Lateral meningocele syndrome: genes and variants
Lateral meningocele syndrome is linked to 1 analyzed protein (NOTCH3). 12 DNA variants are known to cause it; 27 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 Lateral meningocele syndrome
NOTCH3: Neurogenic locus notch homolog protein 3
Its signaling helps maintain vascular smooth-muscle and mural-cell identity in small arteries. Pathogenic cysteine-altering variants cause CADASIL, with migraine, recurrent ischemic strokes, white-matter disease, and progressive cognitive impairment.
12 disease-causing and 27 uncertain variants in NOTCH3 are linked to Lateral meningocele syndrome.
Where Lateral meningocele syndrome variants cluster
- NOTCH3 EGF-like 3 (positions 119–156): 3 of 12 disease-causing changes, 15.3× more than its size predicts.
Known disease-causing variants in Lateral meningocele syndrome
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| NOTCH3 C146Y | 146 | EGF-like 3 | Disease-causing (★★) |
| NOTCH3 C1099Y | 1099 | EGF-like 28 | Disease-causing (★★) |
| NOTCH3 R54C | 54 | EGF-like 1 | Disease-causing (★★) |
| NOTCH3 R133C | 133 | EGF-like 3 | Disease-causing (★★) |
| NOTCH3 R141C | 141 | EGF-like 3 | Disease-causing (★★) |
| NOTCH3 R207C | 207 | EGF-like 5 | Disease-causing (★★) |
| NOTCH3 C49G | 49 | EGF-like 1 | Disease-causing (★★) |
| NOTCH3 C106G | 106 | EGF-like 2 | Disease-causing (★★) |
| NOTCH3 R169C | 169 | EGF-like 4 | Disease-causing (★★) |
| NOTCH3 C206Y | 206 | EGF-like 5 | Disease-causing (★★) |
| NOTCH3 R607C | 607 | EGF-like 15 | Disease-causing (★★) |
| NOTCH3 R544C | 544 | Extracellular | Disease-causing (★★) |
Which prediction tools work for Lateral meningocele syndrome
How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).
- REVEL: 96 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- CATVariant: 95 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- CADD: 85 out of 100
- PolyPhen-2: 81 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- SIFT: 70 out of 100
- phyloP: 57 out of 100
Same protein, different disease
- Cerebral arteriopathy, autosomal dominant, with subcortical infarcts and leukoencephalopathy, type 1 is also caused by NOTCH3 variants; they fall mostly in different places as the Lateral meningocele syndrome variants (89 disease-causing).
Diseases related to Lateral meningocele syndrome
- Cerebral arteriopathy, autosomal dominant, with subcortical infarcts and leukoencephalopathy, type 1, also linked to NOTCH3
- Myofibromatosis, infantile, 2, also linked to NOTCH3
- Auditory neuropathy, also linked to NOTCH3
- Adams-Oliver syndrome, also linked to NOTCH3
- Ischemic stroke, also linked to NOTCH3
- Cerebral arteriopathy with subcortical infarcts and leukoencephalopathy, also linked to NOTCH3
Frequently asked questions
Which genes are linked to Lateral meningocele syndrome?
In CATVariant, Lateral meningocele syndrome is linked to 1 analyzed protein: NOTCH3 (Neurogenic locus notch homolog protein 3).
How many genetic variants are linked to Lateral meningocele syndrome?
57 variants: 12 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 27 are of uncertain significance or have conflicting reports.
Which uncertain variants in Lateral meningocele 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 Lateral meningocele syndrome?
Among tools not trained on clinical labels, CADD separates this disease's known disease-causing variants from harmless ones best (AUROC 0.85, based on 9 disease-causing and 84 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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