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Background <p>Adolescent depression, including subthreshold depression (SD) and major depressive disorder (MDD), is a growing public health concern, yet objective signatures remain lacking. Accumulating evidence implicates gut microbiota alterations in depression. Our study aimed to characterize gut microbiota alterations among healthy controls (HCs), SD, and MDD, and to identify microbial signatures with potential discriminative value in adolescents.</p> Methods <p>We profiled gut microbiota from 411 adolescents, including 117 HCs, 87 with SD, and 117 with MDD in the discovery set, along with an independent validation cohort of 45 HCs and 45 MDD patients. 16S rRNA sequencing was used to assess compositional and predicted functional differences. Random forest (RF) models and Linear discriminant analysis Effect Size (LEfSe) were applied to identify microbial signatures associated with depressive states.</p> Results <p>Adolescents with MDD exhibited significantly reduced microbial diversity compared with HCs and SD, accompanied by compositional differences, with modest effect sizes observed for beta-diversity. Using LEfSe and RF modeling, twelve microbial features were identified that showed discriminative capacity across depressive states. Among these, <i>Turicibacter</i> (amplicon sequence variant, ASV792) and <i>Clostridiaceae</i> (ASV6392) emerged as the most consistently discriminative features, both showing a stepwise decrease across groups. The rsulting multi-ASV panel demonstrated reproducible classification performance, achieving area under the curve (AUC) values of 0.89 for MDD vs. HCs and 0.83 for MDD vs. SD. PICRUSt2-based functional prediction suggested differences in amino acid- and carbohydrate metabolsm-related pathways in MDD.</p> Conclusions <p>Our observational study demonstrates distinct gut microbiota profiles across different levels of depressive symptom severity in adolescents. The identified microbial features provide a research framework for future studies examining microbiome-associated patterns in adolescent depression.</p>

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Gut microbiota alterations and signatures across subthreshold depression and major depressive disorders in adolescents

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月22日

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  • Xiaoxia Xu,
  • Bingjie Qin,
  • Tingting Lei,
  • Xueer Liu,
  • Xuemei Li,
  • Yao Li,
  • Jushuang Zhang,
  • Fei Chen,
  • Chenxi Liu,
  • Luman Zhang,
  • Hanchen Hou,
  • Teng Teng,
  • Xinyu Zhou

摘要

Background

Adolescent depression, including subthreshold depression (SD) and major depressive disorder (MDD), is a growing public health concern, yet objective signatures remain lacking. Accumulating evidence implicates gut microbiota alterations in depression. Our study aimed to characterize gut microbiota alterations among healthy controls (HCs), SD, and MDD, and to identify microbial signatures with potential discriminative value in adolescents.

Methods

We profiled gut microbiota from 411 adolescents, including 117 HCs, 87 with SD, and 117 with MDD in the discovery set, along with an independent validation cohort of 45 HCs and 45 MDD patients. 16S rRNA sequencing was used to assess compositional and predicted functional differences. Random forest (RF) models and Linear discriminant analysis Effect Size (LEfSe) were applied to identify microbial signatures associated with depressive states.

Results

Adolescents with MDD exhibited significantly reduced microbial diversity compared with HCs and SD, accompanied by compositional differences, with modest effect sizes observed for beta-diversity. Using LEfSe and RF modeling, twelve microbial features were identified that showed discriminative capacity across depressive states. Among these, Turicibacter (amplicon sequence variant, ASV792) and Clostridiaceae (ASV6392) emerged as the most consistently discriminative features, both showing a stepwise decrease across groups. The rsulting multi-ASV panel demonstrated reproducible classification performance, achieving area under the curve (AUC) values of 0.89 for MDD vs. HCs and 0.83 for MDD vs. SD. PICRUSt2-based functional prediction suggested differences in amino acid- and carbohydrate metabolsm-related pathways in MDD.

Conclusions

Our observational study demonstrates distinct gut microbiota profiles across different levels of depressive symptom severity in adolescents. The identified microbial features provide a research framework for future studies examining microbiome-associated patterns in adolescent depression.