STAT3 gain of function: genes and variants
STAT3 gain of function is linked to 1 analyzed protein (STAT3). 49 DNA variants are known to cause it; 167 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 STAT3 gain of function
STAT3: Signal transducer and activator of transcription 3
It translates cytokine and growth-factor signals into transcriptional programs governing immune regulation, survival, proliferation, and tissue repair. Dominant-negative variants cause hyper-IgE syndrome, while activating germline variants cause early autoimmunity and lymphoproliferation and somatic activation contributes to cancer.
49 disease-causing and 167 uncertain variants in STAT3 are linked to STAT3 gain of function.
Where STAT3 gain of function variants cluster
- STAT3 SH2 (positions 580–670): 17 of 49 disease-causing changes, 2.9× more than its size predicts.
Known disease-causing variants in STAT3 gain of function
| Variant | Position | Protein part | Clinical label |
|---|---|---|---|
| STAT3 R382W | 382 | Disease-causing (★★) | |
| STAT3 R382Q | 382 | Disease-causing (★★) | |
| STAT3 F621L | 621 | SH2 | Disease-causing (★★) |
| STAT3 V637M | 637 | SH2 | Disease-causing (★★) |
| STAT3 L706P | 706 | Disease-causing (★★) | |
| STAT3 R278C | 278 | Disease-causing (★★) | |
| STAT3 G421R | 421 | Disease-causing (★★) | |
| STAT3 R423Q | 423 | Disease-causing (★★) | |
| STAT3 Y657C | 657 | SH2 | Disease-causing (★★) |
| STAT3 I659N | 659 | SH2 | Disease-causing (★★) |
| STAT3 M660T | 660 | SH2 | Disease-causing (★★) |
| STAT3 K709E | 709 | Disease-causing (★★) | |
| STAT3 P715L | 715 | Disease-causing (★★) | |
| STAT3 R152W | 152 | Essential for nuclear import | Disease-causing (★★) |
| STAT3 H332Y | 332 | Disease-causing (★★) | |
| STAT3 R335W | 335 | Disease-causing (★★) | |
| STAT3 T389A | 389 | Disease-causing (★★) | |
| STAT3 N466T | 466 | Disease-causing (★★) | |
| STAT3 E594K | 594 | SH2 | Disease-causing (★★) |
| STAT3 T716M | 716 | Disease-causing (★★) | |
| STAT3 L673P | 673 | Disease-causing (★★) | |
| STAT3 P695L | 695 | Disease-causing (★★) | |
| STAT3 R382P | 382 | Disease-causing (★) | |
| STAT3 F621V | 621 | SH2 | Disease-causing (★) |
| STAT3 S636F | 636 | SH2 | Disease-causing (★) |
| STAT3 S636Y | 636 | SH2 | Disease-causing (★) |
| STAT3 V637L | 637 | SH2 | Disease-causing (★) |
| STAT3 P639A | 639 | SH2 | Disease-causing (★) |
| STAT3 P639T | 639 | SH2 | Disease-causing (★) |
| STAT3 Y705H | 705 | Disease-causing (★) | |
| STAT3 T714I | 714 | Disease-causing (★) | |
| STAT3 T714K | 714 | Disease-causing (★) | |
| STAT3 Y705C | 705 | Disease-causing (★) | |
| STAT3 L706M | 706 | Disease-causing (★) | |
| STAT3 R278H | 278 | Disease-causing (★) | |
| STAT3 M394T | 394 | Disease-causing (★) | |
| STAT3 M394I | 394 | Disease-causing (★) | |
| STAT3 T622I | 622 | SH2 | Disease-causing (★) |
| STAT3 K642E | 642 | SH2 | Disease-causing (★) |
| STAT3 Y672C | 672 | Disease-causing (★) | |
| STAT3 T620S | 620 | SH2 | Disease-causing (★) |
| STAT3 V713L | 713 | Disease-causing (★) | |
| STAT3 R103W | 103 | Disease-causing (★) | |
| STAT3 L287F | 287 | Disease-causing (★) | |
| STAT3 M329K | 329 | Disease-causing (★) | |
| STAT3 H410Y | 410 | Disease-causing (★) | |
| STAT3 H437Q | 437 | Disease-causing (★) | |
| STAT3 T600S | 600 | SH2 | Disease-causing (★) |
| STAT3 L645Q | 645 | SH2 | Disease-causing (★) |
Uncertain variants in STAT3 gain of function that look disease-causing
| Variant | Position | Protein part | Clinical label | Evidence |
|---|---|---|---|---|
| STAT3 R335Q | 335 | Conflicting reports (★) | +7: 2 other pathogenic changes within 3 positions; R335W at the same position is pathogenic; seen in 4.1e-06 of gnomAD DNA copies; REVEL 0.818 | |
| STAT3 G421E | 421 | Uncertain (★) | +6: 2 other pathogenic changes within 3 positions; G421R at the same position is pathogenic; seen in 6.8e-07 of gnomAD DNA copies; REVEL 0.700 |
Which prediction tools work for STAT3 gain of function
How often each tool ranks a disease-causing variant above a harmless one (AUROC × 100).
- CATVariant: 88 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- CADD: 88 out of 100
- REVEL: 88 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- SIFT: 84 out of 100
- PolyPhen-2: 79 out of 100 (learned from overlapping clinical labels, so this is optimistic)
- phyloP: 56 out of 100
Same protein, different disease
- Hyper-IgE recurrent infection syndrome 1, autosomal dominant is also caused by STAT3 variants; they fall in the same places as the STAT3 gain of function variants (65 disease-causing).
- STAT3-related early-onset multisystem autoimmune disease is also caused by STAT3 variants; they fall partly in the same places as the STAT3 gain of function variants (21 disease-causing).
Diseases related to STAT3 gain of function
- Hyper-IgE recurrent infection syndrome 1, autosomal dominant, also linked to STAT3
- STAT3-related early-onset multisystem autoimmune disease, also linked to STAT3
- Inherited Immunodeficiency Diseases, also linked to STAT3
- Hyper-IgE syndrome 6, autosomal dominant, with recurrent infections, also linked to STAT3
Frequently asked questions
Which genes are linked to STAT3 gain of function?
In CATVariant, STAT3 gain of function is linked to 1 analyzed protein: STAT3 (Signal transducer and activator of transcription 3).
How many genetic variants are linked to STAT3 gain of function?
246 variants: 49 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 167 are of uncertain significance or have conflicting reports.
Which uncertain variants in STAT3 gain of function look disease-causing?
2 uncertain variants reach the likely-pathogenic range of the ACMG/AMP points scale on computable evidence, for example STAT3 R335Q and STAT3 G421E. These are leads for expert review, not diagnoses.
Which variant effect predictor works best for STAT3 gain of function?
Among tools not trained on clinical labels, CADD separates this disease's known disease-causing variants from harmless ones best (AUROC 0.88, based on 8 disease-causing and 25 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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