How phenotype and developmental stage affect the genes we find: GABRA2 and impulsivity

CONTEXT: The detection and replication of genes involved in psychiatric outcome has been notoriously difficult. Phenotypic measurement has been offered as one explanation, although most of this discussion has focused on problems with binary diagnoses. OBJECTIVE: This article focuses on two additional components of phenotypic measurement that deserve further consideration in evaluating genetic associations: (1) the measure used to reflect the outcome of interest, and (2) the developmental stage of the study population. We focus our discussion of these issues around the construct of impulsivity and externalizing disorders, and the association of these measures with a specific gene, GABRA2. DESIGN, SETTING, AND PARTICIPANTS: Data were analyzed from the Collaborative Study on the Genetics of Alcoholism Phase IV assessment of adolescents and young adults (ages 12–26; N = 2,128). MAIN OUTCOME MEASURES: Alcohol dependence, illicit drug dependence, childhood conduct disorder, and adult antisocial personality disorder symptoms were measured by psychiatric interview; Achenbach youth/adult self-report externalizing scale; Zuckerman Sensation-Seeking scale; Barratt Impulsivity scale; NEO extraversion and consciousness. RESULTS: GABRA2 was associated with subclinical levels of externalizing behavior as measured by the Achenbach in both the adolescent and young adult samples. Contrary to previous associations in adult samples, it was not associated with clinical-level DSM symptom counts of any externalizing disorders in these younger samples. There was also association with sensation-seeking and extraversion, but only in the adolescent sample. There was no association with the Barratt impulsivity scale or conscientiousness. CONCLUSIONS: Our results suggest that the pathway by which GABRA2 initially confers risk for eventual alcohol problems begins with a predisposition to sensation-seeking early in adolescence. The findings support the heterogeneous nature of impulsivity and demonstrate that both the measure used to assess a construct of interest and the age of the participants can have profound implications for the detection of genetic associations

Variants Located Upstream of CHRNB4 on Chromosome 15q25.1 Are Associated with Age at Onset of Daily Smoking and Habitual Smoking

Several genome-wide association and candidate gene studies have linked chromosome 15q24–q25.1 (a region including the CHRNA5-CHRNA3-CHRNB4 gene cluster) with alcohol dependence, nicotine dependence and smoking-related illnesses such as lung cancer and chronic obstructive pulmonary disease. To further examine the impact of these genes on the development of substance use disorders, we tested whether variants within and flanking theCHRNA5-CHRNA3-CHRNB4 gene cluster affect the transition to daily smoking (individuals who smoked cigarettes 4 or more days per week) in a cross sectional sample of adolescents and young adults from the COGA (Collaborative Study of the Genetics of Alcoholism) families. Subjects were recruited from families affected with alcoholism (either as a first or second degree relative) and the comparison families. Participants completed the SSAGA interview, a comprehensive assessment of alcohol and other substance use and related behaviors. Using the Quantitative trait disequilibrium test (QTDT) significant association was detected between age at onset of daily smoking and variants located upstream of CHRNB4. Multivariate analysis using a Cox proportional hazards model further revealed that these variants significantly predict the age at onset of habitual smoking among daily smokers. These variants were not in high linkage disequilibrium (0.28CHRNB4 with onset of chronic smoking behaviors in adolescents and young adults and may improve genetic information that will lead to better prevention and intervention for substance use disorders among adolescents and young adults

Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium

To provide insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing 4503 OD cases, 4173 opioid-exposed controls, and 32,500 opioid-unexposed controls, including participants of European and African descent (EUR and AFR, respectively). Among the variants identified, rs9291211 was associated with OE (exposed vs. unexposed controls; EUR z = -5.39, p = 7.2 × 10-8). This variant regulates the transcriptomic profiles of SLC30A9 and BEND4 in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N > 360,000) found association of this variant with propensity to use dietary supplements (p = 1.68 × 10-8). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (EUR + AFR z = 4.69, p = 10-6), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (AFR z = 5.55, p = 2.9 × 10-8) and a significant association with musculoskeletal disorders in the UK Biobank (p = 4.88 × 10-7). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (n = 466,571) was positively associated with OD (OD vs. unexposed controls, p = 8.1 × 10-5; OD cases vs. exposed controls, p = 0.054) and OE (exposed vs. unexposed controls, p = 3.6 × 10-5). A PRS based on a GWAS of neuroticism (n = 390,278) was positively associated with OD (OD vs. unexposed controls, p = 3.2 × 10-5; OD vs. exposed controls, p = 0.002) but not with OE (p = 0.67). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls in studies of addiction

Cox-proportional hazard analysis using age at onset of habitual smoking censored at non-habitual smokers.

1<p>Analysis was performed within family clusters using additive model. Age at interview in quartiles, gender, pc1, parental smoking and parental drinking were included as covariates.</p>2<p>Nominal P values are shown uncorrected for multiple testing. The Bonferroni-corrected significance threshold is P = 0.005.</p

Characteristics of study subjects who are daily smokers.

*<p>Indicates t test (two tailed) p = 0.0001.</p

Distribution of age at onset of daily smokers with reference to alleles of rs1996371.

*<p>Indicates t test (two tailed) p = 0.0002.</p