Edwin J van den Oord

Virginia Commonwealth University, Richmond, VA, United States

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Publications (19)157.4 Total impact

  • Karolina A Aberg, Edwin Jcg van den Oord
    Biomarkers in Medicine 06/2014; 8(5):607-11. · 3.22 Impact Factor
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    ABSTRACT: Clozapine is a particularly effective antipsychotic medication but its use is curtailed by the risk of clozapine-induced agranulocytosis/granulocytopenia (CIAG), a severe adverse drug reaction occurring in up to 1% of treated individuals. Identifying genetic risk factors for CIAG could enable safer and more widespread use of clozapine. Here we perform the largest and most comprehensive genetic study of CIAG to date by interrogating 163 cases using genome-wide genotyping and whole-exome sequencing. We find that two loci in the major histocompatibility complex are independently associated with CIAG: a single amino acid in HLA-DQB1 (126Q) (P ¼ 4.7 Â 10 À 14 , odds ratio (OR) ¼ 0.19, 95% confidence interval (CI) ¼ 0.12–0.29) and an amino acid change in the extracellular binding pocket of HLA-B (158T) (P ¼ 6.4 Â 10 À 10 , OR ¼ 3.3, 95% CI ¼ 2.3–4.9). These associations dovetail with the roles of these genes in immunogenetic phenotypes and adverse drug responses for other medications, and provide insight into the pathophysiology of CIAG.
    01/2014; 1718192123252628(27).
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    ABSTRACT: Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17–29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn’s disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.
    Nature Genetics 08/2013; AOP. · 35.21 Impact Factor
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    ABSTRACT: Aim: As the primary relevant tissue (brain) for psychiatric disorders is commonly not available, we aimed to investigate whether blood can be used as a proxy in methylation studies on the basis of two models. In the 'signature' model methylation-disease associations occur because a disease-causing factor affected methylation in the blood. In the 'mirror-site' model the methylation status in the blood is correlated with the corresponding disease-causing site in the brain. Materials, methods & results: Methyl-binding domain enrichment and next-generation sequencing of the blood, cortex and hippocampus from four haloperidol-treated and ten untreated C57BL/6 mice revealed high levels of correlation in methylation across tissues. Despite the treatment inducing a large number of methylation changes, this correlation remains high. Conclusion: Our results show that, consistent with the signature model, factors that affect brain processes (i.e., haloperidol) leave biomarker signatures in the blood and, consistent with the mirror-site model, the methylation status of many sites in the blood mirror those in the brain.
    Epigenomics 08/2013; 5(4):367-77. · 2.43 Impact Factor
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    ABSTRACT: Schizophrenia (SCZ) is a devastating psychiatric condition. Identifying the specific genetic variants and pathways that increase susceptibility to SCZ is critical to improve disease understanding and address the urgent need for new drug targets. To identify SCZ susceptibility genes. We integrated results from a meta-analysis of 18 genome-wide association studies (GWAS) involving 1,085,772 single-nucleotide polymorphisms (SNPs) and 6 databases that showed significant informativeness for SCZ. The 9380 most promising SNPs were then specifically genotyped in an independent family-based replication study that, after quality control, consisted of 8107 SNPs. Linkage meta-analysis, brain transcriptome meta-analysis, candidate gene database, OMIM, relevant mouse studies, and expression quantitative trait locus databases. We included 11,185 cases and 10,768 control subjects from 6 databases and, after quality control 6298 individuals (including 3286 cases) from 1811 nuclear families. Case-control status for SCZ. Replication results showed a highly significant enrichment of SNPs with small P values. Of the SNPs with replication values of P.01, the proportion of SNPs that had the same direction of effects as in the GWAS meta-analysis was 89% in the combined ancestry group (sign test, P < 2.20 x 10(-16) and 93% in subjects of European ancestry only (P < 2.20 < 10(-16)). Our results supported the major histocompatibility complex region showing a3.7-fold overall enrichment of replication values of P < .01 in subjects from European ancestry. We replicated SNPs in TCF4 (P = 2.53 x 10(-10)) and NOTCH4 (P = 3.16 x 10(-7)) that are among the most robust SCZ findings. More novel findings included POM121L2 (P = 3.51 x 10(-7)), AS3MT (P = 9.01 x 10(-7)), CNNM2 (P = 6.07 = 10(-7)), and NT5C2(P = 4.09 x 10(-7)). To explore the many small effects, we performed pathway analyses. The most significant pathways involved neuronal function (axonal guidance, neuronal systems, and L1 cell adhesion molecule interaction)and the immune system (antigen processing, cell adhesion molecules relevant to T cells, and translocation to immunological synapse). We replicated novel SCZ disease genes and pathogenic pathways. Better understanding the molecular and biological mechanisms involved with schizophrenia may improve disease management and may identify new drug targets.
