Cargando…

Metabolomics profiling in predicting of post-herpetic neuralgia induced by varicella zoster

To explore potential metabolomics biomarkers in predicting post-herpetic neuralgia (PHN) induced by herpes zoster (HZ). A total of 90 eligible patients were prospectively enrolled and assigned into an acute pain (ACP) group and a PHN group. Serum samples were collected before clinical intervention t...

Descripción completa

Detalles Bibliográficos
Autores principales: Lu, Lina, Mei, Lihong, Li, Xushuo, Lin, Yanhua, Wang, Hongfeng, Yang, Gao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495364/
https://www.ncbi.nlm.nih.gov/pubmed/37697028
http://dx.doi.org/10.1038/s41598-023-42363-z
Descripción
Sumario:To explore potential metabolomics biomarkers in predicting post-herpetic neuralgia (PHN) induced by herpes zoster (HZ). A total of 90 eligible patients were prospectively enrolled and assigned into an acute pain (ACP) group and a PHN group. Serum samples were collected before clinical intervention to perform metabolomics profiling analyses using gas chromatography mass spectrometry (GC–MS). Key metabolites were identified using partial least squares discriminant analysis (PLS-DA). A binary logistic regression was used to build a combined biomarker model to predict PHN from ACP. The discriminating efficiency of the combined biomarker model was investigated and validated by internal validation. Six metabolites were identified as the key metabolites related to PHN. All these metabolites (N-Acetyl-5-hydroxytryptaMine, glucose, dehydroascorbic acid, isopropyl-beta-d-thiogalactopyranoside, 1,5-anhydro-d-sorbitol, and glutamic acid) were found elevated in the PHN group. Pathway analyses showed that glucose-alanine cycle, tryptophan metabolism, tyrosine metabolism, lactose degradation, malate-aspartate shuttle were top five metabolic pathways evolved in PHN. The AUC was 0.85 (95% CI 0.76–0.93) for the combined biomarker model, and was 0.91 (95% CI 0.84–1.00) for the internal validation data set to predict PHN. Metabolomics analyses of key metabolites could be used to predict PHN induced by HZ.