Genetic heterogeneity could reduce the power of linkage analysis to detect risk loci for complex traits such as alcohol dependence (AD). Previously, we performed a genomewide linkage analysis for AD in African-Americans (AAs) (Gelernter et al., 2009). The power of that linkage analysis could have been reduced by the presence of genetic heterogeneity owing to differences in admixture among AA families. We hypothesized that by examining a study sample whose genetic ancestry was more homogeneous we could increase the power to detect linkage. To test this hypothesis, we performed ordered subset linkage analysis (OSA) in 384 AA families using admixture proportion as a covariate to identify a more homogeneous subset of families and determine whether there is increased evidence for linkage with AD. Statistically significant increases in lod scores in subsets relative to the overall sample were identified on chromosomes 4 (P=0.0001), 12 (P=0.021), 15 (P=0.026) and 22 (P=0.0069). In a subset of 44 families with African ancestry proportions ranging from 0.858 to 0.996, we observed a genomewide significant linkage at 180 cM on chromosome 4 (lod=4.24, pointwise P<0.00001, empirical genomewide P=0.008). A promising candidate gene located there, GLRA3, which encodes a subunit of the glycine neurotransmitter receptor. Our results demonstrate that admixture proportion can be used as a covariate to reduce genetic heterogeneity and enhance the detection of linkage for AD in an admixed population such as AAs. This approach could be applied to any linkage analysis for complex traits conducted in an admixed population.
linkage; ordered subset linkage analysis; genetic heterogeneity; alcohol dependence; admixture
Understanding genetic influences on both healthy and disordered brain function is a major focus in psychiatric neuroimaging. We utilized task-related imaging findings from an fMRI auditory oddball task known to be robustly associated with abnormal activation in schizophrenia, to investigate genomic factors derived from multiple single nucleotide polymorphisms (SNP’s) from genes previously shown to be associated with schizophrenia. Our major aim was to investigate the relationship of these genomic factors to normal/abnormal brain functionality between controls and schizophrenia patients. We studied a Caucasian-only sample of 35 healthy controls and 31 schizophrenia patients. All subjects performed an auditory oddball task, which consists of detecting an infrequent sound within a series of frequent sounds. Each subject was characterized on 24 different SNP markers spanning multiple risk genes previously associated with schizophrenia. We used a recently developed technique named parallel independent component analysis (para-ICA) to analyze this multimodal dataset (Liu et al., 2008). The method aims to identify simultaneously independent components of each modality (functional imaging, genetics) and the relationships between them. We detected 3 fMRI components significantly correlated with two distinct gene components. The fMRI components, along with their significant genetic profile (dominant SNP) correlations were as follows: 1) Inferior frontal- anterior/posterior cingulate-thalamus-caudate with SNPs from Brain derived neurotropic factor (BDNF) & Dopamine Transporter, (DAT) [r=−0.51; p<0.0001], 2) Superior/middle temporal gyrus-Cingulate-premotor with SLC6A4_PR and SLC6A4_PR_AG (Serotonin transporter promoter; 5HTTLPR) [r=0.27; p=0.03], 3) Default Mode-fronto-temporal gyrus with Brain derived neurotropic factor & Dopamine Transporter (BDNF, DAT) [r=−0.25; p=0.04]. Functional components comprised taskrelevant regions (including PFC, ACC, STG and MTG) frequently identified as abnormal in schizophrenia. Further, gene-fMRI combinations 1 (Z=1.75; p=0.03), 2 (Z=1.84;p=0.03) and 3 (Z=1.67; p=0.04) listed above showed significant differences between controls and patients, based on their correlated loading coefficients. We demonstrate a framework to identify interactions between “clusters” of brain function and of genetic information. Our results reveal the effect/influence of specific interactions, (perhaps epistastatic in nature), between schizophrenia risk genes on imaging endophenotypes representing attention/working memory and goal directed related brain function, thus establishing a useful methodology to probe multivariate genotype-phenotype relationships.
