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[Preprint]. 2023 Apr 11:2023.04.03.23288081.
doi: 10.1101/2023.04.03.23288081.

A signature of pre-operative biomarkers of cellular senescence to predict risk of cardiac and kidney adverse events after cardiac surgery

Amy Entwistle, Susan Walker, Anne Knecht, Susan L Strum, Asad Shah, Mihai V Podgoreanu, Aliaksei Pustavoitau, Natalia Mitin, Judson B Williams

A signature of pre-operative biomarkers of cellular senescence to predict risk of cardiac and kidney adverse events after cardiac surgery

Amy Entwistle et al. medRxiv. .

Update in

Abstract

Objective: Understand the potential for pre-operative biomarkers of cellular senescence, a primary aging mechanism, to predict risk of cardiac surgery-associated adverse events.

Methods: Biomarkers of senescence were assessed in blood samples collected prior to surgery in 331 patients undergoing CABG +/-valve repair or replacement. Patients were followed throughout the hospital stay and at a 30-day follow-up visit. Logistic regression models for pre-operative risk prediction were built for age-related clinical outcomes with high incidence including KDIGO-defined acute kidney injury (AKI), decline in eGFR ≥25% between pre-op and 30 days, and MACKE30, a composite endpoint of major adverse cardiac and kidney events at 30d.

Results: AKI occurred in 19.9% of patients, persistent decline in kidney function at 30d occurred in 11.0%, and MACKE30 occurred in 13.4%. A network of six biomarkers of senescence (p16, p14, LAG3, CD244, CD28 and suPAR) were able to identify patients at risk for AKI (AUC 0.76), kidney decline at 30d (AUC 0.73), and MACKE30 (AUC 0.71). Comparing the top and bottom tertiles of senescence-based risk models, patients in the top tertile had 7.8 (3.3-8.4) higher odds of developing AKI, 4.5 (1.6-12.6) higher odds of developing renal decline at 30d, and 5.7 (2.1-15.6) higher odds of developing MACKE30. All models remained significant when adjusted for clinical variables. Patients with kidney function decline at 30d were largely non-overlapping and clinically distinct from those who experienced AKI, suggesting a different etiology. Typical clinical factors that predispose to AKI (e.g., age, CKD, surgery type) associated with AKI but not the 30d decline endpoint which was instead associated with new-onset atrial fibrillation.

Conclusions: A six-member network of biomarkers of senescence, a fundamental mechanism of aging, can identify patients for risk of adverse kidney and cardiac events when measured pre-operatively.

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