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Genome-wide association studies (GWAS) in admixed populations such as African Americans (AA) have limited sample sizes, resulting in poor performance of polygenic risk scores (PRS). Based on the observations that many disease-causing genes are shared between AA and European ancestry (EA) populations, and some disease-causing variants are located within the boundaries of these genes, we proposed a novel gene-based PRS framework (PRSgene) by using variants located within disease-associated genes. Using the AA GWAS of alcohol use disorder (AUD) from the Million Veteran Program and the EA GWAS of problematic alcohol use as the discovery GWAS, we identified 858 variants from 410 genes that were AUD-related in both AA and EA. PRSgene calculated using these variants were significantly associated with AUD in three AA target datasets (P-values ranged from 7.61E−05 to 6.27E−03; Betas ranged from 0.15 to 0.21) and outperformed PRS calculated using all variants (P-values ranged from 7.28E−03 to 0.16; Betas ranged from 0.06 to 0.18). PRSgene were also associated with AUD in an EA target dataset (P-value = 0.02, Beta = 0.11). In AA, individuals in the highest PRSgene decile had an odds ratio of 1.76 (95% CI: 1.32–2.34) to develop AUD compared to those in the lowest decile. The 410 genes were enriched in 54 Gene Ontology biological processes, including ethanol oxidation and processes involving the synaptic system, which are known to be AUD-related. In addition, 26 genes were targets of drugs used to treat AUD or other diseases that might be considered for repurposing to treat AUD. Our study demonstrated that the gene-based PRS had improved performance in evaluating AUD risk in AA and provided new insight into AUD genetics.

Aberrant connectivity of large-scale brain networks has been observed among individuals with alcohol use disorders (AUDs) as well as in those at risk, suggesting deficits in neural communication between brain regions in the liability to develop AUD. Electroencephalographical (EEG) coherence, which measures the degree of synchrony between brain regions, may be a useful measure of connectivity patterns in neural networks for studying the genetics of AUD. In 8810 individuals (6644 of European and 2166 of African ancestry) from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a Multi-Trait Analyses of genome-wide association studies (MTAG) on parietal resting-state theta (3–7 Hz) EEG coherence, which previously have been associated with AUD. We also examined developmental effects of GWAS findings on trajectories of neural connectivity in a longitudinal subsample of 2316 adolescent/young adult offspring from COGA families (ages 12–30) and examined the functional and clinical significance of GWAS variants. Six correlated single nucleotide polymorphisms located in a brain-expressed lincRNA (ENSG00000266213) on chromosome 18q23 were associated with posterior interhemispheric low theta EEG coherence (3–5 Hz). These same variants were also associated with alcohol use behavior and posterior corpus callosum volume, both in a subset of COGA and in the UK Biobank. Analyses in the subsample of COGA offspring indicated that the association of rs12954372 with low theta EEG coherence occurred only in females, most prominently between ages 25 and 30 (p

Shared genetic factors contribute to the high degree of comorbidity among externalizing problems (e.g. substance use and antisocial behavior). We leverage this common genetic etiology to identify genetic influences externalizing problems in participants from the Collaborative Study on the Genetics of Alcoholism (European ancestry = 7,568; African ancestry = 3,274). We performed a family-based genome-wide association study (GWAS) on externalizing scores derived from criterion counts of five DSM disorders (alcohol dependence, alcohol abuse, illicit drug dependence, illicit drug abuse, and either antisocial personality disorder or conduct disorder). We meta analyzed these results with a similar measure of externalizing in an independent sample, Spit for Science (combined sample N = 15,112). We did not discover any robust genome-wide significant signals. Polygenic scores derived from the ancestry-specific GWAS summary statistics predicted externalizing problems in an independent European ancestry sample, but not in those of African ancestry. However, these PRS were no longer significant after adjusting for multiple testing. Larger samples with deep phenotyping are necessary for the discovery of SNPs related to externalizing problems.

