Gilbert syndrome: genes and variants

Gilbert syndrome is linked to 1 analyzed protein (UGT1A1). 10 DNA variants are known to cause it; 28 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 Gilbert syndrome

Weakly linked (only a few uncertain records): SLCO1B1.

Known disease-causing variants in Gilbert syndrome

VariantPositionProtein partClinical label
UGT1A1 G308E308Disease-causing (★★)
UGT1A1 R209W209Disease-causing (★★)
UGT1A1 P387R387Disease-causing (★★)
UGT1A1 Y486D486Disease-causing (★★)
UGT1A1 Q331R331Disease-causing (★★)
UGT1A1 C177Y177Disease-causing (★★)
UGT1A1 Q357R357Disease-causing (★★)
UGT1A1 L15R15Disease-causing (★)
UGT1A1 F83L83Disease-causing (★)
UGT1A1 S306F306Disease-causing

Which prediction tools work for Gilbert syndrome

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

Same protein, different disease

Diseases related to Gilbert syndrome

Frequently asked questions

Which genes are linked to Gilbert syndrome?

In CATVariant, Gilbert syndrome is linked to 1 analyzed protein: UGT1A1 (UDP-glucuronosyltransferase 1A1).

How many genetic variants are linked to Gilbert syndrome?

53 variants: 10 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 28 are of uncertain significance or have conflicting reports.

Which uncertain variants in Gilbert syndrome 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 Gilbert syndrome?

Among tools not trained on clinical labels, CADD separates this disease's known disease-causing variants from harmless ones best (AUROC 0.98, based on 9 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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