INTRODUCTION
Porphyromonas gingivalis is a well-established keystone pathogen in the etiology of periodontitis, a chronic inflammatory disease affecting the supporting structures of teeth. This study aims to explore the distribution of P. gingivalis fimA genotypes and their relationship with smoking and disease severity in a Korean adult population. The research is grounded in the hypothesis that environmental and host factors, such as smoking, may influence the prevalence and pathogenic potential of specific fimA genotypes. Utilizing subgingival biofilm samples from 283 individuals categorized into healthy non-smokers, non-smoking periodontitis patients, and smoking periodontitis patients, the study employs PCR-based genotyping and robust statistical analyses. By highlighting the genotype-specific associations of P. gingivalis with disease severity and smoking, the research provides a critical step forward in understanding microbial-host-environment interactions in periodontal disease progression.
GENOTYPE DISTRIBUTION AND DISEASE CORRELATION
The distribution of P. gingivalis fimA genotypes was found to vary significantly among health and disease groups. Notably, type II emerged as the most prevalent genotype across all categories, with a marked increase in frequency among individuals with periodontitis. This suggests a potential role of type II fimA in advancing periodontal tissue destruction. Statistical evidence, particularly from Fisher’s exact test, demonstrated that all genotypes except types I and III showed significant differential distributions between healthy and diseased individuals. These findings support the hypothesis that specific genotypes may harbor distinct pathogenic potentials, contributing differently to the development and progression of periodontitis.
IMPACT OF SMOKING ON GENOTYPE VARIATION
Smoking, a known environmental risk factor for periodontal disease, showed a significant impact on the distribution of certain P. gingivalis genotypes. Types IV and Ib were particularly associated with smokers, suggesting that these genotypes may exhibit adaptive or selective responses to the altered subgingival environment caused by tobacco exposure. This association emphasizes the need for genotype-aware analyses in populations with varying smoking statuses. It further supports the concept that environmental exposures not only contribute to disease severity but also modulate the microbial composition at the strain level, potentially altering the trajectory of disease pathogenesis.
AGE AND HOST FACTORS IN GENOTYPE ASSOCIATION
In addition to smoking, age emerged as a notable host factor influencing fimA genotype prevalence. The logistic regression analysis identified significant correlations between specific genotypes (notably types IV and Ib) and older age groups. This suggests an age-related susceptibility to colonization by certain strains of P. gingivalis. These findings warrant further investigation into how host aging, immunosenescence, and oral microbiome dynamics contribute to differential genotype colonization and pathogenicity. Understanding this interplay is essential for developing targeted prevention strategies in elderly populations at higher risk for periodontal disease.
STATISTICAL MODELS AND DISEASE PREDICTION
The application of logistic regression models provided robust insights into the predictive power of fimA genotype presence on disease status. An odds ratio of 7.5 for the association between P. gingivalis detection and advanced periodontitis underscores the pathogen’s significant contribution to disease progression. This statistical approach enhances the resolution of genotype-disease associations, enabling researchers to predict disease severity based on microbial strain presence. Such models could potentially be integrated into clinical diagnostic frameworks to improve risk assessment and individualized treatment planning in periodontology.
IMPLICATIONS FOR STRAIN-SPECIFIC RESEARCH AND THERAPY
This study’s findings underscore the critical need for strain-specific research in microbial pathogenesis. The differential distribution and environmental associations of P. gingivalis fimA genotypes highlight that not all strains contribute equally to disease. These insights pave the way for more precise investigations into virulence mechanisms, vaccine development, and genotype-targeted antimicrobial strategies. As periodontal therapies evolve, recognizing and addressing microbial heterogeneity will be vital in optimizing treatment outcomes and preventing disease recurrence, especially in high-risk populations like smokers and older adults.
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Hashtags
#PorphyromonasGingivalis, #fimAGenotypes, #PeriodontitisResearch, #OralMicrobiome, #SmokingAndHealth, #MicrobialGenotyping, #PeriodontalPathogens, #EnvironmentalRiskFactors, #DentalResearch, #HostMicrobeInteraction, #KoreanHealthStudy, #PCRGenotyping, #MicrobiomeVariation, #DiseasePrediction, #EpidemiologicalStudy, #InflammatoryDiseases, #SubgingivalBiofilm, #GenotypeSpecificPathogenesis, #StatisticalAnalysis, #PrecisionDentistry,
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