Drug-free bipolar depression was linked to a distinct gut bacteriome, virome, and serum metabolome pattern that strongly separated patients from controls.
Evidence
Cross-sectional of 90 drug-free patients with bipolar depression and 30 healthy controls measured gut bacterial and viral species, serum metabolites, clinical correlations, and random-forest discrimination.
Caveat
The case-control design cannot establish causality, and the integrated AUC = 0.986 biomarker panel remains a candidate finding requiring external validation.
Simplified
The involvement of microbiota-gut-brain axis in bipolar disorder (BD) has been uncovered, yet the specific tripartite interplay between the gut bacteriome, virome, and serum metabolome remains to be elucidated. We conducted a cross-sectional on 90 drug-free patients with bipolar depression and 30 healthy controls. A significant between-group difference in gut bacterial α-diversity was observed. Non-parametric test revealed 1929 bacterial and 134 viral species with significant inter-group difference, among which 249 bacterial and 7 viral species remained significant after FDR correction (P < 0.05). Metabolomic analysis identified 261 significantly differential serum metabolites, which were enriched in 70 biological pathways and 40 pathways remained significant after correction. Integration of the datasets revealed strong cross-omic correlations, while only eight significant viral-metabolic correlations were detected. Post-FDR significant correlations with clinical features were exclusively observed between differential metabolites and scores of disease severity, with a predominance of negative correlations. Clinically, a random forest model integrating bacteriome, virome, and metabolome features achieved superior discriminative power (AUC = 0.986) compared to single-omics models (metabolites: 0.970; bacteria: 0.823; viruses: 0.732). This work demonstrated a dysregulated bacteriome-virome-metabolome network of patients with bipolar depression, providing a robust panel of candidate biomarkers for the precise diagnosis of BD. adjusted
Key numbers
249
Bacterial Species Difference
Bacterial species showing significant differences after FDR correction.
261
Serum Metabolites Difference
Metabolites identified with significant differences between groups.
0.986
Random Forest Model AUC
AUC achieved by the combined model of bacteriome, virome, and metabolome features.
Full Text
We can’t show the full text here under this license.
Competing interests: Author S.H.H. is Guest Editor of Collection “Microbiome, gut brain axis and mental health”. S.H.H. was not involved in the journal’s review of, or decisions related to, this manuscript. The other authors do not have a competing interest. Declaration of Generative AI and AI-assisted technologies in the writing process: We confirm that there is no artificial intelligence (AI) or AI-assisted technologies used in literature search, data collection, figure and table formation, or writing process.