    Archives of General Psychiatry 06/2013; 70(6):573-81. · 13.77 Impact Factor
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    ABSTRACT: BACKGROUND: In methylome-wide association studies (MWAS) there are many possible differences between cases and controls (e.g. related to life style, diet, and medication use) that may affect the methylome and produce false positive findings. An effective approach to control for these confounders is to first capture the major sources of variation in the methylation data and then regress out these components in the association analyses. This approach is, however, computationally very challenging due to the extremely large number of methylation sites in the human genome.Result: We introduce MethylPCA that is specifically designed to control for potential confounders in studies where the number of methylation sites is extremely large. MethylPCA offers a complete and flexible data analysis including 1) an adaptive method that performs data reduction prior to PCA by empirically combining methylation data of neighboring sites, 2) an efficient algorithm that performs a principal component analysis (PCA) on the ultra high-dimensional data matrix, and 3) association tests. To accomplish this MethylPCA allows for parallel execution of tasks, uses C++ for CPU and I/O intensive calculations, and stores intermediate results to avoid computing the same statistics multiple times or keeping results in memory. Through simulations and an analysis of a real whole methylome MBD-seq study of 1,500 subjects we show that MethylPCA effectively controls for potential confounders. CONCLUSIONS: MethylPCA provides users a convenient tool to perform MWAS. The software effectively handles the challenge in memory and speed to perform tasks that would be impossible to accomplish using existing software when millions of sites are interrogated with the sample sizes required for MWAS.
    BMC Bioinformatics 03/2013; 14(1):74. · 3.02 Impact Factor
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    ABSTRACT: BACKGROUND: Methylation studies are a promising complement to genetic studies of DNA sequence. However, detailed prior biological knowledge is typically lacking, so methylome-wide association studies (MWAS) will be critical to detect disease relevant sites. A cost-effective approach involves the next-generation sequencing (NGS) of single-end libraries created from samples that are enriched for methylated DNA fragments. A limitation of single-end libraries is that the fragment size distribution is not observed. This hampers several aspects of the data analysis such as the calculation of enrichment measures that are based on the number of fragments covering the CpGs. RESULTS: We developed a non-parametric method that uses isolated CpGs to estimate sample-specific fragment size distributions from the empirical sequencing data. Through simulations we show that our method is highly accurate. While the traditional (extended) read count methods resulted in severely biased coverage estimates and introduces artificial inter-individual differences, through the use of the estimated fragment size distributions we could remove these biases almost entirely. Furthermore, we found correlations of 0.999 between coverage estimates obtained using fragment size distributions that were estimated with our method versus those that were "observed" in paired-end sequencing data. CONCLUSIONS: We propose a non-parametric method for estimating fragment size distributions that is highly precise and can improve the analysis of cost-effective MWAS studies that sequence single-end libraries created from samples that are enriched for methylated DNA fragments.