auditory oddball; DAT; BDNF; fMRI; gene; parallel ICA; multivariate; 5HTTLPR
Multiple substance dependence (MSD) trait comorbidity is common, and MSD patients are often severely affected clinically. While shared genetic risks have been documented, so far there has been no published report using the linkage scan approach to survey risk loci for MSD as a phenotype. A total of 1,758 individuals in 739 families [384 African American (AA) and 355 European American (EA) families] ascertained via affected sib-pairs with cocaine or opioid or alcohol dependence were genotyped using an array-based linkage panel of single-nucleotide polymorphism markers. Fuzzy clustering analysis was conducted on individuals with alcohol, cannabis, cocaine, opioid, and nicotine dependence for AAs and EAs separately, and linkage scans were conducted for the output membership coefficients using Merlin-regression. In EAs, we observed an autosome-wide significant linkage signal on chromosome 4 (peak lod = 3.31 at 68.3 cM; empirical autosome-wide P = 0.038), and a suggestive linkage signal on chromosome 21 (peak lod = 2.37 at 19.4 cM). In AAs, four suggestive linkage peaks were observed: two peaks on chromosome 10 (lod = 2.66 at 96.7 cM and lod = 3.02 at 147.6 cM] and the other two on chromosomes 3 (lod = 2.81 at 145.5 cM) and 9 (lod = 1.93 at 146.8 cM). Three particularly promising candidate genes, GABRA4, GABRB1, and CLOCK, are located within or very close to the autosome-wide significant linkage region for EAs on chromosome 4. This is the first linkage evidence supporting existence of genetic loci influencing risk for several comorbid disorders simultaneously in two major US populations.
comorbidity; multiple substance dependence; fuzzy clustering; chromosome 4
Child abuse is highly prevalent and associated with increased risk for a range of health problems including: cancer, cardiovascular disease, diabetes, psychiatric disorders, and other health problems. Little is currently known about the mechanism by which early adversity confers risk for health problems later in life.
To determine if there are epigenetic differences associated with child maltreatment that may help explain association between adverse childhood experiences and later health problems.
As part of a study examining genetic and environmental factors associated with depression, saliva DNA specimens were collected on 96 maltreated children removed from their parents due to abuse or neglect and 96 demographically-matched control children between 2003 and 2010. In 2011, the Illumina 450K BeadChip was used on stored DNA specimens and analyzed to examine whole-genome methylation differences between maltreated and control children.
After controlling for multiple comparisons, maltreated and control children had significantly different methylation values at 2868 CpG sites (p< 5.0 × 10−7, all sites; average methylation difference per site=17%; range 1%–62%). The gene set contained numerous markers of diseases and biological processes related to the health problems associated with early childhood adversity.
While replication is required, this study suggests that epigenetic mechanisms may be associated with risk for health problems later in life in maltreated children. This study lays the groundwork for future studies examining health and methylation measures to further characterize the role of epigenetic mechanisms in conferring risk for medical problems in individuals with histories of early adversity.
Epigenetic regulation through DNA methylation may influence vulnerability to numerous disorders, including alcohol dependence (AD).
Peripheral blood DNA methylation levels of 384 CpGs in the promoter regions of 82 candidate genes were examined in 285 African Americans (AAs; 141 AD cases and 144 controls) and 249 European Americans (EAs; 144 AD cases and 105 controls) using Illumina GoldenGate Methylation Array assays. Association of AD and DNA methylation changes were analyzed using multivariate analyses of covariance with frequency of intoxication, sex, age and ancestry proportion as covariates. CpGs showing significant methylation alterations in AD cases were further examined in a replication sample (49 EA cases and 32 EA controls) using Sequenom’s MassARRAY EpiTYPER technology.
In AAs, two CpGs in two genes (GABRB3 and POMC) were hypermethylated in AD cases compared to controls (P≤0.001). In EAs, six CpGs in six genes (HTR3A, NCAM1, DRD4, MBD3, HTR2B and GRIN1) were hypermethylated in AD cases compared to controls (P≤0.001); CpG cg08989585 in the HTR3A promoter region showed a significantly higher methylation level in EA cases than in EA controls after Bonferroni correction (P=0.00007). Additionally, methylation levels of six CpGs (including cg08989585) in the HTR3A promoter region were analyzed in the replication sample. Although the six HTR3A promoter CpGs did not show significant methylation differences between EA cases and EA controls (P=0.067–0.877), the methylation level of CpG cg08989585 was non-significantly higher in EA cases (26.9%) than in EA controls (18.6%) (P=0.139).
The findings from this study suggest that DNA methylation profile appears to be associated with AD in a population-specific way and the predisposition to AD may result from a complex interplay of genetic variation and epigenetic modifications.
