Dian Wang1, Xingxing Wang1, Jing Kong1, Jiayan Wu1, Minchao Lai2. 1. Department of Forensic Medicine, Shantou University Medical College, China. 2. Department of Neurology, First Affiliated Hospital of Shantou University Medical College, China. Electronic address: laiminchao0327@outlook.com.
Abstract
OBJECTIVE: Understanding the overall and common metabolic changes of seizures can provide novel clues for their control and prevention. Here, we aim to investigate the global metabolic feature of serum for three types of seizures. METHODS: We recruited 27 patients who had experienced a seizure within 48h (including 11 who had a generalized seizure, nine who had a generalized seizure secondary to partial seizure and seven who had a partial seizure) and 23 healthy controls. We analyzed the global metabolic changes of serum after seizures using gas chromatography-mass spectrometry-based metabolomics. Based on differential metabolites, the metabolic pathways and their potential to diagnose seizures were analyzed, and metabolic differences among three types of seizures were compared. RESULTS: The metabolic profiles of serum were distinctive between the seizure group and the controls but were not different among the three types of seizures. Compared to the controls, patients with seizures had higher levels of lactate, butanoic acid, proline and glutamate and lower levels of palmitic acid, linoleic acid, elaidic acid, trans-13-octadecenoic acid, stearic acid, citrate, cysteine, glutamine, asparagine, and glyceraldehyde in the serum. Furthermore, these differential metabolites had common change trends among the three types of seizures. Related pathophysiological processes reflected by these metabolites are energy deficit, inflammation, nervous excitation and neurotoxicity. Importantly, transamination inhibition is suspected to occur in seizures. Lactate, glyceraldehyde and trans-13-octadecenoic acid in serum jointly enabled a precision of 92.9% for diagnosing seizures. CONCLUSIONS: There is a common metabolic feature in three types of seizures. Lactate, glyceraldehyde and trans-13-octadecenoic acid levels jointly enable high-precision seizure diagnosis.
OBJECTIVE: Understanding the overall and common metabolic changes of seizures can provide novel clues for their control and prevention. Here, we aim to investigate the global metabolic feature of serum for three types of seizures. METHODS: We recruited 27 patients who had experienced a seizure within 48h (including 11 who had a generalized seizure, nine who had a generalized seizure secondary to partial seizure and seven who had a partial seizure) and 23 healthy controls. We analyzed the global metabolic changes of serum after seizures using gas chromatography-mass spectrometry-based metabolomics. Based on differential metabolites, the metabolic pathways and their potential to diagnose seizures were analyzed, and metabolic differences among three types of seizures were compared. RESULTS: The metabolic profiles of serum were distinctive between the seizure group and the controls but were not different among the three types of seizures. Compared to the controls, patients with seizures had higher levels of lactate, butanoic acid, proline and glutamate and lower levels of palmitic acid, linoleic acid, elaidic acid, trans-13-octadecenoic acid, stearic acid, citrate, cysteine, glutamine, asparagine, and glyceraldehyde in the serum. Furthermore, these differential metabolites had common change trends among the three types of seizures. Related pathophysiological processes reflected by these metabolites are energy deficit, inflammation, nervous excitation and neurotoxicity. Importantly, transamination inhibition is suspected to occur in seizures. Lactate, glyceraldehyde and trans-13-octadecenoic acid in serum jointly enabled a precision of 92.9% for diagnosing seizures. CONCLUSIONS: There is a common metabolic feature in three types of seizures. Lactate, glyceraldehyde and trans-13-octadecenoic acid levels jointly enable high-precision seizure diagnosis.
Authors: Danielle Brister; Brianna A Werner; Geoffrey Gideon; Patrick J McCarty; Alison Lane; Brian T Burrows; Sallie McLees; P David Adelson; Jorge I Arango; William Marsh; Angelea Flores; Matthew T Pankratz; Ngoc Han Ly; Madison Flood; Danni Brown; David Carpentieri; Yan Jin; Haiwei Gu; Richard E Frye Journal: Metabolites Date: 2022-04-20
Authors: Chelsea L Gibson; Simona G Codreanu; Alexandra C Schrimpe-Rutledge; Cassandra L Retzlaff; Jane Wright; Doug P Mortlock; Stacy D Sherrod; John A McLean; Randy D Blakely Journal: Mol Omics Date: 2018-06-12
Authors: Federica Murgia; Antonella Muroni; Monica Puligheddu; Lorenzo Polizzi; Luigi Barberini; Gianni Orofino; Paolo Solla; Simone Poddighe; Francesco Del Carratore; Julian L Griffin; Luigi Atzori; Francesco Marrosu Journal: Front Neurol Date: 2017-09-04 Impact factor: 4.003