Circulating Metabolites as Biomarkers of Disease in Patients with Mesial Temporal Lobe Epilepsy.

1H Nuclear Magnetic Resonance antiseizure medication focal epilepsy metabolomics response to treatment

Journal

Metabolites
ISSN: 2218-1989
Titre abrégé: Metabolites
Pays: Switzerland
ID NLM: 101578790

Informations de publication

Date de publication:
17 May 2022
Historique:
received: 20 03 2022
revised: 06 05 2022
accepted: 12 05 2022
entrez: 28 5 2022
pubmed: 29 5 2022
medline: 29 5 2022
Statut: epublish

Résumé

A major challenge in the clinical management of patients with mesial temporal lobe epilepsy (MTLE) is identifying those who do not respond to antiseizure medication (ASM), allowing for the timely pursuit of alternative treatments such as epilepsy surgery. Here, we investigated changes in plasma metabolites as biomarkers of disease in patients with MTLE. Furthermore, we used the metabolomics data to gain insights into the mechanisms underlying MTLE and response to ASM. We performed an untargeted metabolomic method using magnetic resonance spectroscopy and multi- and univariate statistical analyses to compare data obtained from plasma samples of 28 patients with MTLE compared to 28 controls. The patients were further divided according to response to ASM for a supplementary and preliminary comparison: 20 patients were refractory to treatment, and eight were responsive to ASM. We only included patients using carbamazepine in combination with clobazam. We analyzed the group of patients and controls and found that the profiles of glucose (p = 0.01), saturated lipids (p = 0.0002), isoleucine (p = 0.0001), β-hydroxybutyrate (p = 0.0003), and proline (p = 0.02) were different in patients compared to controls (p < 0.05). In addition, we found some suggestive metabolites (without enough predictability) by multivariate analysis (VIP scores > 2), such as lipoproteins, lactate, glucose, unsaturated lipids, isoleucine, and proline, that might be relevant to the process of pharmacoresistance in the comparison between patients with refractory and responsive MTLE. The identified metabolites for the comparison between MTLE patients and controls were linked to different biological pathways related to cell-energy metabolism and pathways related to inflammatory processes and the modulation of neurotransmitter release and activity in MTLE. In conclusion, in addition to insights into the mechanisms underlying MTLE, our results suggest that plasma metabolites may be used as disease biomarkers. These findings warrant further studies exploring the clinical use of metabolites to assist in decision-making when treating patients with MTLE.

Identifiants

pubmed: 35629950
pii: metabo12050446
doi: 10.3390/metabo12050446
pmc: PMC9148034
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : São Paulo Research Foundation
ID : 2013/07559-3
Organisme : São Paulo Research Foundation
ID : 2018/24069-3
Organisme : São Paulo Research Foundation
ID : 2019/00213-0
Organisme : São Paulo Research Foundation
ID : 2019/00048-0
Organisme : São Paulo Research Foundation
ID : 2019/25948-3
Organisme : São Paulo Research Foundation
ID : 2021/04441-8
Organisme : São Paulo Research Foundation
ID : 2017/26167-0
Organisme : São Paulo Research Foundation
ID : 2021/04451-3
Organisme : National Council for Scientific and Technological Development
ID : 311923/2019-4
Organisme : Coordenação de Aperfeicoamento de Pessoal de Nível Superior
ID : 001

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Auteurs

Alexandre B Godoi (AB)

Department of Translational Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.
Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas 13083-888, Brazil.

Amanda M do Canto (AM)

Department of Translational Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.
Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas 13083-888, Brazil.

Amanda Donatti (A)

Department of Translational Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.
Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas 13083-888, Brazil.

Douglas C Rosa (DC)

Department of Translational Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.
Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas 13083-888, Brazil.

Danielle C F Bruno (DCF)

Department of Translational Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.
Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas 13083-888, Brazil.

Marina K Alvim (MK)

Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas 13083-888, Brazil.
Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.

Clarissa L Yasuda (CL)

Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas 13083-888, Brazil.
Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.

Lucas G Martins (LG)

Department of Organic Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.

Melissa Quintero (M)

Department of Organic Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.

Ljubica Tasic (L)

Department of Organic Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.

Fernando Cendes (F)

Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas 13083-888, Brazil.
Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.

Iscia Lopes-Cendes (I)

Department of Translational Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-888, Brazil.
Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas 13083-888, Brazil.

Classifications MeSH