Cross-species evidence from human and rat brain transcriptome for growth factor signaling pathway dysregulation in major depression (original) (raw)
Related papers
Gene expression studies in major depression
2010
The dramatic technical advances in methods to measure gene expression on a genome-wide level thus far have not been paralleled by breakthrough discoveries in psychiatric disorders-including major depression (MD)using these hypothesis-free approaches. In this review, we first describe the methodologic advances made in gene expression analysis, from quantitative polymerase chain reaction to nextgeneration sequencing. We then discuss issues in gene expression experiments specific to MD, ranging from the choice of target tissues to the characterization of the case group. We provide a synopsis of the gene expression studies published thus far for MD, with a focus on studies using mRNA microarray methods. Finally, we discuss possible new strategies for the gene expression studies in MD that circumvent some of the addressed issues.
Identification and replication of RNA-Seq gene network modules associated with depression severity
Translational psychiatry, 2018
Genomic variation underlying major depressive disorder (MDD) likely involves the interaction and regulation of multiple genes in a network. Data-driven co-expression network module inference has the potential to account for variation within regulatory networks, reduce the dimensionality of RNA-Seq data, and detect significant gene-expression modules associated with depression severity. We performed an RNA-Seq gene co-expression network analysis of mRNA data obtained from the peripheral blood mononuclear cells of unmedicated MDD (n = 78) and healthy control (n = 79) subjects. Across the combined MDD and HC groups, we assigned genes into modules using hierarchical clustering with a dynamic tree cut method and projected the expression data onto a lower-dimensional module space by computing the single-sample gene set enrichment score of each module. We tested the single-sample scores of each module for association with levels of depression severity measured by the Montgomery-Åsberg Depr...
Frontiers in Psychiatry
Tissue-specific gene expression has been found to be associated with multiple complex diseases including cancer, metabolic disease, aging, etc. However, few studies of brain-tissue-specific gene expression patterns have been reported, especially in psychiatric disorders. In this study, we performed joint analysis on large-scale transcriptome multi-tissue data to investigate tissue-specific expression patterns in major depressive disorder (MDD) and bipolar disorder (BP). We established the strategies of identifying tissues-specific modules, annotated pathways for elucidating biological functions of tissues, and tissue-specific genes based on weighted gene co-expression network analysis (WGCNA) and robust rank aggregation (RRA) with transcriptional profiling data from different human tissues and genome wide association study (GWAS) data, which have been expanded into overlapping tissue-specific modules and genes sharing with MDD and BP. Nine tissue-specific modules were identified and...
Scientific Reports, 2016
Several microarray-based studies have investigated gene expression profiles in major depressive disorder (MDD), yet with highly variable findings. We examined blood-based genome-wide expression signatures of MDD, focusing on molecular pathways and networks underlying differentially expressed genes (DEGs) and behaviours of hypothesis-driven, evidence-based candidate genes for depression. Agilent human whole-genome arrays were used to measure gene expression in 14 medication-free outpatients with MDD who were at least moderately ill and 14 healthy controls matched pairwise for age and sex. After filtering, we compared expression of entire probes between patients and controls and identified DEGs. The DEGs were evaluated by pathway and network analyses. For the candidate gene analysis, we utilized 169 previously prioritized genes and examined their case-control separation efficiency and correlational co-expression network in patients relative to controls. The 317 screened DEGs mapped to a significantly over-represented pathway, the "synaptic transmission" pathway. The protein-protein interaction network was also significantly enriched, in which a number of key molecules for depression were included. The co-expression network of candidate genes was markedly disrupted in patients. This study provided evidence for an altered molecular network along with several key molecules in MDD and confirmed that the candidate genes are worthwhile targets for depression research. Major depressive disorder (MDD) is a common psychiatric condition characterized by persistent low mood and/ or diminished interest or pleasure in activities that used to be pleasurable. With an estimated 350 million people affected, depression is a leading cause of disability worldwide according to World Health Organization statistics. However, the pathogenesis is yet to be fully understood, and at present, there are no laboratory tests available to aid in its diagnosis or prognosis. With the development of bioinformatics and systems biology methods, analysis of genome-wide gene expression patterns has emerged as a powerful tool to probe a molecular phenotype of a disease without requiring an a priori hypothesis. Using this technique, studies have suggested gene expression profiles as reliable markers for classification, prognostication and prediction of various diseases such as cancer 1 , autoimmune diseases 2 and neurological disorders 3. As gene expression profiling can reflect a dynamic picture of genomic responses to environmental contributions 4 , it is considered relevant to psychiatric disorders as well 5-8. Concerning the type of sample, earlier genome-wide expression studies in psychiatry often used post-mortem brain tissues as the target for sampling. Recently, much attention has turned to more easily accessible peripheral blood samples 8,9. Several studies to compare gene expression in the blood and brain have demonstrated considerable
