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Potential Microbial Markers Of Depression

Posted on:2022-06-11Degree:DoctorType:Dissertation
Country:ChinaCandidate:H P ZhangFull Text:PDF
GTID:1484306527497684Subject:Neurology
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Background:Depression(MDD)is a serious mental disorder with unclear pathogenesis and lack of objective diagnostic biomarkers.Previous studies by our team have preliminarily confirmed that intestinal microbiome disturbance is a potential new cause of depression,but the candidate strains associated with depression and its pathogenic mechanism remain unclear.In addition,the incidence of depression is gender-specific,with women at about twice the risk of developing depression as men.This prompted us to further explore whether disturbed gut microbiome is associated with sexual susceptibility to depression.Objectives:1.To clarify the structure and functional characteristics of intestinal microorganisms in patients with MDD,revealing the potential molecular mechanism of microbial turbulence mediated depression,and laying a foundation for screening diagnostic markers and developing diagnostic kits.2.To reveal the gender difference of the gut microbiome of depression and screen the candidate biomarkers with sex specific characteristics.By comparing with the different bacterial microbiome of patients with bipolar disorder of different genders,it is clear whether the sex-related markers of depression have disease specificity.3.To establish workstation for strain culture and isolation,and AIMD mouse model for exploring the mechanism of candidate strains.To optimize the research platform of single bacteria function by colonizing Rhamnosus,to lay a foundation for the gut-brain mechanism study of key pathogenic microbial biomarkers of depression.Methods:Firstly,we compared intestinal microbial structure and metabolic function between MDD patients(N = 118)and healthy controls(HC)(N =118)using shotgun metagenomic sequencing and untargeted metabolomics in 236 fecal samples from cross-sectional studies.The co-occurring networks of different strains and fecal metabolites were constructed to clarify the interaction between them.With the help of KEGG database,the metabolic pathways closely associated with the different strains were explored to clarify the potential metabolic mechanism of intestinal microbial disturbance regulation.Secondly,we included a total of 456 subjects(MDD,N = 120;BD,N= 165;HC,N = 171)were divided into male subgroup(MDD,N = 43;BD,N = 82;HC,N = 71)and female subgroup(MDD,N = 77;BD,N = 83;HC,N = 100).16 S r RNA gene sequencing was used to compare the characteristics of the gut microbiote of the subjects to determine whether the disturbed intestinal microbes were sex specific.Linear discriminant analysis Effect Size(LEf Se)was used to picture the changes of intestinal microbiote in MDD patients compared with BD patients and HC subjects.Secondly,in order to explore the potential correlation between differential gut bacterium,we conducted co-occurring analysis based on the relative abundance of differential OTUs to construct key co-occurring networks for different genders.Finally,the random forest model was used to screen gender-specific microbial biomarkers,and the five-fold cross-validation method was used to verify the performance of biomarkers in differential diagnosis.Results:1.The microbial structure and metabolic characteristics of MDD and HC were significantly different.We found that 47 intestinal bacteria and 50 fecal metabolites were differentially expressed between the two groups.Compared with HC,MDD were characterized by enrichment of Bacteroides and depletion of Blautia and Eubacterium.In addition,16 fecal metabolites were enriched and 34 metabolites were depleted in MDD.Functional enrichment analysis showed that it was mainly related to the metabolism of amino acids,nucleotides,carbohydrates and lipids,with the turbulence of amino acid metabolism as the main characteristic.2.Co-occurring analysis showed that the covariant clusters composed of Bacteroides and Blautia in the intestinal microbiome of MDD patients were closely related to fecal amino acid metabolism.Significantly altered intestinal microbial genes and fecal metabolites were uniformly enriched in the ?-aminobutyric acid,phenylalanine,and tryptophan metabolic pathways.3.Through the exploration of the gender-specific intestinal microbial turbulence of MDD,the study found that,consistent with the results of the first part of the metagenomic analysis,patients with depression were accompanied by changes in intestinal microbiota.We found that both male and female MDD patients were enriched with the expression of Lachnospiraceae.Interestingly,female MDD patients were accompanied by the enrichment of Bacteroidaceae,showing sex specificity.4.Using the random forest model,candidate biomarkers were selected from the male subgroup(5 differentially expressed OTU)and the female subgroup(11 differentially expressed OTU).Compared with BD patients,gender-specific microbial biomarkers were able to effectively identify male MDD patients(AUC = 0.831)or female MDD patients(AUC = 0.898),showing a high disease specificity.5.The platform of candidate strain culture and enrichment as well as the mouse model of AMID for candidate single strain transplantation were successfully established.Conclusions:1.MDD patients are accompanied by intestinal microbial structure and metabolic function disorders.And the turbulence of microbial amino acid metabolism is an important characteristic of the disturbance of intestinal microecosystem in depression.2.The microbiological alternation in MDD patients are sex specific.Male MDD patients were enriched in the expression of Lachnospiraceae.Female MDD patients were enriched in the expression of the Lachnospiraceae and Bacteroidaceae.Future studies should further focus on pathogenic strains and explore their gender-specific "gut-brain" mechanism.3.The intestinal microbial biomarkers of MDD provide new dimensions for developing objective diagnostic methods and revealing the potential new pathogenesis of MDD.
Keywords/Search Tags:Gut microbiote, Depression, Metabolites, Gender specific, Biomarkers
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