Eurecat, Centre Tecnològic de Catalunya, Unitat de Nutrició i Salut, 43204 Reus, Spain.
Department of Biochemistry and Biotechnology, Universitat Rovira i Virgili, 43007 Tarragona, Spain.
Int J Mol Sci. 2021 Nov 29;22(23):12931. doi: 10.3390/ijms222312931.
Stress disorders have dramatically increased in recent decades becoming the most prevalent psychiatric disorder in the United States and Europe. However, the diagnosis of stress disorders is currently based on symptom checklist and psychological questionnaires, thus making the identification of candidate biomarkers necessary to gain better insights into this pathology and its related metabolic alterations. Regarding the identification of potential biomarkers, omic profiling and metabolic footprint arise as promising approaches to recognize early biochemical changes in such disease and provide opportunities for the development of integrative candidate biomarkers. Here, we studied plasma and urine metabolites together with metagenomics in a 3 days Chronic Unpredictable Mild Stress (3d CUMS) animal approach that aims to focus on the early stress period of a well-established depression model. The multi-omics integration showed a profile composed by a signature of eight plasma metabolites, six urine metabolites and five microbes. Specifically, threonic acid, malic acid, alpha-ketoglutarate, succinic acid and cholesterol were proposed as key metabolites that could serve as key potential biomarkers in plasma metabolome of early stages of stress. Such findings targeted the threonic acid metabolism and the tricarboxylic acid (TCA) cycle as important pathways in early stress. Additionally, an increase in opportunistic microbes as virus of the was observed in the microbiota as an effect of the primary stress stages. Our results provide an experimental biochemical characterization of the early stage of CUMS accompanied by a subsequent omic profiling and a metabolic footprinting that provide potential candidate biomarkers.
应激障碍在最近几十年急剧增加,成为美国和欧洲最普遍的精神疾病。然而,应激障碍的诊断目前基于症状清单和心理问卷,因此需要确定候选生物标志物,以更好地了解这种病理及其相关的代谢改变。关于潜在生物标志物的识别,组学分析和代谢组学分析成为识别这种疾病早期生化变化的有前途的方法,并为综合候选生物标志物的开发提供了机会。在这里,我们在 3 天慢性不可预测轻度应激(3d CUMS)动物模型中研究了血浆和尿液代谢物以及宏基因组学,该模型旨在关注已建立的抑郁症模型的早期应激期。多组学整合显示出由八种血浆代谢物、六种尿液代谢物和五种微生物组成的特征。具体来说,提议 threonic 酸、苹果酸、α-酮戊二酸、琥珀酸和胆固醇作为关键代谢物,可以作为应激早期血浆代谢组中关键的潜在生物标志物。这些发现针对 threonic 酸代谢和三羧酸(TCA)循环作为早期应激中的重要途径。此外,作为主要应激阶段的结果,观察到机会性微生物(如病毒)在微生物组中的增加。我们的结果提供了 CUMS 早期阶段的实验生化特征描述,随后进行了组学分析和代谢组学分析,提供了潜在的候选生物标志物。