“The results highlight that Nightingale’s biomarkers provide a quantitative proxy for smoking exposure and may be used as a tool for predicting smoking-related disease risk.”
Smoking is well known as a dramatic risk factor for chronic diseases like lung cancer, chronic obstructive pulmonary disease (COPD), and heart disease. It also increases the risk of many other diseases to different degrees and is in general one of the most important covariates in epidemiological analyses.
Smoking behavior is most often assessed using questionnaire-based categorical variables (e.g., current smoker / never smoked) or self-estimated quantitative measures (e.g., the number of cigarettes smoked per day). However, the reliability and availability of these variables is limited in many cohorts. It is possible to directly measure biomarkers of nicotine metabolism, such as cotinine, but collecting a sample and taking this measurement is typically only done in studies specifically focused on smoking itself.
Another possibility is to use general-purpose blood metabolites to estimate smoking behavior. Here we explore associations of Nightingale’s blood biomarkers with smoking and consider how they can be used to capture this exposure.
Smoking is associated with fatty acids and chronic inflammation
To assess the associations of biomarkers with smoking, we utilized metabolomic data obtained from Nightingale Health's platform, comprising data from over 270,000 UK Biobank samples. We computed associations of 251 blood biomarkers with smoking status and adjusted for age, sex, body-mass index, and cholesterol medication.
Our analysis revealed widespread associations between smoking status and biomarkers, consistent with the expectation that it perturbs many aspects of normal metabolism. Fatty acids exhibited the strongest associations, for example an odds ratio (OR) of 0.58 (0.58-0.59 95% CI) for the ratio of polyunsaturated and monounsaturated fatty acids and 0.64 (0.64-0.65 95% CI) for percentage Omega-3 fatty acids. These findings are particularly intriguing given the growing scientific evidence implicating that fatty acids play a causal role in various diseases (Davyson et al. 2023, He et al. 2022, Li et al. 2022). Additionally, we observed substantial, unfavorable associations with a biomarker of chronic inflammation, Glycoprotein acetyls (GlycA), which exhibited an OR of 1.50 (95% CI: 1.48-1.52). Figure 1 shows how long-term smokers show a distorted metabolic profile across nearly all the key functions captured by our biomarkers.