Neurodevelopmental abnormalities in neural connectivity have been long implicated in the etiology of schizophrenia (SCZ); however, it remains unclear whether these neural connectivity patterns are associated with genetic risk for SCZ in unaffected individuals (i.e., an absence of clinical features of SCZ or a family history of SCZ). We examine whether polygenic risk scores (PRS) for SCZ are associated with functional neural connectivity in adolescents and young adults without SCZ, whether this association is moderated by sex and age, and if similar associations are observed for genetically related neuropsychiatric PRS. One-thousand four-hundred twenty-six offspring from 913 families, unaffected with SCZ, were drawn from the Collaborative Study of the Genetics of Alcoholism (COGA) prospective cohort (median age at first interview = 15.6 (12–26), 51.6% female, 98.1% European American, 41% with a family history of alcohol dependence). Participants were followed longitudinally with resting-state EEG connectivity (i.e., coherence) assessed every two years. Higher SCZ PRS were associated with elevated theta (3–7 Hz) and alpha (7–12 Hz) EEG coherence. Associations differed by sex and age; the most robust associations were observed between PRS and parietal-occipital, central-parietal, and frontal-parietal alpha coherence among males between ages 15–19 (B: 0.15–0.21, p –4). Significant associations among EEG coherence and Bipolar and Depression PRS were observed, but differed from SCZ PRS in terms of sex, age, and topography. Findings reveal that polygenic risk for SCZ is robustly associated with increased functional neural connectivity among young adults without a SCZ diagnosis. Striking differences were observed between men and women throughout development, mapping onto key periods of risk for the onset of psychotic illness and underlining the critical importance of examining sex differences in associations with neuropsychiatric PRS across development.

Despite moderate heritability, only one study has identified genomewide significant loci for cannabis-related phenotypes. We conducted meta-analyses of genomewide association study (GWAS) data on 2,080 DSM-IV cannabis dependent cases and 6,435 cannabis exposed controls of European descent. A cluster of correlated single nucleotide polymorphisms (SNPs) in a novel region on chromosome 10 was genomewide significant (lowest p = 1.3E-8). Among the SNPs, rs1409568 showed enrichment for H3K4me1 and H3K427ac marks, suggesting its role as an enhancer in addiction-relevant brain regions, such as the dorsolateral prefrontal cortex and the angular and cingulate gyri. This SNP is also predicted to modify binding scores for several transcription factors. We found modest evidence for replication for rs1409568 in an independent cohort of African-American (896 cases and 1591 controls; p=0.03) but not European-American (781 cases and 1905 controls) participants. The combined meta-analysis (3,757 cases and 9,931 controls) indicated trend-level significance for rs1409568 (p=2.85E-7). No genomewide significant loci emerged for cannabis dependence criterion count (n=8,050). There was also evidence that the minor allele of rs1409568 was associated with a 2.1% increase in right hippocampal volume in an independent sample of 430 European-American college students (fwe-p=.007). The identification and characterization of genomewide significant loci for cannabis dependence is amongst the first steps towards understanding the biological contributions to the etiology of this psychiatric disorder, which appears to be rising in some developed nations.

Twin studies indicate that latent genetic factors overlap across comorbid psychiatric disorders. In this study, we used a novel approach to elucidate shared genetic factors across psychiatric outcomes by clustering single nucleotide polymorphisms based on their genome-wide association patterns. We applied latent profile analysis (LPA) to p-values resulting from genome-wide association studies across three phenotypes: symptom counts of alcohol dependence (AD), antisocial personality disorder (ASP), and major depression (MD), using the European-American case-control genome-wide association study subsample of the collaborative study on the genetics of alcoholism (N = 1399). In the 3-class model, classes were characterized by overall low associations (85.6% of SNPs), relatively stronger association only with MD (6.8%), and stronger associations with AD and ASP but not with MD (7.6%), respectively. These results parallel the genetic factor structure identified in twin studies. The findings suggest that applying LPA to association results across multiple disorders may be a promising approach to identify the specific genetic etiologies underlying shared genetic variance.

