Periodontitis is a complex, polymicrobial disease characterized by chronic inflammation, leading to the destruction of tooth-supporting structures. If left untreated, it results in periodontal pocket formation, alveolar bone resorption, and eventual tooth loss (Van Dyke et al., 2020). Among the numerous bacterial species implicated in periodontitis, Porphyromonas gingivalis is recognized as a keystone pathogen due to its profound influence on host immune modulation and microbial dysbiosis (Hajishengallis et al., 2012). P. gingivalis employs multiple virulence factors, including fimbriae, gingipains, lipopolysaccharides, haemagglutinins, and outer membrane vesicles, to facilitate adhesion, colonization, and immune evasion (Hajishengallis et al., 2012).

Among these, fimbriae play a crucial role in bacterial adhesion, biofilm formation, and host cell invasion (Amano, 2003, Enersen et al., 2013, Nakagawa et al., 2002). The major fimbrial subunit, encoded by the fimA gene, exhibits six genotypic variants (I, II, III, IV, V, and Ib), each displaying distinct adhesion and invasion properties. Several studies have reported that types II, IV, and Ib are particularly associated with periodontitis (Enersen et al., 2013, Moon et al., 2012, Moon et al., 2013, Wang et al., 2020). For example, a meta-analysis by Wang et al. (2020) found that fimA types II and IV were significantly more prevalent in chronic periodontitis patients than in healthy individuals, with type II being the most dominant. Similarly, Pan et al. (2017) demonstrated that the presence of fimA types II and IV correlated with higher gingival index scores and more severe periodontal conditions in adolescent patients undergoing orthodontic treatment. These findings highlight the clinical relevance of fimA genotyping in evaluating strain-level virulence potential of P. gingivalis in periodontitis.

While the impact of smoking on host immune responses has been extensively studied (Chang et al., 2002, Cho et al., 2015, Johnson et al., 2010, Lallier et al., 2017, Meenawat et al., 2015, Xanthoulea et al., 2013, Zhang et al., 2019, Zhou et al., 2007, Ng et al., 2015), its influence on the composition and structure of the subgingival microbiome has become increasingly well characterized in recent years, particularly through next-generation sequencing (NGS)-based studies (Mason et al., 2015, Shchipkova et al., 2010, Moon et al., 2015). These studies have reported that smokers exhibit distinct subgingival microbial profiles compared to non-smokers, including increased abundance of pathogenic species such as Fusobacterium nucleatum and Treponema denticola. Earlier studies using culture-based or PCR-based methods reported inconsistent findings regarding microbial differences between smokers and non-smokers (Apatzidou et al., 2005, Boström et al., 2001, Darby et al., 2000, Haffajee and Socransky, 2001, Preber et al., 1992, Renvert et al., 1998, Stoltenberg et al., 1993, Zambon et al., 1996), likely due to a combination of methodological limitations and biological variability such as age, oral hygiene status, and disease severity. Despite these advancements, NGS-based microbiome studies primarily focus on species-level taxonomy, often overlooking strain- and genotype-specific differences. In our prior 16S rRNA sequencing study (Moon et al., 2015), the sequencing depth was insufficient to resolve P. gingivalis strains, precluding a more detailed investigation into fimA genotype-specific variations. Given that fimA genotypes differ not only in their intrinsic virulence potential but also in how they interact with host responses, environmental exposures, and other microbial species—including selective synergy with cohabiting pathogens (Kwack et al., 2022)—their distribution should be assessed in the context of modifiable risk factors such as smoking.

Although previous studies have reported associations between certain fimA genotypes and smoking or periodontitis, most were limited to univariate analyses without adjusting for confounding factors such as disease stage or age (Teixeira et al., 2009). Additionally, few studies have systematically examined less common but potentially relevant genotypes such as fimA types IV and Ib. To address this gap, we reanalyzed residual subgingival biofilm samples from our earlier studies (Moon et al., 2013, Moon et al., 2015) using genotype-specific PCR to investigate the associations between fimA prevalence and host/environmental variables including smoking status, disease stage, and age. Both Fisher’s exact test and multivariable logistic regression analyses were used to identify potential genotype-specific microbial patterns beyond simple group comparisons. An overview of the study process is provided in Fig. 1.

By integrating genotype-level analysis with multivariable modeling, this study seeks to clarify whether environmental exposures such as smoking influence the distribution of P. gingivalis fimA genotypes. We hypothesized that specific fimA genotypes—particularly types II, IV, and Ib—would exhibit differential associations with smoking, disease stage, and age, reflecting genotype-specific microbial adaptation within the periodontal environment.