Differentially Expressed Genes in Major Depression Reside on the Periphery of Resilient Gene Coexpression Networks

The structure of gene coexpression networks reflects the activation and interaction of multiple cellular systems. Since the pathology of neuropsychiatric disorders is influenced by diverse cellular systems and pathways, we investigated gene coexpression networks in major depression, and searched for putative unifying themes in network connectivity across neuropsychiatric disorders. Specifically, based on the prevalence of the lethality–centrality relationship in disease-related networks, we hypothesized that network changes between control and major depression-related networks would be centered around coexpression hubs, and secondly, that differentially expressed (DE) genes would have a characteristic position and connectivity level in those networks. Mathematically, the first hypothesis tests the relationship of differential coexpression to network connectivity, while the second “hybrid” expression-and-network hypothesis tests the relationship of differential expression to network connectivity. To answer these questions about the potential interaction of coexpression network structure with differential expression, we utilized all available human post-mortem depression-related datasets appropriate for coexpression analysis, which spanned different microarray platforms, cohorts, and brain regions. Similar studies were also performed in an animal model of depression and in schizophrenia and bipolar disorder microarray datasets. We now provide results which consistently support (1) that genes assemble into small-world and scale-free networks in control subjects, (2) that this efficient network topology is largely resilient to changes in depressed subjects, and (3) that DE genes are positioned on the periphery of coexpression networks. Similar results were observed in a mouse model of depression, and in selected bipolar- and schizophrenia-related networks. Finally, we show that baseline expression variability contributes to the propensity of genes to be network hubs and/or to be DE in disease. In summary, our results suggest that the small-world and scale-free properties of gene networks are resilient to pathological changes in major depression, and that the network structure may constrain the extent to which a gene may be DE in the illness, hence informing further gene-network-based mechanistic studies of neuropsychiatric disorders

Elevated Hippocampal Cholinergic Neurostimulating Peptide precursor protein (HCNP-pp) mRNA in the amygdala in major depression

The amygdala is innervated by the cholinergic system and is involved in major depressive disorder (MDD). Evidence suggests a hyper-activate cholinergic system in MDD. Hippocampal Cholinergic Neurostimulating Peptide (HCNP) regulates acetylcholine synthesis. The aim of the present work was to investigate expression levels of HCNP-precursor protein (HCNP-pp) mRNA and other cholinergic-related genes in the postmortem amygdala of MDD patients and matched controls (females: N=16 pairs; males: N=12 pairs), and in the mouse unpredictable chronic mild stress (UCMS) model that induced elevated anxiety-/depressive-like behaviors (females: N=6 pairs; males: N=6 pairs). Results indicate an up-regulation of HCNP-pp mRNA in the amygdala of women with MDD (p<0.0001), but not males, and of UCMS-exposed mice (males and females; p=0.037). HCNP-pp protein levels were investigated in the human female cohort, but no difference was found. There were no differences in gene expression of acetylcholinesterase (AChE), muscarinic (mAChRs) or nicotinic receptors (nAChRs) between MDD subjects and controls or UCMS and control mice, except for an up-regulation of AChE in UCMS-exposed mice (males and females; p=0.044). Exploratory analyses revealed a baseline expression difference of cholinergic signaling-related genes between women and men (p<0.0001). In conclusion, elevated amygdala HCNP-pp expression may contribute to mechanisms of MDD in women, potentially independently from regulating the cholinergic system. The differential expression of genes between women and men could also contribute to the increased vulnerability of females to develop MDD.Fil: Bassi, Sabrina Cecilia. University of Pittsburgh; Estados Unidos. Hospital Italiano. Instituto de Ciencias Básicas y Medicina Experimental; ArgentinaFil: Seney, Marianne L.. University of Pittsburgh; Estados UnidosFil: Argibay, Pablo. Hospital Italiano. Instituto de Ciencias Básicas y Medicina Experimental; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sibille, Etienne. University of Pittsburgh; Estados Unidos. University of Toronto; Canad

Age-Related Gene Expression in the Frontal Cortex Suggests Synaptic Function Changes in Specific Inhibitory Neuron Subtypes

