Frontiers in microbiology · 2026
Gut microbiota dysbiosis in adolescent depression: a comparative analysis with adult depression and healthy adolescent.
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Ma Yongchun, Luo Liyuan, Li Huichao, Zhou YuXin, Xiang Shasha, Liu Xiaohong, Zhu Xuan
Аннотация
INTRODUCTION: Adolescent depression differs substantially from adult depression in neurodevelopmental and pathophysiological aspects, with gut microbiota dysbiosis recognized as a key regulator via the microbiota-gut-brain axis. Nevertheless, the age-specific microbial and metabolic signatures of adolescent depression remain poorly defined.
METHODS: 125 participants including 33 adolescents with depression, 62 adults with depression, and 30 healthy adolescent controls were recruited. Full-length 16S rRNA gene sequencing was applied to profile gut microbial composition and functional metabolism.
RESULTS: Alpha diversity was markedly reduced in adolescents with depression relative to healthy adolescent, whereas no significant difference was observed between adolescent and adult depression. PCoA and age-adjusted PERMANOVA revealed distinct microbial community separation across the three groups, with disease status contributing substantially to community divergence. A significant Group × Age interaction indicated that depression may exerted age-dependent effects on gut microbiota. At the genus level, 19 differential taxa were identified between depressed and healthy adolescents, with Akkermansia, Faecalibacterium, Prevotella, and Roseburia depleted, while only Eubacterium hallii group was enriched. Four genera differed between adolescent and adult depression, and 3 genera exhibited obvious age-interaction patterns, suggesting that adolescent depression disrupts microbial developmental trajectories and induces an adult-like dysbiotic phenotype. A Random Forest diagnostic model based on differential bacterial biomarkers achieved achieved promising exploratory performance in distinguishing depressed adolescents from healthy controls (5-CV AUC = 0.966), but failed to differentiate adolescent from adult depression. PICRUSt2 prediction further revealed that gut microbiota metabolism alterations in depression are primarily driven by depressive status.
DISCUSSION: Our findings reveal both age-conserved and adolescent-specific microbial signatures, providing candidate microbial signatures and hypothesis-generating functional insights.
METHODS: 125 participants including 33 adolescents with depression, 62 adults with depression, and 30 healthy adolescent controls were recruited. Full-length 16S rRNA gene sequencing was applied to profile gut microbial composition and functional metabolism.
RESULTS: Alpha diversity was markedly reduced in adolescents with depression relative to healthy adolescent, whereas no significant difference was observed between adolescent and adult depression. PCoA and age-adjusted PERMANOVA revealed distinct microbial community separation across the three groups, with disease status contributing substantially to community divergence. A significant Group × Age interaction indicated that depression may exerted age-dependent effects on gut microbiota. At the genus level, 19 differential taxa were identified between depressed and healthy adolescents, with Akkermansia, Faecalibacterium, Prevotella, and Roseburia depleted, while only Eubacterium hallii group was enriched. Four genera differed between adolescent and adult depression, and 3 genera exhibited obvious age-interaction patterns, suggesting that adolescent depression disrupts microbial developmental trajectories and induces an adult-like dysbiotic phenotype. A Random Forest diagnostic model based on differential bacterial biomarkers achieved achieved promising exploratory performance in distinguishing depressed adolescents from healthy controls (5-CV AUC = 0.966), but failed to differentiate adolescent from adult depression. PICRUSt2 prediction further revealed that gut microbiota metabolism alterations in depression are primarily driven by depressive status.
DISCUSSION: Our findings reveal both age-conserved and adolescent-specific microbial signatures, providing candidate microbial signatures and hypothesis-generating functional insights.