Abstract 105: Lipid Regulation of Senescent Effector CD8 T Cells in Type 2 Diabetes
Bibliographic record
Abstract
Introduction: Atherosclerotic plaques from patients with Type 2 Diabetes (T2D) present a more severe pathology than non-T2D (ND) plaques and response to cholesterol-lowering is compromised. An increased level of circulating senescent CD8 T cells in T2D patients is associated with increased risk for myocardial infarction. However, whether senescent T cells infiltrate human atherosclerotic plaques and how they are regulated by lipid lowering is unknown. Hypothesis: Senescent CD8+ T cells are increased in atherosclerotic plaques and circulation of T2D, and are normalized by aggressive lipid lowering in T2D. Methods: We performed unbiased scRNA-seq analysis (75,049 total cells) of immune cells in plaques from T2D (n=12) and ND patients (n=10) to identify senescent T cells in human atherosclerotic plaques. Using CyTOF we tested the effect of aggressive lipid lowering on circulating CD8 T cells in T2D (n=16) and ND (n=6) patients. Results: We identified senescent T cells within atherosclerotic plaques and found that senescent CD8 T cells largely accumulate in plaques from T2D patients (p<0.001). Plaque CD8 T cells showed a terminally differentiated effector memory phenotype with high expression of CX3CR1 and low expression of SELL and CCR7 genes. CD8 T cell clusters express senescence markers ( B3GAT1,KLRG1,KLRD1,KLRF1 ) and presented senescence associated secretory phenotype with high expression of cytotoxic ( GZMB,PRF1,GNLY ) and proatherogenic ( IFNG,TNFA,CCL5 ) genes. CyTOF analysis showed higher levels of circulating senescent CD57+CD28-CD8 T cells in patients with T2D vs ND controls (p<0.001). Potent lipid lowering with PCSK9 inhibitor + statin/ezetimibe, which reduced LDL-C levels by >70% in all patients at 4 weeks, normalized the frequency of circulating senescent CD8 T cells (p<0.001) in T2D patients to the levels found in ND. Conclusion: Our results show that senescent CD8 T cells accumulated in blood and plaques of T2D patients and that potent lipid lowering diminished circulating aged CD8 T cells, suggesting that CD8 T cell senescence can be improved by aggressive lipid control in high-risk T2D subjects. Further analyses are needed to understand the role of lipid metabolism in the T cell senescence and the impact on atherosclerosis progression.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".