Buccal Swabs Reveal Smoking’s Inflammatory Fingerprint in Young Adults’ Oral Cavities

Young smokers show a measurably distinct molecular profile in their mouths before any clinical disease appears, according to a new study published in Bratislava Medical Journal. Researchers used buccal swabs and liquid chromatography-mass spectrometry to compare 54 smokers with 54 nonsmokers, all aged 18 to 25, and found significant increases in eight metabolites and thirteen proteins tied to inflammation and oxidative stress. The findings raise the possibility that a simple, non-invasive cheek swab could serve as an early-warning tool for tobacco-related oral damage.

Eight Metabolites Elevated in Young Smokers' Oral Cavities

The most striking metabolomic signal was N-acetylcadaverine, which appeared at 14.12 times the level seen in nonsmokers, a gap that held to p < 0.001. N-acetylspermine followed at 3.64 times the nonsmoker level. Spermidine, tyramine, pipecolic acid, methylthiophene, 5-oxoproline, and histidine also rose significantly, with ratios ranging from 2.24 to 2.98.

These are not random molecules. N-acetylcadaverine is a byproduct of Fusobacterium nucleatum, a periodontal pathogen that converts the amino acid lysine into cadaverine and creates an alkaline, low-oxidative environment favorable to other pathogens like Porphyromonas gingivalis. Elevated cadaverine and its derivatives can suppress bactericidal superoxide enzymes and disrupt leukocyte migration to inflammation sites. The polyamines spermidine and N-acetylspermine are also linked to cellular growth, DNA stabilization, and apoptosis; when their metabolism is dysregulated, the results include cytotoxicity and associations with stroke, renal failure, and tumor progression.

Tyramine's rise likely reflects both bacterial proteolytic activity and the well-documented inhibition of monoamine oxidase (MAO) by tobacco smoke. MAO inhibition is considered a key mechanism in nicotine dependence, and tyramine accumulation may signal elevated colonization by periodontitis-associated species such as Capnocytophaga gingivalis and Eikenella corrodens. Meanwhile, elevated 5-oxoproline and pipecolic acid point to impaired glutathione synthesis and altered antioxidant defenses, consistent with the broader metabolic disruptions identified in smokers across larger cohorts, where hundreds of metabolites shift in smoking-associated patterns tied to metabolic disorders.

Thirteen Inflammatory Proteins Surge in Smoker Buccal Samples

The proteomic results were equally striking. MRP14 (S100A9), a component of the calprotectin complex, was nearly 10-fold higher in smokers (ratio 9.96, p < 0.001). MCP-1, a chemokine that recruits monocytes to inflammation sites, was more than 7-fold higher (ratio 7.18, p < 0.001). Eleven other proteins also rose significantly, including C-reactive protein (CRP), CXCL10, neutrophil gelatinase-associated lipocalin (NGAL), transferrin, macrophage inflammatory protein-1 alpha (MIP-1α), serum amyloid A (SAA), EPAS1, MRP8 (S100A8), immunoglobulin A (IgA), haptoglobin, and salivary alpha-amylase.

Several of these proteins converge on the Toll-like receptor (TLR) signaling pathway and the IL-17 inflammatory axis, both of which respond to microbial patterns like lipopolysaccharide from gram-negative periodontal pathogens. CXCL10, which was 2.92-fold higher in smokers, activates and recruits T cells, NK cells, and monocytes, and can also stimulate osteoclastogenesis via RANKL upregulation, linking it to bone resorption in periodontitis. The calprotectin complex formed by MRP8 and MRP14 is a well-established marker of neutrophil-driven inflammation, and its marked elevation in young adults without overt oral disease is notable. Elevated CRP and haptoglobin further signal low-grade systemic inflammatory activation even at this early stage. Previous untargeted omics work has shown the value of multi-omics biomarkers in characterizing tobacco use risk and treatment compliance, and this study extends that approach to the buccal mucosal surface specifically.

How a Cohort of 108 Young Adults Made the Case

The team recruited 108 volunteers from the University of Ss. Cyril and Methodius in Trnava, Slovakia, split evenly between 54 smokers and 54 nonsmokers. Smokers were defined as those using cigarettes, e-cigarettes, nicotine pouches, or combinations at least twice per day for more than three months. Nonsmokers had never smoked. Participants were asked to avoid eating, drinking, or smoking for at least one hour before sample collection.

Buccal swabs were rubbed along the inner cheek surface for one minute and immediately frozen at minus 20 degrees Celsius. Each swab was split into two portions for separate metabolomic and proteomic extraction, both analyzed by LC-MS using a Thermo Scientific LTQ linear ion trap mass spectrometer. Compound identification was putative, based on comparison with a custom panel drawn from the Human Metabolome Database (HMDB 5.0). Signal intensities were normalized to total ion current to reduce analytical variability. Statistical testing used Student's t-tests and chi-squared tests, with effect sizes confirmed by Cohen's d.

The cohort was deliberately young and generally healthy, a design choice motivated by Slovak epidemiological data showing the country's highest smoking prevalence in the youngest age group. Because nearly 90% of daily adult smokers began by age 18, and 99% had tried smoking by age 25, this window captures early exposure before overt pathology develops. Earlier metabolomic studies using blood confirmed that distinct metabolic profiles separating smokers from nonsmokers are detectable via mass spectrometry-based approaches, but buccal swab-based profiling in this age group had not been specifically characterized.

Key Limitations: Self-Report, Cross-Section, and No Microbiome Data

The authors are candid about what the study cannot yet establish. Smoking status and product use were self-reported and unverified; there were no salivary cotinine measurements to objectively confirm exposure intensity or quantify pack-years. The smoker group was heterogeneous, mixing cigarette, e-cigarette, and nicotine pouch users, which makes product-specific interpretation impossible.

The cross-sectional design rules out causal inference. Observing that MCP-1 is sevenfold higher in smokers does not tell us whether smoking caused that elevation, whether it predates smoking, or whether some unmeasured confound, such as diet or alcohol use, explains part of the difference. Diet and alcohol consumption were not fully analyzed. Microbiome profiling was not performed, which limits interpretation of the host-microbe relationships that the authors discuss at length in the context of polyamine production and bacterial dysbiosis. Compound identification was putative rather than confirmed by orthogonal methods like targeted mass spectrometry or immunoassay. Whether any of these molecular changes reverse after smoking cessation also remains unknown.

What Validated Buccal Biomarkers Could Mean for Early Detection

Despite those caveats, the study adds an important piece to a growing picture. Prior research has used blood to identify metabolites linked to smoking behaviors across multiple biochemical pathways, including amino acid, carbohydrate, and steroid metabolism. What Kozáčiková and colleagues demonstrate is that a comparable signal is readable from a non-invasive cheek swab in people under 25 who have no clinical oral disease yet.

If validated in larger, independent, longitudinal cohorts with objective exposure metrics, a panel built around markers like N-acetylcadaverine, MRP14, and MCP-1 could theoretically support early screening or cessation monitoring without blood draws or dental examinations. The authors call for ELISA or targeted mass spectrometry confirmation in independent samples, integration of microbiome profiling, and studies that track whether the molecular signature changes after quitting. Until that work is done, the current findings are best read as a well-characterized hypothesis, pointing to a genuinely accessible tissue and a clearly disturbed molecular landscape, even at the earliest stages of tobacco use.