Citation

BibTex format

@article{Macko:2026:qjmed/hcag209,
author = {Macko, A and Pecon-Slattery, J and Shovlin, CL},
doi = {qjmed/hcag209},
journal = {QJM: An International Journal of Medicine},
title = {Translating evolutionary history and protein-focused machine learning supports increased prevalence of hereditary haemorrhagic telangiectasia, one of the most common inherited disorders},
url = {http://dx.doi.org/10.1093/qjmed/hcag209},
year = {2026}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - <jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Aim</jats:title> <jats:p>To test, we examined if missense variants in HHT disease-causing genes may have been misclassified as pathogenic (LP/P) or benign (B/LB).</jats:p> </jats:sec> <jats:sec> <jats:title>Design</jats:title> <jats:p>Evaluation of ClinVar-annotated missense variants in ENG, ACVRL1 and SMAD4.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>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</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>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 c
AU - Macko,A
AU - Pecon-Slattery,J
AU - Shovlin,CL
DO - qjmed/hcag209
PY - 2026///
SN - 1460-2725
TI - Translating evolutionary history and protein-focused machine learning supports increased prevalence of hereditary haemorrhagic telangiectasia, one of the most common inherited disorders
T2 - QJM: An International Journal of Medicine
UR - http://dx.doi.org/10.1093/qjmed/hcag209
UR - https://doi.org/10.1093/qjmed/hcag209
ER -