Developmental perspective on the role of genes in smoking risk

Genetic influences impacting nicotine use and abuse during adolescence: Insights from human and rodent studies

Nicotine use continues to be a major public health concern, with an alarming recent rise in electronic cigarette consumption. Heritability estimates of nicotine use and abuse range from 40% to 80%, providing strong evidence that genetic factors impact nicotine addiction-relevant phenotypes. Although nicotine use during adolescence is a key factor in the development of addiction, it remains unclear how genetic factors impact adolescent nicotine use and abuse. This review will discuss studies investigating genetic factors impacting nicotine use during adolescence. Evidence from both rodent and human studies will be summarized and integrated when possible. Human adolescent studies have largely included candidate gene studies for genes identified in adult populations, such as genes involved in nicotine metabolism, nicotinic acetylcholine receptor signaling, dopaminergic signaling, and other neurotransmitter signaling systems. Alternatively, rodent studies have largely taken a discovery-based approach identifying strain differences in adolescent nicotine addiction-relevant behaviors. Here, we aim to answer the following three questions by integrating human and rodent findings: (1) Are there genetic variants that uniquely impact nicotine use during adolescence? (2) Are there genetic variants that impact both adolescent and adult nicotine use? and (3) Do genetic factors in adolescence significantly impact long-term consequences of adolescent nicotine use? Determining answers for these three questions will be critical for the development of preventative measures and treatments for adolescent nicotine use and addiction.

Genetics in population health science: strategies and opportunities

Translational research is needed to leverage discoveries from the frontiers of genome science to improve public health. So far, public health researchers have largely ignored genetic discoveries, and geneticists have ignored important aspects of population health science. This mutual neglect should end. In this article, we discuss 3 areas where public health researchers can help to advance translation: (1) risk assessment: investigate genetic profiles as components in composite risk assessments; (2) targeted intervention: conduct life-course longitudinal studies to understand when genetic risks manifest in development and whether intervention during sensitive periods can have lasting effects; and (3) improved understanding of environmental causation: collaborate with geneticists on gene-environment interaction research. We illustrate with examples from our own research on obesity and smoking.

Polygenic risk and the developmental progression to heavy, persistent smoking and nicotine dependence: evidence from a 4-decade longitudinal study

IMPORTANCE

Genome-wide hypothesis-free discovery methods have identified loci that are associated with heavy smoking in adulthood. Research is needed to understand developmental processes that link newly discovered genetic risks with adult heavy smoking.

OBJECTIVE

To test how genetic risks discovered in genome-wide association studies of adult smoking influence the developmental progression of smoking behavior from initiation through conversion to daily smoking, progression to heavy smoking, nicotine dependence, and struggles with cessation.

DESIGN

A 38-year, prospective, longitudinal study of a representative birth cohort.

SETTING

The Dunedin Multidisciplinary Health and Development Study of New Zealand.

PARTICIPANTS

The study included 1037 male and female participants.

EXPOSURE

We assessed genetic risk with a multilocus genetic risk score. The genetic risk score was composed of single-nucleotide polymorphisms identified in 3 meta-analyses of genome-wide association studies of smoking quantity phenotypes.

MAIN OUTCOMES AND MEASURES

Smoking initiation, conversion to daily smoking, progression to heavy smoking, nicotine dependence (Fagerström Test of Nicotine Dependence), and cessation difficulties were evaluated at 8 assessments spanning the ages of 11 to 38 years.

RESULTS

Genetic risk score was unrelated to smoking initiation. However, individuals at higher genetic risk were more likely to convert to daily smoking as teenagers, progressed more rapidly from smoking initiation to heavy smoking, persisted longer in smoking heavily, developed nicotine dependence more frequently, were more reliant on smoking to cope with stress, and were more likely to fail in their cessation attempts. Further analysis revealed that 2 adolescent developmental phenotypes-early conversion to daily smoking and rapid progression to heavy smoking-mediated associations between the genetic risk score and mature phenotypes of persistent heavy smoking, nicotine dependence, and cessation failure. The genetic risk score predicted smoking risk over and above family history.

CONCLUSIONS AND RELEVANCE

Initiatives that disrupt the developmental progression of smoking behavior among adolescents may mitigate genetic risks for developing adult smoking problems. Future genetic research may maximize discovery potential by focusing on smoking behavior soon after smoking initiation and by studying young smokers.

ANKK1, TTC12, and NCAM1 polymorphisms and heroin dependence: importance of considering drug exposure

CONTEXT

The genetic contribution to liability for opioid dependence is well established; identification of the responsible genes has proved challenging.

OBJECTIVE

To examine association of 1430 candidate gene single-nucleotide polymorphisms (SNPs) with heroin dependence, reporting here only the 71 SNPs in the chromosome 11 gene cluster (NCAM1, TTC12, ANKK1, DRD2) that include the strongest observed associations.

DESIGN

Case-control genetic association study that included 2 control groups (lacking an established optimal control group).

SETTING

Semistructured psychiatric interviews.

PARTICIPANTS

A total of 1459 Australian cases ascertained from opioid replacement therapy clinics, 531 neighborhood controls ascertained from economically disadvantaged areas near opioid replacement therapy clinics, and 1495 unrelated Australian Twin Registry controls not dependent on alcohol or illicit drugs selected from a twin and family sample.

MAIN OUTCOME MEASURE

Lifetime heroin dependence.

RESULTS

Comparison of cases with Australian Twin Registry controls found minimal evidence of association for all chromosome 11 cluster SNPs (P ≥ .01); a similar comparison with neighborhood controls revealed greater differences (P ≥ 1.8 × 10(-4)). Comparing cases (n = 1459) with the subgroup of neighborhood controls not dependent on illicit drugs (n = 340), 3 SNPs were significantly associated (correcting for multiple testing): ANKK1 SNP rs877138 (most strongly associated; odds ratio = 1.59; 95% CI, 1.32-1.92; P = 9.7 × 10(-7)), ANKK1 SNP rs4938013, and TTC12 SNP rs7130431. A similar pattern of association was observed when comparing illicit drug-dependent (n = 191) and nondependent (n = 340) neighborhood controls, suggesting that liability likely extends to nonopioid illicit drug dependence. Aggregate heroin dependence risk associated with 2 SNPs, rs877138 and rs4492854 (located in NCAM1), varied more than 4-fold (P = 2.7 × 10(-9) for the risk-associated linear trend).

CONCLUSIONS

Our results provide further evidence of association for chromosome 11 gene cluster SNPs with substance dependence, including extension of liability to illicit drug dependence. Our findings highlight the necessity of considering drug exposure history when selecting control groups for genetic investigations of illicit drug dependence.