BENTA disease: genes and variants
BENTA disease is linked to 1 analyzed protein (CARD11). 8 DNA variants are known to cause it; 388 more are uncertain, and 2 of those already look disease-causing on computable evidence.
Last updated 2026-09-30. Research information, not medical advice.
Genes linked to BENTA disease
CARD11: Caspase recruitment domain-containing protein 11
It assembles the CARD11-BCL10-MALT1 signaling complex after antigen-receptor activation, allowing lymphocytes to activate NF-kappaB and related pathways. Gain-of-function variants cause lymphoproliferative disease, while loss-of-function or dominant-negative variants can cause immunodeficiency or severe atopy.
8 disease-causing and 388 uncertain variants in CARD11 are linked to BENTA disease.
Where BENTA disease variants cluster
- CARD11 Linker (positions 111–128): 3 of 8 disease-causing changes, 24.0× more than its size predicts.
- CARD11 CARD (positions 18–110): 4 of 8 disease-causing changes, 6.2× more than its size predicts.
Known disease-causing variants in BENTA disease
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| CARD11 R30W | 30 | CARD | Disease-causing (★★) |
| CARD11 G123S | 123 | Linker | Disease-causing (★★) |
| CARD11 G123D | 123 | Linker | Disease-causing (★★) |
| CARD11 R47H | 47 | CARD | Disease-causing (★★) |
| CARD11 G126D | 126 | Linker | Disease-causing (★) |
| CARD11 C49Y | 49 | CARD | Disease-causing (★) |
| CARD11 R30G | 30 | CARD | Disease-causing |
| CARD11 E134G | 134 | Coiled coil | Disease-causing |
Uncertain variants in BENTA disease that look disease-causing
| Variant | Position | Protein part | Clinical label | Evidence |
|---|---|---|---|---|
| CARD11 R47C | 47 | CARD | Uncertain (★) | +6: 2 other pathogenic changes within 3 positions; R47H at the same position is pathogenic; not seen in the gnomAD population database; AlphaMissense 1.00 |
| CARD11 R47S | 47 | CARD | Uncertain (★) | +6: 2 other pathogenic changes within 3 positions; R47H at the same position is pathogenic; not seen in the gnomAD population database; AlphaMissense 1.00 |
Which prediction tools work for BENTA disease
How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).
- CATVariant: 98 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- PolyPhen-2: 98 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- SIFT: 91 out of 100
Same protein, different disease
- Immunodeficiency 11b with atopic dermatitis is also caused by CARD11 variants; they fall mostly in different places as the BENTA disease variants (5 disease-causing).
Diseases related to BENTA disease
- Severe combined immunodeficiency due to CARD11 deficiency, also linked to CARD11
- Immunodeficiency 11b with atopic dermatitis, also linked to CARD11
Frequently asked questions
Which genes are linked to BENTA disease?
In CATVariant, BENTA disease is linked to 1 analyzed protein: CARD11 (Caspase recruitment domain-containing protein 11).
How many genetic variants are linked to BENTA disease?
509 variants: 8 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 388 are of uncertain significance or have conflicting reports.
Which uncertain variants in BENTA disease look disease-causing?
2 uncertain variants reach the likely-pathogenic range of the ACMG/AMP points scale on computable evidence, for example CARD11 R47C and CARD11 R47S. These are leads for expert review, not diagnoses.
Which variant effect predictor works best for BENTA disease?
Among tools not trained on clinical labels, SIFT separates this disease's known disease-causing variants from harmless ones best (AUROC 0.91, based on 8 disease-causing and 100 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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