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Polygenic risk scores for smoking: predictors for alcohol and cannabis use?

ABSTRACT: BACKGROUND AND AIMS:A strong correlation exists between smoking and the use of alcohol and cannabis. This paper uses polygenic risk scores to explore the possibility of overlapping genetic factors. Those scores reflect a combined effect of selected risk alleles for smoking. METHODS:Summary-level P-values were available for smoking initiation, age at onset of smoking, cigarettes per day and smoking cessation from the Tobacco and Genetics Consortium (n between 22,000 and 70,000 subjects). Using different P-value thresholds (0.1, 0.2 and 0.5) from the meta-analysis, sets of 'risk alleles' were defined and used to generate a polygenic risk score (weighted sum of the alleles) for each subject in an independent target sample from the Netherlands Twin Register (n?=?1583). The association between polygenic smoking scores and alcohol/cannabis use was investigated with regression analysis. RESULTS:The polygenic scores for 'cigarettes per day' were associated significantly with the number of glasses alcohol per week (P?=?0.005, R2 =?0.4-0.5%) and cannabis initiation (P?=?0.004, R2 =?0.6-0.9%). The polygenic scores for 'age at onset of smoking' were associated significantly with 'age at regular drinking' (P?=?0.001, R2 =?1.1-1.5%), while the scores for 'smoking initiation' and 'smoking cessation' did not significantly predict alcohol or cannabis use. CONCLUSIONS:Smoking, alcohol and cannabis use are influenced by aggregated genetic risk factors shared between these substances. The many common genetic variants each have a very small individual effect size.

SUBMITTER: Vink JM

PROVIDER: S-EPMC4048635 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Polygenic risk scores for smoking: predictors for alcohol and cannabis use?

Vink Jacqueline M JM Hottenga Jouke Jan JJ de Geus Eco J C EJ Willemsen Gonneke G Neale Michael C MC Furberg Helena H Boomsma Dorret I DI

Addiction (Abingdon, England) 20140318 7

<h4>Background and aims</h4>A strong correlation exists between smoking and the use of alcohol and cannabis. This paper uses polygenic risk scores to explore the possibility of overlapping genetic factors. Those scores reflect a combined effect of selected risk alleles for smoking.<h4>Methods</h4>Summary-level P-values were available for smoking initiation, age at onset of smoking, cigarettes per day and smoking cessation from the Tobacco and Genetics Consortium (n between 22,000 and 70,000 subj ...[more]

PMID: 24450588

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Project description:BackgroundEarly identification of individuals at high risk for alcohol use disorder (AUD) coupled with prompt interventions could reduce the incidence of AUD. In this study, we investigated whether Polygenic Risk Scores (PRS) can be used to evaluate the risk for AUD and AUD severity (as measured by the number of DSM-5 AUD diagnostic criteria met) and compared their performance with a measure of family history of AUD.MethodsWe studied individuals of European ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA). DSM-5 diagnostic criteria were available for 7203 individuals, of whom 3451 met criteria for DSM-IV alcohol dependence or DSM-5 AUD and 1616 were alcohol-exposed controls aged ≥21 years with no history of AUD or drug dependence. Further, 4842 individuals had a positive first-degree family history of AUD (FH+), 2722 had an unknown family history (FH?), and 336 had a negative family history (FH-). PRS were derived from a meta-analysis of a genome-wide association study of AUD from the Million Veteran Program and scores from the problem subscale of the Alcohol Use Disorders Identification Test in the UK Biobank. We used mixed models to test the association between PRS and risk for AUD and AUD severity.ResultsAUD cases had higher PRS than controls with PRS increasing as the number of DSM-5 diagnostic criteria increased (p-values ≤ 1.85E-05 ) in the full COGA sample, the FH+ subsample, and the FH? subsample. Individuals in the top decile of PRS had odds ratios (OR) for developing AUD of 1.96 (95% CI: 1.54 to 2.51, p-value = 7.57E-08 ) and 1.86 (95% CI: 1.35 to 2.56, p-value = 1.32E-04 ) in the full sample and the FH+ subsample, respectively. These values are comparable to previously reported ORs for a first-degree family history (1.91 to 2.38) estimated from national surveys. PRS were also significantly associated with the DSM-5 AUD diagnostic criterion count in the full sample, the FH+ subsample, and the FH? subsample (p-values ≤6.7E-11 ). PRS remained significantly associated with AUD and AUD severity after accounting for a family history of AUD (p-values ≤6.8E-10 ).ConclusionsBoth PRS and family history were associated with AUD and AUD severity, indicating that these risk measures assess distinct aspects of liability to AUD traits.

