Introduction to Deep Sequencing and Its Application to Drug Addiction Research with a Focus on Rare Variants

Through linkage analysis, candidate gene approach, and genome-wide association studies (GWAS), many genetic susceptibility factors for substance dependence have been discovered such as the alcohol dehydrogenase gene (ALDH2) for alcohol dependence (AD) and nicotinic acetylcholine receptor (nAChR) subunit variants on chromosomes 8 and 15 for nicotine dependence (ND). However, these confirmed genetic factors contribute only a small portion of the heritability responsible for each addiction. Among many potential factors, rare variants in those identified and unidentified susceptibility genes are supposed to contribute greatly to the missing heritability. Several studies focusing on rare variants have been conducted by taking advantage of next-generation sequencing technologies, which revealed that some rare variants of nAChR subunits are associated with ND in both genetic and functional studies. However, these studies investigated variants for only a small number of genes and need to be expanded to broad regions/genes in a larger population. This review presents an update on recently developed methods for rare-variant identification and association analysis and on studies focused on rare-variant discovery and function related to addictions.     

Substance abuse vulnerability loci: converging genome scanning data

Classical genetic studies suggest strong complex genetic contributions to a predisposition to abuse multiple addictive substances. Until recently, there were no reproducible genome scanning data identifying chromosomal positions likely to contain allelic variants that predispose the carrier to illegal substance addiction. Nominal results of linkage-based genome scanning studies for ethanol and nicotine addictions failed to display much agreement. Our recent data from association-based genome scans for illegal addictions, and reanalyses of previous results now provide a substantial body of converging results. The 15 reproducible chromosomal loci identified here are good candidates to harbor allelic variants that alter human substance abuse vulnerabilities. We discuss several approaches to identifying the specific gene variants that underlie these convergent association and linkage observations, and the impact that these convergent observations should have on understanding important human addictive disorders.     

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 the CHRNA5-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 (0.28相似文献   

Association and interaction analyses of 5-HT3 receptor and serotonin transporter genes with alcohol,cocaine, and nicotine dependence using the SAGE data

Previous studies have implicated genes encoding the 5-HT3_AB receptors (HTR3A and HTR3B) and the serotonin transporter (SLC6A4), both independently and interactively, in alcohol (AD), cocaine (CD), and nicotine dependence (ND). However, whether these genetic effects also exist in subjects with comorbidities remains largely unknown. We used 1,136 African-American (AA) and 2,428 European-American (EA) subjects from the Study of Addiction: Genetics and Environment (SAGE) to determine associations between 88 genotyped or imputed variants within HTR3A, HTR3B, and SLC6A4 and three types of addictions, which were measured by DSM-IV diagnoses of AD, CD, and ND and the Fagerström Test for Nicotine Dependence (FTND), an independent measure of ND commonly used in tobacco research. Individual SNP-based association analysis revealed a significant association of rs2066713 in SLC6A4 with FTND in AA (β = ?1.39; P = 1.6E ? 04). Haplotype-based association analysis found one major haplotype formed by SNPs rs3891484 and rs3758987 in HTR3B that was significantly associated with AD in the AA sample, and another major haplotype T–T-G, formed by SNPs rs7118530, rs12221649, and rs2085421 in HTR3A, which showed significant association with FTND in the EA sample. Considering the biologic roles of the three genes and their functional relations, we used the GPU-based Generalized Multifactor Dimensionality Reduction (GMDR-GPU) program to test SNP-by-SNP interactions within the three genes and discovered two- to five-variant models that have significant impacts on AD, CD, ND, or FTND. Interestingly, most of the SNPs included in the genetic interaction model(s) for each addictive phenotype are either overlapped or in high linkage disequilibrium for both AA and EA samples, suggesting these detected variants in HTR3A, HTR3B, and SLC6A4 are interactively contributing to etiology of the three addictive phenotypes examined in this study.     

