The research, published as an open-access paper in the journal Heliyon, was carried out by a team at the University of Queensland led by Min-Tz Weng and Kathryn Steadman. It is the first investigation to compare the nicotine metabolite ratio, a standard biomarker of nicotine metabolism, between cigarette smokers and users of nicotine vaping products in an Australian population. The finding aligns with three earlier studies from the United States and Spain, which likewise reported no difference in metabolism speed between the two consumer groups.

The biology behind the measurement hinges on a single liver enzyme. Roughly 70 to 80 percent of the nicotine absorbed from any inhaled product is converted into a compound called cotinine, and the same enzyme, CYP2A6, then transforms cotinine into 3-hydroxycotinine. Because cotinine is only turned into 3-hydroxycotinine through CYP2A6 activity, the ratio of total 3-hydroxycotinine to free cotinine in urine, known as the nicotine metabolite ratio or NMR, provides a reliable window into how quickly a person processes nicotine. A high ratio marks a fast metaboliser; a low ratio marks a slow one.

Decades of research in smokers have shown that this ratio matters clinically. People with higher NMR values tend to smoke more cigarettes, absorb more nicotine, and struggle more when attempting cessation, because their nicotine levels drop faster and trigger stronger cravings. In principle, a simple urine test could help clinicians match would-be quitters to the most effective therapies, with fast metabolisers often faring better with certain forms of nicotine replacement than others. Sex and ethnicity also leave fingerprints on the ratio: women typically metabolise nicotine faster than men, and White and Latino populations faster than Asian and African-American populations, partly reflecting inherited differences in CYP2A6 genes.

What has been missing is data on vapers, and on Australian users generally. Previous comparisons of NMR between smokers and vapers had been limited to a large cohort of primarily White women in the US, a smaller group from the American Indian population, and an adult sample in Barcelona measured through saliva. The only prior Australian measurement came from a methods-validation study of 280 Tasmanian smokers, without any within-cohort comparisons. The Queensland team set out to fill both gaps at once.

The researchers recruited 44 adults in Brisbane who used either conventional cigarettes or nicotine vaping products exclusively, at least daily. Each participant kept a three-day diary recording brands, strengths, flavours and consumption, then collected every drop of urine over a full 24-hour period on the third day. After excluding two vapers whose cotinine levels fell below a biochemical threshold confirming active nicotine use, the final analysis covered 42 people: 22 smokers and 20 vapers. Most were male, aged 18 to 29, and ethnically diverse, including Asian, White, Latino and one Australian Aboriginal participant.

The laboratory work was exacting. Urine samples were diluted, split, and analysed by liquid chromatography with tandem mass spectrometry, a technique sensitive enough to detect metabolites at concentrations below a tenth of a microgram per litre. Half of each sample was treated with an enzyme that strips off glucuronide conjugates, allowing the team to measure total nicotine, cotinine and 3-hydroxycotinine, six compounds in all, summed as total nicotine equivalents. Creatinine measurements normalised the results for differences in hydration. The overall mean NMR of 2.71 sat comfortably within the range of 1.7 to 5.2 reported in earlier populations worldwide.

The headline result was a null finding with real weight: urinary NMR did not differ between smokers and vapers. Metabolism speed, it appears, is a property of the person, not the product. But exposure told a different story. Vapers excreted significantly higher concentrations of cotinine and 3-hydroxycotinine, and consequently higher total nicotine equivalents, whether expressed per milligram of creatinine or per 24-hour urine volume. The authors suggest this reflects the higher nicotine content of vaping liquids and their enhanced palatability, which can encourage more frequent and deeper intake. Consistent with national Australian survey data, the vapers were also significantly younger than the smokers, averaging 26 years against 34.

Within the cohort, the expected demographic patterns emerged. Women averaged an NMR of 3.49 compared with 2.43 in men, a statistically significant difference, and participants of White background averaged 2.99 against 1.94 for those of Asian descent, echoing the known prevalence of reduced-function CYP2A6 variants among Asian populations. Splitting the group at the median ratio of 2.31, the researchers found that faster metabolisers carried higher concentrations of cotinine, 3-hydroxycotinine and total nicotine equivalents than slower ones, exactly as predicted by the wider literature. Intriguingly, the single Australian Aboriginal participant, a woman using cigarettes, posted one of the highest ratios recorded, at 5.25, a hint of variation in a population for which no NMR data previously existed.

