Corpus callosum, agenesis of: genes and variants
Corpus callosum, agenesis of is linked to 2 analyzed proteins (CDH2 and DCC). 10 DNA variants are known to cause it; 3 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 Corpus callosum, agenesis of
CDH2: Cadherin-2
It mediates calcium-dependent cell-cell adhesion in neural, cardiac, and mesenchymal tissues and helps organize adherens junctions during development. Heterozygous pathogenic variants can cause a syndromic neurodevelopmental disorder with variable cardiac and craniofacial abnormalities.
4 disease-causing and 0 uncertain variants in CDH2 are linked to Corpus callosum, agenesis of.
DCC: Netrin receptor DCC
It guides developing axons in response to netrin signals and helps establish long-range neural connections across the midline. Heterozygous pathogenic variants can cause congenital mirror movements, while biallelic or severe variants can produce complex neurodevelopmental syndromes.
6 disease-causing and 0 uncertain variants in DCC are linked to Corpus callosum, agenesis of.
Weakly linked (only a few uncertain records): BCOR, EP300 and ERCC2.
Known disease-causing variants in Corpus callosum, agenesis of
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| CDH2 D353N | 353 | Cadherin 2 | Disease-causing (★) |
| CDH2 D597Y | 597 | Cadherin 4 | Disease-causing |
| CDH2 N601T | 601 | Cadherin 4 | Disease-causing |
| CDH2 D627G | 627 | Cadherin 5 | Disease-causing |
| DCC V793G | 793 | Fibronectin type-III 4 | Disease-causing |
| DCC G805E | 805 | Fibronectin type-III 4 | Disease-causing |
| DCC R597P | 597 | Fibronectin type-III 2 | Disease-causing |
| DCC A1250T | 1250 | Cytoplasmic | Disease-causing |
| DCC A893T | 893 | Fibronectin type-III 5 | Disease-causing |
| DCC M1217V | 1217 | Cytoplasmic | Disease-causing |
Which prediction tools work for Corpus callosum, agenesis of
How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).
- PolyPhen-2: 83 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- MetaLR: 81 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- SIFT: 78 out of 100
- CATVariant: 73 out of 100 (learned from overlapping clinical labels, so this is optimistic)
Diseases related to Corpus callosum, agenesis of
- Auditory neuropathy, also linked to CDH2
- Carcinoma of colon, also linked to DCC
- Mirror movements 1, also linked to DCC
- Agenesis of corpus callosum, cardiac, ocular, and genital syndrome, also linked to CDH2
- Arrhythmogenic right ventricular dysplasia, familial, 14, also linked to CDH2
- Gaze palsy, familial horizontal, with progressive scoliosis, 2, also linked to DCC
Frequently asked questions
Which genes are linked to Corpus callosum, agenesis of?
In CATVariant, Corpus callosum, agenesis of is linked to 2 analyzed proteins: CDH2 (Cadherin-2) and DCC (Netrin receptor DCC).
How many genetic variants are linked to Corpus callosum, agenesis of?
13 variants: 10 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 3 are of uncertain significance or have conflicting reports.
Which uncertain variants in Corpus callosum, agenesis of 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 Corpus callosum, agenesis of?
Among tools not trained on clinical labels, SIFT separates this disease's known disease-causing variants from harmless ones best (AUROC 0.79, based on 10 disease-causing and 354 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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