Abstract
This study sought to structure a genetic score for smoking behaviour in a Chinese population. Single-nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS) were evaluated in a community-representative sample (N = 3,553) of Beijing, China. The candidate SNPs were tested in four genetic models (dominance model, recessive model, heterogeneous codominant model and additive model), and 7 SNPs were selected to structure a genetic score. A total of 3,553 participants (1,477 males and 2,076 females) completed the survey. Using the unweighted score, we found that participants with a high genetic score had a 34% higher risk of trying smoking and a 43% higher risk of SI at ≤18 years of age after adjusting for age, gender, education, occupation, ethnicity, body mass index (BMI) and sports activity time. The unweighted genetic scores were chosen to best extrapolate and understand these results. Importantly, genetic score was significantly associated with smoking behaviour (smoking status and SI at ≤18 years of age). These results have the potential to guide relevant health education for individuals with high genetic scores and promote the process of smoking control to improve the health of the population.
Highlights
This study sought to structure a genetic score for smoking behaviour in a Chinese population
We retested all 18 significant single-nucleotide polymorphisms (SNPs) (P < 5 × 10−8) from genome-wide association studies (GWAS) conducted on smoking behaviour (cigarettes smoked per day (CPD), SI) in a Chinese population; we chose 7 of these SNPs to derive genetic scores
We derived three types of genetic scores to evaluate the genetic risk of smoking behaviour and found that the evaluation capacities of these three scores were approximately the same
Summary
This study sought to structure a genetic score for smoking behaviour in a Chinese population. Since 2005, genome-wide association studies (GWASs) of smoking behaviour (regular smoking, cigarettes per day and smoking initiation (SI) age) have identified 21 single-nucleotide polymorphisms (SNPs) with significant genome-wide associations (P < 5 × 10−8) in or near the following genes: CHRNB3, CHRNA6, BDNF, CHRNA3, CHRNA5, AGPHD1, CHRNB4, CYP2A6 and EGLN219–26. Many of these genes are expressed in or known to act in nicotine or dopamine receptor or brain-derived neurotrophic factor pathways. We conducted this study to verify these SNPs in a Chinese population and subsequently create a genetic score combining the effects of these SNPs on smoking behaviour
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