Whole Exome Sequencing of Distant Relatives in Multiplex Families Implicates Rare Variants in Candidate Genes for Oral Clefts

A dozen genes/regions have been confirmed as genetic risk factors for oral clefts in human association and linkage studies, and animal models argue even more genes may be involved. Genomic sequencing studies should identify specific causal variants and may reveal additional genes as influencing risk to oral clefts, which have a complex and heterogeneous etiology. We conducted a whole exome sequencing (WES) study to search for potentially causal variants using affected relatives drawn from multiplex cleft families. Two or three affected second, third, and higher degree relatives from 55 multiplex families were sequenced. We examined rare single nucleotide variants (SNVs) shared by affected relatives in 348 recognized candidate genes. Exact probabilities that affected relatives would share these rare variants were calculated, given pedigree structures, and corrected for the number of variants tested. Five novel and potentially damaging SNVs shared by affected distant relatives were found and confirmed by Sanger sequencing. One damaging SNV in CDH1, shared by three affected second cousins from a single family, attained statistical significance (P = 0.02 after correcting for multiple tests). Family-based designs such as the one used in this WES study offer important advantages for identifying genes likely to be causing complex and heterogeneous disorders.     

Gene-centric genomewide association study via entropy

Genes are the functional units in most organisms. Compared to genetic variants located outside genes, genic variants are more likely to affect disease risk. The development of the human HapMap project provides an unprecedented opportunity for genetic association studies at the genomewide level for elucidating disease etiology. Currently, most association studies at the single-nucleotide polymorphism (SNP) or the haplotype level rely on the linkage information between SNP markers and disease variants, with which association findings are difficult to replicate. Moreover, variants in genes might not be sufficiently covered by currently available methods. In this article, we present a gene-centric approach via entropy statistics for a genomewide association study to identify disease genes. The new entropy-based approach considers genic variants within one gene simultaneously and is developed on the basis of a joint genotype distribution among genetic variants for an association test. A grouping algorithm based on a penalized entropy measure is proposed to reduce the dimension of the test statistic. Type I error rates and power of the entropy test are evaluated through extensive simulation studies. The results indicate that the entropy test has stable power under different disease models with a reasonable sample size. Compared to single SNP-based analysis, the gene-centric approach has greater power, especially when there is more than one disease variant in a gene. As the genomewide genic SNPs become available, our entropy-based gene-centric approach would provide a robust and computationally efficient way for gene-based genomewide association study.     

Genetics of schizophrenia: advances in the study of candidate genes

Schizophrenia is one of the most severe mental disorders that affect 1% of the population worldwide. It is clear that both genetic and environmental factors participate in its etiology. Nonetheless, the effort to identify susceptibility genes has been difficult and there are no unequivocal findings until now. Notwithstanding this, during the last couple of years, a group of candidate genes has been identified because of their possible role in the physiopathology or by association and linkage studies. In this article, the role of these genes is summarized as well as the results of the studies conducted in Costa Rica by our group.     

A Linkage Disequilibrium–Based Approach to Selecting Disease-Associated Rare Variants

Rare variants have increasingly been cited as major contributors in the disease etiology of several complex disorders. Recently, several approaches have been proposed for analyzing the association of rare variants with disease. These approaches include collapsing rare variants, summing rare variant test statistics within a particular locus to improve power, and selecting a subset of rare variants for association testing, e.g., the step-up approach. We found that (a) if the variants being pooled are in linkage disequilibrium, the standard step-up method of selecting the best subset of variants results in loss of power compared to a model that pools all rare variants and (b) if the variants are in linkage equilibrium, performing a subset selection using step-based selection methods results in a gain of power of association compared to a model that pools all rare variants. Therefore, we propose an approach to selecting the best subset of variants to include in the model that is based on the linkage disequilibrium pattern among the rare variants. The proposed linkage disequilibrium–based variant selection model is flexible and borrows strength from the model that pools all rare variants when the rare variants are in linkage disequilibrium and from step-based selection methods when the variants are in linkage equilibrium. We performed simulations under three different realistic scenarios based on: (1) the HapMap3 dataset of the DRD2 gene, and CHRNA3/A5/B4 gene cluster (2) the block structure of linkage disequilibrium, and (3) linkage equilibrium. We proposed a permutation-based approach to control the type 1 error rate. The power comparisons after controlling the type 1 error show that the proposed linkage disequilibrium–based subset selection approach is an attractive alternative method for subset selection of rare variants.     

