Multi-Polygenic Analysis of Nicotine Dependence in Individuals of European Ancestry

Author:

Risner Victoria A1,Benca-Bachman Chelsie E1,Bertin Lauren1,Smith Alicia K2,Kaprio Jaakko34,McGeary John E56,Chesler Elissa7,Knopik Valerie S8,Friedman Naomi P9,Palmer Rohan H C1ORCID

Affiliation:

1. Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, Atlanta, GA, USA

2. Smith Lab, Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta, GA, USA

3. Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland

4. Department of Public Health, University of Helsinki, Helsinki, Finland

5. Department of Psychiatry & Human Behavior, Brown University, Providence, RI, USA

6. The Genomic Laboratory, Providence VA Medical Center, Providence, RI, USA

7. The Jackson Laboratory, Bar Harbor, ME, USA

8. Department of Human Development and Family Studies, College of Health and Human Sciences, Purdue University, West Lafayette, IN, USA

9. Department of Psychology, University of Colorado at Boulder, Boulder, CO, USA

Abstract

Abstract Introduction Heritability estimates of nicotine dependence (ND) range from 40% to 70%, but discovery GWAS of ND are underpowered and have limited predictive utility. In this work, we leverage genetically correlated traits and diseases to increase the accuracy of polygenic risk prediction. Methods We employed a multi-trait model using summary statistic-based best linear unbiased predictors (SBLUP) of genetic correlates of DSM-IV diagnosis of ND in 6394 individuals of European Ancestry (prevalence = 45.3%, %female = 46.8%, µ age = 40.08 [s.d. = 10.43]) and 3061 individuals from a nationally-representative sample with Fagerström Test for Nicotine Dependence symptom count (FTND; 51.32% female, mean age = 28.9 [s.d. = 1.70]). Polygenic predictors were derived from GWASs known to be phenotypically and genetically correlated with ND (i.e., Cigarettes per Day [CPD], the Alcohol Use Disorders Identification Test [AUDIT-Consumption and AUDIT-Problems], Neuroticism, Depression, Schizophrenia, Educational Attainment, Body Mass Index [BMI], and Self-Perceived Risk-Taking); including Height as a negative control. Analyses controlled for age, gender, study site, and the first 10 ancestral principal components. Results The multi-trait model accounted for 3.6% of the total trait variance in DSM-IV ND. Educational Attainment (β = –0.125; 95% CI: [–0.149,–0.101]), CPD (0.071 [0.047,0.095]), and Self-Perceived Risk-Taking (0.051 [0.026,0.075]) were the most robust predictors. PGS effects on FTND were limited. Conclusions Risk for ND is not only polygenic, but also pleiotropic. Polygenic effects on ND that are accessible by these traits are limited in size and act additively to explain risk. Implications These findings enhance our understanding of inherited genetic factors for nicotine dependence. The data show that genome-wide association study (GWAS) findings across pre- and comorbid conditions of smoking are differentially associated with nicotine dependence and that when combined explain significantly more trait variance. These findings underscore the utility of multivariate approaches to understand the validity of polygenic scores for nicotine dependence, especially as the power of GWAS of broadly-defined smoking behaviors increases. Realizing the potential of GWAS to inform complex smoking behaviors will require similar theory-driven models that reflect the myriad of mechanisms that drive individual differences.

Funder

National Institute on Drug Abuse

Academy of Finland

National Institutes of Health

National Heart, Lung, and Blood Institute

Sandler Family Foundation

American Asthma Foundation

RWJF Amos Medical Faculty Development Program

Center for Inherited Disease Research

National Institute on Alcohol Abuse and Alcoholism

Genetics of Alcohol Dependence in American Populations

Publisher

Oxford University Press (OUP)

Subject

Public Health, Environmental and Occupational Health

Reference51 articles.

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