Multi-cohort analysis of depression-associated gut microbiota sheds insight on bacterial biomarkers across populations
Abstract Gut microbes are associated with the development of depression based on extensive evidence. However, previous studies have led to conflicting reports on this association, posing challenges to the application of the gut microbiota in the diagnostics and treatment of depression. To minimize heterogenicity in data analysis, the present meta-analysis adopted a standardized bioinformatic and statistical pipeline to analyze 16s rRNA sequences of 1827 samples from 8 different cohorts. Although changes in the overall microbial community were identified by our meta-analysis, depressive-correlated changes in alpha-diversity were absent. Enrichment of Bacteroidetes, Parabacteroides, Barnesiella, Bacteroides, Alistipes inops, Bacteroides massiliensis, along with depletion in Firmicutes, Dialister and Bacteroides plebeius were observed in depressive-associated microbiota. By contrast, elevated L-glutamine degradation and reduced L-glutamate production and L-isoleucine biosynthesis were identified in depressive-associated microbiome. After systemically reviewing the data of these collected cohorts, we have established a microbial classifier to identify depressive symptoms with AUC > 78%. Moreover, a low-risk microbial cluster for depressive symptoms was identified, which presented by a lower abundance of Escherichia-Shigella, and a higher abundance of Faecalibacterium, Oscillospiraceae UCG 002, Ruminococcus and Christensenellaceae R.7 group..
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Preprint| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
ResearchSquare.com - (2022) vom: 22. Juni Zur Gesamtaufnahme - year:2022 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Liang, Suisha [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.21203/rs.3.rs-1753610/v1 |
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| 520 | |a Abstract Gut microbes are associated with the development of depression based on extensive evidence. However, previous studies have led to conflicting reports on this association, posing challenges to the application of the gut microbiota in the diagnostics and treatment of depression. To minimize heterogenicity in data analysis, the present meta-analysis adopted a standardized bioinformatic and statistical pipeline to analyze 16s rRNA sequences of 1827 samples from 8 different cohorts. Although changes in the overall microbial community were identified by our meta-analysis, depressive-correlated changes in alpha-diversity were absent. Enrichment of Bacteroidetes, Parabacteroides, Barnesiella, Bacteroides, Alistipes inops, Bacteroides massiliensis, along with depletion in Firmicutes, Dialister and Bacteroides plebeius were observed in depressive-associated microbiota. By contrast, elevated L-glutamine degradation and reduced L-glutamate production and L-isoleucine biosynthesis were identified in depressive-associated microbiome. After systemically reviewing the data of these collected cohorts, we have established a microbial classifier to identify depressive symptoms with AUC > 78%. Moreover, a low-risk microbial cluster for depressive symptoms was identified, which presented by a lower abundance of Escherichia-Shigella, and a higher abundance of Faecalibacterium, Oscillospiraceae UCG 002, Ruminococcus and Christensenellaceae R.7 group. | ||
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