Glanzmann thrombasthenia: genes and variants
Glanzmann thrombasthenia is linked to 2 analyzed proteins (ITGA2B and ITGB3). 135 DNA variants are known to cause it; 324 more are uncertain, and 4 of those already look disease-causing on computable evidence.
Last updated 2026-09-30. Research information, not medical advice.
Also known as: Glanzmann thrombasthenia 1; Glanzmann thrombasthenia 2
Genes linked to Glanzmann thrombasthenia
ITGA2B: Integrin alpha-IIb
Together with ITGB3, it forms the major platelet fibrinogen receptor that becomes activated during platelet stimulation and drives aggregation. Biallelic loss-of-function variants cause Glanzmann thrombasthenia, a severe inherited platelet-aggregation disorder.
74 disease-causing and 259 uncertain variants in ITGA2B are linked to Glanzmann thrombasthenia.
ITGB3: Integrin beta-3
In platelets it pairs with ITGA2B to bind fibrinogen and mediate aggregation, while in other cells it forms integrins involved in matrix adhesion and signaling. Biallelic loss-of-function variants cause Glanzmann thrombasthenia.
61 disease-causing and 65 uncertain variants in ITGB3 are linked to Glanzmann thrombasthenia.
Where Glanzmann thrombasthenia variants cluster
- ITGB3 VWFA (positions 135–377): 34 of 61 disease-causing changes, 1.8× more than its size predicts.
- ITGA2B FG-GAP 3 (positions 187–238): 9 of 74 disease-causing changes, 2.4× more than its size predicts.
- ITGA2B FG-GAP 5 (positions 306–371): 9 of 74 disease-causing changes, 1.9× more than its size predicts.
- ITGB3 I-EGF 4 (positions 586–625): 6 of 61 disease-causing changes, 1.9× more than its size predicts.
- ITGA2B FG-GAP 4 (positions 251–305): 7 of 74 disease-causing changes, 1.8× more than its size predicts.
Known disease-causing variants in Glanzmann thrombasthenia
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| ITGA2B P176A | 176 | Extracellular | Disease-causing (★★★) |
| ITGA2B L214R | 214 | FG-GAP 3 | Disease-causing (★★★) |
| ITGA2B G159V | 159 | FG-GAP 2 | Disease-causing (★★★) |
| ITGA2B G159S | 159 | FG-GAP 2 | Disease-causing (★★★) |
| ITGA2B P176H | 176 | Extracellular | Disease-causing (★★★) |
| ITGA2B L214P | 214 | FG-GAP 3 | Disease-causing (★★★) |
| ITGA2B G321W | 321 | FG-GAP 5 | Disease-causing (★★★) |
| ITGA2B G321V | 321 | FG-GAP 5 | Disease-causing (★★★) |
| ITGB3 L143S | 143 | VWFA | Disease-causing (★★★) |
| ITGB3 L143W | 143 | VWFA | Disease-causing (★★★) |
| ITGB3 D145N | 145 | VWFA | Disease-causing (★★★) |
| ITGB3 D145Y | 145 | VWFA | Disease-causing (★★★) |
| ITGB3 Y216C | 216 | VWFA | Disease-causing (★★★) |
| ITGB3 D243V | 243 | VWFA | Disease-causing (★★★) |
| ITGB3 Q254K | 254 | VWFA | Disease-causing (★★★) |
| ITGB3 Q254R | 254 | VWFA | Disease-causing (★★★) |
| ITGB3 D314Y | 314 | VWFA | Disease-causing (★★★) |
| ITGB3 C532F | 532 | I-EGF 2 | Disease-causing (★★★) |
| ITGB3 C532Y | 532 | I-EGF 2 | Disease-causing (★★★) |
| ITGB3 C547W | 547 | I-EGF 2 | Disease-causing (★★★) |
| ITGB3 C601G | 601 | I-EGF 4 | Disease-causing (★★★) |
| ITGB3 C601R | 601 | I-EGF 4 | Disease-causing (★★★) |
| ITGA2B Y174H | 174 | Extracellular | Disease-causing (★★★) |
| ITGA2B P176L | 176 | Extracellular | Disease-causing (★★★) |
| ITGA2B A216V | 216 | FG-GAP 3 | Disease-causing (★★★) |
| ITGA2B F320S | 320 | FG-GAP 5 | Disease-causing (★★★) |
| ITGA2B L452R | 452 | FG-GAP 7 | Disease-causing (★★★) |
| ITGA2B R551W | 551 | Extracellular | Disease-causing (★★★) |
| ITGB3 M144R | 144 | VWFA | Disease-causing (★★★) |
| ITGB3 Y216H | 216 | VWFA | Disease-causing (★★★) |
| ITGB3 R240Q | 240 | VWFA | Disease-causing (★★★) |
| ITGB3 R240W | 240 | VWFA | Disease-causing (★★★) |
| ITGB3 D243H | 243 | VWFA | Disease-causing (★★★) |
| ITGB3 D314A | 314 | VWFA | Disease-causing (★★★) |
| ITGB3 C532R | 532 | I-EGF 2 | Disease-causing (★★★) |
| ITGB3 D250G | 250 | VWFA | Disease-causing (★★★) |
| ITGB3 H281P | 281 | VWFA | Disease-causing (★★★) |
| ITGB3 I330N | 330 | VWFA | Disease-causing (★★★) |
| ITGB3 Y344C | 344 | VWFA | Disease-causing (★★★) |
