Reduction of plasma angiopoietin‐like 2 after cardiac surgery is related to tissue inflammation and senescence status of patients
Bibliographic record
Abstract
Introduction A strong positive relationship has been reported in humans between high levels of circulating angiopoietin‐like 2 (ANGPTL2), a pro‐inflammatory adipokine, and cardiovascular diseases (CVD). ANGPTL2 levels can predict the incidence of CVD, but whether a cardiac surgery such as a coronary artery bypass graft (CABG), aortic valve replacement or both, is able to modulate ANGPTL2 levels is unknown. Hypothesis Cardiac surgery alleviates cardiac stress and lowers ANGPTL2 circulating levels. Methods In patients undergoing CABG (n=16), valve replacement (n=16), or both (n=15), blood was taken before surgery and 24h, 4±1 days (hospital discharge) and 60±30 days (follow‐up visit) post‐surgery to quantify plasma levels of ANGPTL2 and plasma hs‐CRP levels. Mediastinal adipose tissue (MAT) and internal mammary fragments (IMA) were dissected out during surgery, RNA extracted and gene expression assessed by quantitative RT‐PCR. Results The type of surgery had no impact on the overall profile of plasma ANGPTL2 or hs‐CRP levels post‐surgery. Both markers rose transiently after 24h and returned progressively to baseline levels. However, we observed two different patterns for ANGPTL2: compared to basal values, levels either decreased in 45% (DECREASED group, n=21) or increased in 55% (INCREASED group, n=26) of the patients at the end of the follow‐up (p<0.001). In contrast, hs‐CRP levels were identical between these two groups (p=0.9967). Patients in the INCREASED group were 8 years older (p=0.002), had a higher systolic blood pressure (p=0.038), and they received 20 times more (p<0.0001) noradrenaline 24h after the surgery, suggesting a higher inflammatory response to the surgery. In addition, patients in the INCREASED group tended to develop more acute atrial fibrillation (35% vs . 14% incidence; p=0.112) than patients in the DECREASED group. Changes in plasma ANGPTL2 levels (ΔANGPTL2=final‐initial levels) positively correlated with the mRNA expression of the inflammatory markers TNF‐α and IL‐8 in both MAT and IMA at baseline (p<0.05) and with the senescence‐associated marker p21 in IMA (p=0.009). In other words, high pre‐operative markers of inflammation and senescence were associated with an INCREASED in ANGPTL2 post‐operatively. Conclusion Changes in ANGPTL2 blood levels discriminate between two types of patients depending on known pre‐operative characteristics (age, blood pressure) and unknown inflammatory and senescent status. In younger patients with lower cardiac adipose tissue inflammation and arterial senescence load, ANGPTL2, but not hs‐CRP levels, decreased following cardiac surgery. A higher ANGPTL2 levels post‐cardiac surgery could potentially contribute to cardiovascular events such as atrial fibrillation. Altogether, our data suggest that circulating ANGPTL2 reflects tissue inflammation and senescence. Support or Funding Information This work was funded by grants from the Canadian Institutes of Health Research (MOP 133649 and 14496) (ET) and by the Foundation of the Montreal Heart Institute (ET, MC). This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.000 | 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".