Abstract 346: 9p21.3 Coronary Artery Disease Risk Variants Disrupt Tead Transcription Factor Binding and Tead-dependent Tgfβ Induction of P16 Expression
Bibliographic record
Abstract
Background: The mechanism by which 9p21.3 locus increases the risk of CAD is elusive. The 9p21.3 risk locus is associated with reduced expression of the cell cycle suppressor genes CDKN2A (p16) and CDKN2B (p15) and increased vascular smooth muscle cell proliferation. We asked whether risk alleles disrupt transcription factor binding that could account for this effect. Methods and Results: A bioinformatic screen predicted which of 59 single nucleotide polymorphisms (SNPs) disrupt or create transcription factor binding sites at the 9p21.3 risk locus. Electrophoretic mobility shift assay (EMSA) and luciferase reporter assays examined the binding and functionality of the predicted regulatory sequences. Primary human aortic smooth muscle cells (HAoSMCs) genotyped for the 9p21.3 risk allele were used in the functional studies. HAoSMCs homozygous for the risk allele showed reduced expression of p15 and p16 protein levels and increased cellular proliferation compared to the other genotypes. Although 14 out of the 59 SNPs were predicted to have an effect on transcription factor binding,. only rs10811656 and rs4977757 disrupted functional binding sites for TEAD transcription factors by EMSA and luciferase reporter assays. TEAD3 and TEAD4 over-expression induced p16 but not p15 in HAoSMCs homozygous for the non-risk allele, but not for the risk allele. TGFβ is known to activate p16 expression and also to functionally interact with TEAD3 and TEAD4. In HAoSMCs homozygous for the risk allele, TGFβ failed to induce p16 or to inhibit cell proliferation. Knockdown of TEAD3 blocked TGFβ-induced p16 expression and dual knockdown of TEAD3 and TEAD4 markedly reduced p16 expression in heterozygous HAoSMCs. Conclusion: We show for the first time a novel mechanism whereby p16 expression is perturbed by the 9p21.3 risk locus through the disruption of TEAD3 and TEAD4 binding. Furthermore, we show that TGFβ induction of p16 is TEAD3-dependent in HAoSMCs. This mechanism accounts, in part, for the effect of the 9p21.3 risk alleles on CAD. Emerging therapies that activate TEAD factors to inhibit cellular proliferation may also be useful to limit atherosclerosis progression in individuals heterozygous or homozygous for the non-risk allele of 9p21.3.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".