Multi-ancestral genome-wide association study of clinically defined nicotine dependence reveals strong genetic correlations with other substance use disorders and health-related traits.
Emma C. JohnsonDongbing LaiAlex P. MillerAlexander S. HatoumJoseph D. DeakJared V. BalbonaDavid A. A. BarangerMarco GalimbertiKittipong SanichwankulThorgeir E. ThorgeirssonSarah M. C. ColbertSandra Sanchez‐RoigeKeyrun AdhikariAnna R. DochertyLouisa DegenhardtTobias EdwardsLouis FoxAlexandros GiannelisPaul W. JeffriesTellervo KorhonenClaire L. MorrisonYaira Z. NuñezTeemu PalviainenMei‐Hsin SuPamela N. Romero VillelaLeah WetherillEmily A. WilloughbyStephanie ZellersLaura J. BierutJadwiga BuchwaldWilliam CopelandRobin CorleyNaomi P. FriedmanTatiana ForoudNathan A. GillespieIan R. GizerAndrew C. HeathIan B. HickieJaakko KaprioMatthew C. KellerJames LeePenelope A. LindPamela A. F. MaddenHermine HM MaesNicholas G. MartinMatt McGueSarah E. MedlandElliot C. NelsonJohn V. PearsonBernice PorjeszMichael C. StallingsScott VriezeKirk C. WilhelmsenRaymond K. WaltersRenato PolimantiRobert T. MalisonHang ZhouHreinn StefánssonMarc N. PotenzaApiwat MutiranguraVorasuk ShotelersukRasmon KalayasiriHoward J. EdenbergJoel GelernterArpana Agrawal
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ABSTRACT Genetic research on nicotine dependence has utilized multiple assessments that are in weak agreement. We conducted a genome-wide association study of nicotine dependence defined using the Diagnostic and Statistical Manual of Mental Disorders (DSM-NicDep) in 61,861 individuals (47,884 of European ancestry, 10,231 of African ancestry, 3,746 of East Asian ancestry) and compared the results to other nicotine-related phenotypes. We replicated the well-known association at the CHRNA5 locus (lead SNP: rs147144681, p =1.27E-11 in European ancestry; lead SNP = rs2036527, p = 6.49e-13 in cross-ancestry analysis). DSM-NicDep showed strong positive genetic correlations with cannabis use disorder, opioid use disorder, problematic alcohol use, lung cancer, material deprivation, and several psychiatric disorders, and negative correlations with respiratory function and educational attainment. A polygenic score of DSM-NicDep predicted DSM-5 tobacco use disorder and 6 of 11 individual diagnostic criteria, but none of the Fagerström Test for Nicotine Dependence (FTND) items, in the independent NESARC-III sample. In genomic structural equation models, DSM-NicDep loaded more strongly on a previously identified factor of general addiction liability than did a “problematic tobacco use” factor (a combination of cigarettes per day and nicotine dependence defined by the FTND). Finally, DSM-NicDep was strongly genetically correlated with a GWAS of tobacco use disorder as defined in electronic health records, suggesting that combining the wide availability of diagnostic EHR data with nuanced criterion-level analyses of DSM tobacco use disorder may produce new insights into the genetics of this disorder.Keywords:
Genome-wide Association Study
Nicotine dependence
Alcohol Dependence
Substance dependence
SNP
Genetic Association
Genome‐wide association studies (GWAS) are a popular approach for identifying common genetic variants and epistatic effects associated with a disease phenotype. The traditional statistical analysis of such GWAS attempts to assess the association between each individual single‐nucleotide polymorphism (SNP) and the observed phenotype. Recently, kernel machine‐based tests for association between a SNP set (e.g., SNPs in a gene) and the disease phenotype have been proposed as a useful alternative to the traditional individual‐SNP approach, and allow for flexible modeling of the potentially complicated joint SNP effects in a SNP set while adjusting for covariates. We extend the kernel machine framework to accommodate related subjects from multiple independent families, and provide a score‐based variance component test for assessing the association of a given SNP set with a continuous phenotype, while adjusting for additional covariates and accounting for within‐family correlation. We illustrate the proposed method using simulation studies and an application to genetic data from the Genetic Epidemiology Network of Arteriopathy (GENOA) study.
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Genome-wide association studies (GWAS) play a critical role in identifying many loci for common diseases and traits. There has been a rapid increase in the number of GWAS over the past decade. As additional GWAS are being conducted, it is unclear whether a novel signal associated with the trait of interest is independent of single nucleotide polymorphisms (SNPs) in the same region that has been previously associated with the trait of interest. The general approach to determining whether the novel association is independent of previous signals is to examine the association of the novel SNP with the trait of interest conditional on the previously identified SNP and/or calculate linkage disequilibrium (LD) between the two SNPs. However, the role of epistasis and SNP by SNP interactions are rarely considered. Through simulation studies, we examined the role of SNP by SNP interactions when determining the independence of two genetic association signals. We have created an R package on Github called gxgRC to generate these simulation studies based on user input. In genetic association studies of asthma, we considered the role of SNP by SNP interactions when determining independence of signals for SNPs in the ARG1 gene and bronchodilator response.