Gene expression patterns in a rodent model for depression
European Journal of Neuroscience, 2010
Disturbances in sleep are encountered in the majority of patients with depression. To elucidate the possible molecular mechanisms behind this relationship we examined gene expression changes in a rodent model for depression and disturbed sleep. Animals were treated with daily injections of clomipramine in their early infancy, after which gene expression in basal forebrain was examined using Affymetrix Rat 230.2 chips. We tested the levels of both single transcripts and involved pathways, and searched for common nominators (i.e. transcription factors) that could explain these changes. We identified 72 differentially expressed gene transcripts, many of which are involved in epigenetic regulation, such as DNMT2. Analysis of functional pathways revealed statistically significant changes of the biological process of synaptic transmission, the cellular compartment of the synapse and the molecular function of GABA signalling, showing that transcripts with altered expression are functionally related. Finally, promoter analysis of the differentially expressed genes showed a clear enrichment of binding sites for the transcription factor CREB1, a molecule also involved in epigenetic regulation (cAMP response element-binding protein induces histone modifications). These results indicate that CREB1 may constitute one of the major links between disturbed sleep and mood. The results also highlight the molecular mechanisms in the murine clomipramine model, previously shown to be a valid model for depression.
Gene expression patterns in brain cortex of three different animal models of depression
Genes Brain and Behavior, 2008
Animal models represent a very useful tool for the study of depressive-like behavior and for the evaluation of the therapeutic efficacy of antidepressants. Nevertheless, gene expression patterns of these different animal models and whether genes classically associated with human major depression are present in these genetic profiles remain unknown. Gene expression was evaluated in three animal models of depression: acute treatment with reserpine, olfactory bulbectomy and chronic treatment with corticosterone. Gene expression analysis was carried out using the Affymetrix GeneChip® technology. The results were evaluated using the GeneChip Operating software (Gcos 1.3) and analyzed with the GeneSpring GX v7.3 bioinformatics software (Agilent) and dChip 2005 software. Expression changes were validated with quantitative real-time polymerase chain reaction (RT-PCR) assays. Many transcripts were differentially expressed in the cortex of depressed-like animals in each model. Gene ontology analysis showed that significant gene changes were clustered primarily into functional neurochemical pathways associated with apoptosis and neuronal differentiation. When expression profiles were compared among the three models, the number of transcripts differentially expressed decreased and only two transcripts (complement component 3 and fatty acid-binding protein 7) were differentially expressed in common. Both genes were validated with RT-PCR. Moreover, five (Htr2a, Ntrk3, Crhr1, Ntrk2 and Crh) of the genes classically related to human major depression were differentially expressed in at least one of these models. The different animal models of depression share relevant characteristics although gene expression patterns are different among them. Moreover, some of the classical genes related to human major depression are differentially expressed in these models.
2013
Aim: This study aims to identify novel genes associated with major depressive disorder and pharmacological treatment response using animal and human mRNA studies. Materials & methods: Weighted gene coexpression network analysis was used to uncover genes associated with stress factors in mice and to inform mRNA probe set selection in a post-mortem study of depression. Results: A total of 171 genes were found to be differentially regulated in response to both early and late stress protocols in a mouse study. Ten human genes, orthologous to mouse genes differentially expressed by stress, were also found to be dysregulated in depressed cases in a human post-mortem brain study from the Stanley Foundation Brain Collection. Conclusion: Several novel genes associated with depression were uncovered, including NOVA1 and USP9X. Moreover, we found further evidence in support of hippocampal neurogenesis and peripheral inflammation in major depressive disorder.
Progress in Neuro-Psychopharmacology and Biological Psychiatry, 2016
Major depressive disorder (MDD) is a serious health concern worldwide. Currently there are no predictive tests for the effectiveness of any particular antidepressant in an individual patient. Thus, doctors must prescribe antidepressants based on educated guesses. With the recent advent of scientific research, genome-wide gene expression microarray studies are widely utilized to analyze hundreds of thousands of biomarkers by high-throughput technologies. In addition to the candidate-gene approach, the genome-wide approach has recently been employed to investigate the determinants of MDD as well as antidepressant response to therapy. In this review, we mainly focused on gene expression studies with genome-wide approaches using RNA derived from peripheral blood cells. Furthermore, we reviewed their limitations and future directions with respect to the genome-wide gene expression profiling in MDD pathogenesis as well as in antidepressant therapy.