    BMC Bioinformatics 02/2013; 14(1):50. · 3.02 Impact Factor
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    ABSTRACT: Aim: We studied the use of methyl-CpG binding domain (MBD) protein-enriched genome sequencing (MBD-seq) as a cost-effective screening tool for methylome-wide association studies (MWAS). Materials & methods: Because MBD-seq has not yet been applied on a large scale, we first developed and tested a pipeline for data processing using 1500 schizophrenia cases and controls plus 75 technical replicates with an average of 68 million reads per sample. This involved the use of technical replicates to optimize quality control for multi- and duplicate-reads, an in silico experiment to identify CpGs in loci with alignment problems, CpG coverage calculations based on multiparametric estimates of the fragment size distribution, a two-stage adaptive algorithm to combine data from correlated adjacent CpG sites, principal component analyses to control for confounders and new software tailored to handle the large data set. Results: We replicated MWAS findings in independent samples using a different technology that provided single base resolution. In an MWAS of age-related methylation changes, one of our top findings was a previously reported robust association involving GRIA2. Our results also suggested that owing to the many confounding effects, a considerable challenge in MWAS is to identify those effects that are informative about disease processes. Conclusion: This study showed the potential of MBD-seq as a cost-effective tool in large-scale disease studies.
    Epigenomics 12/2012; 4(6):605-21. · 2.43 Impact Factor
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    ABSTRACT: 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, P(SR) and P(OR), 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 P(SR)P-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.
    European journal of human genetics: EJHG 04/2012; 20(10):1078-84. · 3.56 Impact Factor
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    ABSTRACT: SIRT1 is a NAD(+)-dependent deacetylase that governs a number of genetic programs to cope with changes in the nutritional status of cells and organisms. Behavioral responses to food abundance are important for the survival of higher animals. Here we used mice with increased or decreased brain SIRT1 to show that this sirtuin regulates anxiety and exploratory drive by activating transcription of the gene encoding the monoamine oxidase A (MAO-A) to reduce serotonin levels in the brain. Indeed, treating animals with MAO-A inhibitors or selective serotonin reuptake inhibitors (SSRIs) normalized anxiety differences between wild-type and mutant animals. SIRT1 deacetylates the brain-specific helix-loop-helix transcription factor NHLH2 on lysine 49 to increase its activation of the MAO-A promoter. Both common and rare variations in the SIRT1 gene were shown to be associated with risk of anxiety in human population samples. Together these data indicate that SIRT1 mediates levels of anxiety, and this regulation may be adaptive in a changing environment of food availability.
    Cell 12/2011; 147(7):1459-72. · 31.96 Impact Factor
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    ABSTRACT: Anxiety disorders are common psychiatric conditions that are highly comorbid with each other and related phenotypes such as depression, likely due to a shared genetic basis. Fear-related behaviors in mice have long been investigated as potential models of anxiety disorders, making integration of information from both murine and human genetic data a powerful strategy for identifying potential susceptibility genes for these conditions. We combined genome-wide association analysis of fear-related behaviors with strain distribution pattern analysis in heterogeneous stock mice to identify a preliminary list of 52 novel candidate genes. We ranked these according to three complementary sources of prior anxiety-related genetic data: 1) extant linkage and knockout studies in mice, 2) a meta-analysis of human linkage scans, and 3) a preliminary human genome-wide association study. We genotyped tagging single nucleotide polymorphisms covering the nine top-ranked regions in a two-stage association study of 1316 subjects from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders chosen for high or low genetic loading for anxiety-spectrum phenotypes (anxiety disorders, neuroticism, and major depression). Multiple single nucleotide polymorphisms in the PPARGC1A gene demonstrated association in both stages that survived gene-wise correction for multiple testing. Integration of genetic data across human and murine studies suggests PPARGC1A as a potential susceptibility gene for anxiety-related disorders.