Illumna GoldenGate Methylation Array; Sequenom MassARRAY EpiTYPER; Promoter CpGs; Alcohol Dependence; Peripheral Blood DNA
The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) will soon replace the DSM-IV, which has existed for nearly two decades. The changes in diagnostic criteria have important implications for research and for the clinical care of individuals with Substance Use Disorders (SUDs).
We used the Semi-Structured Assessment for Drug Dependence and Alcoholism to evaluate the lifetime presence of DSM-IV abuse and dependence diagnoses and DSM-5 mild, moderate, or severe SUDs for alcohol, cocaine, opioids, and cannabis in a sample of 7,543 individuals recruited to participate in genetic studies of substance dependence.
Switches between diagnostic systems consistently resulted in a modestly greater prevalence for DSM-5 SUDs, based largely on the assignment of DSM-5 diagnoses to DSM-IV “diagnostic ophans” (i.e., individuals meeting one or two criteria for dependence and none for abuse, and thus not receiving a DSM-IV SUD diagnosis). The vast majority of these diagnostic switches were attributable to the requirement that only two of 11 criteria be met for a DSM-5 SUD diagnosis. We found evidence to support the omission from DSM-5 of the legal criterion due to its limited diagnostic utility. The addition of craving as a criterion in DSM-5 did not substantially affect the likelihood of an SUD diagnosis.
The greatest advantage of DSM-5 appears to be its ability to capture diagnostic orphans. In this sample, changes reflected in DSM-5 had a minimal impact on the prevalence of SUD diagnoses.
DSM-IV; DSM-5; Substance Use Disorders; Substance Abuse; Substance Dependence
Catechol-O-methyltransferase (genetic locus, COMT) is a major enzyme involved in catecholamine metabolism and has been associated with numerous psychiatric phenotypes. We studied COMT SNPs and haplotypes in cocaine-induced paranoia (CIP) in African-American (AA) and European-American (EA) populations. We genotyped 17 SNPs across the COMT locus in 319 AA pedigrees (848 individuals) and 302 EA pedigrees (707 individuals). Family-controlled association analyses were conducted using FBAT. We found SNP rs737865 to be nominally significantly associated in the AA family population (p=0.05). In EAs, the best-known marker, rs4680 (Val158Met), was nominally significant in additive models (p=0.03). SNP rs174696 also showed nominal significance in additive models (p=0.02). We considered the 3 SNPs (rs737866-rs4680-rs174696) together in haplotype analysis in both family populations, using HBAT. The A-A-T haplotype was significantly associated with CIP in EAs (Z=2.845; p=0.0044, global p=0.020). We then studied COMT SNPs in an additional 738 AA and 404 EA unrelated cocaine dependent individuals with and without paranoia. The A-A-T haplotype was significantly associated to CIP in the AA unrelated population (p=0.0015). Two haplotypes, A-G-C and A-A-C, were significant in the EA unrelated population (p=0.001 and p=0.0003). We also identified rs4680 and three other SNPs, rs933271, rs5993883, and rs740603, as potentially functional variants, as predicted by a signature of positive selection in unrelated EAs and AAs. Based on our robust family-controlled and unrelated-affected analyses, we conclude that COMT is associated with CIP, possibly as a result of its role in the metabolism of dopamine and norepinephrine.
COMT; cocaine-induced paranoia; family-based analysis; haplotype; SNP; positive selection
Childhood adversity has been shown to interact with monoamine
oxidase-A (MAOA) genotype to confer risk for antisocial
behavior. Studies examining this gene-by-environment (G×E)
association, however, have produced mixed results.
Relevant research is reviewed, and results of a study with 114
children (73 maltreated and 41 control subjects) are presented. The
maltreated children represent the extreme on a continuum of adversity and
were assessed at a time of extreme stress—shortly after removal from
their parents’ care due to abuse. Measures of aggressive behavior
were obtained using standard research instruments, and monoamine oxidase-A
MAOA genotypes were obtained from saliva-derived DNA
specimens. Population structure was controlled for using ancestral
proportion scores computed on the basis of genotypes of ancestry informative
Many prior investigations appear to have had reduced power to detect
the predicted G×E interaction because of low base rates of
maltreatment and antisocial behavior in their samples and failure to use
optimal procedures to control for population structure in ethnically diverse
cohorts. In this investigation, a significant interaction was detected
between exposure to moderate trauma and the “low-activity”
MAOA genotype in conferring risk for aggression.
Children with exposure to extreme levels of trauma, however, had high
aggression scores regardless of genotype.