Genomic regions identified by overlapping clusters of nominally-positive SNPs from genome-wide studies of alcohol and illegal substance dependence

Declaring "replication" from results of genome wide association (GWA) studies is straightforward when major gene effects provide genome-wide significance for association of the same allele of the same SNP in each of multiple independent samples. However, such unambiguous replication is unlikely when phenotypes display polygenic genetic architecture, allelic heterogeneity, locus heterogeneity and when different samples display linkage disequilibria with different fine structures. We seek chromosomal regions that are tagged by clustered SNPs that display nominally-significant association in each of several independent samples. This approach provides one "nontemplate" approach to identifying overall replication of groups of GWA results in the face of difficult genetic architectures. We apply this strategy to 1 M SNP GWA results for dependence on: a) alcohol (including many individuals with dependence on other addictive substances) and b) at least one illegal substance (including many individuals dependent on alcohol). This approach provides high confidence in rejecting the null hypothesis that chance alone accounts for the extent to which clustered, nominally-significant SNPs from samples of the same racial/ethnic background identify the same sets of chromosomal regions. It identifies several genes that are also reported in other independent alcohol-dependence GWA datasets. There is more modest confidence in: a) identification of individual chromosomal regions and genes that are not also identified by data from other independent samples, b) the more modest overlap between results from samples of different racial/ethnic backgrounds and c) the extent to which any gene not identified herein is excluded, since the power of each of these individual samples is modest. Nevertheless, the strong overlap identified among the samples with similar racial/ethnic backgrounds supports contributions to individual differences in vulnerability to addictions that come from newer allelic variants that are common in subsets of current humans.     

Review. Genetics of addictions: strategies for addressing heterogeneity and polygenicity of substance use disorders

Addictions are common psychiatric disorders that exert high cost to the individual and to society. Addictions are a result of the interplay of multiple genetic and environmental factors. They are characterized by phenotypic and genetic heterogeneity as well as polygenicity, implying a contribution of different neurobiological mechanisms to the clinical diagnosis. Therefore, treatments for most substance use disorders are often only partially effective, with a substantial proportion of patients failing to respond. To address heterogeneity and polygenicity, strategies have been developed to identify more homogeneous subgroups of patients and to characterize genes contributing to their phenotype. These include genetic linkage and association studies as well as functional genetic analysis using endophenotypes and animal behavioural experimentation. Applying these strategies in a translational context aims at improving therapeutic response by the identification of subgroups of addiction patients for individualized, targeted treatment strategies. This article aims to discuss strategies addressing heterogeneity and polygenicity of substance use disorders by presenting results of recent research on genetic and environmental components of addiction. It will also introduce the European IMAGEN study that aims to integrate methodical approaches discussed in order to identify the genetic and neurobiological basis of behavioural traits relevant to the development of addictions.     

The collaborative study on the genetics of alcoholism: Genetics

This review describes the genetic approaches and results from the family-based Collaborative Study on the Genetics of Alcoholism (COGA). COGA was designed during the linkage era to identify genes affecting the risk for alcohol use disorder (AUD) and related problems, and was among the first AUD-focused studies to subsequently adopt a genome-wide association (GWAS) approach. COGA's family-based structure, multimodal assessment with gold-standard clinical and neurophysiological data, and the availability of prospective longitudinal phenotyping continues to provide insights into the etiology of AUD and related disorders. These include investigations of genetic risk and trajectories of substance use and use disorders, phenome-wide association studies of loci of interest, and investigations of pleiotropy, social genomics, genetic nurture, and within-family comparisons. COGA is one of the few AUD genetics projects that includes a substantial number of participants of African ancestry. The sharing of data and biospecimens has been a cornerstone of the COGA project, and COGA is a key contributor to large-scale GWAS consortia. COGA's wealth of publicly available genetic and extensive phenotyping data continues to provide a unique and adaptable resource for our understanding of the genetic etiology of AUD and related traits.     

Genetic vulnerability and susceptibility to substance dependence

The development of substance dependence requires the initiation of substance use and the conversion from experimental use to established use before development of dependence. Numerous large twin studies have indicated a significant genetic contribution to this process. Genetic studies to date have been most successful at identifying genetic factors that influence the transition from regular use to dependence. The availability of large cohort samples for nicotine and alcohol dependence has resulted in significant progress being made in understanding at least some of the genetic contributions to these addictions. Fewer studies have replicated specific genetic contributions to illicit drug use, though it is clear that there is a strong genetic component involved here as well. Substance dependence can be thought of as a pharmacogenetic illness, and most likely hundreds and more probably thousands of genetic variants will be required to fully explain the genetic input to this disease.     

