White Matter Integrity and Nicotine Dependence: Evaluating Vertical and Horizontal Pleiotropy

Abstract

Tobacco smoking is an addictive behavior that supports nicotine dependence and is an independent risk factor for cancer and other illnesses. Its neurogenetic mechanisms are not fully understood but may act through alterations in the cerebral white matter (WM). We hypothesized that the vertical pleiotropic pathways, where genetic variants influence a trait that in turn influences another trait, link genetic factors, integrity of cerebral WM, and nicotine addiction. We tested this hypothesis using individual genetic factors, WM integrity measured by fractional anisotropy (FA), and nicotine dependence-related smoking phenotypes, including smoking status (SS) and cigarettes per day (CPDs), in a large epidemiological sample collected by the UK Biobank. We performed a genome-wide association study (GWAS) to identify previously reported loci associated with smoking behavior. Smoking was found to be associated with reduced WM integrity in multiple brain regions. We then evaluated two competing vertical pathways: Genes → WM integrity → Smoking versus Genes → Smoking → WM integrity and a horizontal pleiotropy pathway where genetic factors independently affect both smoking and WM integrity. The causal pathway analysis identified 272 pleiotropic single-nucleotide polymorphisms (SNPs) whose effects on SS were mediated by FA, as well as 22 pleiotropic SNPs whose effects on FA were mediated by CPD. These SNPs were mainly located in important susceptibility genes for smoking-induced diseases NCAM1 and IREB2. Our findings revealed the role of cerebral WM in the maintenance of the complex addiction and provided potential genetic targets for future research in examining how changes in WM integrity contribute to the nicotine effects on the brain.

The Interaction Effects of Age, APOE and Common Environmental Risk Factors on Human brain Structure

“…The decreased FA and increased AxD, RD and MD matched well the accelerating brain aging process among heavy smokers [87]. Studies on causal pathways of nicotine dependence [10] using 23,624 subjects from UKB revealed that 272 SNP effects on smoking status were mediated by the FA, particularly at the right ALIC, suggesting this association can be genetically driven.…”

“…Previous study on physical activity discovered an association with the increase of gray matter volume among older adults (> 60 years old) [16] based on the 5272 participants of UK Biobank. Studies on causal pathways of nicotine dependence [10] using 23,624 subjects from UK Biobank revealed that 272 SNP effects on smoking status were mediated by the FA, particularly at the right ALIC, suggesting this association can be genetically driven. Another literature [9] recognized the causal relationship between heavy alcohol use and smoking and the reduced subcortical volume.…”

“…Since many modifiable exposome variables are often the root cause of the health disparities, it is of high demand to identify risk factors associated with aging and fully understand the synergistic effect of these risk factors on the aging mechanism. Multiple lines of evidence show that the effect of biological factors and environmental variables on the aging process is mediated by brain structure, including regional morphometrics and the wiring patterns of white matter tracts [7]- [10]. Many factors, such as age [11], genetics [12]- [14], lifestyle factors [15]- [18], socioeconomic status (SES) [19], [20], and sex [21]- [23], may contribute to an individual's changes in brain structure in a comprehensive way.…”

Evaluating the causal effect of tobacco smoking on white matter brain aging: a two‐sample Mendelian randomization analysis in UK Biobank

“…The CPD was a quantitative variable representing the average number of cigarettes smoked per day for tobacco users, characterizing the level of nicotine craving in current smokers. We defined the CPD (ranges from 0 to 60) of current smokers based on three UKB data fields (IDs: 2887, 3456 and 6183) following the commonly used procedure in smoking genome‐wide association studies (GWAS) [50, 51]. For those subjects who smoked fewer than one CPD, the CPD values were rounded down and recoded to 0; for those who smoked more than 60 CPD, the CPD values were truncated recoded to 60.…”

“…This study focused up on two smoking behaviors (phenotypes): SS and CPD, following the commonly used definitions in the literature [50,51]. SS was a binary variable classifying participants as current smokers and non-smokers who had never smoked according to the UKB data field 2016 (SS).…”