Our study suggests that problems in aggressive behavior in maltreated
children are moderated by MAOA genotype, but only up to
moderate levels of trauma exposure. Extreme levels of trauma appear to
overshadow the effect of MAOA genotype, especially in
children assessed at time of acute crisis.
Aggression; antisocial; child abuse; gene–environment interaction; maltreatment; MAOA
Genetic factors influence the risk for posttraumatic stress disorder (PTSD), a potentially chronic and disabling psychiatric disorder that can arise after exposure to trauma. Candidate gene association studies have identified few genetic variants that contribute to PTSD risk.
We conducted genome-wide association analyses in 1578 European Americans (EAs), including 300 PTSD cases, and 2766 African Americans, including 444 PTSD cases, to find novel common risk alleles for PTSD. We used the Illumina Omni1-Quad microarray, which yielded approximately 870,000 single nucleotide polymorphisms (SNPs) suitable for analysis.
In EAs, we observed that one SNP on chromosome 7p12, rs406001, exceeded genome-wide significance (p = 3.97×10−8). A SNP that maps to the first intron of the Tolloid-Like 1 gene (TLL1) showed the second strongest evidence of association, although no SNPs at this locus reached genome-wide significance. We then tested six SNPs in an independent sample of nearly 2000 EAs and successfully replicated the association findings for two SNPs in the first intron of TLL1, rs6812849 and rs7691872, with p values of 6.3×10−6 and 2.3×10−4, respectively. In the combined sample, rs6812849 had a p value of 3.1 ×10−9. No significant signals were observed in the African American part of the sample. Genome-wide association study analyses restricted to trauma-exposed individuals yielded very similar results.
This study identified TLL1 as a new susceptibility gene for PTSD.
American populations; genome-wide association study; posttraumatic stress disorder; TLL1
Although there is evidence that opioid dependence (OD) is heritable, efforts to identify genes contributing to risk for the disorder have been hampered by its complex etiology and variable clinical manifestations. Decomposition of a complex set of opioid users into homogeneous subgroups could enhance genetic analysis. We applied a series of data mining techniques, including multiple correspondence analysis, variable selection and cluster analysis, to 69 opioid-related measures from 5,390 subjects aggregated from family-based and case-control genetic studies to identify homogeneous subtypes and estimate their heritability. Novel aspects of this work include our use of 1) heritability estimates of specific clinical features of OD to enhance the heritability of the subtypes and 2) a k-medoids clustering method in combination with hierarchical clustering to yield replicable clusters that are less sensitive to noise than previous methods. We identified five homogeneous groups, including two large groups comprised of 762 and 1,353 heavy opioid users, with estimated heritability of 0.69 and 0.76, respectively. These methods represent a promising approach to the identification of highly heritable subtypes in complex, heterogeneous disorders.
Opioid dependence; Subtypes; Phenotype; k-medoids clustering; Hierarchical clustering; Heritability
Genetic factors underlying trait neuroticism, reflecting a tendency towards negative affective states, may overlap genetic susceptibility for anxiety disorders and help explain the extensive comorbidity amongst internalizing disorders. Genome-wide linkage (GWL) data from several studies of neuroticism and anxiety disorders have been published, providing an opportunity to test such hypotheses and identify genomic regions that harbor genes common to these phenotypes. In all, 11 independent GWL studies of either neuroticism (n=8) or anxiety disorders (n=3) were collected, which comprised of 5341 families with 15 529 individuals. The rank-based genome scan meta-analysis (GSMA) approach was used to analyze each trait separately and combined, and global correlations between results were examined. False discovery rate (FDR) analysis was performed to test for enrichment of significant effects. Using 10 cM intervals, bins nominally significant for both GSMA statistics, PSR and POR, were found on chromosomes 9, 11, 12, and 14 for neuroticism and on chromosomes 1, 5, 15, and 16 for anxiety disorders. Genome-wide, the results for the two phenotypes were significantly correlated, and a combined analysis identified additional nominally significant bins. Although none reached genome-wide significance, an excess of significant PSRP-values were observed, with 12 bins falling under a FDR threshold of 0.50. As demonstrated by our identification of multiple, consistent signals across the genome, meta-analytically combining existing GWL data is a valuable approach to narrowing down regions relevant for anxiety-related phenotypes. This may prove useful for prioritizing emerging genome-wide association data for anxiety disorders.
