Is depression associated with gut mycobacteria dysbiosis in children?

In a recent study published in the Journal of Affective Disorders, researchers from Zhejiang University, China, evaluated the gut mycobiota in adolescents/children with depression.

Study: Altered gut bacterial–fungal interkingdom networks in children and adolescents with depression. Image Credit: HelenaNechaeva/

Study: Altered gut bacterial–fungal interkingdom networks in children and adolescents with depression. Image Credit: HelenaNechaeva/


Fungi represent a minor component (0.1%) of the human gut microbiome. Studies suggest that Ascomycota, Basidiomycota, and Zygomycota phyla are predominant in the gut mycobiota.

Clinical studies have identified distinct mycobiota dysbiosis in individuals with neuropsychiatric disorders like Rett syndrome, schizophrenia, and autism.

Previously, the authors reported fungal composition alterations in depressive adults. Interactions between bacteria and fungi have also been reported, including biofilm formation in vitro. Moreover, some commensal bacteria induce antifungal peptide secretion by epithelial cells in the colon.

About the study

In the present study, researchers characterized the gut mycobiota in young individuals with depressive symptoms. Patients with depression were identified from two hospitals in China between February 2019 and December 2020. Individuals aged 12-18 who did not use probiotics, prebiotics, antibiotics, or synbiotics in the past month and had depressive symptoms were eligible.

Subjects with irritable bowel syndrome, inflammatory bowel disease, active infection, epilepsy, obesity, asthma, neurodevelopmental disorders, diabetes, celiac disease, or bipolar disorder were excluded.

In addition, health controls matched by sex, age, ethnicity, and body mass index (BMI) were recruited. Fecal samples were collected from participants; DNA was extracted and quantified.

The researchers used internal transcribed spacer (ITS) amplicon sequencing for the gut mycobiome analysis. The ITS sequence data were processed, and operational taxonomic units (OTUs) were identified.

Alpha diversity was evaluated using Shannon, Sobs, Simpson, Chao, and abundance-based coverage estimator (ACE) indices. Beta diversity was measured by computing weighted UniFrac distances; it was visualized using principal coordinate analysis (PCoA).

The connectedness of bacteria-fungi networks was estimated as the ratio of the number of significant interactions to the number of taxa. Categorical and continuous variables were compared between groups using chi-squared and Kruskal-Wallis tests, respectively. Correlation analysis was performed using Spearman’s rank correlation test.


Overall, 145 patients and 110 controls were included in the analysis. Most patients had moderate/severe depressive symptoms, requiring medical attention. Two patients reported regular use of tobacco products in the past month; none reported alcohol consumption. There were more than 14.9 million high-quality reads for analysis.

The Alpha diversity was not significantly different between groups. Distinct clusters were observed for each group in Bray-Curtis and PCoA plots. Unweighted UniFrac distances did not differentiate the two groups.

Patients and controls shared 703 OTUs; the depression group had 728 unique OTUs. Ascomycota was the predominant phylum in both groups, followed by the Basidiomycota phylum.

Candida, Saccharomyces, Aspergillus, Penicillium, Cladosporium, Apiotrichum, Cutaneotrichosporon, and Wallemia genera were the most abundant in both groups. Ten taxa were significantly different between groups.

Aspergillus, Saccharomycopsis, Nigrospora, and Xeromyces were the most abundant in controls. Apiotrichum, Saccharomyces, and Gliomastix were the most abundant in patients.

The researchers found no differences in the Alpha diversity between patients using psychotropic drugs and drug-naïve patients. Further, hierarchical clustering did not segregate drug-naïve patients from those using drugs.

Notably, the relative proportion of the Saccharomyces genus was significantly higher in patients using drugs.

Furthermore, the researchers constructed a correlation network of fungal abundance to examine the fungi ecosystem. This revealed a more complex network in patients, suggesting that fungal alterations occur throughout the gut microbial ecosystem in patients with depression. The fungi-bacteria interkingdom network was also altered in patients.

Finally, they examined correlations between bacteria and fungi for the ten most abundant taxa. In the depression group, Candida was positively correlated with Parasutterella and Bacteroides and negatively with Bifidobacterium.

In patients, Aspergillus was positively correlated with Prevotella and negatively with Parasutterella and Bacteroides. In controls, Penicillium was positively correlated with Faecalibacterium but not in patients.


The team observed the distinct mycobiota profiles and altered fungi-bacteria interactions in depressive children/adolescents. Fungal diversity was not different between groups. The authors could not establish a causal association between gut mycobiota and depression.

Taken together, the authors demonstrated gut mycobiota dysbiosis in depressive adolescents/children. Fungi-bacteria interkingdom differences were evident in depressive patients.

The findings suggest that gut mycobiota might be a potential therapeutic target for depression, warranting further research.

Journal reference:
Tarun Sai Lomte

Written by

Tarun Sai Lomte

Tarun is a writer based in Hyderabad, India. He has a Master’s degree in Biotechnology from the University of Hyderabad and is enthusiastic about scientific research. He enjoys reading research papers and literature reviews and is passionate about writing.


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