Home Research Feeds Gut Microbial Signatures Can Discriminate Unipolar from Bipolar Depression

Gut Microbial Signatures Can Discriminate Unipolar from Bipolar DepressionOriginal paper

Researched by:

  • Karen Pendergrass

Last Updated: 2026-07-04

Karen Pendergrass
Karen Pendergrass

Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease, four years before the first published case study.

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Location
China
Sample Site
Feces
Species
Homo sapiens

What was studied?

Researchers compared gut microbial composition among 165 people with major depressive disorder (MDD), 217 with bipolar disorder (BD), and 217 healthy controls. The goal was to find microbial features that could distinguish MDD from BD, a distinction that is often difficult clinically.

How was it studied?

Stool samples from 599 subjects underwent 16S rRNA gene sequencing to profile bacterial operational taxonomic units (OTUs). Findings from a discovery set were then tested in an independent validation set using a random forest classifier.

What did they find?

Compared to controls, MDD showed altered covarying OTUs in the Bacteroidaceae family, while BD showed disturbed covarying OTUs in Lachnospiraceae, Prevotellaceae, and Ruminococcaceae. A 26 OTU signature separated the groups with AUCs of 0.961 to 0.986 in the discovery set and 0.702 to 0.741 in validation, and 4 of the 26 markers correlated with depression severity.

Why it matters

Misdiagnosis between MDD and BD can lead to the wrong treatment, since antidepressants and mood stabilizers are used differently for each. A validated gut microbial panel could offer a noninvasive tool to support differential diagnosis.

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