Kufor-Rakeb syndrome: genes and variants
Kufor-Rakeb syndrome is linked to 1 analyzed protein (ATP13A2). 3 DNA variants are known to cause it; 363 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 Kufor-Rakeb syndrome
ATP13A2: Polyamine-transporting ATPase 13A2
It supports lysosomal and endolysosomal homeostasis and transports polyamines and other cationic substrates across intracellular membranes. Biallelic pathogenic variants cause Kufor-Rakeb syndrome and related early-onset parkinsonian-neurodegenerative phenotypes.
3 disease-causing and 363 uncertain variants in ATP13A2 are linked to Kufor-Rakeb syndrome.
Known disease-causing variants in Kufor-Rakeb syndrome
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| ATP13A2 G504R | 504 | Cytoplasmic | Disease-causing (★★) |
| ATP13A2 G877R | 877 | Cytoplasmic | Disease-causing |
| ATP13A2 M854R | 854 | Cytoplasmic | Disease-causing |
Diseases related to Kufor-Rakeb syndrome
- Neurodegeneration with brain iron accumulation, also linked to ATP13A2
- Autosomal recessive spastic paraplegia type 78, also linked to ATP13A2
- Parkinson disease, also linked to ATP13A2
Frequently asked questions
Which genes are linked to Kufor-Rakeb syndrome?
In CATVariant, Kufor-Rakeb syndrome is linked to 1 analyzed protein: ATP13A2 (Polyamine-transporting ATPase 13A2).
How many genetic variants are linked to Kufor-Rakeb syndrome?
394 variants: 3 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 363 are of uncertain significance or have conflicting reports.
Which uncertain variants in Kufor-Rakeb 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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