Translating evolutionary history and protein-focused machine learning supports increased prevalence of hereditary haemorrhagic telangiectasia, one of the most common inherited disorders.

BACKGROUND: Recent genetic data suggest hereditary haemorrhagic telangiectasia (HHT) is 2-12 times more common than the clinically-ascertained prevalence, potentially above the 'rare disease' designation threshold, and undermining clinical predictions for asymptomatic individuals diagnosed by genetic testing. AIM: To test, we examined if missense variants in HHT disease-causing genes may have been misclassified as pathogenic (LP/P) or benign (B/LB). DESIGN: Evaluation of ClinVar-annotated missense variants in ENG, ACVRL1 and SMAD4. METHODS: Human-independent methods using CodeXome for pan-primate evolutionary history, and AlphaMissense which incorporates AlphaFold predictions for protein misfolding were used to validate/reclassify pathogenic and benign missense variants. RESULTS: ClinVar annotations were commonly conservative with 35-90% of rare missense substitutions in ENG, ACVRL1 and SMAD4 classified as variants of uncertain significance (VUS). CodeXome identified 92% of ClinVar-annotated B/LB variants were shared with other primate species, supporting their benign classification. AlphaMissense metrics strongly correlated with CodeXome, and 380/403 (94.3%) variants matched ClinVar benign-pathogenic annotations. However, a small number of variants showed conflicting classifications with ClinVar: 19/293 (6.5%) appeared to be over-called as LP/P by ClinVar representing 15/408 (3.7%) of genotyped families at Imperial, while 4/110 (3.6%) were apparently under-called as B/LB, and not accessible through clinical gene test reports. Newer pathobiological understanding of variants, and recognition of shared familial tendencies reflecting non-HHT heritable burdens were identified as possible explanations of over-calls. CONCLUSIONS: Our findings suggest tools to simplify variant pathogenicity predictions; molecular diagnoses to revisit for HHT families, but do not materially influence prevalence estimates for 'genetic' HHT, challenging current clinical policies, training and standards.

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PubMed
Published
2026-08-26
DOI
https://doi.org/10.1093/qjmed/hcag209
Primary Topic
Vascular Anomalies and Treatments
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article
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article

Translating evolutionary history and protein-focused machine learning supports increased prevalence of hereditary haemorrhagic telangiectasia, one of the most common inherited disorders.

Claire L. Shovlin, Jill Pecon‐Slattery, Adriana Macko
PubMed
Vascular Anomalies and Treatments
article

Translating evolutionary history and protein-focused machine learning supports increased prevalence of hereditary haemorrhagic telangiectasia, one of the most common inherited disorders.

Claire L. Shovlin, Jill Pecon‐Slattery, Adriana Macko
article en

Abstract

BACKGROUND: Recent genetic data suggest hereditary haemorrhagic telangiectasia (HHT) is 2-12 times more common than the clinically-ascertained prevalence, potentially above the 'rare disease' designation threshold, and undermining clinical predictions for asymptomatic individuals diagnosed by genetic testing. AIM: To test, we examined if missense variants in HHT disease-causing genes may have been misclassified as pathogenic (LP/P) or benign (B/LB). DESIGN: Evaluation of ClinVar-annotated missense variants in ENG, ACVRL1 and SMAD4. METHODS: Human-independent methods using CodeXome for pan-primate evolutionary history, and AlphaMissense which incorporates AlphaFold predictions for protein misfolding were used to validate/reclassify pathogenic and benign missense variants. RESULTS: ClinVar annotations were commonly conservative with 35-90% of rare missense substitutions in ENG, ACVRL1 and SMAD4 classified as variants of uncertain significance (VUS). CodeXome identified 92% of ClinVar-annotated B/LB variants were shared with other primate species, supporting their benign classification. AlphaMissense metrics strongly correlated with CodeXome, and 380/403 (94.3%) variants matched ClinVar benign-pathogenic annotations. However, a small number of variants showed conflicting classifications with ClinVar: 19/293 (6.5%) appeared to be over-called as LP/P by ClinVar representing 15/408 (3.7%) of genotyped families at Imperial, while 4/110 (3.6%) were apparently under-called as B/LB, and not accessible through clinical gene test reports. Newer pathobiological understanding of variants, and recognition of shared familial tendencies reflecting non-HHT heritable burdens were identified as possible explanations of over-calls. CONCLUSIONS: Our findings suggest tools to simplify variant pathogenicity predictions; molecular diagnoses to revisit for HHT families, but do not materially influence prevalence estimates for 'genetic' HHT, challenging current clinical policies, training and standards.

PubMed
Cornerstone University (US), Imperial College Healthcare NHS Trust (GB), NIHR Imperial Biomedical Research Centre (GB), Imperial College London (GB), Colorado State University (US)
Openalex Percentile: Top 10%
Vascular Anomalies and Treatments
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