    Biological psychiatry 08/2011; 70(9):888-96. · 8.93 Impact Factor
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    ABSTRACT: Pharmacogenomics is yet to fulfill its promise of manifestly altering clinical medicine. As one example, a predictive test for tardive dyskinesia (TD) (an adverse drug reaction consequent to antipsychotic exposure) could greatly improve the clinical treatment of schizophrenia but human studies are equivocal. A complementary approach is the mouse-then-human design in which a valid mouse model is used to identify susceptibility loci, which are subsequently tested in human samples. We used inbred mouse strains from the Mouse Phenome Project to estimate the heritability of haloperidol-induced activity and orofacial phenotypes. In all, 159 mice from 27 inbred strains were chronically treated with haloperidol (3 mg kg(-1) per day via subdermal slow-release pellets) and monitored for the development of vacuous chewing movements (VCMs; the mouse analog of TD) and other movement phenotypes derived from open-field activity and the inclined screen test. The test battery was assessed at 0, 30, 60, 90 and 120 days in relation to haloperidol exposure. As expected, haloperidol caused marked changes in VCMs, activity in the open field and extrapyramidal symptoms (EPS). Unexpectedly, factor analysis demonstrated that these measures were imprecise assessments of a latent construct rather than discrete constructs. The heritability of a composite phenotype was ∼0.9 after incorporation of the longitudinal nature of the design. Murine VCMs are a face valid animal model of antipsychotic-induced TD, and heritability estimates from this study support the feasibility of mapping of susceptibility loci for VCMs.
    The Pharmacogenomics Journal 11/2010; 12(2):147-55. · 5.13 Impact Factor
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    ABSTRACT: The relation of gamma-aminobutyric acid (GABA) to alcohol dependence (AD) has been widely studied. Several previous studies suggest that GABA may be involved in alcohol withdrawal, tolerance, and the symptoms that form an AD diagnosis. The genes coding for glutamate decarboxylase (GAD), the rate-limiting enzyme in GABA synthesis, are of potential interest for their association to ethanol consumption and AD. There are two isoforms of GAD, GAD1 and GAD2, which were reported to be associated with AD in males of Han Taiwanese (GAD1) and Russian (GAD2) ancestry. The present study examined the association of the two GAD isoforms with AD and relevant alcohol-related traits in the Irish Affected Sib Pair Study of Alcohol Dependence [Prescott, C.A., Sullivan, P.F., Myers, J.M., Patterson, D.G., Devitt, M., Halberstadt, L.J., Walsh, D., Kendler, K.S., 2005. The Irish Affected Sib Pair Study of Alcohol Dependence: study methodology and validation of diagnosis by interview and family history. Alcohol.-Clin. Exp. Res. 29 (3) 417-429]. Participants were recruited in Ireland, including 575 independent cases who met DSM-IV AD criteria and 530 controls, screened for heavy drinking. We first conducted case-control analyses of the GAD genes with AD and, within the cases, examined associations with age at onset of AD, withdrawal symptoms, and two quantitative measures: initial sensitivity and tolerance (based on scales from the Self-Rating of the Effects of Ethanol) [Schuckit, M.A., Smith, T.L., Tipp, J.E., 1997. The self-rating of the effects of alcohol (SRE) form as a retrospective measure of the risk for alcoholism. Addiction 92, 979-988]. A total of 29 SNPs were genotyped for GAD1 and GAD2 using the Illumina GoldenGate protocols. Statistical procedures were implemented to control for false discovery rates (FDR). Nine of 29 markers with minor allele frequencies less than 0.01 were removed from standard analysis; the remaining 20 markers were all in Hardy-Weinberg equilibrium. Three markers in the intronic regions of GAD1 were associated with initial sensitivity to alcohol (P=0.002); the associations remained significant after a FDR based correction for multiple testing. In addition, one marker located 3kb upstream of GAD1 exhibited association with age at onset of AD (P=0.0001). Gender specific effects were observed in results of both single marker and haplotype analyses. We found no evidence for the association of GAD genes with AD but significant association of GAD1 with initial sensitivity and age at onset of AD. Our findings suggest that the underlying pathophysiology regulated by genes like GAD1 may be more directly related to the component processes that form AD than to the clinical disorder.
