Tobacco smoking is a complex addictive behavior and is the chief modifiable causal factor for cancer, coronary and cerebrovascular disorders, chronic obstructive pulmonary disorder, hypertension, and many other illnesses (McBride, 1992; Ziedonis et al., 2008). Additive genetic factors explain up to ∼75% of the variance on traits that quantify nicotine dependence and smoking-related behaviors in population studies, thus supporting the hypothesis of a strong genetic susceptibility for nicotine addiction (Kendler et al., 1999; Vink et al., 2005). Genome-wide association studies (GWASs) localized and replicated multiple genetic variants conferring susceptibility to smoking/nicotine addiction including those regulating nicotinic acetylcholine receptors (nAChRs) (True et al., 1999; Erzurumluoglu et al., 2019). However, its neurogenetic mechanisms remain unknown. Neuroimaging studies reported observational (Zhang et al., 2010; Gons et al., 2011; Gray et al., 2020) and direct associations (Kochunov et al., 2013) between smoking and nicotine administration and white matter (WM) integrity, assessed by the fractional anisotropy (FA) of water diffusion in diffusion tensor imaging (DTI) (Kochunov et al., 2007). Cerebral WM is hypothesized to be involved in both positive and negative reinforcement mechanisms of nicotine addiction (Benowitz, 2010). The positive effect of nicotine is associated with cognitive and mood enhancement, which could be driven through the transient elevation in WM integrity following nicotine administration (Perkins, 1999; Kochunov et al., 2013). The nAChRs have been found in the cerebral WM of both human and nonhuman primates in the previous PET ligand and histological binding studies (Fujita et al., 2003; Ding et al., 2004; Pimlott et al., 2004; Hillmer et al., 2011). Their functions have been studied in peripheral (Lang et al., 2003) and central (Zhang et al., 2011a) nervous systems. The negative effect of nicotine in avoiding withdrawal symptoms may also be caused by reduction in WM integrity due to cerebrovascular and neurodegenerative risks associated with heavy chronic smoking (Hudkins et al., 2010; Kim et al., 2010; Gons et al., 2011; Liao et al., 2011; Zhang et al., 2011a).

Vertical and horizontal pleiotropic pathways are chief causal mechanisms explaining the phenomenon of genetic variants affecting multiple traits (Tyler et al., 2009; Paaby and Rockman, 2013; Jordan et al., 2019). Vertical pleiotropy is observed when a trait influenced by genetic factors has, in turn, influenced another trait by acting as a mediator. Horizontal pleiotropy refers to two traits being independently influenced by the same genetic factors. In the first vertical pleiotropic pathway (Figure 1: model 1), we assume that genetic factors underpinning susceptibility to nicotine dependence do so through alterations in WM integrity. In the second vertical pleiotropic pathway (Figure 1: model 2), we alternatively hypothesize that genetic factors underpin nicotine addiction directly, and the reduction in WM integrity occurs due to a multitude of harmful effects of chronic or heavy smoking. Lastly, we also test horizontal pleiotropy (Figure 1: model 0) where genetic factors affect both WM integrity and nicotine addiction independently. The proposed models are complementary to the widely used Mendelian randomization (MR) models that estimate the causal influence between the traits by relaxing the conditional independence assumption in instrumental variable (IV) analysis (Davey Smith and Hemani, 2014; Hemani et al., 2018a,b). We then develop rigorous analytical approaches to determine and validate the best causal model for pleiotropic genetic variants associated with both WM integrity and nicotine addiction.

We analyzed two smoking phenotypes for their biological relevance to nicotine dependence, smoking status (SS) and cigarettes per day (CPD), to test the proposed causal pathways in large-scale epidemiological data from the UK Biobank (UKBB). We used FA to measure WM integrity. Smoking (being current smoker or having higher CPD) was found to be associated with reduced WM integrity in multiple brain regions. Our data showed that the genetic effects on FA and the two smoking phenotypes were not independent, so the horizontal pleiotropy does not hold. Since model 1 and model 2 with a vertical pleiotropic relationship are two mutually exclusive causal pathways, we performed mediation analysis and used Bayes factor to select the optimal model. We identified 272 pleiotropic variants associated with both SS and FA whose effects on SS were mediated by FA (model 1 preferred). On the contrary, 22 pleiotropic variants were found to be associated with both CPD and FA, where CPD acts as a mediator for the genetic effects on FA (model 2 preferred). The identified variants mainly reside in two genes NCAM1 and IREB2. Their relationship to the smoking-induced brain mechanisms will need to be further examined for their functionality in future studies.

In this study, we used novel causative imaging genetics analyses to test neurogenetic mechanisms of nicotine dependence through altered WM integrity. We hypothesized and tested three pleiotropic models to explain the complex causal relationship among genetics, WM integrity, and nicotine dependence. Our GWAS on SS and CPD identified two different sets of associated genetic variants including many reported to be related to smoking in previous large-scale GWASs or meta-analyses (Hardin et al., 2012; Wain et al., 2015; Zeng et al., 2020). We also found smoking (being current smoker or having higher CPD) to be associated with lower WM integrity measured by FA in multiple brain regions. The causal pathway analysis identified 272 pleiotropic SNPs associated with FA in ALIC(R) and SS, and 22 pleiotropic SNPs associated with FA in ALIC(R) and PCR(L) and CPD. These SNPs are mainly located in genes NCAM1 and IREB2. NCAM1 was found to influence risk of nicotine addiction (Gelernter et al., 2006; Muskiewicz et al., 2018). IREB2, which regulates iron mechanism in the cell, was a susceptibility gene for both neurodegeneration and smoking-induced diseases (DeMeo et al., 2009; Cooper et al., 2019). Interestingly, these two sets of SNPs favored different vertical pleiotropic pathways: Gene → FA → SS vs. Gene → CPD → FA. The basic genetic components of addiction might have produced a pattern change in WM among smokers, reinforcing the addiction behavior. Chronic severe smoking (reflected in, e.g., CPD) will have negative impact to overall health, which in turn reduces the WM integrity.