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ABSTRACT Aim To examine the pros and cons of using the same diagnostic criteria for dependence across all drugs versus using dependence criteria specific to the drug of interest. Methods A qualitative review of the similarities and differences in nicotine versus alcohol and opiate dependence is used as an example of the utility of using generic versus drug‐specific criteria. Results Many scientists implicitly recognize that nicotine dependence is different when they do not include nicotine dependence when studying ‘drug dependence’. Nicotine and alcohol/opiate dependence have many similarities (e.g. both can cause withdrawal). Among the several differences, the most important is that nicotine dependence does not cause acute behavioral impairment. Some of the generic dependence criteria do not apply to nicotine dependence (e.g. giving up activities to use the drug) and some well‐validated measures of nicotine dependence (e.g. time to first cigarette) are not included in the generic criteria. Conclusion Empirical tests of the relative utility of generic versus drug‐specific criteria are needed.
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Aim: Recent genome‐wide association studies (GWAS) of bipolar disorder (BD) have detected new candidate genes, including DGKH , DFNB31 and SORCS2 . However, the results of these GWAS were not necessarily consistent, indicating the importance of replication studies. In this study, we tested the genetic association of DGKH , DFNB31 and SORCS2 with BD. Methods: We genotyped 18 single‐nucleotide polymorphisms (SNP) in DGKH , DFNB31 and SORCS2 using Japanese samples (366 cases and 370 controls). We also performed a meta‐analysis of four SNP in DGKH , using the previously published allele frequency data of Han‐Chinese case–control samples (1139 cases and 1138 controls). Results: In the association analysis using Japanese samples, a SNP in SORCS2 (rs10937823) showed nominal genotypic association. However, we could not find any association in an additional analysis of tag SNP around rs10937823. In the meta‐analysis of SNP in DGKH , rs9315897, which was not significantly associated with BD in the previous Chinese study, showed nominal association. Conclusion: Although the association was not strong, the result of this study would support the association between DGKH and BD.
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Nicotine dependence
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Abstract Background It is well established that COMT is a strong candidate gene for substance use disorder and schizophrenia. Recently we identified two SNPs in COMT (rs4680 and rs165774) that are associated with schizophrenia in an Australian cohort. Individuals with schizophrenia were more than twice as likely to carry the GG genotype compared to the AA genotype for both the rs165774 and rs4680 SNPs. Association of both rs4680 and rs165774 with substance dependence, a common comorbidity of schizophrenia has not been investigated. Methods To determine whether COMT is important in substance dependence, rs165774 and rs4680 were genotyped and haplotyped in patients with nicotine, alcohol and opiate dependence. Results The rs165774 SNP was associated with alcohol dependence. However, it was not associated with nicotine or opiate dependence. Individuals with alcohol dependence were more than twice as likely to carry the GG or AG genotypes compared to the AA genotype, indicating a dominant mode of inheritance. The rs4680 SNP showed a weak association with alcohol dependence at the allele level that did not reach significance at the genotype level but it was not associated with nicotine or opiate dependence. Analysis of rs165774/rs4680 haplotypes also revealed association with alcohol dependence with the G/G haplotype being almost 1.5 times more common in alcohol-dependent cases. Conclusions Our study provides further support for the importance of the COMT in alcohol dependence in addition to schizophrenia. It is possible that the rs165774 SNP, in combination with rs4680, results in a common molecular variant of COMT that contributes to schizophrenia and alcohol dependence susceptibility. This is potentially important for future studies of comorbidity. As our participant numbers are limited our observations should be viewed with caution until they are independently replicated.
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Amyloid β protein (Aβ) ending at amino acid 40 (Aβ40) and 42 (Aβ42) accumulates in human brain with aging and as a defining pathological component in Alzheimer's disease (AD). Plasma Aβ has been suggested as a marker of AD susceptibility, diagnosis and treatment effects. Moreover, clear heritability of plasma Aβ levels has been shown in late onset AD pedigrees, supporting the importance of genes in plasma Aβ regulation. In our study we aim to identify genetic factors involved in the regulation of Aβ levels in human plasma. In this study we investigated 1282 individuals within the Uppsala Longitudinal Study of Adult Men (ULSAM). ELISA measurements of Aβ40 and Aβ42 were performed in more than 2400 plasma samples collected at the 70, 77 and 82 year follow-ups. In addition, over 1100 DNA samples from ULSAM participants have been genotyped for 3 118 SNP's in 370 candidate genes for common diseases. Using UNPHASED software we have performed association analysis between quantitative measures of Aβ and genetic variants. We have performed association analyses between SNP's and Aβ40 and Aβ42 levels at age 70, 77 and 82. We have also performed association analysis between SNP's and averaged Aβ40 and Aβ42 levels from two or three time points. Over 70 genes showed association with levels of Aβ40 or Aβ42 at individual time points. Average levels of Aβ40 were associated with polymorphisms in 16 genes and average levels of Aβ42 were associated with polymorphisms in 13 genes (p < 0.05). However, only six genes showed association with both Aβ40 and Aβ42. Interestingly, carriers of the known AD susceptibility gene APOE ϵ4 allele have lower Aβ40 and Aβ42 levels in plasma, as compared to individuals without the ϵ4 allele. These results support a genetic component to plasma amyloid beta protein levels that may also reflect AD risk.
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