Liver Disease and Periodontal Pathogens: A Bidirectional Relationship Between Liver and Oral Microbiota
Bibliographic record
Abstract
Background: Periodontal dysbiosis contributes to liver injury through systemic inflammation, oral–gut microbial translocation, and endotoxemia. Lipopolysaccharides (LPSs) and virulence factors derived from periodontal pathogens, particularly Porphyromonas gingivalis (P. gingivalis) activate Toll-like receptor (TLR) signaling, trigger NF-κB-mediated cytokine release (e.g., TNF-α, IL-1β, IL-6), and promote oxidative stress and Kupffer cell activation within the liver. The present systematic review summarized clinical evidence supporting these mechanistic links between periodontal pathogens and hepatic outcomes, highlighting the role of microbial crosstalk in liver pathophysiology. Methods: A PRISMA-compliant systematic review was conducted by searching PubMed, Scopus, and the Cochrane library, as well as gray literature. Eligible study designs were observational studies and trials evaluating P. gingivalis and other periodontal pathogens (Aggregatibacter actinomycetemcomitans, Prevotella intermedia, and Tannerella forsythia) for liver phenotypes (Non-Alcoholic Fatty Liver Disease [NAFLD]/Metabolic Dysfunction-Associated Steatotic Liver Disease [MASLD], fibrosis/cirrhosis, acute alcoholic hepatitis [AAH], and Hepatocellular carcinoma [HCC]). Risk of bias was assessed using the Newcastle–Ottawa Scale adapted for cross-sectional studies (NOS-CS) for observational designs and the RoB 2 scale for single randomized controlled trials (RCTs). Due to the heterogeneity of exposures/outcomes, results were summarized narratively. Results: In total, twenty studies (2012–2025; ~34,000 participants) met the inclusion criteria. Population-level evidence was conflicting (no clear association between anti-P. gingivalis serology and NAFLD), while clinical cohorts more frequently linked periodontal exposure, particularly to P. gingivalis, to more advanced liver phenotypes, including fibrosis. Microbiome studies suggested stage-related changes in oral communities rather than the effect of a single pathogen, and direct translocation into ascitic fluid was not observed in decompensated cirrhosis. Signals from interventional and behavioral research (periodontal therapy; toothbrushing frequency) indicate a potential modifiability of liver indices. The overall methodological quality was moderate with substantial heterogeneity, precluding meta-analysis. Conclusions: Current evidence supports a biologically plausible oral–liver axis in which periodontal inflammation, often involving P. gingivalis, is associated with liver damage. Causality has not yet been proven; however, periodontal evaluation and treatment may represent a low-risk option in periodontitis-associated NAFLD. Well-designed, multicenter prospective studies and randomized trials with standardized periodontal and liver measurements are needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".