Genetic and Environmental Factors in Complex Neurodevelopmental Disorders

Complex neurodevelopmental disorders, such as schizophrenia, autism, attention deficit (hyperactivity) disorder, (manic) depressive illness and addiction, are thought to result from an interaction between genetic and environmental factors. Association studies on candidate genes and genome-wide linkage analyses have identified many susceptibility chromosomal regions and genes, but considerable efforts to replicate association have been surprisingly often disappointing. Here, we summarize the current knowledge of the genetic contribution to complex neurodevelopmental disorders, focusing on the findings from association and linkage studies. Furthermore, the contribution of the interaction of the genetic with environmental and epigenetic factors to the aetiology of complex neurodevelopmental disorders as well as suggestions for future research are discussed.Key Words: Neurodevelopmental disorders, susceptibility genes, environmental factors, gene-environment interactions, association studies, linkage analysis.     

Genomic View of Bipolar Disorder Revealed by Whole Genome Sequencing in a Genetic Isolate

Bipolar disorder is a common, heritable mental illness characterized by recurrent episodes of mania and depression. Despite considerable effort to elucidate the genetic underpinnings of bipolar disorder, causative genetic risk factors remain elusive. We conducted a comprehensive genomic analysis of bipolar disorder in a large Old Order Amish pedigree. Microsatellite genotypes and high-density SNP-array genotypes of 388 family members were combined with whole genome sequence data for 50 of these subjects, comprising 18 parent-child trios. This study design permitted evaluation of candidate variants within the context of haplotype structure by resolving the phase in sequenced parent-child trios and by imputation of variants into multiple unsequenced siblings. Non-parametric and parametric linkage analysis of the entire pedigree as well as on smaller clusters of families identified several nominally significant linkage peaks, each of which included dozens of predicted deleterious variants. Close inspection of exonic and regulatory variants in genes under the linkage peaks using family-based association tests revealed additional credible candidate genes for functional studies and further replication in population-based cohorts. However, despite the in-depth genomic characterization of this unique, large and multigenerational pedigree from a genetic isolate, there was no convergence of evidence implicating a particular set of risk loci or common pathways. The striking haplotype and locus heterogeneity we observed has profound implications for the design of studies of bipolar and other related disorders.     

Investigation of Rare Single-Nucleotide PCDH15 Variants in Schizophrenia and Autism Spectrum Disorders

Both schizophrenia (SCZ) and autism spectrum disorders (ASD) are neuropsychiatric disorders with overlapping genetic etiology. Protocadherin 15 (PCDH15), which encodes a member of the cadherin super family that contributes to neural development and function, has been cited as a risk gene for neuropsychiatric disorders. Recently, rare variants of large effect have been paid attention to understand the etiopathology of these complex disorders. Thus, we evaluated the impacts of rare, single-nucleotide variants (SNVs) in PCDH15 on SCZ or ASD. First, we conducted coding exon-targeted resequencing of PCDH15 with next-generation sequencing technology in 562 Japanese patients (370 SCZ and 192 ASD) and detected 16 heterozygous SNVs. We then performed association analyses on 2,096 cases (1,714 SCZ and 382 ASD) and 1,917 controls with six novel variants of these 16 SNVs. Of these six variants, four (p.R219K, p.T281A, p.D642N, c.3010-1G>C) were ultra-rare variants (minor allele frequency < 0.0005) that may increase disease susceptibility. Finally, no statistically significant association between any of these rare, heterozygous PCDH15 point variants and SCZ or ASD was found. Our results suggest that a larger sample size of resequencing subjects is necessary to detect associations between rare PCDH15 variants and neuropsychiatric disorders.     

Family study designs in the age of genome-wide association studies: experience from the Framingham Heart Study

PURPOSE OF REVIEW: The past year has seen the publication of many genome-wide association studies, most of which are case-control studies. These publications are at the forefront of current research into the examination of genetic effects for numerous diseases, including diabetes, heart disease and cancer. Over the past 25 years the tour de force of genetics research has been in family studies, using segregation, linkage and association analyses. Are these approaches now passé? Here we discuss the role of family studies in modern genetics research, using results from the Framingham Heart Study as examples. RECENT FINDINGS: Family studies permit both linkage and association analyses. Importantly, family-based association tests that consider transmission of genetic variants within a family provide important information on the genetic etiology of disease traits and avoid the potential of false-positive findings due to population substructure. SUMMARY: Family-based study designs continue to contribute much to the modern era of genome-wide association studies.     

