Acroosteolysis-keloid-like lesions-premature aging syndrome: genes and variants

Acroosteolysis-keloid-like lesions-premature aging syndrome is linked to 1 analyzed protein (PDGFRB). 6 DNA variants are known to cause it; 114 more are uncertain, and 0 of those already look disease-causing on computable evidence.

Last updated 2026-09-30. Research information, not medical advice.

Genes linked to Acroosteolysis-keloid-like lesions-premature aging syndrome

Where Acroosteolysis-keloid-like lesions-premature aging syndrome variants cluster

Known disease-causing variants in Acroosteolysis-keloid-like lesions-premature aging syndrome

VariantPositionProtein partClinical label
PDGFRB R561C561CytoplasmicDisease-causing (★★)
PDGFRB W566R566CytoplasmicDisease-causing (★★)
PDGFRB N666H666Protein kinaseDisease-causing (★★)
PDGFRB P560L560CytoplasmicDisease-causing (★★)
PDGFRB A828E828Protein kinaseDisease-causing (★)
PDGFRB V665A665Protein kinaseDisease-causing

Same protein, different disease

Diseases related to Acroosteolysis-keloid-like lesions-premature aging syndrome

Frequently asked questions

Which genes are linked to Acroosteolysis-keloid-like lesions-premature aging syndrome?

In CATVariant, Acroosteolysis-keloid-like lesions-premature aging syndrome is linked to 1 analyzed protein: PDGFRB (Platelet-derived growth factor receptor beta).

How many genetic variants are linked to Acroosteolysis-keloid-like lesions-premature aging syndrome?

181 variants: 6 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 114 are of uncertain significance or have conflicting reports.

Which uncertain variants in Acroosteolysis-keloid-like lesions-premature aging syndrome look disease-causing?

None of the uncertain variants currently reaches the likely-pathogenic range on computable evidence alone.

About this data

Variant–disease links come from ClinVar, Open Targets and UniProt, pooled from the latest public CATVariant analysis of each human protein. Evidence scores use the ACMG/AMP Bayesian points scale with computable criteria only (position among known disease variants, rarity in gnomAD, calibrated predictors, deep mutational scanning); there is no family or patient data, so they prioritise variants for expert review and never classify them.

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