Genome-wide expression profiling of the human brain has revealed genes that are differentially expressed across the lifespan. Characterizing these genes adds to our understanding of both normal functions and pathological conditions. Additionally, the specific cell-types that contribute to the motor, sensory and cognitive declines during aging are unclear. Here we test if age-related genes show higher expression in specific neural cell types. Our study leverages data from two sources of murine single-cell expression data and two sources of age-associations from large gene expression studies of postmortem human brain. We used nonparametric gene set analysis to test for age-related enrichment of genes associated with specific cell-types; we also restricted our analyses to specific gene ontology groups. Our analyses focused on a primary pair of single-cell expression data from the mouse visual cortex and age-related human post-mortem gene expression information from the orbitofrontal cortex. Additional pairings that used data from the hippocampus, prefrontal cortex, somatosensory cortex and blood were used to validate and test specificity of our findings. We found robust age-related up-regulation of genes that are highly expressed in oligodendrocytes and astrocytes, while genes highly expressed in layer 2/3 glutamatergic neurons were down-regulated across age. Genes not specific to any neural cell type were also down-regulated, possibly due to the bulk tissue source of the age-related genes. A gene ontology-driven dissection of the cell-type enriched genes highlighted the strong down-regulation of genes involved in synaptic transmission and cell-cell signaling in the Somatostatin (Sst) neuron subtype that expresses the cyclin dependent kinase 6 (Cdk6) and in the vasoactive intestinal peptide (Vip) neuron subtype expressing myosin binding protein C, slow type (Mybpc1). These findings provide new insights into cell specific susceptibility to normal aging, and suggest age-related synaptic changes in specific inhibitory neuron subtypes

A human-mouse conserved sex bias in amygdala gene expression related to circadian clock and energy metabolism

Background\ud Major depression affects twice as many women as men, but the underlying molecular mechanisms responsible for the heightened female vulnerability are not known. The amygdala, composed of heterogeneous subnuclei, participates in multiple functional circuits regulating emotional responses to stress. We hypothesized that sex differences in molecular structure may contribute to differential mood regulation and disease vulnerability.\ud \ud Findings\ud Using gene arrays followed by quantitative PCR validation, we compared the transcriptome profiles between sexes in human and mouse amygdala. We now report sexually dimorphic features of transcriptomes in the basolateral nucleus of the amygdala, and these features are highly conserved across species. A functional analysis of differential gene expression showed that mitochondrial-related gene groups were identified as the top biological pathways associated with sexual dimorphism in both species.\ud \ud Conclusions\ud These results suggest that the basolateral amygdala is a sexually dimorphic structure, featuring a regulatory cascade of mitochondrial function and circadian rhythm, potentially linked through sirtuins and hormone nuclear receptors. Hence, baseline differences in amygdalar circadian regulation of cellular metabolism may contribute to sex-related differences in mood regulation and vulnerability to major depression

Detecting disease-associated genes with confounding variable adjustment and the impact on genomic meta-analysis: With application to major depressive disorder

<p>Abstract</p> <p>Background</p> <p>Detecting candidate markers in transcriptomic studies often encounters difficulties in complex diseases, particularly when overall signals are weak and sample size is small. Covariates including demographic, clinical and technical variables are often confounded with the underlying disease effects, which further hampers accurate biomarker detection. Our motivating example came from an analysis of five microarray studies in major depressive disorder (MDD), a heterogeneous psychiatric illness with mostly uncharacterized genetic mechanisms.</p> <p>Results</p> <p>We applied a random intercept model to account for confounding variables and case-control paired design. A variable selection scheme was developed to determine the effective confounders in each gene. Meta-analysis methods were used to integrate information from five studies and post hoc analyses enhanced biological interpretations. Simulations and application results showed that the adjustment for confounding variables and meta-analysis improved detection of biomarkers and associated pathways.</p> <p>Conclusions</p> <p>The proposed framework simultaneously considers correction for confounding variables, selection of effective confounders, random effects from paired design and integration by meta-analysis. The approach improved disease-related biomarker and pathway detection, which greatly enhanced understanding of MDD neurobiology. The statistical framework can be applied to similar experimental design encountered in other complex and heterogeneous diseases.</p

Abnormal expression of cortical cell cycle regulators underlying anxiety and depressive-like behavior in mice exposed to chronic stress

