The human Stat1 gain-of-function T385M mutation causes expansion of activated T-follicular helper/T-helper 1-like CD4 T cells and sex-biased autoimmunity in specific pathogen-free mice
Bibliographic record
Abstract
Introduction: Humans with gain-of-function (GOF) mutations in STAT1 (Signal Transducer and Activator of Transcription 1), a potent immune regulator, experience frequent infections. About one-third, especially those with DNA-binding domain (DBD) mutations such as T385M, also develop autoimmunity, sometimes accompanied by increases in T-helper 1 (Th1) and T-follicular helper (Tfh) CD4 effector T cells, resembling those that differentiate following infection-induced STAT1 signaling. However, environmental and molecular mechanisms contributing to autoimmunity in STAT1 GOF patients are not defined. Methods: We generated Stat1T385M/+ mutant mice to model the immune impacts of STAT1 DBD GOF under specific-pathogen free (SPF) conditions. Results: Stat1T385M/+ lymphocytes had more total Stat1 at baseline and also higher amounts of IFNg-induced pStat1. Young mutants exhibited expansion of Tfh-like cells, while older mutants developed autoimmunity accompanied by increased Tfh-like cells, B cell activation and germinal center (GC) formation. Mutant females exhibited these immune changes sooner and more robustly than males, identifying significant sex effects of Stat1T385M-induced immune dysregulation. Single cell RNA-Seq (scRNA-Seq) analysis revealed that Stat1T385M activated transcription of GC-associated programs in both B and T cells. However, it had the strongest transcriptional impact on T cells, promoting aberrant CD4 T cell activation and imparting both Tfh-like and Th1-like effector programs. Discussion: Collectively, these data demonstrate that in the absence of overt infection, Stat1T385M disrupted naïve CD4 T cell homeostasis and promoted expansion and differentiation of abnormal Tfh/Th1-like helper and GC-like B cells, eventually leading to sex-biased autoimmunity, suggesting a model for STAT1 GOF-induced immune dysregulation and autoimmune sequelae in humans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".