anxiety; neuroticism; panic disorder; linkage; meta-analysis
Next generation sequencing (NGS) has been leading the genetic study of human disease into an era of unprecedented productivity. Many bioinformatics pipelines have been developed to call variants from NGS data. The performance of these pipelines depends crucially on the variant caller used and on the calling strategies implemented. We studied the performance of four prevailing callers, SAMtools, GATK, glftools and Atlas2, using single-sample and multiple-sample variant-calling strategies. Using the same aligner, BWA, we built four single-sample and three multiple-sample calling pipelines and applied the pipelines to whole exome sequencing data taken from 20 individuals. We obtained genotypes generated by Illumina Infinium HumanExome v1.1 Beadchip for validation analysis and then used Sanger sequencing as a “gold-standard” method to resolve discrepancies for selected regions of high discordance. Finally, we compared the sensitivity of three of the single-sample calling pipelines using known simulated whole genome sequence data as a gold standard. Overall, for single-sample calling, the called variants were highly consistent across callers and the pairwise overlapping rate was about 0.9. Compared with other callers, GATK had the highest rediscovery rate (0.9969) and specificity (0.99996), and the Ti/Tv ratio out of GATK was closest to the expected value of 3.02. Multiple-sample calling increased the sensitivity. Results from the simulated data suggested that GATK outperformed SAMtools and glfSingle in sensitivity, especially for low coverage data. Further, for the selected discrepant regions evaluated by Sanger sequencing, variant genotypes called by exome sequencing versus the exome array were more accurate, although the average variant sensitivity and overall genotype consistency rate were as high as 95.87% and 99.82%, respectively. In conclusion, GATK showed several advantages over other variant callers for general purpose NGS analyses. The GATK pipelines we developed perform very well.
Alcohol dependence (AD), a genetically influenced phenotype, is extremely costly to individuals and to society in the United States and throughout the world, contributing to morbidity and mortality and a host of economic, interpersonal, and societal problems. Although until recently the only genes established to affect risk for AD were those encoding several alcohol metabolizing enzymes, there are now several other genes that can be regarded as confirmed risk loci, discovered through linkage and candidate gene association studies. While the mechanism of action of the effects of alcohol-metabolizing enzymes on AD risk is thought to be well understood, we are still in the early stages of understanding the physiology of other risk loci. Further, it is clear that only a small number of the many genes that influence risk for AD have been identified. Newer methodologies (e.g., genomewide association, study of copy number variation, and deep sequencing of candidate loci to identify rare risk variants) that have improved our understanding of other complex traits hold the promise of identifying a greater set of AD susceptibility loci.
The goal of this study was to test a hypothesis associating impulsivity with an elevated body mass index (BMI).
To this end, we examined associations of BMI with putative genetic, neurophysiological, psychiatric, and psychological indicators of impulsivity in 78 women and 74 men formerly dependent on alcohol or drugs. A second analysis was designed to test the replicability of the genetic findings in an independent sample of 109 women and 111 men with a similar history of substance dependence.
The results of the first analysis showed that BMI was positively correlated with Total and Nonplanning Scale Scores on the Barratt Impulsiveness Scale and the number of childhood symptoms of Attention-Deficit/Hyperactivity Disorder in women. It was also positively correlated, in women, with a GABRA2 variant previously implicated as a risk factor for substance dependence and an objective electroencephalographic feature previously associated with GABRA2 and relapse risk. The second analysis confirmed that the correlation between BMI and the substance-dependence-associated GABRA2 genotype was reliable and sex-specific.
We conclude that an elevated BMI is associated with genetic, neurophysiological, psychiatric, and psychological indicators of impulsivity. The sex difference may be explained by greater opportunities to eat and overeat, a preference for higher calorie foods, a longer duration of alcohol/drug abstinence, or previous pregnancies in women.
