An Integrative Genomic Study Implicates the Postsynaptic Density in the Pathogenesis of Bipolar Disorder.
ABSTRACT: Genome-wide association studies (GWAS) have identified several common variants associated with bipolar disorder (BD), but the biological meaning of these findings remains unclear. Integrative genomics-the integration of GWAS signals with gene expression data-may illuminate genes and gene networks that have key roles in the pathogenesis of BD. We applied weighted gene co-expression network analysis (WGCNA), which exploits patterns of co-expression among genes, to brain transcriptome data obtained by sequencing of poly-A RNA derived from postmortem dorsolateral prefrontal cortex from people with BD, along with age- and sex-matched controls. WGCNA identified 33 gene modules. Many of the modules corresponded closely to those previously reported in human cortex. Three modules were associated with BD, enriched for genes differentially expressed in BD, and also enriched for signals in prior GWAS of BD. Functional analysis of genes within these modules revealed significant enrichment of several functionally related sets of genes, especially those involved in the postsynaptic density (PSD). These results provide convergent support for the hypothesis that dysregulation of genes involved in the PSD is a key factor in the pathogenesis of BD. If replicated in larger samples, these findings could point toward new therapeutic targets for BD.
Project description:Bipolar disorder (BD) is a complex mental disorder with high mortality and disability rates worldwide; however, research on its pathogenesis and diagnostic methods remains limited. This study aimed to elucidate potential candidate hub genes and key pathways related to BD in a pre-frontal cortex sample. Raw gene expression profile files of GSE53987, including 36 samples, were obtained from the gene expression omnibus (GEO) database. After data pre-processing, 10,094 genes were selected for weighted gene co-expression network analysis (WGCNA). After dividing highly related genes into 19 modules, we found that the pink, midnight blue, and brown modules were highly correlated with BD. Functional annotation and pathway enrichment analysis for modules, which indicated some key pathways, were conducted based on the Enrichr database. One of the most remarkable significant pathways is the Hippo signaling pathway and its positive transcriptional regulation. Finally, 30 hub genes were identified in three modules. Hub genes with a high degree of connectivity in the PPI network are significantly enriched in positive regulation of transcription. In addition, the hub genes were validated based on another dataset (GSE12649). Taken together, the identification of these 30 hub genes and enrichment pathways might have important clinical implications for BD treatment and diagnosis.
Project description:Schizophrenia (SCZ) and bipolar disorder (BD) are highly heritable psychiatric disorders. Associated genetic and gene expression changes have been identified, but many have not been replicated and have unknown functions. We identified groups of genes whose expressions varied together, that is co-expression modules, then tested them for association with SCZ. Using weighted gene co-expression network analysis, we show that two modules were differentially expressed in patients versus controls. One, upregulated in cerebral cortex, was enriched with neuron differentiation and neuron development genes, as well as disease genome-wide association study genetic signals; the second, altered in cerebral cortex and cerebellum, was enriched with genes involved in neuron protection functions. The findings were preserved in five expression data sets, including sets from three brain regions, from a different microarray platform, and from BD patients. From those observations, we propose neuron differentiation and development pathways may be involved in etiologies of both SCZ and BD, and neuron protection function participates in pathological process of the diseases.