Maximum number of alcoholic drinks consumed in a 24-h period (maxdrinks) is a heritable (50 %) trait and is strongly correlated with vulnerability to excessive alcohol consumption and subsequent alcohol dependence (AD). Several genome-wide association studies (GWAS) have studied alcohol dependence, but few have concentrated on excessive alcohol consumption. We performed two GWAS using maxdrinks as an excessive alcohol consumption phenotype: one in 118 extended families (N = 2,322) selected from the Collaborative Study on the Genetics of Alcoholism (COGA), and the other in a case-control sample (N = 2,593) derived from the Study of Addiction: Genes and Environment (SAGE). The strongest association in the COGA families was detected with rs9523562 (p = 2.1 × 10(-6)) located in an intergenic region on chromosome 13q31.1; the strongest association in the SAGE dataset was with rs67666182 (p = 7.1 × 10(-7)), located in an intergenic region on chromosome 8. We also performed a meta-analysis with these two GWAS and demonstrated evidence of association in both datasets for the LMO1 (p = 7.2 × 10(-7)) and PLCL1 genes (p = 4.1 × 10(-6)) with maxdrinks. A variant in AUTS2 and variants in INADL, C15orf32 and HIP1 that were associated with measures of alcohol consumption in a meta-analysis of GWAS studies and a GWAS of alcohol consumption factor score also showed nominal association in the current meta-analysis. The present study has identified several loci that warrant further examination in independent samples. Among the top SNPs in each of the dataset (p ≤ 10(-4)) far more showed the same direction of effect in the other dataset than would be expected by chance (p = 2 × 10(-3), 3 × 10(-6)), suggesting that there are true signals among these top SNPs, even though no SNP reached genome-wide levels of significance.

Several studies have identified genes associated with alcohol use disorders, but the variation in each of these genes explains only a small portion of the genetic vulnerability. The goal of the present study was to perform a genome-wide association study (GWAS) in extended families from the Collaborative Study on the Genetics of Alcoholism (COGA) to identify novel genes affecting risk for alcohol dependence. To maximize the power of the extended family design we used a quantitative endophenotype, measured in all individuals: number of alcohol dependence symptoms endorsed (symptom count). Secondary analyses were performed to determine if the single nucleotide polymorphisms (SNPs) associated with symptom count were also associated with the dichotomous phenotype, DSM-IV alcohol dependence. This family-based GWAS identified SNPs in C15orf53 that are strongly associated with DSM-IV alcohol (p=4.5×10−8, inflation corrected p=9.4×10−7). Results with DSM-IV alcohol dependence in the regions of interest support our findings with symptom count, though the associations were less significant. Attempted replications of the most promising association results were conducted in two independent samples: non-overlapping subjects from the Study of Addiction: Genes and Environment (SAGE) and the Australian twin-family study of alcohol use disorders (OZALC). Nominal association of C15orf53 with symptom count was observed in SAGE. The variant that showed strongest association with symptom count, rs12912251 and its highly correlated variants (D′=1, r2≥ 0.95), has previously been associated with risk for bipolar disorder.

A coding variant in alcohol dehydrogenase 1B (ADH1B) (rs1229984) that leads to the replacement of Arg48 with His48 is common in Asian populations and reduces their risk for alcoholism, but because of very low allele frequencies the effects in European or African populations have been difficult to detect. We genotyped and analyzed this variant in three large European and African-American case-control studies in which alcohol dependence was defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria, and demonstrated a strong protective effect of the His48 variant (odds ratio (OR) 0.34, 95% confidence interval (CI) 0.24, 0.48) on alcohol dependence, with genome-wide significance (6.6 × 10(-10)). The hypothesized mechanism of action involves an increased aversive reaction to alcohol; in keeping with this hypothesis, the same allele is strongly associated with a lower maximum number of drinks in a 24-hour period (lifetime), with P=3 × 10(-13). We also tested the effects of this allele on the development of alcoholism in adolescents and young adults, and demonstrated a significantly protective effect. This variant has the strongest effect on risk for alcohol dependence compared with any other tested variant in European populations.

Topographical patterns of bipolar EEG coherence are frequency specific, indicating the presence of diverse neuroanatomical and neurophysiological factors in EEG production. Bipolar EEG coherence values were calculated at 50 frequency bins ranging from 3 to 28 Hz for 39 coherence pairs. Data were derived from 4.25 min of resting EEG obtained from 106 healthy adult male subjects and analyzed in 0.5 Hz bins by Fourier transform methods. Frequency bands were clearly separated at 8.5 and 13 Hz, with a less distinct separations at 6 and 20 Hz. Within pair (non-topographic) and across pair (topographic), measures gave similar patterns of separation. Significant pathways were primarily anterior-posterior interhemispheric or perpendicular to the anterior-posterior axis. There was little difference between left and right for comparable pairs. Theta band coherent activity involves distinct midline and temporal sources, with temporal sources showing anterior/posterior differentiation. In contrast, alpha activity has a distinct posterior focus, while beta activity shows no clear global structure. A spatially homogeneous model based on characteristics of thalamocortical connectivity accounts for much of the data, but departures from the model indicate the contribution of other neural factors to coherence.

