Familial temporal lobe epilepsy 7: genes and variants
Familial temporal lobe epilepsy 7 is linked to 1 analyzed protein (RELN). 4 DNA variants are known to cause it; 1,431 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 Familial temporal lobe epilepsy 7
RELN: Reelin
It is secreted during brain development to guide neuronal migration and cortical layering and later modulates synaptic plasticity. Biallelic loss-of-function variants cause lissencephaly with cerebellar hypoplasia, while heterozygous variants can be associated with epilepsy.
4 disease-causing and 1,431 uncertain variants in RELN are linked to Familial temporal lobe epilepsy 7.
Known disease-causing variants in Familial temporal lobe epilepsy 7
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| RELN D763G | 763 | Disease-causing | |
| RELN H798N | 798 | BNR 2 | Disease-causing |
| RELN G2783C | 2783 | BNR 13 | Disease-causing |
| RELN E3176K | 3176 | Disease-causing |
Diseases related to Familial temporal lobe epilepsy 7
- Self-limited epilepsy with centrotemporal spikes, also linked to RELN
Frequently asked questions
Which genes are linked to Familial temporal lobe epilepsy 7?
In CATVariant, Familial temporal lobe epilepsy 7 is linked to 1 analyzed protein: RELN (Reelin).
How many genetic variants are linked to Familial temporal lobe epilepsy 7?
1,660 variants: 4 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 1,431 are of uncertain significance or have conflicting reports.
Which uncertain variants in Familial temporal lobe epilepsy 7 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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