Afibrinogenemia: genes and variants
Afibrinogenemia is linked to 3 analyzed proteins (FGB, FGA and FGG). 9 DNA variants are known to cause it; 108 more are uncertain, and 0 of those already look disease-causing on computable evidence.
Last updated 2026-09-30. Research information, not medical advice.
Also known as: congenital afibrinogenemia
Genes linked to Afibrinogenemia
FGB: Fibrinogen beta chain
It contributes the beta chains required for assembly and secretion of functional fibrinogen and subsequent fibrin-clot formation. Pathogenic variants can reduce fibrinogen quantity or alter clot properties, producing bleeding, thrombosis, or both.
5 disease-causing and 21 uncertain variants in FGB are linked to Afibrinogenemia.
FGA: Fibrinogen alpha chain
It contributes the alpha chains of fibrinogen, which thrombin converts into fibrin to form the structural mesh of blood clots. Pathogenic variants can cause afibrinogenemia, hypofibrinogenemia, dysfibrinogenemia, thrombosis, or certain hereditary amyloidoses.
2 disease-causing and 68 uncertain variants in FGA are linked to Afibrinogenemia.
FGG: Fibrinogen gamma chain
It contributes the gamma chains of fibrinogen and provides binding sites important for fibrin polymerization, platelet interactions, and clot stabilization. Pathogenic variants can cause quantitative or qualitative fibrinogen disorders and, in some alleles, hereditary renal amyloidosis.
2 disease-causing and 19 uncertain variants in FGG are linked to Afibrinogenemia.
Known disease-causing variants in Afibrinogenemia
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| FGG R301H | 301 | Fibrinogen C-terminal | Disease-causing (★★) |
| FGG R401W | 401 | Fibrinogen C-terminal | Disease-causing (★★) |
| FGA R35C | 35 | Disease-causing (★★) | |
| FGA E545V | 545 | Coiled coil | Disease-causing (★★) |
| FGB A98T | 98 | Disease-causing (★) | |
| FGB L202Q | 202 | Coiled coil | Disease-causing |
| FGB G325A | 325 | Fibrinogen C-terminal | Disease-causing |
| FGB L383R | 383 | Fibrinogen C-terminal | Disease-causing |
| FGB G430D | 430 | Fibrinogen C-terminal | Disease-causing |
Which prediction tools work for Afibrinogenemia
How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).
- PolyPhen-2: 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)
- SIFT: 93 out of 100
Same protein, different disease
- Familial dysfibrinogenemia is also caused by FGG variants; they fall mostly in different places as the Afibrinogenemia variants (9 disease-causing).
Diseases related to Afibrinogenemia
- Hypertrophic cardiomyopathy, also linked to FGA, FGB and FGG
- Noonan syndrome, also linked to FGA, FGB and FGG
- Costello syndrome, also linked to FGA, FGB and FGG
- Familial dysfibrinogenemia, also linked to FGA, FGB and FGG
- Hereditary spastic paraplegia, also linked to FGG
- Deep venous thrombosis, also linked to FGA
- Familial visceral amyloidosis, Ostertag type, also linked to FGA
Frequently asked questions
Which genes are linked to Afibrinogenemia?
In CATVariant, Afibrinogenemia is linked to 3 analyzed proteins: FGB (Fibrinogen beta chain), FGA (Fibrinogen alpha chain) and FGG (Fibrinogen gamma chain).
How many genetic variants are linked to Afibrinogenemia?
158 variants: 9 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 108 are of uncertain significance or have conflicting reports.
Which uncertain variants in Afibrinogenemia 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 Afibrinogenemia?
Among tools not trained on clinical labels, SIFT separates this disease's known disease-causing variants from harmless ones best (AUROC 0.93, based on 9 disease-causing and 17 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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