    Drug and alcohol dependence 01/2009; 101(1-2):80-7. · 3.60 Impact Factor
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    ABSTRACT: The genes coding for ethanol metabolism enzymes [alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH)] have been widely studied for their influence on the risk to develop alcohol dependence (AD). However, the relation between polymorphisms of these metabolism genes and AD in Caucasian subjects has not been clearly established. The present study examined evidence for the association of alcohol metabolism genes with AD in the Irish Affected Sib Pair Study of alcohol dependence. We conducted a case-control association study with 575 independent subjects who met Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, AD diagnosis and 530 controls. A total of 77 single nucleotide polymorphisms (SNPs) in the seven ADH (ADH1-7) and two ALDH genes (ALDH1A1 and ALDH2) were genotyped using the Illumina GoldenGate protocols. Several statistical procedures were implemented to control for false discoveries. All markers with minor allele frequency greater than 0.01 were in Hardy-Weinberg equilibrium. Numerous SNPs in ADH genes showed association with AD, including one marker in the coding region of ADH1C (rs1693482 in exon6, Ile271Gln). Haplotypic association was observed in the ADH5 and ADH1C genes, and in a long haplotype block formed by the ADH1A and ADH1B loci. We detected two significant interactions between pairs of markers in intron 6 of ADH6 and intron 12 of ALDH2 (p = 5 x 10(-5)), and 5' of both ADH4 and ADH1A (p = 2 x 10(-4)). We found evidence for the association of several ADH genes with AD in a sample of Western European origin. The significant interaction effects between markers in ADH and ALDH genes suggest possible epistatic roles between alcohol metabolic enzymes in the risk for AD.
    Alcoholism Clinical and Experimental Research 06/2008; 32(5):785-95. · 3.42 Impact Factor
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    ABSTRACT: Alcoholism is a phenotypically and probably genetically heterogeneous condition. Thus, one strategy for finding genes influencing liability to alcoholism is to study the components of alcoholism, which may be more directly related to the underlying pathophysiology than is clinical diagnosis. The goal of this study was to identify genomic regions containing susceptibility loci for alcohol-related traits. A 4-cM dense whole-genome linkage study was conducted in the Irish Affected Sib Pair Study of Alcohol Dependence. Probands, affected siblings, and parents were evaluated by structured interview. Variance component linkage analysis was applied to data from 485 families for 5 measures: initial sensitivity and tolerance (based on scales from the self-report of the effects of ethanol; maximum drinks within 24 hours, an empirically derived factor score based on withdrawal symptoms, and age at onset of alcohol dependence. Evidence for linkage (p<0.005) was found on 9 chromosomes. For age at onset, 2 regions were found on chromosome 9 (highest Lod=2.3, p=0.0005). For initial level of response to alcohol, suggestive regions were on chromosomes 1 and 11 (highest Lod=2.9, p=0.0001 on chromosome 11), while those for tolerance signals were on chromosomes 1, 6, and 22. Maximum drinking was associated with regions on chromosomes 12 and 18. For withdrawal symptoms, the highest peak was on chromosome 2 (Lod=2.2, p=0.0007). Using quantitative measures of components of alcohol dependence, we identified several regions of the genome that may contain susceptibility loci for specific alcohol-related traits and merit additional study.
