| Ethnopharamaology:Depression is a common mental illness.The pathogenesis has not yet been fully elucidated.More and more evidence shows that the development of depression is closely related to metabolism in the body.Metabolomics is an important method to study the metabolic characteristics of depression,~1H-NMR,LC-MS and GC-MS are the common metabolomics detection platforms,Multivariate statistical analysis has always been the main data analysis method for metabonomics.Traditional static metabolomics data analysis methods mostly use cross-sectional data as the research object.The research results can reflect the metabolic characteristics of the body during specific stages of disease development,but it is difficult to reflect the dynamic effects of various complex factors on the body’s metabolism during the development of the disease,and ignore the time-related important variations as a confounding factor,which has limitations.The dynamic metabolomics data analysis method aims at the above limitations of the static metabolomics analysis method,and captures the variation caused by the temporal trend while reducing the dimensionality of the high-dimensional data of metabolomics,and more truly reveals the dynamics of metabolism in the process of disease development and development.Change characteristics.The combined application of static and dynamic metabolomics data analysis methods can overcome the above limitations of static metabolomics,and can also obtain key metabolic characteristics that are more closely linked to disease progression by comparing the similarities and differences between the two data analysis results.The relationship between metabolism and disease pathology provides support.Research Objective:This study intends to model the development of depression using a chronic,unpredictable,and unresponsive stimulus model,and to apply static and dynamic metabolomics data analysis methods to study the plasma and fecal metabolic characteristics and relatedness in depressed rats to provide insights into the body’s metabolism.The relationship with the pathology of depression and the research on the intervention of depression based on endogenous metabolites provide reference.Research methods:1.Replicate the chronic mild unpredictable stress model,dynamically monitor the behavioral indicators on the 0 d,7 d,14 d,21 d,and 28 d of the model replication process.LC-MS/MS was used to quantitatively detect plasma neurotransmitters for 28 days to verify the effect of model replication.2.The metabolomes of plasma and fecal were detected in the process of replicating chronic mild unpredictable emergency models,and study metabolic profile and characteristic metabolites by the Static metabolomics data analysis method.3.Dynamic metabolomics data analysis methods such as ASCA were used to study the characteristics of metabolites related to factors such as phenotype,time,and phenotypic timing in the process of replication in depressed rat models.4.Use Spearman correlation analysis of dynamic and static metabolomics studies to determine the correlation between differential metabolites and behavioral markers、neurotransmitters in depressed-like rats,and further analyze metabolic pathways of significant related metabolites to enrich the metabolism and depression of the body.relationship.Results:1.This article the CUMS model is successfully copied in terms of behavioral indicators and neurotransmitters.The preference of sugar water was positively correlated with DA and Ach.The resting time was negatively correlated with grooming time.GABA was positively correlated with Tyr,and NE was positively correlated with Tyr.2.Based on the analysis of static metabolomics model 28 d plasma metabolomics to find the differential metabolites linolenic acid,propionic acid,allose.Based on the dynamic metabolomics ASCA analysis,the differential metabolites of the plasma metabolite group related to the time factor were found to be allose,inositol,and 1,5-anhydro-D-sorbitol.In order to find the differential metabolites related to depression and to explore the changes in feces metabolism during CUMS model replication,this experiment GC-MS was used to study the dynamic changes of the plasma of the depressive-like rat model over time.3.Combined with static and dynamic metabolomic analysis to find fecal metabolites associated with depression phenotype including Lactic acid,Pyrimidine,Glutaric acid,Alanine,Aspartic acid,Glutamic acid,Phenylalanine,Ammonia acid,2-piperidine carboxylic acid,Glucaric acid.Metabolites associated with the time factor of depression include Phosphoric acid,Valeric acid,Caproic acid,Succinic acid,Propionic acid,Methylamine,Fructose,Fucose,Allose,Hexadecanoic acid,Inositol,lactose.The metabolites of L-proline,Glycerol,Glycine,L-Threonine,Malic acid,oxy-Proline,and Arabinose are closely related to the time and phenotype of depression.4.The results of this study showed that endogenous metabolites in the plasma and feces of the CUMS model rats were disordered to varying degrees,indicating that the occurrence and development of depression are closely related to metabolic disorders in the body.Changes in body metabolites involve Iinositol phosphate metabolism,Amino acid metabolism,Fatty acid metabolism and other metabolic pathways.Inositol phosphate metabolism is a common metabolic pathway for plasma metabolism and intestinal metabolism.5.Comparing the results of plasma and fecal static analysis,alloses are common metabolites related to their phenotypes.Based on the dynamic analysis ASCA found that alloses and inositols are common time-dependent metabolites,and that in plasma Allose was positively correlated with inositol in feces.Inositol in plasma was negatively correlated with allose in feces,with a correlation coefficient of 0.4.Propionic acid is based on the ASCA analysis to find the phenotype-associated metabolites common to plasma and feces.There is a positive correlation between plasma inositol and neurotransmitters NE and Tyr.Propionic acid in plasma is related to the preference of sugar water.Inositol in feces is positively correlated with grooming time and number of erections.Inositol in the feces is positively correlated with the neurotransmitters Ach,GABA,DA,and NE.Conclusion:In this paper,static and dynamic analysis are used to analyze the plasma and faecal metabolism of depression,ie,the differential metabolites related to the disease phenotype are found,and the dynamic differences are used to find important differences in the replication process of the CUMS model..Dynamic analysis can not only filter the contribution variables at a certain point in time,but also visualize the relationship between variables and time factors,and can help to understand the dynamic changes in diseases.Therefore,applying static and dynamic analysis to metabolomics research can provide new research ideas for understanding the dynamic development of diseases. |
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