Lewy body dementia: genes and variants

Lewy body dementia is linked to 3 analyzed proteins (GBA1, SNCA and APOE). 8 DNA variants are known to cause it; 9 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 Lewy body dementia

Weakly linked (only a few uncertain records): VCP.

Known disease-causing variants in Lewy body dementia

VariantPositionProtein partClinical label
GBA1 G416S416Disease-causing (★★)
GBA1 W351S351Disease-causing (★★)
GBA1 V433L433Disease-causing (★★)
GBA1 T362I362Disease-causing (★★)
GBA1 N409S409Disease-causing (★★)
SNCA A53T533Disease-causing (★★)
SNCA E46K463Disease-causing (★)
GBA1 P454L454Disease-causing

Which prediction tools work for Lewy body dementia

How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).

Same protein, different disease

Diseases related to Lewy body dementia

Frequently asked questions

Which genes are linked to Lewy body dementia?

In CATVariant, Lewy body dementia is linked to 3 analyzed proteins: GBA1 (Lysosomal acid glucosylceramidase), SNCA (Alpha-synuclein) and APOE (Apolipoprotein E).

How many genetic variants are linked to Lewy body dementia?

18 variants: 8 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 9 are of uncertain significance or have conflicting reports.

Which uncertain variants in Lewy body dementia 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 Lewy body dementia?

Among tools not trained on clinical labels, SIFT separates this disease's known disease-causing variants from harmless ones best (AUROC 0.73, based on 8 disease-causing and 11 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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