Project description:Patients with schizophrenia display characteristic smoking-related behaviors and genetic correlations between smoking behaviors and schizophrenia have been identified in European individuals. However, the genetic etiology of the association remains to be clarified. The present study investigated transethnic genetic overlaps between European-based smoking behaviors and the risk of Japanese schizophrenia by conducting polygenic risk score (PRS) analyses. Large-scale European genome-wide association study (GWAS) datasets (n = 24,114-74,035) related to four smoking-related intermediate phenotypes [(i) smoking initiation, (ii) age at smoking initiation, (iii) smoking quantity, and (iv) smoking cessation] were utilized as discovery samples. PRSs derived from these discovery GWASs were calculated for 332 Japanese subjects [schizophrenia patients, their unaffected first-degree relatives (FRs), and healthy controls (HCs)] as a target sample. Based on GWASs of European smoking phenotypes, we investigated the effects of PRSs on smoking phenotypes and the risk of schizophrenia in the Japanese population. Of the four smoking-related behaviors, the PRSs for age at smoking initiation in Europeans significantly predicted the age at smoking initiation (R2 = 0.049, p = 0.026) and the PRSs for smoking cessation significantly predicted the smoking cessation (R2 = 0.092, p = 0.027) in Japanese ever-smokers. Furthermore, the PRSs related to age at smoking initiation in Europeans were higher in Japanese schizophrenia patients than in the HCs and those of the FRs were intermediate between those of patients with schizophrenia and those of the HCs (R2 = 0.015, p = 0.015). In our target subjects, patients with schizophrenia had a higher mean age at smoking initiation (p = 0.018) and rate of daily smoking initiation after age 20 years (p = 0.023) compared with the HCs. A total of 60.6% of the patients started to smoke before the onset of schizophrenia. These findings suggest that genetic factors affecting late smoking initiation are associated with the risk of schizophrenia.