The authors are candid about the study’s limits. Forty-two participants is a small sample, and the sex and ethnicity subgroup analyses are exploratory. Factors known to shift the ratio, such as menthol ingredients, CYP2A6-altering medications, pregnancy and alcohol, were not assessed, and the unsupervised at-home urine collections mean the 24-hour totals deserve cautious interpretation. Still, the message for the fast-growing population of vapers is clear: their bodies handle nicotine no differently than smokers’ bodies do, even as modern devices deliver a heavier dose. If the nicotine metabolite ratio proves useful for tailoring cessation therapy, that guidance should apply equally to anyone trying to give up vaping.

Subject of Research: Nicotine metabolism rate measured by urinary nicotine metabolite ratio in cigarette smokers versus nicotine vaping product users

Article Title: Exploring nicotine metabolism among people who smoke and vape

Article References: Weng, M.-T., Zheng, Q., Deng, Y., Shrestha, S., Fan, W., Thai, P. K., Gartner, C. E., & Steadman, K. J. (2026). Exploring nicotine metabolism among people who smoke and vape. Heliyon, 12(15), Article e45549. https://doi.org/10.1016/j.heliyon.2026.e45549

Image Credits: AI Generated

DOI: 10.1016/j.heliyon.2026.e45549

Keywords: nicotine metabolism, CYP2A6, nicotine metabolite ratio, cotinine, 3-hydroxycotinine, vaping, cigarette smoking, smoking cessation, LC-MS/MS, urine biomarkers, Australia, nicotine exposure

The study, published in Holistic Integrative Oncology, drew on five cycles of the National Health and Nutrition Examination Survey, or NHANES, the rolling federal program that collects standardized laboratory measurements from a cross-section of the civilian, noninstitutionalized US population. The researchers assembled a final analytic population of 7,174 men with concurrent measurements of serum cotinine, total PSA, and free PSA. The free-to-total PSA ratio, a value clinicians use to sharpen the interpretation of borderline PSA results, was calculated directly from the two measured fractions. Cotinine, measured with isotope dilution high-performance liquid chromatography coupled to atmospheric pressure chemical ionization tandem mass spectrometry, served as the objective window onto recent nicotine exposure — capturing not only active smoking but also secondhand smoke and other nicotine sources that self-reported questionnaires routinely miss or misclassify.

What the analysis found was a story of two biomarkers going their separate ways. In fully adjusted multivariable linear regression models that accounted for age, race and ethnicity, body mass index, education, marital status, estimated kidney function, alcohol use, family income, and survey cycle, serum cotinine showed essentially no independent association with total PSA — the regression coefficient hovered at effectively zero, with a P value of 0.801. Yet the same exposure variable was consistently and significantly associated with a lower free-to-total PSA ratio: each additional nanogram per milliliter of cotinine corresponded to a decrease of roughly 0.005 percentage points in the ratio (95% confidence interval -0.00705 to -0.00283; P = 0.000005). The signal survived every tier of statistical adjustment, growing rather than shrinking as confounders were layered in, and the direction remained consistent when cotinine was log-transformed to temper the influence of heavy smokers.

The discordance between the two endpoints is what makes the result scientifically interesting. Total PSA reflects the overall circulating concentration of a kallikrein-related serine protease secreted by the androgen-responsive prostate gland, a concentration that climbs with benign prostatic hyperplasia, prostatitis, and prostate cancer alike. The free-to-total ratio, by contrast, depends not on how much PSA is in the blood but on how it is distributed between molecular forms — free PSA floating unbound versus PSA complexed with proteins such as alpha-1-antichymotrypsin. Because the two endpoints track different aspects of PSA chemistry, a compound that shifts the composition of circulating PSA without changing its total concentration would produce exactly the pattern observed: a null association with total PSA and a robust inverse association with the ratio.

Recognizing that a single cotinine measurement captures only a narrow biological window — days, not decades — the team added a second exposure dimension. From self-reported cigarette histories, they calculated pack-years, the classic epidemiological measure of cumulative smoking burden, for 6,132 of the participants, 3,433 of whom were current or former smokers. Correlation analyses confirmed that cotinine and pack-years point in the same direction but are far from interchangeable: the Pearson correlation between raw values was a modest 0.209, the Spearman rank correlation 0.270, and only after log-transforming both variables did the relationship strengthen to 0.337. A heavy lifetime smoker who quit years ago can carry low cotinine today; a recent relapser can carry high cotinine on a thin lifetime foundation. The two metrics measure genuinely different things.

