Autosomal recessive early-onset Parkinson disease 6: genes and variants
Autosomal recessive early-onset Parkinson disease 6 is linked to 2 analyzed proteins (PINK1 and PARK7). 14 DNA variants are known to cause it; 153 more are uncertain, and 0 of those already look disease-causing on computable evidence.
Last updated 2026-09-30. Research information, not medical advice.
Also known as: Autosomal recessive early-onset Parkinson disease 7
Genes linked to Autosomal recessive early-onset Parkinson disease 6
PINK1: Serine/threonine-protein kinase PINK1, mitochondrial
It accumulates on damaged mitochondria and recruits parkin to initiate selective mitophagy and mitochondrial quality control. Biallelic loss-of-function variants cause autosomal recessive early-onset Parkinson disease.
7 disease-causing and 125 uncertain variants in PINK1 are linked to Autosomal recessive early-onset Parkinson disease 6.
PARK7: Parkinson disease protein 7
It supports mitochondrial quality control, redox homeostasis, and cellular responses to oxidative stress. Biallelic loss-of-function variants cause a rare autosomal recessive form of early-onset Parkinson disease.
7 disease-causing and 28 uncertain variants in PARK7 are linked to Autosomal recessive early-onset Parkinson disease 6.
Known disease-causing variants in Autosomal recessive early-onset Parkinson disease 6
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| PINK1 A168P | 168 | Protein kinase | Disease-causing (★★) |
| PINK1 L347P | 347 | Protein kinase | Disease-causing (★★) |
| PINK1 T313M | 313 | Protein kinase | Disease-causing (★★) |
| PARK7 L101P | 101 | Disease-causing (★) | |
| PARK7 G108S | 108 | Disease-causing (★) | |
| PINK1 Q126P | 126 | Disease-causing (★) | |
| PARK7 M26I | 26 | Disease-causing | |
| PARK7 R28Q | 28 | Disease-causing | |
| PARK7 E163K | 163 | Disease-causing | |
| PARK7 L166P | 166 | Disease-causing | |
| PINK1 A217D | 217 | Protein kinase | Disease-causing |
| PINK1 H271Q | 271 | Protein kinase | Disease-causing |
| PINK1 G309D | 309 | Protein kinase | Disease-causing |
| PARK7 E64D | 64 | Disease-causing |
Which prediction tools work for Autosomal recessive early-onset Parkinson disease 6
How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).
- SIFT: 94 out of 100
- CATVariant: 92 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- REVEL: 91 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- CADD: 84 out of 100
- PolyPhen-2: 81 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- phyloP: 79 out of 100
Diseases related to Autosomal recessive early-onset Parkinson disease 6
- Parkinson disease, also linked to PARK7 and PINK1
- Young-onset Parkinson disease, also linked to PARK7
Frequently asked questions
Which genes are linked to Autosomal recessive early-onset Parkinson disease 6?
In CATVariant, Autosomal recessive early-onset Parkinson disease 6 is linked to 2 analyzed proteins: PINK1 (Serine/threonine-protein kinase PINK1, mitochondrial) and PARK7 (Parkinson disease protein 7).
How many genetic variants are linked to Autosomal recessive early-onset Parkinson disease 6?
178 variants: 14 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 153 are of uncertain significance or have conflicting reports.
Which uncertain variants in Autosomal recessive early-onset Parkinson disease 6 look disease-causing?
None of the uncertain variants currently reaches the likely-pathogenic range on computable evidence alone.
Which variant effect predictor works best for Autosomal recessive early-onset Parkinson disease 6?
Among tools not trained on clinical labels, SIFT separates this disease's known disease-causing variants from harmless ones best (AUROC 0.94, based on 14 disease-causing and 14 harmless variants).
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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