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Record W4412526554 · doi:10.3390/jcm14145162

Association Between Oral Dysbiosis and Depression: A Systematic Review

2025· review· en· W4412526554 on OpenAlexaboutno aff
Paula García-Rios, María Pilar Pecci‐Lloret, Laura Murcia, Nuria Pérez-Guzmán

Bibliographic record

VenueJournal of Clinical Medicine · 2025
Typereview
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAssociation (psychology)Depression (economics)DysbiosisPsychiatryPsychotherapistGut floraImmunology

Abstract

fetched live from OpenAlex

Background: Depression is a mental disorder characterized by a combination of somatic and cognitive disturbances, in which a predominantly sad or irritable mood significantly interferes with the patient’s functioning. This condition can affect individuals of all ages and socioeconomic backgrounds. Currently, various studies are exploring a possible association between oral dysbiosis and depression—an increasingly relevant topic, as confirmation of such a relationship could position the oral microbiota as a potential etiological or diagnostic factor for depression, given its accessibility and ease of analysis. Aim: To present a qualitative synthesis of studies addressing how oral dysbiosis influences the onset of depression, as well as the importance of controlling this alteration of the oral microbiota to aid in the prevention of the disease. Materials and Methods: The PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) outline the procedures to be followed for conducting this systematic review. The article search was carried out on 22 May 2025, across the PubMed, Scopus, Scielo, and The Cochrane Library databases, using terms related to “depression” and “oral dysbiosis”. Studies published within the last 10 years that addressed the potential association between oral dysbiosis, and depression were included. Furthermore, the quality of the studies was assessed using various tools depending on their design: the Newcastle–Ottawa Scale (NOS) was applied to case-control and cohort studies; the Joanna Briggs Institute (JBI) critical appraisal checklist was used for cross-sectional studies; and experimental studies were evaluated using SYRCLE’s Risk of Bias Tool. Results: A total of eleven studies were included in this systematic review. The findings suggest the presence of alterations in the oral microbiota of patients with depression, particularly in terms of composition, structure, and diversity. A reduction in alpha diversity—an indicator of local microbial balance—was observed, along with an increase in beta diversity, indicating greater inter-individual variability, which may be associated with inflammatory processes or immunological dysfunctions. Some studies reported differing results, which may be attributable to methodological variability regarding study design, or the populations sampled. Conclusions: This systematic review suggests that the oral microbiome could be considered a diagnostic biomarker and therapeutic target for depression, as the analyzed studies demonstrate a significant association between oral microbiome dysbiosis and this mental disorder. However, the methodological heterogeneity among the studies highlights the need for further research to confirm this potential relationship.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.008
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.143
GPT teacher head0.510
Teacher spread0.367 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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