Project description:Alcohol consumption is known to lead to gene expression changes in the brain. After performing weighted gene co-expression network analyses (WGCNA) on genome-wide mRNA and microRNA (miRNA) expression in Nucleus Accumbens (NAc) of subjects with alcohol dependence (AD; N = 18) and of matched controls (N = 18), six mRNA and three miRNA modules significantly correlated with AD were identified (Bonferoni-adj. p? 0.05). Cell-type-specific transcriptome analyses revealed two of the mRNA modules to be enriched for neuronal specific marker genes and downregulated in AD, whereas the remaining four mRNA modules were enriched for astrocyte and microglial specific marker genes and upregulated in AD. Gene set enrichment analysis demonstrated that neuronal specific modules were enriched for genes involved in oxidative phosphorylation, mitochondrial dysfunction and MAPK signaling. Glial-specific modules were predominantly enriched for genes involved in processes related to immune functions, i.e. cytokine signaling (all adj. p? 0.05). In mRNA and miRNA modules, 461 and 25 candidate hub genes were identified, respectively. In contrast to the expected biological functions of miRNAs, correlation analyses between mRNA and miRNA hub genes revealed a higher number of positive than negative correlations (?2 test p? 0.0001). Integration of hub gene expression with genome-wide genotypic data resulted in 591 mRNA cis-eQTLs and 62 miRNA cis-eQTLs. mRNA cis-eQTLs were significantly enriched for AD diagnosis and AD symptom counts (adj. p = 0.014 and p = 0.024, respectively) in AD GWAS signals in a large, independent genetic sample from the Collaborative Study on Genetics of Alcohol (COGA). In conclusion, our study identified putative gene network hubs coordinating mRNA and miRNA co-expression changes in the NAc of AD subjects, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD.
Project description:BACKGROUND:Multiple sclerosis (MS) is a complex disease in which the immune system attacks the central nervous system. The molecular mechanisms contributing to the etiology of MS remain poorly understood. Genome-wide association studies (GWAS) of MS have identified a small number of genetic loci significant at the genome level, but they are mainly non-coding variants. Network-assisted analysis may help better interpret the functional roles of the variants with association signals and potential translational medicine application. The Dense Module Searching of GWAS tool (dmGWAS version 2.4) developed in our team is applied to 2 MS GWAS datasets (GeneMSA and IMSGC GWAS) using the human protein interactome as the reference network. A dual evaluation strategy is used to generate results with reproducibility. RESULTS:Approximately 7500 significant network modules were identified for each independent GWAS dataset, and 20 significant modules were identified from the dual evaluation. The top modules included GRB2, HDAC1, JAK2, MAPK1, and STAT3 as central genes. Top module genes were enriched with functional terms such as "regulation of glial cell differentiation" (adjusted p-value?=?2.58?×?10-?3), "T-cell costimulation" (adjusted p-value?=?2.11?×?10-?6) and "virus receptor activity" (adjusted p-value?=?1.67?×?10-?3). Interestingly, top gene networks included several MS FDA approved drug target genes HDAC1, IL2RA, KEAP1, and RELA, CONCLUSIONS: Our dmGWAS network analyses highlighted several genes (GRB2, HDAC1, IL2RA, JAK2, KEAP1, MAPK1, RELA and STAT3) in top modules that are promising to interpret GWAS signals and link to MS drug targets. The genes enriched with glial cell differentiation are important for understanding neurodegenerative processes in MS and for remyelination therapy investigation. Importantly, our identified genetic signals enriched in T cell costimulation and viral receptor activity supported the viral infection onset hypothesis for MS.
Project description:Long non-coding RNAs (lncRNAs) are an emerging class of regulatory RNA that may be implicated in psychiatric disorders. Here we performed RNA-sequencing in the rostral anterior cingulate cortex of 26 depressed suicides and 24 matched controls. We first performed differential lncRNA expression analysis, and then conducted Weighted Gene Co-expression Network Analysis (WGCNA) to identify co-expression modules associating with depression and suicide. We identified 23 differentially expressed lncRNAs (FDR?<?0.1) as well as their differentially expressed overlapping and antisense protein-coding genes. Several of these overlapping or antisense genes were associated with interferon signaling, which is a component of the innate immune response. Using WGCNA, we identified modules of highly co-expressed genes associated with depression and suicide and found protein-coding genes highly connected to differentially expressed lncRNAs within these modules. These protein-coding genes were located distal to their associated lncRNAs and were found to be part of several GO terms enriched in the significant modules, which include: cytoskeleton organization, plasma membrane, cell adhesion, nucleus, DNA-binding, and regulation of dendrite development and morphology. Altogether, we report that lncRNAs are differentially expressed in the brains of depressed individuals who died by suicide and may represent regulators of important molecular functions and biological processes.
