of variants of unknown significance (VUS) discovered by next-generation sequencing. Establishing VUS pathogenicity requires in vitro studies that slow diagnosis and treatment initiation. The recently developed protein structure prediction software AlphaFold2/ColabFold has revolutionized structural biology; such predictions have also been leveraged in AlphaMissense, which predicts ClinVar variant pathogenicity with 90% accuracy. Few reports, however, have tested these tools on rigorously characterized clinical data. We therefore assessed ColabFold and AlphaMissense as diagnostic aids for CMSs, using variants of the CHRN genes that encode the nicotinic acetylcholine receptor (nAChR). Methods: Utilizing a dataset of 61 clinically validated CHRN variants, (1) we evaluated the possibility of a ColabFold metric (either predicted structural disruption, prediction confidence, or prediction quality) that distinguishes variant pathogenicity; (2) we assessed AlphaMissense’s ability to differentiate variant pathogenicity; and (3) we compared AlphaMissense to the existing pathogenicity prediction programs AlamutVP and EVE. Results: Analyzing the variant effects on ColabFold CHRN structure prediction, prediction confidence, and prediction quality did not yield any reliable pathogenicity indicative metric. However, AlphaMissense predicted variant pathogenicity with 63.93% accuracy in our dataset—a much greater proportion than AlamutVP (27.87%) and EVE (28.33%). Conclusions: Emerging in silico tools can revolutionize genetic disease diagnosis—however, improvement, refinement, and clinical validation are imperative prior to practical acquisition.https://www.mdpi.com/2227-9059/12/11/2549CMSAlphaFold2ColabFoldAlphaMissensepathogenicityprediction |
| spellingShingle | Finlay Ryan-Phillips Leighann Henehan Sithara Ramdas Jacqueline Palace David Beeson Yin Yao Dong Assessing the Utility of ColabFold and AlphaMissense in Determining Missense Variant Pathogenicity for Congenital Myasthenic Syndromes Biomedicines CMS AlphaFold2 ColabFold AlphaMissense pathogenicity prediction |
| title | Assessing the Utility of ColabFold and AlphaMissense in Determining Missense Variant Pathogenicity for Congenital Myasthenic Syndromes |
| title_full | Assessing the Utility of ColabFold and AlphaMissense in Determining Missense Variant Pathogenicity for Congenital Myasthenic Syndromes |
| title_fullStr | Assessing the Utility of ColabFold and AlphaMissense in Determining Missense Variant Pathogenicity for Congenital Myasthenic Syndromes |
| title_full_unstemmed | Assessing the Utility of ColabFold and AlphaMissense in Determining Missense Variant Pathogenicity for Congenital Myasthenic Syndromes |
| title_short | Assessing the Utility of ColabFold and AlphaMissense in Determining Missense Variant Pathogenicity for Congenital Myasthenic Syndromes |
| title_sort | assessing the utility of colabfold and alphamissense in determining missense variant pathogenicity for congenital myasthenic syndromes |
| topic | CMS AlphaFold2 ColabFold AlphaMissense pathogenicity prediction |
| url | https://www.mdpi.com/2227-9059/12/11/2549 |
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