Exploratory Genome and Transcriptome-Wide Association Analyses of Addiction-Related Phenotypes in a Twin Cohort

Pleiotropic genetic architecture linking schizophrenia and substance use disorders

Genetic Basis of Tobacco Use Disorder

Tobacco use disorder (TUD) is a complex multifactorial condition resulting from the interplay between nicotine-induced neurobiological adaptations, behavioral and learning processes, environmental influences, and individual genetic susceptibility. Genetic research has progressively evolved from twin and family studies through candidate-gene approaches to large-scale genome-wide association studies (GWAS), substantially improving our understanding of the genetic architecture of tobacco use and nicotine dependence. This review summarizes the current evidence on the genetic basis of TUD, with particular emphasis on major biological pathways. We also discuss the limitations of early candidate-gene studies and the paradigm shift introduced by large GWAS and meta-analyses, and polygenic risk scores, which indicate that tobacco use and nicotine dependence have a highly polygenic and pleiotropic architecture. Finally, we review the potential clinical applications of genetic information in smoking-cessation treatment, while highlighting current limitations in clinical translation. In the future, it is clear that a multidisciplinary approach—combining genetics, clinical practice, and social sciences—will be necessary to transform tobacco use management into a precision-based model and reduce its impact on public health.

Genetic associations and candidate functional genes linking depression and obesity: a multi-omics integrative study

These findings provide a hypothesis-generating reframing of the traditional comorbidity model, suggesting that divergent molecular programs may converge on shared pathways and offer a preliminary foundation for exploring therapeutic strategies at the mood–metabolism interface.

Genome-Wide Association Studies and Deep-Learning Functional Annotation of Opioid Use Disorder across Three Ancestries in the All of Us Research Program

Genetic liability to addiction underlies comorbid bipolar and substance use disorders.

BACKGROUND Bipolar disorder (BIP) frequently co-occurs with heightened substance use (SU) and substance use disorders (SUDs). Although the strong co-occurrence of these heritable traits points to shared genetic susceptibility, the extent to which there are differences in how SU and SUD overlap with BIP genetic architecture remains unclear. METHODS We quantified the polygenic overlap between BIP and SUDs (alcohol, cannabis, opioid, and tobacco), and BIP and SU traits (drinks per week, lifetime cannabis use, prescription opioid use, and smoking initiation) using GWAS summary statistics and trivariate MiXeR. We then isolated the general and unique genetic contributions of SUD and SU using GWAS-by-subtraction via Genomic SEM. Next, we tested associations between polygenic risk scores derived from these latent factors and diagnostic and behavioral outcomes in the Norwegian Mother, Father and Child Cohort Study. Finally, we applied GSA-MiXeR to explore pleiotropic pathway enrichment shared between the latent factors and BIP. RESULTS We found extensive polygenic overlap between traits, with SUDs being more genetically correlated with BIP than SU traits. The unique SUD factor correlated positively with psychiatric disorders, whereas unique SU correlated negatively. PRS for BIP, shared SUD/SU, and unique SUD were significantly associated with BIP, SUD, and comorbid SUD-BIP; PRS for unique SU was only associated with self-reported lifetime SU. GSA-MiXeR revealed richer gene-set enrichment for SUD/BIP than SU/BIP implicating dopamine signaling and interneuron function. CONCLUSION By dissecting the genetic liability to SUD and SU and investigating their relationship with BIP we find a genetic signature correlated with substance dependence but not substance use more broadly.

An Initial Genetic Correlation Analysis of Externalizing Behavior and Neuroimaging Phenotypes in the ABCD Cohort

Although several associations reached nominal significance, none remained significant after correction for multiple comparisons and the precision of the estimates was constrained by the available imaging GWAS sample size, uncertainty in SNP-heritability estimates, and the large number of regional comparisons.