Department of Dermatology, Jinshan Hospital, Fudan University, Shanghai, 201508, China.
Department of Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, 201508, China.
Sci Rep. 2023 Sep 11;13(1):14940. doi: 10.1038/s41598-023-42363-z.
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.
探讨预测带状疱疹后神经痛(PHN)的潜在代谢组学标志物。共纳入 90 例符合条件的患者,前瞻性分为急性疼痛(ACP)组和 PHN 组。在临床干预前采集血清样本,采用气相色谱-质谱联用(GC-MS)进行代谢组学分析。采用偏最小二乘判别分析(PLS-DA)鉴定关键代谢物。采用二元逻辑回归建立联合生物标志物模型,从 ACP 预测 PHN。通过内部验证研究和验证联合生物标志物模型的判别效率。确定了 6 种与 PHN 相关的关键代谢物。所有这些代谢物(N-乙酰-5-羟色胺、葡萄糖、脱氢抗坏血酸、异丙基-β-D-硫代半乳糖苷、1,5-脱水-D-山梨醇和谷氨酸)均在 PHN 组中升高。途径分析显示,葡萄糖-丙氨酸循环、色氨酸代谢、酪氨酸代谢、乳糖降解、苹果酸-天冬氨酸穿梭是 PHN 中演变的前五大代谢途径。联合生物标志物模型的 AUC 为 0.85(95%CI 0.76-0.93),内部验证数据集的 AUC 为 0.91(95%CI 0.84-1.00),用于预测 PHN。对关键代谢物的代谢组学分析可用于预测带状疱疹引起的 PHN。