Dataset Information

Cross-disorder genomewide analysis of schizophrenia, bipolar disorder, and depression.

ABSTRACT: OBJECTIVE:Family and twin studies indicate substantial overlap of genetic influences on psychotic and mood disorders. Linkage and candidate gene studies have also suggested overlap across schizophrenia, bipolar disorder, and major depressive disorder. The purpose of this study was to apply genomewide association study (GWAS) analysis to address the specificity of genetic effects on these disorders. METHOD:The authors combined GWAS data from three large effectiveness studies of schizophrenia (CATIE, genotyped: N=741), bipolar disorder (STEP-BD, geno-typed: N=1,575), and major depressive disorder (STAR*D, genotyped: N=1,938) as well as from psychiatrically screened control subjects (NIMH-Genetics Repository: N=1,204). A two-stage analytic procedure involving an omnibus test of allele frequency differences among case and control groups was applied, followed by a model selection step to identify the best-fitting model of allelic effects across disorders. RESULTS:The strongest result was seen for a single nucleotide polymorphism near the adrenomedullin (ADM) gene (rs6484218), with the best-fitting model indicating that the effect was specific to bipolar II disorder. Findings also revealed evidence suggesting that several genes may have effects that transcend clinical diagnostic boundaries, including variants in NPAS3 that showed pleiotropic effects across schizophrenia, bipolar disorder, and major depressive disorder. CONCLUSIONS:This study provides the first genomewide significant evidence implicating variants near the ADM gene on chromosome 11p15 in psychopathology, with effects that appear to be specific to bipolar II disorder. Although genomewide significant evidence of cross-disorder effects was not detected, the results provide evidence that there are both pleiotropic and disorder-specific effects on major mental illness and illustrate an approach to dissecting the genetic basis of mood and psychotic disorders that can inform future large-scale cross-disorder GWAS analyses.

SUBMITTER: Huang J

PROVIDER: S-EPMC3880556 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Cross-disorder genomewide analysis of schizophrenia, bipolar disorder, and depression.

Huang Jie J Perlis Roy H RH Lee Phil H PH Rush A John AJ Fava Maurizio M Sachs Gary S GS Lieberman Jeffrey J Hamilton Steven P SP Sullivan Patrick P Sklar Pamela P Purcell Shaun S Smoller Jordan W JW

The American journal of psychiatry 20100816 10

<h4>Objective</h4>Family and twin studies indicate substantial overlap of genetic influences on psychotic and mood disorders. Linkage and candidate gene studies have also suggested overlap across schizophrenia, bipolar disorder, and major depressive disorder. The purpose of this study was to apply genomewide association study (GWAS) analysis to address the specificity of genetic effects on these disorders.<h4>Method</h4>The authors combined GWAS data from three large effectiveness studies of sch ...[more]

PMID: 20713499

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Project description:BACKGROUND: Schizophrenia, bipolar disorder, and major depression are devastating mental diseases, each with distinctive yet overlapping epidemiologic characteristics. Microarray and proteomics data have revealed genes which expressed abnormally in patients. Several single nucleotide polymorphisms (SNPs) and mutations are associated with one or more of the three diseases. Nevertheless, there are few studies on the interactions among the disease-associated genes and proteins. RESULTS: This study, for the first time, incorporated microarray and protein-protein interaction (PPI) databases to construct the PPI network of abnormally expressed genes in postmortem brain samples of schizophrenia, bipolar disorder, and major depression patients. The samples were collected from Brodmann area (BA) 10 of the prefrontal cortex. Abnormally expressed disease genes were selected by t-tests comparing the disease and control samples. These genes were involved in housekeeping functions (e.g. translation, transcription, energy conversion, and metabolism), in brain specific functions (e.g. signal transduction, neuron cell differentiation, and cytoskeleton), or in stress responses (e.g. heat shocks and biotic stress).The diseases were interconnected through several "switchboard"-like nodes in the PPI network or shared abnormally expressed genes. A "core" functional module which consisted of a tightly knitted sub-network of clique-5 and -4s was also observed. These cliques were formed by 12 genes highly expressed in both disease and control samples. CONCLUSIONS: Several previously unidentified disease marker genes and drug targets, such as SBNO2 (schizophrenia), SEC24C (bipolar disorder), and SRRT (major depression), were identified based on statistical and topological analyses of the PPI network. The shared or interconnecting marker genes may explain the shared symptoms of the studied diseases. Furthermore, the "switchboard" genes, such as APP, UBC, and YWHAZ, are proposed as potential targets for developing new treatments due to their functional and topological significance.

Project description:Schizophrenia, bipolar disorder and major depressive disorder (MDD) have all been associated with aberrant blood cytokine levels; however, neither the pattern of cytokine alterations nor the impact of clinical status have been compared across disorders. We performed a meta-analysis of blood cytokines in acutely and chronically ill patients with these major psychiatric disorders. Articles were identified by searching the PubMed, PsycInfo and Web of Science, and the reference lists of these studies. Sixty-eight studies met the inclusion criteria (40 schizophrenia, 10 bipolar disorder and 18 MDD) for acutely ill patients. Forty-six studies met the inclusion criteria (18 schizophrenia, 16 bipolar disorder and 12 MDD) for chronically ill patients. Levels of two cytokines (interleukin-6 (IL-6), tumor necrosis factor-? (TNF-?)), one soluble cytokine receptor (sIL-2R), and one cytokine receptor antagonist (IL-1RA) were significantly increased in acutely ill patients with schizophrenia, bipolar mania and MDD compared with controls (P<0.01). Following treatment of the acute illness, IL-6 levels significantly decreased in both schizophrenia and MDD (P<0.01); sIL-2R levels increased in schizophrenia; and IL-1RA levels in bipolar mania decreased. In chronically ill patients, the levels of IL-6 were significantly increased in schizophrenia, euthymic (but not depressed) bipolar disorder and MDD compared with controls (P<0.01). The levels of IL-1? and sIL-2R were significantly increased in both chronic schizophrenia and euthymic bipolar disorder. Overall, there were similarities in the pattern of cytokine alterations in schizophrenia, bipolar disorder and MDD during acute and chronic phases of illness, raising the possibility of common underlying pathways for immune dysfunction. Effects of treatment on cytokines were more robust for schizophrenia and MDD, but were more frequently studied than for acute mania. These findings have important implications for our understanding of the pathophysiology and treatment of major psychiatric disorders.

Dataset Information

Cross-disorder genomewide analysis of schizophrenia, bipolar disorder, and depression.

Publications

Cross-disorder genomewide analysis of schizophrenia, bipolar disorder, and depression.

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