BackgroundThe cell cycle is a critical mechanism for proper cellular growth, development and viability. The p16INK4a and p21Waf1/Cip1 are important regulators of the cell cycle progression in response to internal and external stimuli (e.g., stress). Accumulating evidence indicates that the prefrontal cortex (PFC) is particularly vulnerable to stress, where stress induces, among others, molecular and morphological alterations, reflecting behavioral changes. Here, we investigated if the p16INK4a and p21Waf1/Cip1 expression are associated with behavioral outcomes.MethodsPrefrontal cortex mRNA and protein levels of p16INK4A and p21Waf1/Cip1 of mice (six independent groups of C57BL/6J, eight mice/group, 50% female) exposed from 0 to 35 days of chronic restraint stress (CRS) were quantified by qPCR and Western Blot, respectively. Correlation analyses were used to investigate the associations between cyclin-dependent kinase inhibitors (CKIs) expression and anxiety- and depression-like behaviors.ResultsOur results showed that the PFC activated the cell cycle regulation pathways mediated by both CKIs p16INK4A and p21Waf1/Cip1 in mice exposed to CRS, with overall decreased mRNA expression and increased protein expression. Moreover, correlation analysis revealed that mRNA and protein levels are statistically significant correlated with anxiety and depressive-like behavior showing a greater effect in males than females.ConclusionOur present study extends the existing literature providing evidence that PFC cells respond to chronic stress exposure by overexpressing CKIs. Furthermore, our findings indicated that abnormal expression of p16INK4A and p21Waf1/Cip1 may significantly contribute to non-adaptive behavioral responses

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

BACKGROUND: Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods. RESULTS: Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression. CONCLUSION: In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects

Abnormal Left-Sided Orbitomedial Prefrontal Cortical–Amygdala Connectivity during Happy and Fear Face Processing: A Potential Neural Mechanism of Female MDD

Background: Pathophysiologic processes supporting abnormal emotion regulation in major depressive disorder (MDD) are poorly understood. We previously found abnormal inverse left-sided ventromedial prefrontal cortical–amygdala effective connectivity to happy faces in females with MDD. We aimed to replicate and expand this previous finding in an independent participant sample, using a more inclusive neural model, and a novel emotion processing paradigm. Methods: Nineteen individuals with MDD in depressed episode (12 females), and 19 healthy individuals, age, and gender matched, performed an implicit emotion processing and automatic attentional control paradigm to examine abnormalities in prefrontal cortical–amygdala neural circuitry during happy, angry, fearful, and sad face processing measured with functional magnetic resonance imaging in a 3-T scanner. Effective connectivity was estimated with dynamic causal modeling in a trinodal neural model including two anatomically defined prefrontal cortical regions, ventromedial prefrontal cortex, and subgenual cingulate cortex (sgACC), and the amygdala. Results: We replicated our previous finding of abnormal inverse left-sided top-down ventromedial prefrontal cortical–amygdala connectivity to happy faces in females with MDD (p = 0.04), and also showed a similar pattern of abnormal inverse left-sided sgACC–amygdala connectivity to these stimuli (p = 0.03). These findings were paralleled by abnormally reduced positive left-sided ventromedial prefrontal cortical–sgACC connectivity to happy faces in females with MDD (p = 0.008), and abnormally increased positive left-sided sgACC–amygdala connectivity to fearful faces in females, and all individuals, with MDD (p = 0.008; p = 0.003). Conclusion: Different patterns of abnormal prefrontal cortical–amygdala connectivity to happy and fearful stimuli might represent neural mechanisms for the excessive self-reproach and comorbid anxiety that characterize female MDD

Δ133p53β isoform pro-invasive activity is regulated through an aggregation-dependent mechanism in cancer cells

International audienceAbstract The p53 isoform, Δ133p53β, is critical in promoting cancer. Here we report that Δ133p53β activity is regulated through an aggregation-dependent mechanism. Δ133p53β aggregates were observed in cancer cells and tumour biopsies. The Δ133p53β aggregation depends on association with interacting partners including p63 family members or the CCT chaperone complex. Depletion of the CCT complex promotes accumulation of Δ133p53β aggregates and loss of Δ133p53β dependent cancer cell invasion. In contrast, association with p63 family members recruits Δ133p53β from aggregates increasing its intracellular mobility. Our study reveals novel mechanisms of cancer progression for p53 isoforms which are regulated through sequestration in aggregates and recruitment upon association with specific partners like p63 isoforms or CCT chaperone complex, that critically influence cancer cell features like EMT, migration and invasion