Autosomal recessive retinitis pigmentosa: genes and variants

Autosomal recessive retinitis pigmentosa is linked to 8 analyzed proteins (MERTK, ABCA4, CRB1, USH2A, EYS, RPE65, PDE6B and RLBP1). 6 DNA variants are known to cause it; 2 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 Autosomal recessive retinitis pigmentosa

Weakly linked (only a few uncertain records): BBS2 and NR2E3.

Known disease-causing variants in Autosomal recessive retinitis pigmentosa

VariantPositionProtein partClinical label
MERTK A740V740Protein kinaseDisease-causing
PDE6B W807R807PDEaseDisease-causing
USH2A A1345P1345Fibronectin type-III 3Disease-causing
CRB1 C27S27ExtracellularDisease-causing
ABCA4 A1881G1881TransmembraneDisease-causing
RLBP1 S149F149CRAL-TRIODisease-causing

Same protein, different disease

Diseases related to Autosomal recessive retinitis pigmentosa

Frequently asked questions

Which genes are linked to Autosomal recessive retinitis pigmentosa?

In CATVariant, Autosomal recessive retinitis pigmentosa is linked to 8 analyzed proteins: MERTK (Tyrosine-protein kinase Mer), ABCA4 (Retinal-specific phospholipid-transporting ATPase ABCA4), CRB1 (Protein crumbs homolog 1), USH2A (Usherin), EYS (Protein eyes shut homolog), RPE65 (Retinoid isomerohydrolase) and 2 more.

How many genetic variants are linked to Autosomal recessive retinitis pigmentosa?

19 variants: 6 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 2 are of uncertain significance or have conflicting reports.

Which uncertain variants in Autosomal recessive retinitis pigmentosa 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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