We report genetic linkage and association findings which implicate the gene encoding the muscarinic acetylcholine receptor M2 (CHRM2) in the modulation of a scalp-recorded electrophysiological phenotype. The P3 (P300) response was evoked using a three-stimulus visual oddball paradigm and a phenotype that relates to the energy in the theta band (4-5 Hz) was analyzed. Studies have shown that similar electrophysiological measures represent cognitive correlates of attention, working memory, and response selection; a role has been suggested for the ascending cholinergic pathway in the same functions. The results of our genetic association tests, combined with knowledge regarding the presence of presynaptic cholinergic M2 autoreceptors in the basal forebrain, indicate that the cognitive processes required by the experiment may in part be mediated by inhibitory neural networks. These findings underscore the utility of electrophysiology and neurogenetics in the understanding of cognitive function and the study of brain-related disorders.

Results from twin studies suggest that overlapping genetic factors influence alcohol dependence and illicit drug dependence. Using data from the Collaborative Study on the Genetics of Alcoholism (COGA), we examined the association between 69 SNPs in the GABAA receptor gene cluster on chromosome 4 and marijuana and illicit drug dependence, individually, and as co-occurring phenotypes with alcohol dependence. Results suggested association between marijuana dependence and illicit drug dependence with SNPs in the GABRA2 gene. Interestingly, the evidence for association previously observed with alcohol dependence came only from individuals with comorbid illicit drug dependence. There was no association with other genes in the GABAA cluster on chromosome 4 with illicit drug dependence.

We use findings from the behavior genetics literature about how genetic factors (latently) influence alcohol dependence and related disorders to develop and test hypotheses about the risk associated with a specific gene, GABRA2, across different developmental stages. This gene has previously been associated with adult alcohol dependence in the Collaborative Study of the Genetics of Alcoholism (COGA) sample [Edenberg, H. J., Dick, D. M., Xuei, X., Tian, H., Almasy, L., Bauer, L. O., Crowe, R., Goate, A., Hesselbrock, V., Jones, K. A., Kwon, J., Li, T. K., Nurnberger Jr., J. I., O'Connor, S. J., Reich, T., Rice, J., Schuckit, M., Porjesz, B., Foroud, T., and Begleiter, H. (2004). Am. J. Hum. Genet. 74:705-714] and other studies [Covault, J., Gelernter, J., Hesselbrock, V., Nellissery, M., and Kranzler, H. R. (2004). Am. J. Med. Genet. B Neuropsychiatr. Genet. 129B:104-109; Lappalainen, J., Krupitsky, E., Remizov, M., Pchelina, S., Taraskina, A., Zvartau, E., Somberg, L. K., Covault, J., Kranzler, H. R., Krystal, J., and Gelernter, J. (2005). Alcohol. Clin. Exp. Res. 29:493-498]. In a sample of children and adolescents ascertained as part of the COGA project, we find that GABRA2 is significantly associated with childhood conduct disorder symptoms, but not with childhood alcohol dependence symptoms. A consistent elevation in risk for alcohol dependence associated with GABRA2 is not evident until the mid-20s and then remains throughout adulthood. GABRA2 is also associated with other drug dependence in our sample, both in adolescence and adulthood.

Intelligence, as measured by standardized psychological tests, has been shown to be highly heritable, though identifying specific genes influencing general intelligence has proven difficult. We conducted genome-wide linkage analyses to identify chromosomal regions containing genes influencing intelligence, as measured by WAIS full-scale IQ (FSIQ), performance IQ (PIQ) and verbal IQ (VIQ). Non-parametric multipoint linkage analyses were conducted with Merlin-regress software, using a sample of 1,111 genotyped and phenotyped individuals from 201 families, ascertained as part of the Collaborative Study on the Genetics of Alcoholism (COGA). The strongest evidence of linkage was obtained for FSIQ on chromosome 6 (LOD=3.28, 12 cM) near the marker D6S1006. This region was also implicated with suggestive linkage in a recently published genome screen of IQ in Australian and Dutch twin pairs, and it has been implicated in linkage studies of developmental dyslexia. Our findings provide further support that chromosome 6p contains gene(s) affecting intelligence.

