Introduction to deep sequencing and its application to drug addiction research with a focus on rare variants

Bayesian linear mixed model with multiple random effects for family-based genetic studies

Motivation: Family-based study design is one of the popular designs used in genetic research, and the whole-genome sequencing data obtained from family-based studies offer many unique features for risk prediction studies. They can not only provide a more comprehensive view of many complex diseases, but also utilize information in the design to further improve the prediction accuracy. While promising, existing analytical methods often ignore the information embedded in the study design and overlook the predictive effects of rare variants, leading to a prediction model with sub-optimal performance. Results: We proposed a Bayesian linear mixed model for the prediction analysis of sequencing data obtained from family-based studies. Our method can not only capture predictive effects from both common and rare variants, but also easily accommodate various disease model assumptions. It uses information embedded in the study design to form surrogates, where the predictive effects from unmeasured/unknown genetic and environmental risk factors can be modelled. Through extensive simulation studies and the analysis of sequencing data obtained from the Michigan State University Twin Registry study, we have demonstrated that the proposed method outperforms commonly adopted techniques. Availability: R package is available at https://github.com/yhai943/FBLMM.

Whole-Exome Sequencing to Identify Potential Genetic Risk in Substance Use Disorders: A Pilot Feasibility Study

Genetics intersects with environmental, cultural, and social factors in the development of addictive disorders. This study reports the feasibility of whole-exome sequencing of trios (subject and two family members) to discover potential genetic variants in the development of substance use disorders (SUD). Family trios were recruited from the National Addictions Management Service in Singapore during the 2016–2018 period. Recruited subjects had severe alcohol use disorder (AUD) or opioid use disorder (OUD), with nicotine dependence (ND) and a family history of addictive disorders. Demographic characteristics and severity of addiction were captured. Whole-exome sequencing (WES) and analysis were performed on salivary samples collected from the trios. WES revealed variants in several genes in each individual and disruptive protein mutations in most. Variants were identified in genes previously associated with SUDs, such as Pleckstrin homology domain-containing family M member 3 (PLEKHM3), coiled-coil serine-rich protein 1 (CCSER1), LIM and calponin homology domains-containing protein 1 (LIMCH1), dynein axonemal heavy chain 8 (DNAH8), and the taste receptor type 2 member 38 (TAS2R38) involved in the perception of bitterness. The feasibility study suggests that subjects with a severe addiction profile, polysubstance use, and family history of addiction may often harbor gene variants that may predispose them to SUDs. This study could serve as a model for future precision medicine-based personalized interventional strategies for behavioral addictions and SUDs and for the discovery of potentially pathogenic genetic variants.

Hemizygous Deletion on Chromosome 3p26.1 Is Associated with Heavy Smoking among African American Subjects in the COPDGene Study

Many well-powered genome-wide association studies have identified genetic determinants of self-reported smoking behaviors and measures of nicotine dependence, but most have not considered the role of structural variants, such as copy number variation (CNVs), influencing these phenotypes. Here, we included 2,889 African American and 6,187 non-Hispanic White subjects from the COPDGene cohort (http://www.copdgene.org) to carefully investigate the role of polymorphic CNVs across the genome on various measures of smoking behavior. We identified a CNV component (a hemizygous deletion) on chromosome 3p26.1 associated with two quantitative phenotypes related to smoking behavior among African Americans. This polymorphic hemizygous deletion is significantly associated with pack-years and cigarettes smoked per day among African American subjects in the COPDGene study. We sought evidence of replication in African Americans from the population based Atherosclerosis Risk in Communities (ARIC) study. While we observed similar CNV counts, the extent of exposure to cigarette smoking among ARIC subjects was quite different and the smaller sample size of heavy smokers in ARIC severely limited statistical power, so we were unable to replicate our findings from the COPDGene cohort. But meta-analyses of COPDGene and ARIC study subjects strengthened our association signal. However, a few linkage studies have reported suggestive linkage to the 3p26.1 region, and a few genome-wide association studies (GWAS) have reported markers in the gene (GRM7) nearest to this 3p26.1 area of polymorphic deletions are associated with measures of nicotine dependence among subjects of European ancestry.

