Smoking index, lifestyle factors, and genomic instability assessed by single-cell gel electrophoresis: a cross-sectional study in subjects from Yucatan, Mexico

BACKGROUND: It is widely accepted that genomic instability is associated with several mechanisms involving oxidative stress, which can increase the rate of DNA breaks. Such factors include smoking, impairments in body composition, an unhealthy lifestyle, and a hereditary history of cancer. The aim was to evaluate the degree of association of genomic instability in smokers and non-smokers, and how the risk could change depending on the lifestyle and other causes. For this purpose, a survey of tobacco consumption, dietary patterns, physical activity, antecedents of cancer, and body composition assessment was carried out. Genomic instability was evaluated through a single-cell gel electrophoresis using peripheral blood mononuclear cells in three different conditions of oxidative stress. The analysis of genomic damage degree was performed through a dimension reduction procedure (principal component analysis) from 16 parameters per treatment (adding up 48 parameters of genomic damage per subject) and a binary logistic regression model for DNA fragmentation risk. RESULTS: The sample consisted of 82 participants, divided into three age groups: young adults (18–35 years), adults (36–59 years), and older adults (60–95 years). As expected, the results showed a significant positive correlation of age with genomic damage rates, represented by 2 PCA groups (p = 0.027, p = 0.004). There were consistent significant positive associations of genomic damage rates with smoking index and three PCA groups (p = 0.007, p = 0.004, p = 0.009). The smoking status and age group analysis revealed that there were significant differences for adult smokers with the same aforementioned PCA groups (p = 0.002, p = 0.001, p = 0.010). In addition, higher DNA damage rates were found in subjects with incorrect diet patterns, long sitting hours, and previous exposure to radiation. The analysis with binary logistic regression displayed two models in which lifestyles (age, diet, and/or sedentarism) did not change the significance of smoking index for DNA fragmentation risk; however, when physical activity was present in the model, the smoking index was not a significant factor for DNA damage risk. CONCLUSIONS: Although it is well known that smoking affects human health in different ways, DNA fragmentation can be analyzed by a damage phenotypic analysis and integrate a risk analysis reshaped by diet and lifestyle in general.