We describe a method to obtain estimates of EEG signal complexity using the well-established wavelet packet transform with best basis selection. In particular, we use the two-dimensional wavelet packet transform to obtain estimates of the complexity of two-dimensional images. This allows us to calculate complexity estimates of high-resolution brain potential maps generated from 61 scalp electrode Visual Oddball paradigm, grand-mean data. A significant reduction in the complexity of the surface Laplacian time-slices is observed during and after the Visual Potential 300 (P3) event for the target case, possibly as a result of increased spatial synchrony associated with visual-related tasks. We also present the results of a statistical analysis of the largest principal component of the time-varying complexity curves, for control, high-risk, and alcoholic groups of male subjects. Parametric and non-parametric analyses show differences in the complexity data which are significant between the control group and the alcoholic and high-risk groups.

This paper describes a method for estimating a set of spatial components (brain maps) and temporal components (waveforms) of brain potentials. These components play the role of bases of a coordinate system, in the sense that the brain potentials of any subject can be represented as superpositions of these components. The representation is unique given the spatial and temporal components, and this decomposition is particularly appealing for comparing the brain potentials of different subjects (say alcoholics and controls). It can also be used for single trial modeling, clinical classification of patients, and data filtering. The method is based on the topographic component model (TCM, Mocks 1988) which models brain potentials in a trilinear form. We extend the TCM in two aspects. First, the diagonal amplitude matrix is replaced by a general loading matrix based on some neurophysiological considerations. Secondly, the number of spatial components and the number of temporal components can be different. The spatial components and temporal components are obtained respectively by performing singular value decomposition (SVD). This method is illustrated with visual P3 data.

To examine the topographic relationship of P3(00) between the visual and auditory modalities, especially to examine whether there are any modality-specific hemispheric differences of P3 in normal adults. Methods: The P3s were recorded from the same 41 normal right-handed males between the ages of 20 and 33 in both a typical auditory oddball task and a visual oddball paradigm with novel stimuli, with an extensive set of 61 scalp electrodes. In addition to the visual comparison and quantitative assessment of current source density (CSD) maps between the two modalities, canonical correlation analyses on the P3 raw amplitudes and examination of interaction effects of modality × location on both raw and normalized P3 data were performed. Results: The canonical correlation between modalities was generally high, especially at the left parietal brain region. There were no significant hemispheric effects in anterior brain but significant left-greater- than-right hemispheric effects in posterior brain regions in both modalities; modality-specific hemispheric effect was observed only at the parietal region. Strong surface current density activities were observed in the midline parietal-occipital area, and left and right boundary areas of temporal and inferior frontal region. Conclusions: The topographic similarities between P3s recorded in the visual and auditory modality outnumber the differences. Combining data from CSD assessments and profile analysis of P3 topography support the hypothesis of multiple generators of P3 that are differentially active in processing stimuli from different sensory modalities and are not symmetrically distributed between the two hemispheres.

Multiresolution analysis is a potentially useful tool to enhance the brain's electrical fields (spatial distributions of event-related potentials (ERP)), and to bring out spatial features which may not be seen in the fields before enhancement. For comparing different images (slices from ERP of different subjects or from the same subject but evoked by different stimuli), we define a measure (surface energy) at each decomposition scale and for different wavelets. The best wavelet and the best level for comparing the given images can be chosen based on this measure. Our experiments show that for very similar images, their difference can be brought out at some scale level. Three preprocessing steps are needed in order to carry out this wavelet analysis. First, a wavelet denoising step is needed to remove noise from the raw ERP. Secondly, a one-to-one mapping is needed to map scalp surface into a square, because the current wavelet analysis theory and algorithm are constructed on regular domains. Finally, a fitting or interpolation step is needed to construct an image on a regular grid in order to apply the fast wavelet transform algorithms.

In this paper, we propose new multivariate composite estimators (MCE) to track multiple channel potential waves of individual and grand averages of recorded potentials at the scalp from a number of trials in a group of subjects. The advantages of these estimators over simple averages used in the literature are that they have larger signal to noise ratios (SNR), and that they have taken into account variations and correlations of the recorded potentials at the electrode sites as well as differences among subjects. Multivariate techniques and composite concept are used for deriving the estimators. We also provide an application to human event-related potentials in a memory for faces experiment.