Project description:Circadian rhythm abnormalities in bipolar disorder (BD) have led to a search for genetic abnormalities in circadian "clock genes" associated with BD. However, no significant clock gene findings have emerged from genome-wide association studies (GWAS). At least three factors could account for this discrepancy: complex traits are polygenic, the organization of the clock is more complex than previously recognized, and/or genetic risk for BD may be shared across multiple illnesses. To investigate these issues, we considered the clock gene network at three levels: essential "core" clock genes, upstream circadian clock modulators, and downstream clock controlled genes. Using relaxed thresholds for GWAS statistical significance, we determined the rates of clock vs. control genetic associations with BD, and four additional illnesses that share clinical features and/or genetic risk with BD (major depression, schizophrenia, attention deficit/hyperactivity). Then we compared the results to a set of lithium-responsive genes. Associations with BD-spectrum illnesses and lithium-responsiveness were both enriched among core clock genes but not among upstream clock modulators. Associations with BD-spectrum illnesses and lithium-responsiveness were also enriched among pervasively rhythmic clock-controlled genes but not among genes that were less pervasively rhythmic or non-rhythmic. Our analysis reveals previously unrecognized associations between clock genes and BD-spectrum illnesses, partly reconciling previously discordant results from past GWAS and candidate gene studies.
Project description:High serum triglyceride (TG) levels is an established risk factor for coronary heart disease (CHD). Fat is stored in the form of TGs in human adipose tissue. We hypothesized that gene co-expression networks in human adipose tissue may be correlated with serum TG levels and help reveal novel genes involved in TG regulation.Gene co-expression networks were constructed from two Finnish and one Mexican study sample using the blockwiseModules R function in Weighted Gene Co-expression Network Analysis (WGCNA). Overlap between TG-associated networks from each of the three study samples were calculated using a Fisher's Exact test. Gene ontology was used to determine known pathways enriched in each TG-associated network.We measured gene expression in adipose samples from two Finnish and one Mexican study sample. In each study sample, we observed a gene co-expression network that was significantly associated with serum TG levels. The TG modules observed in Finns and Mexicans significantly overlapped and shared 34 genes. Seven of the 34 genes (ARHGAP30, CCR1, CXCL16, FERMT3, HCST, RNASET2, SELPG) were identified as the key hub genes of all three TG modules. Furthermore, two of the 34 genes (ARHGAP9, LST1) reside in previous TG GWAS regions, suggesting them as the regional candidates underlying the GWAS signals.This study presents a novel adipose gene co-expression network with 34 genes significantly correlated with serum TG across populations.
Project description:Alcohol consumption is known to lead to gene expression changes in the brain. After performing gene co-expression network analysis (WGCNA) of genome-wide mRNA and microRNA expressions in the Nucleus Accumbens (NAc) from subjects with alcohol dependence (AD) and matched controls six mRNA and three miRNA modules significantly correlated with AD after Bonferroni correction (adj. p? 0.05) were identified. Cell-type-specific transcriptome analysis revealed two of the mRNA modules to be enriched for neuronal specific marker genes and downregulated in AD, whereas the remaining four were enriched for astrocyte and microglial specific marker genes and were upregulated in AD. Using gene set enrichment analysis, the neuronal specific modules were enriched for genes involved in oxidative phosphorylation, mitochondrial dysfunction and MAPK signaling, while the glial-specific modules were enriched mostly for genes involved in processes related to immune functions, i.e. reactome cytokine signaling in immune system (all adj. p? 0.05). In the mRNA and miRNA modules, 461 and 25 candidate hub genes were identified, respectively. In contrast to the expected miRNAs’ biological functions, the correlation analyses between mRNA and miRNA hub genes revealed a significantly higher number of positive than negative correlations (chi-square p? 0.0001). At FDR? 0.1, integration of the mRNA and miRNA hubs genes expression with genome-wide genotypic data identified 591 cis-eQTLs and 62 cis-eQTLs for the mRNA and miRNA hubs, respectively. Adjusting for the number of tests, the mRNA cis-eQTLs were significantly enriched for AD GWAS signals in the Collaborative Study on Genetics of Alcohol (COGA) sample (adj. p=0.024), providing a novel biological role for these association signals. In conclusion, our study identified coordinated mRNA and miRNA co-expression changes in the NAc of AD subjects, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD. Tissue samples were received from the Australian Brain Donor Programs New South Wales Tissue Resource Centre, which is supported by The University of Sydney, National Health and Medical Research Council of Australia, Schizophrenia Research Institute, National Institute of Alcohol Abuse and Alcoholism, and the New South Wales Department of Health. Cases were excluded if they had an infectious disease (i.e. HIV/AIDS, hepatitis B or C, or Creutzfeldt-Jakob disease), an unsatisfactory agonal status determined from the circumstances surrounding the death, post-mortem delays >48 hours, or significant head injury. In addition to case status, age, sex, ethnicity, brain weight, brain pH, post-mortem interval (PMI), tissue hemisphere, clinical cause of death, blood toxicology at time of death, smoking status, neuropathology and liver pathology were also provided for each subject. MiRNA and mRNA expression in 18 matched case-control pairs (N=36) with sample RINs ?6 were assessed on the Affymetrix GeneChip® Human Genome U133A 2.0 (HG-U133A 2.0) and Affymetrix GeneChip miRNA 3.0 microarray.