Next generation sequencing is widely used to study complex diseases because of its ability to identify both common and rare variants without prior single nucleotide polymorphism (SNP) information. Pooled sequencing of implicated target regions can lower costs and allow more samples to be analyzed, thus improving statistical power for disease-associated variant detection. Several methods for disease association tests of pooled data and for optimal pooling designs have been developed under certain assumptions of the pooling process, e.g. equal/unequal contributions to the pool, sequencing depth variation, and error rate. However, these simplified assumptions may not portray the many factors affecting pooled sequencing data quality, such as PCR amplification during target capture and sequencing, reference allele preferential bias, and others. As a result, the properties of the observed data may differ substantially from those expected under the simplified assumptions. Here, we use real datasets from targeted sequencing of pooled samples, together with microarray SNP genotypes of the same subjects, to identify and quantify factors (biases and errors) affecting the observed sequencing data. Through simulations, we find that these factors have a significant impact on the accuracy of allele frequency estimation and the power of association tests. Furthermore, we develop a workflow protocol to incorporate these factors in data analysis to reduce the potential biases and errors in pooled sequencing data and to gain better estimation of allele frequencies. The workflow, Psafe, is available at http://bioinformatics.med.yale.edu/group/.
pooled sequencing; allele frequency estimation; next-generation sequencing; disease association tests
We reported that the 5-HTTLPR polymorphism in the promoter region of the serotonin transporter gene (SLC6A4) moderates the effect of childhood adversity on posttraumatic stress disorder (PTSD)risk (Xie and others 2009). In the present study, we considered 5178 subjects (a group with generally high substance dependence comorbidity, as for our previous study) using similar methodology to replicate our previous results.
We used logistic regression analyses to explore the interaction effect of 5-HTTLPR genotype and childhood adversity on PTSD risk. We found that, as reported in our previous study, in individuals with childhood adversity, the presence of one or two copies of the S allele of 5-HTTLPR increased the risk to develop PTSD. This gene-environment interaction effect was present in European Americans (EAs), but not in African Americans (AAs) (EAs, OR=1.49, 95% CI=1.07–2.08, P=0.019; AAs, OR=0.90, 95% CI=0.60–1.35, P=0.62). The statistical power to detect this interaction effect was increased when data were combined with those from our previous study (Xie and others 2009).
The findings reported here replicate those from our previous work, adding to a growing body of research demonstrating that the 5-HTTLPR genotype moderates risk for anxiety and depression phenotypes in the context of stress and adverse events.
gene-environment interaction; PTSD; childhood adversity; 5-HTTLPR
Recent advances in next-generation sequencing technologies have transformed the genetics study of human diseases; this is an era of unprecedented productivity. Exome sequencing, the targeted sequencing of the protein-coding portion of the human genome, has been shown to be a powerful and cost-effective method for detection of disease variants underlying Mendelian disorders. Increasing effort has been made in the interest of the identification of rare variants associated with complex traits in sequencing studies. Here we provided an overview of the application fields for exome sequencing in human diseases. We describe a general framework of computation and bioinformatics for handling sequencing data. We then demonstrate data quality and agreement between exome sequencing and exome microarray (chip) genotypes using data collected on the same set of subjects in a genetic study of panic disorder. Our results show that, in sequencing data, the data quality was generally higher for variants within the exonic target regions, compared to that outside the target regions, due to the target enrichment. We also compared genotype concordance for variant calls obtained by exome sequencing vs. exome genotyping microarrays. The overall consistency rate was >99.83% and the heterozygous consistency rate was >97.55%. The two platforms share a large amount of agreement over low frequency variants in the exonic regions, while exome sequencing provides much more information on variants not included on exome genotyping microarrays. The results demonstrate that exome sequencing data are of high quality and can be used to investigate the role of rare coding variants in human diseases.
exome sequencing; exome arrays; Mendelian diseases; complex traits; whole-genome sequencing
CHRNA4, the gene that encodes the nicotinic
acetylcholine receptor α4 subunit, is a potential candidate
gene for nicotine dependence (ND). However, studies of the association of
CHNRA4 with smoking behavior have shown inconsistent
results. Our meta-analysis of linkage studies of smoking behavior identified a
genome-wide significant linkage of the phenotype maximum number of cigarettes
smoked in a 24-hour period to a region (20q13.12-q13.32) harboring
CHRNA4. This motivated us to examine the association of
CHRNA4 with smoking behavior in two independent samples. In
this study, we examined five single nucleotide polymorphisms (SNPs) within
CHRNA4 and three smoking-related behaviors: one
quantitative trait [cigarettes smoked per day (CPD)], and two
binary traits [DSM-IV diagnosis of ND and dichotomized Fagerstrom test
of ND (FTND)], in 1,249 unrelated European-Americans (EAs) and 1,790
unrelated African-Americans (AAs). Using the combined sample with sex, age and
race as covariates, the synonymous SNP rs1044394 was significantly associated
with ND (P = 0.001) and FTND (P
= 0.01). Rs2236196, which has a low correlation with rs1044394, was also
significantly associated with CPD (P = 0.003). The
pattern of association for these SNPs was similar in AAs and EAs. After
correction for multiple testing, the association between rs1044394 and ND in the
combined sample remained significant (P = 0.033). In
summary, our study supports association between CHRNA4 common
variation and ND in AA and EA samples. Additional studies will be necessary to
evaluate the role of rare variants at CHRNA4 for ND.