| ITGB3 Y344S | 344 | VWFA | Disease-causing (★★★) |
| ITGB3 C547G | 547 | I-EGF 2 | Disease-causing (★★★) |
| ITGB3 G605D | 605 | I-EGF 4 | Disease-causing (★★★) |
| ITGA2B L86P | 86 | FG-GAP 1 | Disease-causing (★★★) |
| ITGA2B P157H | 157 | FG-GAP 2 | Disease-causing (★★★) |
| ITGA2B S160R | 160 | FG-GAP 2 | Disease-causing (★★★) |
| ITGA2B S318L | 318 | FG-GAP 5 | Disease-causing (★★★) |
| ITGA2B D396N | 396 | FG-GAP 6 | Disease-causing (★★★) |
| ITGA2B G454D | 454 | FG-GAP 7 | Disease-causing (★★★) |
| ITGA2B I518N | 518 | Extracellular | Disease-causing (★★★) |
| ITGA2B R551Q | 551 | Extracellular | Disease-causing (★★★) |
| ITGA2B C705R | 705 | Extracellular | Disease-causing (★★★) |
| ITGB3 Y141C | 141 | VWFA | Disease-causing (★★★) |
| ITGB3 V219M | 219 | VWFA | Disease-causing (★★★) |
| ITGB3 C549S | 549 | I-EGF 3 | Disease-causing (★★★) |
| ITGA2B G44V | 44 | FG-GAP 1 | Disease-causing (★★★) |
| ITGA2B A139V | 139 | FG-GAP 2 | Disease-causing (★★★) |
| ITGA2B W141C | 141 | FG-GAP 2 | Disease-causing (★★★) |
| ITGA2B G201S | 201 | FG-GAP 3 | Disease-causing (★★★) |
| ITGA2B T207I | 207 | FG-GAP 3 | Disease-causing (★★★) |
| ITGA2B G267E | 267 | FG-GAP 4 | Disease-causing (★★★) |
Showing 60 of 135.
Uncertain variants in Glanzmann thrombasthenia that look disease-causing
| Variant | Position | Protein part | Clinical label | Evidence |
|---|---|---|---|---|
| ITGB3 C568Y | 568 | I-EGF 3 | Uncertain (★) | +6: 2 other pathogenic changes within 3 positions; C568R at the same position is pathogenic; seen in 0 of gnomAD DNA copies; AlphaMissense 0.99 |
| ITGA2B A341V | 341 | FG-GAP 5 | Uncertain (★★★) | +6: 2 other pathogenic changes within 3 positions; A341T at the same position is pathogenic; seen in 0 of gnomAD DNA copies; REVEL 0.764 |
| ITGA2B G296E | 296 | FG-GAP 4 | Uncertain (★) | +6: 2 other pathogenic changes within 3 positions; G296R at the same position is pathogenic; not seen in the gnomAD population database; AlphaMissense 0.96 |
| ITGA2B R358C | 358 | FG-GAP 5 | Uncertain (★★★) | +6: 2 other pathogenic changes within 3 positions; R358H at the same position is pathogenic; seen in 1.4e-06 of gnomAD DNA copies; REVEL 0.656 |
Which prediction tools work for Glanzmann thrombasthenia
How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).
- REVEL: 95 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- CADD: 89 out of 100
- PolyPhen-2: 88 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- SIFT: 87 out of 100
- CATVariant: 86 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- phyloP: 80 out of 100
- MetaLR: 78 out of 100 (learned from overlapping clinical labels, so this is optimistic)
Diseases related to Glanzmann thrombasthenia
- Hypertrophic cardiomyopathy, also linked to ITGA2B and ITGB3
- Noonan syndrome, also linked to ITGA2B and ITGB3
- Costello syndrome, also linked to ITGA2B and ITGB3
- Myocardial infarction, also linked to ITGA2B and ITGB3
- Bleeding disorder, platelet-type, 24, also linked to ITGB3
Frequently asked questions
Which genes are linked to Glanzmann thrombasthenia?
In CATVariant, Glanzmann thrombasthenia is linked to 2 analyzed proteins: ITGA2B (Integrin alpha-IIb) and ITGB3 (Integrin beta-3).
How many genetic variants are linked to Glanzmann thrombasthenia?
569 variants: 135 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 324 are of uncertain significance or have conflicting reports.
Which uncertain variants in Glanzmann thrombasthenia look disease-causing?
4 uncertain variants reach the likely-pathogenic range of the ACMG/AMP points scale on computable evidence, for example ITGB3 C568Y, ITGA2B A341V, ITGA2B G296E and ITGA2B R358C. These are leads for expert review, not diagnoses.
Which variant effect predictor works best for Glanzmann thrombasthenia?
Among tools not trained on clinical labels, CADD separates this disease's known disease-causing variants from harmless ones best (AUROC 0.89, based on 74 disease-causing and 21 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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