Infantile myofibromatosis: genes and variants
Infantile myofibromatosis is linked to 1 analyzed protein (PDGFRB). 8 DNA variants are known to cause it; 95 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 Infantile myofibromatosis
PDGFRB: Platelet-derived growth factor receptor beta
Its signaling supports pericytes, vascular smooth-muscle cells, and other mesenchymal lineages during growth and tissue repair. Oncogenic fusions drive myeloid neoplasms, while germline activating or loss-of-function variants can cause developmental and vascular disorders.
8 disease-causing and 95 uncertain variants in PDGFRB are linked to Infantile myofibromatosis.
Where Infantile myofibromatosis variants cluster
- PDGFRB Cytoplasmic (positions 554–1106): 7 of 8 disease-causing changes, 1.8× more than its size predicts.
Known disease-causing variants in Infantile myofibromatosis
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| PDGFRB N666H | 666 | Protein kinase | Disease-causing (★★) |
| PDGFRB N666K | 666 | Protein kinase | Disease-causing (★★) |
| PDGFRB R561C | 561 | Cytoplasmic | Disease-causing (★★) |
| PDGFRB W566R | 566 | Cytoplasmic | Disease-causing (★★) |
| PDGFRB I538N | 538 | Transmembrane | Disease-causing (★) |
| PDGFRB Y562D | 562 | Cytoplasmic | Disease-causing (★) |
| PDGFRB A828E | 828 | Protein kinase | Disease-causing (★) |
| PDGFRB D850V | 850 | Protein kinase | Disease-causing (★) |
Which prediction tools work for Infantile myofibromatosis
How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).
- CATVariant: 97 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- PolyPhen-2: 94 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- SIFT: 91 out of 100
Same protein, different disease
- Skeletal overgrowth-craniofacial dysmorphism-hyperelastic skin-white matter lesions syndrome is also caused by PDGFRB variants; they fall mostly in different places as the Infantile myofibromatosis variants (4 disease-causing).
Diseases related to Infantile myofibromatosis
- Gastrointestinal stromal tumor, also linked to PDGFRB
- Acute myeloid leukemia, also linked to PDGFRB
- Colorectal cancer, also linked to PDGFRB
- Non-small cell lung carcinoma, also linked to PDGFRB
- Myofibromatosis, infantile, 2, also linked to PDGFRB
- Idiopathic pulmonary fibrosis, also linked to PDGFRB
- Hepatocellular carcinoma, also linked to PDGFRB
- Acroosteolysis-keloid-like lesions-premature aging syndrome, also linked to PDGFRB
- Renal cell carcinoma, also linked to PDGFRB
- Skeletal overgrowth-craniofacial dysmorphism-hyperelastic skin-white matter lesions syndrome, also linked to PDGFRB
- Basal ganglia calcification, idiopathic, 4, also linked to PDGFRB
- Myeloproliferative disorder, chronic, with eosinophilia, also linked to PDGFRB
Frequently asked questions
Which genes are linked to Infantile myofibromatosis?
In CATVariant, Infantile myofibromatosis is linked to 1 analyzed protein: PDGFRB (Platelet-derived growth factor receptor beta).
How many genetic variants are linked to Infantile myofibromatosis?
139 variants: 8 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 95 are of uncertain significance or have conflicting reports.
Which uncertain variants in Infantile myofibromatosis 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 Infantile myofibromatosis?
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 87 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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