EPHA4 regulates vascular smooth muscle cell contractility and is a sex-specific hypertension risk gene in individuals with type 2 diabetes
Bibliographic record
Abstract
OBJECTIVE: We investigated the association of genetic variants of EPHA4, a receptor tyrosine kinase, with hypertension, and its role in vascular smooth muscle cell (VSMC) contractility. METHODS: Data from two human genetic studies, ADVANCE and HCHS/SOL, were analyzed for association of EPHA4 single nucleotide variants (SNVs) with hypertension risks. The effect of EPHA4 signalling on mouse VSMC contractility was assessed. RESULTS: We identified a SNV (rs75843691 hg19 chr2:g.222395371 C>G), located in the third intron of EPHA4 gene, being significantly associated with hypertension in human female patients (P value = 8.3 × 10, below the Bonferroni-corrected critical P value) but not male patients with type 2 diabetes from the ADVANCE clinical trial. We found that EPHA4 was expressed in VSMCs and its stimulation by anti-EPHA4 antibody led to reduced VSMC contractility. Estrogen enhanced the contractility-lowering effect of EPHA4 stimulation. Conversely, siRNA knockdown of Epha4 expression in VSMCs resulted in increased contractility of VSMCs from female mice but not from male mice. CONCLUSION: EPHA4 appears to be a sex-specific hypertension risk gene in type 2 diabetic patients. Forward EPHA4 signalling reduces VSMC contractility, and estrogen is a modifier of this effect. The effect of EPHA4 on VSMCs contractility explains the association of EPHA4 gene with hypertension risks in female patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".