The contribution of rare and common variants in 30 genes to risk nicotine dependence

Genetic and functional studies have revealed that both common and rare variants of several nicotinic acetylcholine receptor subunits are associated with nicotine dependence (ND). In this study, we identified variants in 30 candidate genes including nicotinic receptors in 200 sib pairs selected from the Mid-South Tobacco Family population with equal numbers of African Americans (AAs) and European Americans (EAs). We selected 135 of the rare and common variants and genotyped them in the Mid-South Tobacco Case-Control (MSTCC) population, which consists of 3088 AAs and 1430 EAs. None of the genotyped common variants showed significant association with smoking status (smokers vs non-smokers), Fagerström Test for ND scores or indexed cigarettes per day after Bonferroni correction. Rare variants in NRXN1, CHRNA9, CHRNA2, NTRK2, GABBR2, GRIN3A, DNM1, NRXN2, NRXN3 and ARRB2 were significantly associated with smoking status in the MSTCC AA sample, with weighted sum statistic (WSS) P-values ranging from 2.42 × 10(-3) to 1.31 × 10(-4) after 10(6) phenotype rearrangements. We also observed a significant excess of rare nonsynonymous variants exclusive to EA smokers in NRXN1, CHRNA9, TAS2R38, GRIN3A, DBH, ANKK1/DRD2, NRXN3 and CDH13 with WSS P-values between 3.5 × 10(-5) and 1 × 10(-6). Variants rs142807401 (A432T) and rs139982841 (A452V) in CHRNA9 and variants V132L, V389L, rs34755188 (R480H) and rs75981117 (N549S) in GRIN3A are of particular interest because they are found in both the AA and EA samples. A significant aggregate contribution of rare and common coding variants in CHRNA9 to the risk for ND (SKAT-C: P=0.0012) was detected by applying the combined sum test in MSTCC EAs. Together, our results indicate that rare variants alone or combined with common variants in a subset of 30 biological candidate genes contribute substantially to the risk of ND.

Common single nucleotide variants underlying drug addiction: more than a decade of research

Drug-related phenotypes are common complex and highly heritable traits. In the last few years, candidate gene (CGAS) and genome-wide association studies (GWAS) have identified a huge number of single nucleotide polymorphisms (SNPs) associated with drug use, abuse or dependence, mainly related to alcohol or nicotine. Nevertheless, few of these associations have been replicated in independent studies. The aim of this study was to provide a review of the SNPs that have been most significantly associated with alcohol-, nicotine-, cannabis- and cocaine-related phenotypes in humans between the years of 2000 and 2012. To this end, we selected CGAS, GWAS, family-based association and case-only studies published in peer-reviewed international scientific journals (using the PubMed/MEDLINE and Addiction GWAS Resource databases) in which a significant association was reported. A total of 371 studies fit the search criteria. We then filtered SNPs with at least one replication study and performed meta-analysis of the significance of the associations. SNPs in the alcohol metabolizing genes, in the cholinergic gene cluster CHRNA5-CHRNA3-CHRNB4, and in the DRD2 and ANNK1 genes, are, to date, the most replicated and significant gene variants associated with alcohol- and nicotine-related phenotypes. In the case of cannabis and cocaine, a far fewer number of studies and replications have been reported, indicating either a need for further investigation or that the genetics of cannabis/cocaine addiction are more elusive. This review brings a global state-of-the-art vision of the behavioral genetics of addiction and collaborates on formulation of new hypothesis to guide future work.

The Genetics, Neurogenetics and Pharmacogenetics of Addiction

Addictions are prevalent psychiatric disorders that confer remarkable personal and social burden. Despite substantial evidence for their moderate, yet robust, heritability (approx. 50%), specific genetic mechanisms underlying their development and maintenance remain unclear. The goal of this selective review is to highlight progress in unveiling the genetic underpinnings of addiction. First, we revisit the basis for heritable variation in addiction before reviewing the most replicable candidate gene findings and emerging signals from genomewide association studies for alcohol, nicotine and cannabis addictions. Second, we survey the modest but growing field of neurogenetics examining how genetic variation influences corticostriatal structure, function, and connectivity to identify neural mechanisms that may underlie associations between genetic variation and addiction. Third, we outline how extant genomic findings are being used to develop and refine pharmacotherapies. Finally, as sample sizes for genetically informed studies of addiction approach critical mass, we posit five exciting possibilities that may propel further discovery (improved phenotyping, rare variant discovery, gene-environment interplay, epigenetics, and novel neuroimaging designs).