MSACL 2025 Abstract

Serial proteomic and metabolomic profiling for early neuroprognostication after out-of-hospital cardiac arrest: a prospective observational study

Xinyi Liu (1,2,3), Kai Lee Woo (4), Liyan Chen (5), Leroy Sivappiragasam Pakkiri (1,2), Rachel Liyu Lim (6), Marcus EH Ong (7,8), Federico Torta (1,6,8), Radoslaw Sobota (5), Hyungwon Choi (1,2,6), A Mark Richards (1,2,9), Chester Lee Drum (1,2,4), Shir Lynn Lim (1,4,8)
(1) Yong Loo Lin School of Medicine, National University of Singapore, Singapore, (2) Cardiovascular Research Institute, National University Health System, Singapore, (3) Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, (4) Department of Cardiology, National University Heart Centre, Singapore, (5) Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore, (6) Center for Life Sciences, National University of Singapore, Singapore, (7) Department of Emergency Medicine, Singapore General Hospital, Singapore, (8) Duke-NUS Medical School, Singapore, (9) Christchurch Heart Institute, University of Otago, New Zealand

Xinyi Liu (Presenter) National University of Singapore

Relevant Financial Disclosures (within past 24 months, reported on Jul 06, 2025) No relevant financial relationship(s) to disclose.

INTRODUCTION:
Serial proteomic and metabolomic profiling of plasma and/or urine after resuscitation from out-of-hospital cardiac arrest (OHCA) may identify biomarkers prognostic of poor neurological recovery. We investigated the proteomic and metabolomic profiles of a multi-ethnic Asian cohort of resuscitated OHCA patients.

METHODS:
Observational single-center cohort study of adult patients who were comatose following OHCA of presumed cardiac etiology. Biological samples were collected at 0, 24 and 72 hours after return of spontaneous circulation (ROSC). Plasma samples were analyzed using four complementary assay platforms (OLINK proteomics, liquid chromatography coupled mass spectrometry (LC-MS) proteomics, LC-MS/MS metabolomics and lipidomics). Urine samples were analyzed using two platforms (OLINK proteomics and LC-MS proteomics). The study outcome was neurological status at hospital discharge, assessed by Cerebral Performance Category (CPC) score. Data from patients with poor (CPC 3-5) versus good (CPC 1-2) neurological recovery were compared using logistic regression and log2(Fold Change) (FC). Predictive performance was evaluated by the areas under receiver operating characteristic curves (AUCs).

RESULTS:
Of 54 eligible patients (median age 63.5 years, 87% males), 31 (57.4%) patients had poor neurological recovery. Across the three sampling timepoints, this subgroup had significant elevations (log2(FC) > 1.0) in 100 proteins and 20 metabolites, and reductions (log2(FC) < -1.0) in 6 metabolites. Of these, 83 proteins and 8 metabolites showed good discrimination (AUC > 0.80) for poor neurological outcome at discharge. Top, previously unreported, candidate biomarkers include galectin-4 (Gal-4) (AUC: 0.94 [0.86-1.00]), V-type proton ATPase subunit F (ATP6V1F) (AUC: 0.94 [0.87-1.00]), proteasome activator complex subunit 1 (PSME1) (AUC: 0.92 [0.84-1.00]), and thiourea (AUC: 0.85 [0.71-0.99]). Energy metabolism, oxidative stress, endothelial dysfunction and neuronal injury were the four main dysregulated biological processes identified. Two temporal clusters of proteins and three temporal clusters of metabolites discriminated poor from good neurological outcome, with the greatest inter-outcome differences in markers observed at 24 hours post-ROSC.

CONCLUSION:
100 proteins and 26 metabolites discriminated poor from good neurological outcomes in our multi-ethnic Asian cohort of resuscitated OHCA patients, with the best signals from samples collected at 24 hours post-ROSC. These findings warrant further validation in an adequately powered multi-center study.