smoking behavior; nicotine dependence; FTND; SNP; association
The alcohol dehydrogenase 1C (ADH1C) subunit is an important member of the alcohol dehydrogenase family, a set of genes that plays a major role in the catabolism of ethanol. Numerous association studies have provided compelling evidence that ADH1C gene variation (formerly ADH3) is associated with altered genetic susceptibility to alcoholism and alcohol-related liver disease, cirrhosis, or pancreatitis. However, the results have been inconsistent, partially because each study involved a limited number of subjects, and some were underpowered. Using cumulative data over the past two decades, this meta-analysis (6,796 cases and 6,938 controls) considered samples of Asian, European, African, and Native American origins to examine whether the aggregate genotype provide statistically significant evidence of association. The results showed strong evidence of association between ADH1C Ile350Val (rs698, formerly ADH1C *1/*2) and alcohol dependence (AD) and abuse in the combined studies. The overall allelic (Val vs. Ile or *2 vs. *1) P value was 1×10−8 and Odds Ratio (OR) was 1.51 (1.31, 1.73). The Asian populations produced stronger evidence of association with an allelic P value of 4×10−33 (OR = 2.14 (1.89, 2.43)) with no evidence of heterogeneity, and the dominant and recessive models revealed even stronger effect sizes. The strong evidence remained when stricter criteria and sub-group analyses were applied, while Asians always showed stronger associations than other populations. Our findings support that ADH1C Ile may lower the risk of AD and alcohol abuse as well as alcohol-related cirrhosis in pooled populations, with the strongest and most consistent effects in Asians.
Meta-analysis; Association; Ethanol Oxidation; Addiction; ADH1C
A genetic contribution to cannabis dependence (CaD) has been established, but susceptibility genes for CaD remain largely unknown.
We employed a multi-stage design to identify genetic variants underlying CaD. We first performed a genomewide linkage scan for CaD in 384 African-American (AA) and 354 European-American (EA) families ascertained for genetic studies of cocaine and opioid dependence. We then conducted association analysis under the linkage peak, first using data from a genomewide association study from the Study of Addiction: Genetics and Environment (SAGE), followed by replication studies of prioritized single nucleotide polymorphisms (SNPs) in independent samples.
We identified the strongest linkage evidence with CaD (lod=2.9) on chromosome 8p21.1 in AAs. In the association analysis of the SAGE sample under the linkage peak, we identified one SNP (rs17664708) associated with CaD in both AAs (minor allele frequency (MAF) = 0.02, OR=2.93, 95% CI=1.47–5.85, P=0.0022) and EAs (MAF=0.096, OR=1.38, 95% CI=1.05–1.81, P=0.02). This SNP, located at NRG1, a susceptibility gene for schizophrenia, was prioritized for further study. We replicated the association of rs17664708 with CaD in an independent sample of AAs (MAF=0.013, OR=2.81, 95% CI=1.23–6.45, P=0.0068). The joint analysis of the two AA samples demonstrated highly significant association between rs17664708 and CaD with adjustment for either global (OR=2.34, 95% CI=1.42–3.85, P=0.00044) or local ancestry (OR=2.33, 95% CI=1.39–3.91, P=0.00075).
Our study shows that NRG1 is probably a susceptibility gene for CaD, based on convergent evidence of linkage and replicated associations in two independent AA samples.
Cannabis dependence; linkage; association; candidate gene; SNP; NRG1
Although adolescents frequently engage in a variety of risky behaviors, much remains unknown about the specific etiologies of such tendencies. Candidate genetic variants, such as the COMT Val158Met polymorphism, may be related to risk-taking propensity, particularly as this variant is linked to functional enzymatic differences influencing dopamine function in regions including the prefrontal cortex. The present study aimed to examine the COMT Val158Met variant in relation to risk taking propensity in a community sample of youth. As part of a larger longitudinal study on adolescent risk behaviors, 223 youths (average age 11.3 years) from the metropolitan Washington D.C. area completed a measure of risk-taking propensity, the Balloon Analogue Risk Task-Youth Version (BART-Y), and provided saliva samples for DNA extraction and genotyping. Results indicate that females, but not males, who are carriers of the COMT158Met allele had higher risk-taking propensity scores on the BART-Y compared to Val homozygotes. Analyses were also conducted in the 111 European American participants, and results were consistent with those of the full sample analyses. This study represents the first investigation of a genetic substrate of risk-taking propensity, measured by a behavioral task, in youth. Results should be taken as quite preliminary, given the small sample. Implications are discussed.