That difference mattered in the sensitivity models. When pack-years replaced cotinine as the exposure variable in fully adjusted regressions, the association with PSA ratio vanished entirely (β = -0.00750, 95% CI -0.02010 to 0.00509; P = 0.243), and the log-transformed version of pack-years fared no better. The cotinine signal, in other words, cannot be explained away as a shadow of lifetime cigarette burden. One provocative secondary pattern emerged for total PSA: log-transformed pack-years showed a statistically significant inverse association in sensitivity analyses, hinting that decades of cumulative exposure may relate to total PSA through chronic tissue, vascular, or endocrine remodeling in ways that an acute biomarker cannot capture. The authors are careful to stress that nothing in these data should be read as evidence that smoking protects the prostate — tobacco exposure has established harmful effects across organ systems and is associated with worse outcomes after prostate cancer diagnosis, including higher mortality and progression risk.

What might cotinine actually be doing to PSA chemistry? The mechanistic clues point toward nicotinic acetylcholine receptor signaling and androgen biology. Cotinine, which persists in serum far longer than nicotine, binds cell-surface cholinergic alpha5 nicotinic receptors, which experimental studies have shown are upregulated in prostate cancer and drive tumor cell proliferation and invasion. Experimental work also suggests cotinine can interact with the androgen receptor and suppress its expression in animal prostate tissue. Because PSA secretion is androgen-regulated, cotinine-related modulation of androgen receptor signaling could preferentially reduce the epithelial secretion of free PSA, shifting a greater share of immunoreactive PSA toward the alpha-1-antichymotrypsin-complexed fraction — lowering the ratio while leaving total PSA nearly untouched. Tobacco-driven systemic inflammation could contribute as well by altering the acute-phase protein milieu in which PSA complexes circulate. These mechanisms remain inferential in a cross-sectional dataset, but they explain the observed geometry of the results with unusual precision.

The interpretation demands caution at every turn. NHANES participants were not enrolled because of suspected prostate disease, and no biopsy adjudication exists for this cohort, so the findings speak to biomarker-level variation in a general population, not to cancer incidence, diagnostic thresholds, or clinical decision-making. Serum cotinine is also shaped by CYP2A6-mediated metabolism, which varies across racial and genetic backgrounds, meaning identical cotinine values may reflect different actual nicotine intake. The authors noted that the cotinine-PSA ratio association appeared more pronounced in certain subgroups, including non-Hispanic White and non-Hispanic Black participants, men aged 40 to 49 and 70 to 79, and those with a body mass index above 18.5, but stratified patterns in cross-sectional data carry their own fragility. Smokers may also differ systematically in screening behavior, comorbidity, and healthcare access, and despite the standardized survey protocol, differential participation and missing laboratory data cannot be excluded as sources of selection.

Within those constraints, the study stakes out a genuinely novel position: it is, according to the authors, the first population-based analysis to link cotinine to prostate-related endpoints in a nationally representative sample. Its strength lies in the objective laboratory measurement of exposure, the large sample, and the statistical persistence of the PSA ratio association after extensive adjustment. Its limitation is time — a single cotinine measurement, a single PSA snapshot, and no way to order cause and effect. The authors call for longitudinal studies with repeated cotinine measurements, validated cumulative smoking metrics, nicotine metabolite profiling that includes trans-3′-hydroxycotinine, and adjudicated prostate disease outcomes to determine whether recent exposure status, cotinine metabolism, or something else entirely drives the association.

For clinicians and epidemiologists alike, the practical message is narrower than the biological one. Nothing in this analysis justifies changing PSA screening practice or interpreting an individual patient’s PSA ratio through the lens of a cotinine blood level. But the results do suggest that tobacco-related biological status is a real and quantifiable source of variation in one of the most widely used prostate biomarkers in medicine — a reminder that the numbers generated by screening assays are not static properties of a gland but dynamic readouts that absorb the chemical history of the person they come from. As molecular epidemiology continues to separate the recent exposure a biomarker captures from the cumulative burden a questionnaire recalls, studies like this one map the fault lines where those two measures diverge, and where the biology of tobacco meets the biochemistry of cancer screening.

Subject of Research: The association between serum cotinine, a biomarker of tobacco exposure, and prostate-related clinical endpoints including PSA measures

Article Title: Association between serum cotinine levels and prostate-related clinical endpoints

Article References: Wang, Z., Ge, Q., Anwaier, A., Xu, W., & Ye, D. (2026). Association between serum cotinine levels and prostate-related clinical endpoints. Holistic Integrative Oncology, 5(1), Article 76. https://doi.org/10.1007/s44178-026-00292-7

Image Credits: AI Generated

DOI: 10.1007/s44178-026-00292-7

Keywords: serum cotinine, prostate-specific antigen, free-to-total PSA ratio, tobacco exposure, NHANES, prostate cancer, pack-years, nicotine metabolism, prostate biomarkers, epidemiology, urology, cancer screening