Studying the Utility of Using Genetics to Predict Smoking-Related Outcomes in a Population-Based Study and a Selected Cohort

Considerations for the application of polygenic scores to clinical care of individuals with substance use disorders

Substance use disorders (SUDs) are highly prevalent and associated with excess morbidity, mortality, and economic costs. Thus, there is considerable interest in the early identification of individuals who may be more susceptible to developing SUDs and in improving personalized treatment decisions for those who have SUDs. SUDs are known to be influenced by both genetic and environmental factors. Polygenic scores (PGSs) provide a single measure of genetic liability that could be used as a biomarker in predicting disease development, progression, and treatment response. Although PGSs are rapidly being integrated into clinical practice, there is little information to guide clinicians in their responsible use and interpretation. In this Review, we discuss the potential benefits and pitfalls of the use of PGSs in the clinical care of SUDs, highlighting current research. We also provide suggestions for important considerations prior to implementing the clinical use of PGSs and recommend future directions for research.

Polygenic risk scores for nicotine use and family history of smoking are associated with smoking behaviour

INTRODUCTION

Formal genetics studies show that smoking is influenced by genetic factors; exploring this on the molecular level can offer deeper insight into the etiology of smoking behaviours.

METHODS

Summary statistics from the latest wave of the GWAS and Sequencing Consortium of Alcohol and Nicotine (GSCAN) were used to calculate polygenic risk scores (PRS) in a sample of ~2200 individuals who smoke/individuals who never smoked. The associations of smoking status with PRS for Smoking Initiation (i.e., Lifetime Smoking; SI-PRS), and Fagerström Test for Nicotine Dependence (FTND) score with PRS for Cigarettes per Day (CpD-PRS) were examined, as were distinct/additive effects of parental smoking on smoking status.

RESULTS

SI-PRS explained 10.56% of variance (Nagelkerke-R2) in smoking status (p=6.45x10-30). In individuals who smoke, CpD-PRS was associated with FTND score (R2=5.03%, p=1.88x10-12). Parental smoking alone explained R2=3.06% (p=2.43×10-12) of smoking status, and 0.96% when added to the most informative SI-PRS model (total R²=11.52%).

CONCLUSION

These results show the potential utility of molecular genetic data for research investigating smoking prevention. The fact that PRS explains more variance than family history highlights progress from formal to molecular genetics; the partial overlap and increased predictive value when using both suggests the importance of combining these approaches.

How has the brain disease model of addiction contributed to tobacco control?

Our paper evaluates the extent to which the brain disease model of addiction (BDMA) has contributed to reducing the prevalence of tobacco smoking and  tobacco-related harm over the past 20 years. We discuss the ways in which genetic and neuroscience research on nicotine addiction have contributed to our understanding of tobacco smoking. We then examine the extent to which the BDMA has produced more effective treatments to assist smoking cessation. We also assess the degree to which the BDMA has contributed to the tobacco control policies that have produced substantial reductions in tobacco-related morbidity and mortality in the two decades since the model was first proposed by Alan Leshner. We also assess whether the BDMA has reduced the stigmatisation of people who smoke tobacco.

Associations of polygenic risk scores for smoking heaviness and lifetime cannabis use with tobacco and cannabis co-use trajectories among African Americans

BACKGROUND

We aimed to identify distinct trajectories of tobacco, cannabis, and their co-use among African Americans, and to investigate whether these patterns were associated with polygenic risk scores (PRS) for tobacco and cannabis use.

METHOD

Participants (N=428 participants; 50.9% male) were initially recruited for an elementary school-based prevention in a Mid-Atlantic city when they were in first grade. From ages 14-26, participants reported on their frequency of tobacco and cannabis use in the past year during annual assessments. DNA was collected from participants at age 21. PRS for smoking heaviness (i.e., cigarettes per day) and lifetime cannabis use were created based on genome-wide association study results derived from Liu et al. (2019) and Pasman et al. (2018), respectively.

RESULTS

We identified five distinct trajectories of tobacco and cannabis co-use, including (1) Low Tobacco and Cannabis Use, (2) Adolescent Limited Tobacco and Cannabis Use, (3) Experimental Cannabis, Young Adult Increasing Tobacco, (4) Experimental Tobacco, Young Adult Increasing Cannabis, and (5) High, Chronic Tobacco and Cannabis Use. Compared to the Low Tobacco and Cannabis Use subgroup, individuals in the High, Chronic Tobacco and Cannabis Use subgroup had greater PRS for smoking heaviness, and individuals in the Experimental Cannabis, Young Adult Increasing Tobacco subgroup had higher PRS for lifetime cannabis use.

CONCLUSIONS

Polygenic risk for lifetime cannabis use and smoking heaviness is associated with the developmental progression of tobacco and cannabis co-use among African Americans, furthering knowledge on the etiology of co-use in this population.

Smoking cessation, harm reduction, and biomarkers protocols in the PhenX Toolkit: Tools for standardized data collection

The use of standard protocols in studies supports consistent data collection, improves data quality, and facilitates cross-study analyses. Funded by the National Institutes of Health, the PhenX (consensus measures for Phenotypes and eXposures) Toolkit is a catalog of recommended measurement protocols that address a wide range of research topics and are suitable for inclusion in a variety of study designs. In 2020, a PhenX Working Group of smoking cessation experts followed a well-established consensus process to identify and recommend measurement protocols suitable for inclusion in smoking cessation and smoking harm reduction studies. The broader scientific community was invited to review and provide feedback on the preliminary recommendation of the Working Group. Fourteen selected protocols for measuring smoking cessation, harm reduction, and biomarkers research associated with smoking cessation were released in the PhenX Toolkit ( https://www.phenxtoolkit.org) in February 2021. These protocols complement existing PhenX Toolkit content related to tobacco regulatory research, substance use and addiction research, and other measures of smoking-related health outcomes. Adopting well-established protocols enables consistent data collection and facilitates comparing and combining data across studies, potentially increasing the scientific impact of individual studies.

Drinking and smoking polygenic risk is associated with childhood and early-adulthood psychiatric and behavioral traits independently of substance use and psychiatric genetic risk

Alcohol drinking and tobacco smoking are hazardous behaviors associated with a wide range of adverse health outcomes. In this study, we explored the association of polygenic risk scores (PRS) related to drinks per week, age of smoking initiation, smoking initiation, cigarettes per day, and smoking cessation with 433 psychiatric and behavioral traits in 4498 children and young adults (aged 8-21) of European ancestry from the Philadelphia neurodevelopmental cohort. After applying a false discovery rate multiple testing correction accounting for the number of PRS and traits tested, we identified 36 associations related to psychotic symptoms, emotion and age recognition social competencies, verbal reasoning, anxiety-related traits, parents' education, and substance use. These associations were independent of the genetic correlations among the alcohol-drinking and tobacco-smoking traits and those with cognitive performance, educational attainment, risk-taking behaviors, and psychopathology. The removal of participants endorsing substance use did not affect the associations of each PRS with psychiatric and behavioral traits identified as significant in the discovery analyses. Gene-ontology enrichment analyses identified several neurobiological processes underlying mechanisms of the PRS associations we report. In conclusion, we provide novel insights into the genetic overlap of smoking and drinking behaviors in children and young adults, highlighting their independence from psychopathology and substance use.