    Alcoholism Clinical and Experimental Research 11/2006; 30(11):1807-16. · 3.42 Impact Factor
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    ABSTRACT: Alcoholism is a relatively common, chronic, disabling and often treatment-resistant disorder. Evidence from twin and adoption studies indicates a substantial genetic influence, with heritability estimates of 50-60%. We conducted a genome scan in the Irish Affected Sib Pair Study of Alcohol Dependence (IASPSAD). Most probands were ascertained through alcoholism treatment settings and were severely affected. Probands, affected siblings and parents were evaluated by structured interview. A 4 cM genome scan was conducted using 474 families of which most (96%) were comprised by affected sib pairs. Nonparametric and quantitative linkage analyses were conducted using DSM-IV alcohol dependence (AD) and number of DSM-IV AD symptoms (ADSX). Quantitative results indicate strong linkage for number of AD criteria to a broad region of chromosome 4, ranging from 4q22 to 4q32 (peak multipoint LOD=4.59, P=2.1 x 10(-6), at D4S1611). Follow-up analyses suggest that the linkage may be due to variation in the symptoms of tolerance and out of control drinking. There was evidence of weak linkage (LODs of 1.0-2.0) to several other regions, including 1q44, 13q31, and 22q11 for AD along with 2q37, 9q21, 9q34 and 18p11 for ADSX. The location of the chromosome 4 peak is consistent with results from prior linkage studies and includes the alcohol dehydrogenase gene cluster. The results of this study suggest the importance of genetic variation in chromosome 4 in the etiology and severity of alcoholism in Caucasian populations.
    Molecular Psychiatry 07/2006; 11(6):603-11. · 15.15 Impact Factor
  • American Journal of Psychiatry - AMER J PSYCHIAT. 01/2006; 163(5):941-942.
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    ABSTRACT: The purpose of this study was to determine whether a haplotype in the dystrobrevin binding protein 1 (DTNBP1) gene previously associated with schizophrenia not only increases the susceptibility to psychotic illness but also to a more or less clinically specific form of psychotic illness. In the Irish Study of High-Density Schizophrenia Families, subjects with psychotic illness (N=755) were given lifetime ratings of clinical features according to the Operational Criteria Checklist for Psychotic Illness. Exploratory and confirmatory factor analyses were used to extract five factors-hallucinations, delusions, negative, manic, and depressive symptoms-and to create factor-derived scores. The family-based transmission disequilibrium test operationalized in the program TRANSMIT was used to determine whether a high-risk haplotype in the DTNBP1 gene was overtransmitted to subjects in the upper 20th and 40th percentiles for each factor score. These results were compared to baseline overtransmission by examining the empirical distribution of chi-square statistics in groups of 5,000 replicates in which 20% and 40% of ill subjects were randomly selected. This analysis was done for both narrow and broad definitions of psychotic illness. Subjects in the upper 40th percentile for the negative symptom factor--in both the narrowly (p=0.004) and broadly (p=0.01) defined illness groups--were more likely to inherit the high-risk haplotype than would be expected by chance. No other significant relationships between clinical features and high-risk haplotype transmission were observed. The etiologically relevant variation in DTNBP1, which is in presumptive linkage disequilibrium with the high-risk haplotype, may predispose individuals to a form of psychotic illness associated with high levels of negative symptoms. This finding supports previous evidence suggesting that genetic factors influence the clinical heterogeneity of schizophrenia.
    American Journal of Psychiatry 11/2005; 162(10):1824-32. · 14.72 Impact Factor
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    ABSTRACT: Background A variety of species and experimental designs have been used to study genetic influences on alcohol dependence, ethanol response, and related traits. Integration of these heterogeneous data can be used to produce a ranked target gene list for additional investigation. Results In this study, we performed a unique multi-species evidence-based data integration using three microarray experiments in mice or humans that generated an initial alcohol dependence (AD) related genes list, human linkage and association results, and gene sets implicated in C. elegans and Drosophila. We then used permutation and false discovery rate (FDR) analyses on the genome-wide association studies (GWAS) dataset from the Collaborative Study on the Genetics of Alcoholism (COGA) to evaluate the ranking results and weighting matrices. We found one weighting score matrix could increase FDR based q-values for a list of 47 genes with a score greater than 2. Our follow up functional enrichment tests revealed these genes were primarily involved in brain responses to ethanol and neural adaptations occurring with alcoholism. Conclusions These results, along with our experimental validation of specific genes in mice, C. elegans and Drosophila, suggest that a cross-species evidence-based approach is useful to identify candidate genes contributing to alcoholism.
    BMC Genomics 13(8). · 4.40 Impact Factor