Project description:ImportanceMajor depressive disorder (MDD) and alcohol dependence (AD) are heritable disorders with significant public health burdens, and they are frequently comorbid. Common genetic factors that influence the co-occurrence of MDD and AD have been sought in family, twin, and adoption studies, and results to date have been promising but inconclusive.ObjectiveTo examine whether AD and MDD overlap genetically, using a polygenic score approach.Design, settings, and participantsAssociation analyses were conducted between MDD polygenic risk score (PRS) and AD case-control status in European ancestry samples from 4 independent genome-wide association study (GWAS) data sets: the Collaborative Study on the Genetics of Alcoholism (COGA); the Study of Addiction, Genetics, and Environment (SAGE); the Yale-Penn genetic study of substance dependence; and the National Health and Resilience in Veterans Study (NHRVS). Results from a meta-analysis of MDD (9240 patients with MDD and 9519 controls) from the Psychiatric Genomics Consortium were applied to calculate PRS at thresholds from P < .05 to P ≤ .99 in each AD GWAS data set.Main outcomes and measuresAssociation between MDD PRS and AD.ResultsParticipants analyzed included 788 cases (548 [69.5%] men; mean [SD] age, 38.2 [10.8] years) and 522 controls (151 [28.9.%] men; age [SD], 43.9 [11.6] years) from COGA; 631 cases (333 [52.8%] men; age [SD], 35.0 [7.7] years) and 756 controls (260 [34.4%] male; age [SD] 36.1 [7.7] years) from SAGE; 2135 cases (1375 [64.4%] men; age [SD], 39.4 [11.5] years) and 350 controls (126 [36.0%] men; age [SD], 43.5 [13.9] years) from Yale-Penn; and 317 cases (295 [93.1%] men; age [SD], 59.1 [13.1] years) and 1719 controls (1545 [89.9%] men; age [SD], 64.5 [13.3] years) from NHRVS. Higher MDD PRS was associated with a significantly increased risk of AD in all samples (COGA: best P = 1.7 × 10-6, R2 = 0.026; SAGE: best P = .001, R2 = 0.01; Yale-Penn: best P = .035, R2 = 0.0018; and NHRVS: best P = .004, R2 = 0.0074), with stronger evidence for association after meta-analysis of the 4 samples (best P = 3.3 × 10-9). In analyses adjusted for MDD status in 3 AD GWAS data sets, similar patterns of association were observed (COGA: best P = 7.6 × 10-6, R2 = 0.023; Yale-Penn: best P = .08, R2 = 0.0013; and NHRVS: best P = .006, R2 = 0.0072). After recalculating MDD PRS using MDD GWAS data sets without comorbid MDD-AD cases, significant evidence was observed for an association between the MDD PRS and AD in the meta-analysis of 3 GWAS AD samples without MDD cases (best P = .007).Conclusions and relevanceThese results suggest that shared genetic susceptibility contributes modestly to MDD and AD comorbidity. Individuals with elevated polygenic risk for MDD may also be at risk for AD.

Project description:BACKGROUND AND AIMS:Few studies have explored how polygenic propensity to cannabis use unfolds across development, and no studies have yet examined this question in the context of environmental contributions such as peer cannabis use. Outlining the factors that contribute to progression from cannabis initiation to problem use over time may ultimately provide insights into mechanisms for targeted interventions. We sought to examine the relationships between polygenic liability for cannabis use, cannabis use trajectories from ages 12-30 years and perceived peer cannabis use at ages 12-17 years. DESIGN:Mixed-effect logistic and linear regressions were used to examine associations between polygenic risk scores, cannabis use trajectory membership and perceived peer cannabis use. SETTING:United States. PARTICIPANTS:From the Collaborative Study on the Genetics of Alcoholism (COGA) study, a cohort of 1167 individuals aged 12-26 years at their baseline (i.e. first) interview. MEASUREMENTS:Key measurements included life-time cannabis use (yes/no), frequency of past 12-month cannabis use, maximum life-time frequency of cannabis use, cannabis use disorder (using DSM-5 criteria) and perceived peer cannabis use. Polygenic risk scores (PRS) were created using summary statistics from a large (n = 162?082) genome-wide association study (GWAS) of cannabis use. FINDINGS:Three trajectories reflecting no/low (n = 844), moderate (n = 137) and high (n = 186) use were identified. PRS were significantly associated with trajectory membership [P = 0.002-0.006, maximum conditional R2 = 1.4%, odds ratios (ORs) = 1.40-1.49]. Individuals who reported that most/all of their best friends used cannabis had significantly higher PRS than those who reported that none of their friends were users [OR = 1.35, 95% confidence interval (CI) = 1.04, 1.75, P = 0.023]. Perceived peer use itself explained up to 11.3% of the variance in trajectory class membership (OR = 1.50-4.65). When peer cannabis use and the cannabis use PRS were entered into the model simultaneously, both the PRS and peer use continued to be significantly associated with class membership (P < 0.01). CONCLUSIONS:Genetic propensity to cannabis use derived from heterogeneous samples appears to correlate with longitudinal increases in cannabis use frequency in young adults.

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Polygenic risk scores for smoking: predictors for alcohol and cannabis use?

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Polygenic risk scores for smoking: predictors for alcohol and cannabis use?

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