Risk taking; BART; COMT Val158Met; Dopamine; Adolescents
Both theory and empirical evidence support possible associations between two candidate genetic polymorphisms (SLC6A4 5-HTTLPR l/s and COMT Val158Met – rs4680 variants) and emotion-regulation difficulties. One particular form of emotion-regulation difficulty, distress intolerance, has been measured using a behavioral assessment in youth; data indicate a relationship with poor psychological functioning. No prior study has investigated genetic influences on emotion-regulation difficulties in youth. As part of a larger longitudinal study on adolescent risk behaviors, 218 10-14 year-old youths from the metropolitan Washington, D.C., area completed a measure of distress intolerance, the Behavioral Indicator of Resilience to Distress (BIRD), and provided saliva samples for DNA extraction and genotyping. Results indicate that those with one or two copies of the s allele of the 5-HTTLPR polymorphism were more likely to perform poorly on the task (i.e., choose to quit) than were those homozygous for the l allele. Participants who were Val allele carriers of the COMT Val158Met polymorphism were also more likely to quit the task compared to Met homozygotes. A summative risk allele score was created to combine the two polymorphisms, and each risk allele was associated with a 1.75 fold increased likelihood of quitting the task. Exploratory analyses revealed that emotional abuse moderated the relationship between the 5-HTTLPR and BIRD performance, as well as the genetic risk allele and the BIRD. This is the first investigation of genetic predictors of a behavioral measure of tolerance to distress. Results suggest that distress tolerance is at least partially regulated by specific genetic variants. Implications are discussed.
COMT; 5-HTTLPR; Distress Tolerance
The increased vulnerability to alcohol dependence (AD) seen in individuals with childhood adversity (CA) may result in part from CA-induced epigenetic changes. To examine CA-associated DNA methylation changes in AD patients, we examined peripheral blood DNA methylation levels of 384 CpGs in promoter regions of 82 candidate genes in 279 African Americans [AAs; 88 with CA (70.5% with AD) and 191 without CA (38.2% with AD)] and 239 European Americans [EAs; 61 with CA (86.9% with AD) and 178 without CA (46.6% with AD)] using Illumina GoldenGate Methylation Array assays. The effect of CA on methylation of individual CpGs and overall methylation in promoter regions of genes was evaluated using a linear regression analysis (with consideration of sex, age, and ancestry proportion of subjects) and a principal components-based analysis, respectively. In EAs, hypermethylation of 10 CpGs in seven genes (ALDH1A1, CART, CHRNA5, HTR1B, OPRL1, PENK, and RGS19) were cross validated in AD patients and healthy controls who were exposed to CA. P values of two CpGs survived Bonferroni correction when all EA samples were analyzed together to increase statistical power [CHRNA5_cg17108064: Padjust = 2.54×10−5; HTR1B_cg06031989: Padjust = 8.98×10−5]. Moreover, overall methylation levels in the promoter regions of three genes (ALDH1A1, OPRL1 and RGS19) were elevated in both EA case and control subjects who were exposed to CA. However, in AAs, CA-associated DNA methylation changes in AD patients were not validated in healthy controls. Our findings suggest that CA could induce population-specific methylation alterations in the promoter regions of specific genes, thus leading to changes in gene transcription and an increased risk for AD and other disorders.
Completed suicide and non-fatal suicide-related outcomes (SRO), such as suicidal ideation and attempts, are heritable. Hishimoto et al. (2008) reported a protective effect of the G allele of Asn40Asp (rs1799971) on risk for completed suicide. We examined the association of three OPRM1 SNPs (rs1799971, rs609148 and rs648893) with SRO in 426 European-Americans, using GEE logistic regression analysis to examine the association of a lifetime history of SRO. There was no allelic association with the SRO phenotypes. A larger sample may be needed to identify risk variants that convey SRO risk. OPRM1 may not be important in the risk of SRO.