Multiple genes for essential-hypertension susceptibility on chromosome 1q

Essential hypertension, defined as elevated levels of blood pressure (BP) without any obvious cause, is a major risk factor for coronary heart disease, stroke, and renal disease. BP levels and susceptibility to development of essential hypertension are partially determined by genetic factors that are poorly understood. Similar to other efforts to understand complex, non-Mendelian phenotypes, genetic dissection of hypertension-related traits employs genomewide linkage analyses of families and association studies of patient cohorts, to uncover rare and common disease alleles, respectively. Family-based mapping studies of elevated BP cover the large intermediate ground for identification of genes with common variants of significant effect. Our genomewide linkage and candidate-gene-based association studies demonstrate that a replicated linkage peak for BP regulation on human chromosome 1q, homologous to mouse and rat quantitative trait loci for BP, contains at least three genes associated with BP levels in multiple samples: ATP1B1, RGS5, and SELE. Individual variants in these three genes account for 2-5-mm Hg differences in mean systolic BP levels, and the cumulative effect reaches 8-10 mm Hg. Because the associated alleles in these genes are relatively common (frequency >5%), these three genes are important contributors to elevated BP in the population at large.     

An analytical enrichment-based review of structural genetic studies on keratoconus

Keratoconus is a progressive bilateral corneal protrusion that leads to irregular astigmatism and impairment of vision. Keratoconus is an etiologically heterogeneous corneal dystrophy and both environmental and genetic factors play a role in its etiopathogenesis. In this analytical review, we have studied all the genes that are structurally associated with keratoconus and have tried to explain the function of each gene and its association with other eye disorders in a concise way. In addition, using gene set enrichment analysis, it was attempted to find the most important impaired metabolic pathways in keratoconus. Several genetic studies have been carried out on keratoconus and several genes have been identified as risk factors involved in the etiology of the disease. In the current study, 16 studies, including nine association studies, five genome-wide association studies, one linkage study, and one meta-analysis, were reviewed and based on the 19 genes found, enrichment was performed and the most important metabolic pathways involved in the disease were identified. The enrichment results indicated that the two pathways, interleukin 1 processing and assembly of collagen fibrils, are significantly associated with the disease. Obviously, the results of this study, in addition to providing information about the genes involved in the disease, can provide an integrated insight into the gene-based etiology of keratoconus and therapeutic opportunities thereof.     

Pathway analysis of genome‐wide association datasets of personality traits

Although several genome‐wide association (GWA) studies of human personality have been recently published, genetic variants that are highly associated with certain personality traits remain unknown, due to difficulty reproducing results. To further investigate these genetic variants, we assessed biological pathways using GWA datasets. Pathway analysis using GWA data was performed on 1089 Korean women whose personality traits were measured with the Revised NEO Personality Inventory for the 5‐factor model of personality. A total of 1042 pathways containing 8297 genes were included in our study. Of these, 14 pathways were highly enriched with association signals that were validated in 1490 independent samples. These pathways include association of: Neuroticism with axon guidance [L1 cell adhesion molecule (L1CAM) interactions]; Extraversion with neuronal system and voltage‐gated potassium channels; Agreeableness with L1CAM interaction, neurotransmitter receptor binding and downstream transmission in postsynaptic cells; and Conscientiousness with the interferon‐gamma and platelet‐derived growth factor receptor beta polypeptide pathways. Several genes that contribute to top‐ranked pathways in this study were previously identified in GWA studies or by pathway analysis in schizophrenia or other neuropsychiatric disorders. Here we report the first pathway analysis of all five personality traits. Importantly, our analysis identified novel pathways that contribute to understanding the etiology of personality traits.     

Discovery of Rare Variants via Sequencing: Implications for the Design of Complex Trait Association Studies

There is strong evidence that rare variants are involved in complex disease etiology. The first step in implicating rare variants in disease etiology is their identification through sequencing in both randomly ascertained samples (e.g., the 1,000 Genomes Project) and samples ascertained according to disease status. We investigated to what extent rare variants will be observed across the genome and in candidate genes in randomly ascertained samples, the magnitude of variant enrichment in diseased individuals, and biases that can occur due to how variants are discovered. Although sequencing cases can enrich for casual variants, when a gene or genes are not involved in disease etiology, limiting variant discovery to cases can lead to association studies with dramatically inflated false positive rates.