Identification of plasma biomarkers in a PTZ-induced Sudden Unexpected Death-like model through integrated proteomics and metabolomics methods

Introduction Sudden Unexpected Death in Epilepsy (SUDEP) refers to the unexplained, sudden death of individuals with epilepsy, and its incidence is closely linked to the severity and duration of seizures. This study aimed to identify plasma biomarkers associated with SUDEP through a combined proteomics and metabolomics approach. Methods A PTZ-induced seizure-related sudden death (SUDEP-like) paradigm was established in Sprague-Dawley (SD) rats via intraperitoneal injection of pentylenetetrazol (PTZ). Hippocampal histology was included to provide pathological context for plasma proteomic and metabolomic changes in the SUDEP-like model. Hippocampal tissue was extracted for hematoxylin and eosin (HE) staining to observe pathological changes. Blood was collected for plasma separation, followed by combined analysis using Data-dependent ion acquisition (dDIA) with Nanoflow Liquid Chromatography-Tandem Mass Spectrometry (nanoLC-MS/MS) for proteomics and Ultra-High Performance Liquid Chromatography-Quadrupole-Orbitrap Mass Spectrometry (UHPLC-QE-MS) for metabolomics. Results Hematoxylin and eosin staining revealed a reduction in the number and morphological alterations of hippocampal neurons in SUDEP rats. Proteomic analysis identified 284 proteins that were significantly differentially expressed in the plasma of SUDEP rats. Key proteins such as mitogen-activated protein kinase 3 (Mapk3), protein BUD31 homolog (Bud31), heterogeneous nuclear ribonucleoprotein K (Hnrnpk), elongation factor 1-alpha (Eef1a1, Eef1a2), small ribosomal subunit proteins (Rps10, 11, 17, 20), and large ribosomal subunit proteins (Rpl23, 24, 38) were found to be highly associated with SUDEP and identified as potential plasma biomarkers. Metabolomic analysis revealed 565 metabolites that were significantly differentially expressed, leading to the identification of seven metabolic pathways potentially linked to the mechanisms of SUDEP. Combined analysis highlighted three pathways of significant association: β-alanine metabolism, sphingolipid metabolism, and pantothenate and Coenzyme A (CoA) biosynthesis. Furthermore, the integrated proteomic and metabolomic analysis highlighted 14 candidate plasma biomarkers. Among these, 11 molecules were identified in the metabolomic dataset, including sphinganine (DHS), phytosphingosine (PHS), sphingosine (SPH), sphingosine 1-phosphate (S1P), sphingomyelin (SM), glucosylceramide (GlcCer), β-alanine, carnosine, uracil, pantothenic acid, and L-histidine, whereas phosphatidylcholine:ceramide cholinephosphotransferase 2 (Sgms2), lysosomal acid glucosylceramidase precursor (Gba1), and aspartate 1-decarboxylase (Gadl1/Csad) were quantified in the plasma proteomic dataset and incorporated into the integrated pathway interpretation. Conclusion These findings nominate candidate circulating signatures associated with seizure-related sudden death in this SUDEP-like paradigm. Translation to SUDEP risk stratification or forensic application requires independent validation in well-phenotyped human cohorts using standardized SUDEP classification.