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Updated: May 21, 2025

Oral Biofilm Sampling for Microbiome Analysis in Healthy Children
Published on: December 31, 2017
Association of Oral Microbiome Diversity With Depression Status: NHANES 2009-2012
Cuifeng Zhang1, Lingli Qu2, Yanhua Huang1
1Department of Stomatology, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, Nanjing, China.
Objectives:
To investigate the relationship between oral microbial diversity and depression symptoms in the U.S.
Methods:
We utilized the US National Health and Nutrition Examination Survey (NHANES; 2009-2012) to assess the association between oral microbial diversity and depression symptoms. A cut-off PHQ-9 score of 15 was used to define severe depression symptoms. We conducted the multivariate linear regression to explore the association of the amplicon sequence variants (ASVs) with PHQ-9 scores. A restricted cubic spline (RCS) model was introduced to curve the dose-response relationship. A logistic regression model was used to calculate the odds ratio (OR) and 95% confidence interval (CI) of the association between ASVs and the risk of severe depression symptoms. Based on Bray-Curtis dissimilarity of beta diversity, analysis of similarity (ANOSIM) is used to assess the dissimilarity between different depression groups.
Results:
A total of 1497 participants were included, with 111 (7.41%) meeting the criteria for severe depression. After adjusting for confounders, we found that ASVs were negatively correlated with PHQ-9 scores (β = -0.008, p = 0.014). The RCS plot showed a linear relationship (p non-linear = 0.232). Logistic regression showed that ASVs were associated with a decreased risk of severe depression symptoms (OR = 0.992, p = 0.003). Analysis of β diversity identified a statistically significant difference (R = 0.087, p = 0.003). Additionally, we developed a nomogram to estimate an individual's risk of severe depression symptoms.
Conclusions:
Alpha diversity of the oral microbiota was associated with a reduced risk of severe depression symptoms, which could contribute to the early identification and intervention of severe depression.
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