Idiopathic generalized epilepsy: genes and variants

Idiopathic generalized epilepsy is linked to 5 analyzed proteins (GABRA1, CASR, KCNMA1, SLC2A1 and ABCB1). 21 DNA variants are known to cause it; 160 more are uncertain, and 3 of those already look disease-causing on computable evidence.

Last updated 2026-09-30. Research information, not medical advice.

Genes linked to Idiopathic generalized epilepsy

Where Idiopathic generalized epilepsy variants cluster

Known disease-causing variants in Idiopathic generalized epilepsy

VariantPositionProtein partClinical label
GABRA1 R214C214ExtracellularDisease-causing (★★)
GABRA1 R214H214ExtracellularDisease-causing (★★)
GABRA1 T289A289TransmembraneDisease-causing (★★)
GABRA1 R147Q147ExtracellularDisease-causing (★★)
GABRA1 T295I295TransmembraneDisease-causing (★★)
GABRA1 T292I292TransmembraneDisease-causing (★)
GABRA1 S213T213ExtracellularDisease-causing (★)
GABRA1 E277G277CytoplasmicDisease-causing (★)
GABRA1 F42L42ExtracellularDisease-causing (★)
GABRA1 F92S92ExtracellularDisease-causing (★)
GABRA1 G251S251ExtracellularDisease-causing (★)
GABRA1 Y252C252ExtracellularDisease-causing (★)
GABRA1 M263T263TransmembraneDisease-causing (★)
GABRA1 L267F267TransmembraneDisease-causing (★)
GABRA1 N275K275CytoplasmicDisease-causing (★)
GABRA1 T288I288TransmembraneDisease-causing (★)
GABRA1 F325L325TransmembraneDisease-causing (★)
GABRA1 A188D188ExtracellularDisease-causing (★)
GABRA1 P280Q280TransmembraneDisease-causing (★)
GABRA1 R2K2Disease-causing (★)
ABCB1 S893Y893ABC transmembrane type-1 2Disease-causing

Uncertain variants in Idiopathic generalized epilepsy that look disease-causing

VariantPositionProtein partClinical labelEvidence
GABRA1 R214S214ExtracellularConflicting reports (★)+6: 3 other pathogenic changes within 3 positions; R214H at the same position is pathogenic; not seen in the gnomAD population database; AlphaMissense 0.89
GABRA1 N275S275CytoplasmicUncertain (★★)+6: 2 other pathogenic changes within 3 positions; N275K at the same position is pathogenic; not seen in the gnomAD population database; AlphaMissense 0.65
GABRA1 E277D277CytoplasmicUncertain (★)+6: 3 other pathogenic changes within 3 positions; E277G at the same position is pathogenic; not seen in the gnomAD population database; AlphaMissense 0.95

Which prediction tools work for Idiopathic generalized epilepsy

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

Diseases related to Idiopathic generalized epilepsy

Frequently asked questions

Which genes are linked to Idiopathic generalized epilepsy?

In CATVariant, Idiopathic generalized epilepsy is linked to 5 analyzed proteins: GABRA1 (Gamma-aminobutyric acid receptor subunit alpha-1), CASR (Extracellular calcium-sensing receptor), KCNMA1 (Calcium-activated potassium channel subunit alpha-1), SLC2A1 (Solute carrier family 2, facilitated glucose transporter member 1) and ABCB1 (ATP-dependent translocase ABCB1).

How many genetic variants are linked to Idiopathic generalized epilepsy?

194 variants: 21 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 160 are of uncertain significance or have conflicting reports.

Which uncertain variants in Idiopathic generalized epilepsy look disease-causing?

3 uncertain variants reach the likely-pathogenic range of the ACMG/AMP points scale on computable evidence, for example GABRA1 R214S, GABRA1 N275S and GABRA1 E277D. These are leads for expert review, not diagnoses.

Which variant effect predictor works best for Idiopathic generalized epilepsy?

Among tools not trained on clinical labels, AlphaMissense separates this disease's known disease-causing variants from harmless ones best (AUROC 0.79, based on 16 disease-causing and 9 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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