We have used an imaging genetics approach to test the neurogenetic mechanisms. Traditional imaging genetics treat neuroimaging as the mediator of the genetic effect on behavior through a unidirectional model (Meyer-Lindenberg and Weinberger, 2006; Bogdan et al., 2017). We use novel causal mediation models to evaluate vertical and horizontal pleiotropy pathways, SNP → behavior → brain vs. SNP → brain → behavior vs. SNP → behavior and SNP → brain, in understanding the neurogenetic mechanism of nicotine addiction behavior. Constraint-based methods and score-based methods are two main categories of conventional causal discovery methods (Glymour et al., 2019). Constraint-based methods identified causal links by conducting conditional independence tests, while score-based methods selected the model with the optimal score from multiple candidate causal models (Spirtes and Zhang, 2016). Here, we proposed to perform conditional independence test to distinguish vertical pleiotropy from horizontal pleiotropy, and we used a BIC score-based method to select the optimal model with the larger score from the two competing vertical pleiotropic models represented by directed acyclic graph (DAG). Such hybrid approach exploited principled ways to combine advantages of both methods and was a computationally efficient strategy to learn the causal structure in a wide range of real-life applications (Wong et al., 2002; Tsamardinos et al., 2006; Scutari et al., 2018). In our data, such an approach indeed resulted in a DAG with higher likelihood values.

Vertical pleiotropy and horizontal pleiotropy are two competing types of pleiotropy in complex polygenic traits (Paaby and Rockman, 2013). Conventional MR framework treats pleiotropic genetic factors as IV to elucidate how one phenotype (modifiable exposure) causally relates to another phenotype (the outcome) (Davey Smith and Hemani, 2014), but it only considers the vertical pleiotropy with no direct causal link between SNP and outcome (known as exclusion restriction assumption) (Hemani et al., 2018a). We developed a model that evaluates both vertical and horizontal pleiotropy pathways simultaneously and used a rigorous likelihood-based approach to determine the optimal model. We found a significant direct effect of SNPs on the outcomes using our data, which violates the exclusion restriction assumption (Davey Smith and Hemani, 2014). Such extension from the MR framework to tolerate SNPs violating the exclusion restriction assumption of IV analysis has also been seen in recent genetic literature (Bowden et al., 2015; Verbanck et al., 2018). In addition, to establish causality, we also carefully checked the main causal mediation model assumptions of the optimal model.

The biophysical mechanisms that link smoking and lower WM integrity are unknown. Most studies in chronic and heavy smokers reported reduced FA values when compared with those in nonsmokers (Swan and Lessov-Schlaggar, 2007; Hudkins et al., 2010; Kim et al., 2010; Cullen et al., 2011; Gons et al., 2011; Liao et al., 2011; Zhang et al., 2011a, b). Absolute WM FA values are sensitive to many parameters including myelin content, intra-voxel axonal crossing, and axonal fiber density and diameter (Beaulieu, 2002). However, long-term changes in regional FA values were shown to be mainly (r > 0.8) driven by changes in regional cerebral myelin concentrations and myelin packing (Song et al., 2003, 2005; Madler et al., 2008). Our findings strongly implicate cerebral WM in the maintenance of this complex addiction and provide genetic targets for further analyses. This finding should encourage future research to examine how changes in WM integrity may or may not contribute to the overall nicotine effects on brain and cognition. Heavy chronic smoking increases the risk of the development of abnormalities in vascular endothelial morphology and function, which may cause cerebral perfusion leading to poorer neurocognition (Pittilo, 2000). Additionally, chronic smoking can impact the vasomotor reactivity/responsivity of the cerebrovascular through upregulation of Ca²⁺ channels and/or modulation of nitric oxide, resulting in the reduction of regional cerebral blood flow (Zubieta et al., 2001; Domino et al., 2004) and the development of WM disease (Liao et al., 1997; Ding et al., 2003; Jeerakathil et al., 2004).

Our study population consists of individuals with white ethnic background, and we pooled the UKBB data from different assessment sites and phases together in the analyses without considering the heterogeneity across sites and phases. Future studies are needed to evaluate the generalization of our conclusion to individuals from other races or ethnicities and to assess whether the conclusions are related to site and phase effects. Our study focused on the most significant variants from GWAS for the causal pathway analysis. Considering the high dimensionality of SNPs and the complex polygenic architecture of both smoking and WM integrity, SNPs with weak signals may not be identified. Further investigation in large independent cohorts is needed to validate current causal analysis results and provide a full picture of the complex genetic architecture of smoking and brain structure, which will in turn improve our understanding of the neurogenetic mechanism of nicotine addiction behavior.

The raw genetic and phenotypic data used in the current study are available from the UK Biobank (UKBB), which can be accessed via https://www.ukbiobank.ac.uk/.

ZY, CM, and SL performed the analysis and wrote the manuscript. TM, SC, and PK supervised the project and took the lead in editing the manuscript. KH, SG, YM, LH, PT, NJ, AA, HG, LS, and TN contributed to the manuscript writing and polishing. All authors provided critical feedback and helped to shape the research, analysis, and manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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