Project description:Most pathway and gene-set enrichment methods prioritize genes by their main effect and do not account for variation due to interactions in the pathway. A portion of the presumed missing heritability in genome-wide association studies (GWAS) may be accounted for through gene-gene interactions and additive genetic variability. In this study, we prioritize genes for pathway enrichment in GWAS of bipolar disorder (BD) by aggregating gene-gene interaction information with main effect associations through a machine learning (evaporative cooling) feature selection and epistasis network centrality analysis. We validate this approach in a two-stage (discovery/replication) pathway analysis of GWAS of BD. The discovery cohort comes from the Wellcome Trust Case Control Consortium (WTCCC) GWAS of BD, and the replication cohort comes from the National Institute of Mental Health (NIMH) GWAS of BD in European Ancestry individuals. Epistasis network centrality yields replicated enrichment of Cadherin signaling pathway, whose genes have been hypothesized to have an important role in BD pathophysiology but have not demonstrated enrichment in previous analysis. Other enriched pathways include Wnt signaling, circadian rhythm pathway, axon guidance and neuroactive ligand-receptor interaction. In addition to pathway enrichment, the collective network approach elevates the importance of ANK3, DGKH and ODZ4 for BD susceptibility in the WTCCC GWAS, despite their weak single-locus effect in the data. These results provide evidence that numerous small interactions among common alleles may contribute to the diathesis for BD and demonstrate the importance of including information from the network of gene-gene interactions as well as main effects when prioritizing genes for pathway analysis.
Project description:Autism spectrum disorder (ASD) is a common, highly heritable neurodevelopmental condition characterized by marked genetic heterogeneity. Thus, a fundamental question is whether autism represents an aetiologically heterogeneous disorder in which the myriad genetic or environmental risk factors perturb common underlying molecular pathways in the brain. Here, we demonstrate consistent differences in transcriptome organization between autistic and normal brain by gene co-expression network analysis. Remarkably, regional patterns of gene expression that typically distinguish frontal and temporal cortex are significantly attenuated in the ASD brain, suggesting abnormalities in cortical patterning. We further identify discrete modules of co-expressed genes associated with autism: a neuronal module enriched for known autism susceptibility genes, including the neuronal specific splicing factor A2BP1 (also known as FOX1), and a module enriched for immune genes and glial markers. Using high-throughput RNA sequencing we demonstrate dysregulated splicing of A2BP1-dependent alternative exons in the ASD brain. Moreover, using a published autism genome-wide association study (GWAS) data set, we show that the neuronal module is enriched for genetically associated variants, providing independent support for the causal involvement of these genes in autism. In contrast, the immune-glial module showed no enrichment for autism GWAS signals, indicating a non-genetic aetiology for this process. Collectively, our results provide strong evidence for convergent molecular abnormalities in ASD, and implicate transcriptional and splicing dysregulation as underlying mechanisms of neuronal dysfunction in this disorder.