Nicotine addiction, like many other forms of addiction, is a multifaceted behavior influenced by both genetic and environmental factors. Despite the well-established role of these influences, relatively few studies have simultaneously examined the interaction between genetic predispositions and environmental variables in the context of substance addiction. This study investigated the role of specific genetic variants within nicotinic acetylcholine receptor (nAChR) and cytochrome P450 genes in relation to nicotine and other substance addictions, as well as environmental factors. From a total of 66,936 genetic variants, a Polygenic Risk Score (PRS) was computed using selected SNPs within the nAChR and cytochrome gene families. Structural Equation Modeling (SEM) was employed to examine the relationships between PRS, the Wisconsin Index of Smoking Dependence Motives (WISDM), socioeconomic status (SES), and various forms of substance addiction, using a dataset comprising 2969 individuals (1786 females, 1168 males). The results demonstrate that substance addiction is shaped by a complex interplay of genetic, environmental, and psychological factors. The PRS significantly predicted the Fagerström Test for Nicotine Dependence (FTND) and DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) based nicotine dependence. PRS had smaller, yet significant, effects on alcohol and marijuana dependence and WISDM. However, it showed no meaningful relationship with SES or other addictions. In contrast, SES strongly influenced smoking motives (WISDM), which in turn significantly predicted multiple types of substance addiction, positioning WISDM as a key mediator. Additionally, alcohol dependence emerged as a central factor, showing cascading effects on nicotine, marijuana, and cocaine addiction. Overall, while genetic predisposition plays a notable role, especially in nicotine-related outcomes, social context and motivational factors exert broader and more substantial effects across various addiction pathways, underscoring the need for multifaceted intervention strategies.
Keywords: nicotine addiction; polygenic risk score; socio‐economic status; structural equation modeling; substance addiction.
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