Genome-Wide Pathway Analysis in Major Depressive Disorder

Circulating myeloid-derived MMP8 in stress susceptibility and depression

Psychosocial stress has profound effects on the body, including the immune system and the brain1,2. Although a large number of pre-clinical and clinical studies have linked peripheral immune system alterations to stress-related disorders such as major depressive disorder (MDD)3, the underlying mechanisms are not well understood. Here we show that expression of a circulating myeloid cell-specific proteinase, matrix metalloproteinase 8 (MMP8), is increased in the serum of humans with MDD as well as in stress-susceptible mice following chronic social defeat stress (CSDS). In mice, we show that this increase leads to alterations in extracellular space and neurophysiological changes in the nucleus accumbens (NAc), as well as altered social behaviour. Using a combination of mass cytometry and single-cell RNA sequencing, we performed high-dimensional phenotyping of immune cells in circulation and in the brain and demonstrate that peripheral monocytes are strongly affected by stress. In stress-susceptible mice, both circulating monocytes and monocytes that traffic to the brain showed increased Mmp8 expression following chronic social defeat stress. We further demonstrate that circulating MMP8 directly infiltrates the NAc parenchyma and controls the ultrastructure of the extracellular space. Depleting MMP8 prevented stress-induced social avoidance behaviour and alterations in NAc neurophysiology and extracellular space. Collectively, these data establish a mechanism by which peripheral immune factors can affect central nervous system function and behaviour in the context of stress. Targeting specific peripheral immune cell-derived matrix metalloproteinases could constitute novel therapeutic targets for stress-related neuropsychiatric disorders.

Sleep deprivation alleviates depression-like behaviors in mice via inhibiting immune and inflammatory pathways and improving neuroplasticity

BACKGROUND

Sleep deprivation (SD) has been suggested to have a rapid antidepressant effect. There is substantial evidence that neuroinflammation and neuroplasticity play critical roles in the pathophysiology and treatment of depression. Here, we investigated the mechanisms of SD to alleviate depression-like behaviors of mice, and the role of neuroinflammation and neuroplasticity in it.

METHODS

Adult male C57BL/6 J mice were subjected to chronic restraint stress (CRS) for 6 weeks, and 6 h of SD were administrated. Behavioral tests were performed to measure depression-like behaviors. RNA-sequencing and bioinformatic analysis were performed in the anterior cingulate cortex (ACC). The differentially expressed genes were confirmed by quantitative real-time polymerase chain reaction (RT-qPCR). Neuroinflammation and neuroplasticity were measured by western blotting and immunofluorescence staining.

RESULTS

Behavioral tests demonstrated that SD swiftly attenuated the depression-like behaviors induced by CRS. RNA-sequencing identified the upregulated immune and inflammatory pathways after CRS exposure were downregulated by SD. Furthermore, SD reversed the levels of immune and inflammation-related mRNA, pro-inflammatory factors and microglia activation in ACC. Additionally, the impaired neuroplasticity elicited by CRS in the prefrontal cortex (PFC) and ACC were improved by SD.

LIMITATIONS

More in-depth studies are required to determine the role of different SD protocols in depressive symptoms and their underlying mechanisms.

CONCLUSIONS

Our study revealed the rapid antidepressant effect of SD on CRS mice through the reduction of the neuroinflammatory response in ACC and the improvement of neuroplasticity in PFC and ACC, providing a theoretical basis for the clinical application of SD as a rapid antidepressant treatment.

Perineuronal Nets: Subtle Structures with Large Implications

Perineuronal nets (PNNs) are specialized structures of the extracellular matrix that surround the soma and proximal dendrites of certain neurons in the central nervous system, particularly parvalbumin-expressing interneurons. Their appearance overlaps the maturation of neuronal circuits and the closure of critical periods in different regions of the brain, setting their connectivity and abruptly reducing their plasticity. As a consequence, the digestion of PNNs, as well as the removal or manipulation of their components, leads to a boost in this plasticity and can play a key role in the functional recovery from different insults and in the etiopathology of certain neurologic and psychiatric disorders. Here we review the structure, composition, and distribution of PNNs and their variation throughout the evolutive scale. We also discuss methodological approaches to study these structures. The function of PNNs during neurodevelopment and adulthood is discussed, as well as the influence of intrinsic and extrinsic factors on these specialized regions of the extracellular matrix. Finally, we review current data on alterations in PNNs described in diseases of the central nervous system (CNS), focusing on psychiatric disorders. Together, all the data available point to the PNNs as a promising target to understand the physiology and pathologic conditions of the CNS.

iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease

Different genes form complex networks within cells to carry out critical cellular functions, while network alterations in this process can potentially introduce downstream transcriptome perturbations and phenotypic variations. Therefore, developing efficient and interpretable methods to quantify network changes and pinpoint driver genes across conditions is crucial. We propose a hierarchical graph representation learning method, called iHerd. Given a set of networks, iHerd first hierarchically generates a series of coarsened sub-graphs in a data-driven manner, representing network modules at different resolutions (e.g., the level of signaling pathways). Then, it sequentially learns low-dimensional node representations at all hierarchical levels via efficient graph embedding. Lastly, iHerd projects separate gene embeddings onto the same latent space in its graph alignment module to calculate a rewiring index for driver gene prioritization. To demonstrate its effectiveness, we applied iHerd on a tumor-to-normal GRN rewiring analysis and cell-type-specific GCN analysis using single-cell multiome data of the brain. We showed that iHerd can effectively pinpoint novel and well-known risk genes in different diseases. Distinct from existing models, iHerd's graph coarsening for hierarchical learning allows us to successfully classify network driver genes into early and late divergent genes (EDGs and LDGs), emphasizing genes with extensive network changes across and within signaling pathway levels. This unique approach for driver gene classification can provide us with deeper molecular insights. The code is freely available at https://github.com/aicb-ZhangLabs/iHerd. All other relevant data are within the manuscript and supporting information files.

Computed tomography-detected extramural venous invasion-related gene signature: a potential negative biomarker of immune checkpoint inhibitor treatment in patients with gastric cancer

BACKGROUND

To investigate the association between computed tomography (CT)-detected extramural venous invasion (EMVI)-related genes and immunotherapy resistance and immune escape in patients with gastric cancer (GC).

METHODS

Thirteen patients with pathologically proven locally advanced GC who had undergone preoperative abdominal contrast-enhanced CT and radical resection surgery were included in this study. Transcriptome sequencing was multidetector performed on the cancerous tissue obtained during surgery, and EMVI-related genes (P value for association < 0.001) were selected. A single-sample gene set enrichment analysis algorithm was also used to divide all GC samples (n = 377) in The Cancer Genome Atlas (TCGA) database into high and low EMVI-immune related groups based on immune-related differential genes. Cluster analysis was used to classify EMVI-immune-related genotypes, and survival among patients was validated in TCGA and Gene Expression Omnibus (GEO) cohorts. The EMVI scores were calculated using principal component analysis (PCA), and GC samples were divided into high and low EMVI score groups. Microsatellite instability (MSI) status, tumor mutation burden (TMB), response rate to immune checkpoint inhibitors (ICIs), immune escape were compared between the high and low EMVI score groups. Hub gene of the model in pan-cancer analysis was also performed.

RESULTS

There were 17 EMVI-immune-related genes used for cluster analysis. PCA identified 8 genes (PCH17, SEMA6B, GJA4, CD34, ACVRL1, SOX17, CXCL12, DYSF) that were used to calculate EMVI scores. High EMVI score groups had lower MSI, TMB and response rate of ICIs, status but higher immune escape status. Among the 8 genes used for EMVI scores, CXCL12 and SOX17 were at the core of the protein-protein interaction (PPI) network and had a higher priority in pan-cancer analysis. Immunohistochemical analysis showed that the expression of CXCL12 and SOX17 was significantly higher in CT-detected EMVI-positive samples than in EMVI-negative samples (P < 0.0001).

CONCLUSION

A CT-detected EMVI gene signature could be a potential negative biomarker for ICIs treatment, as the signature is negatively correlated with TMB, and MSI, resulting in poorer prognosis.

The Genomic Landscape of Corticotroph Tumors: From Silent Adenomas to ACTH-Secreting Carcinomas

Corticotroph cells give rise to aggressive and rare pituitary neoplasms comprising ACTH-producing adenomas resulting in Cushing disease (CD), clinically silent ACTH adenomas (SCA), Crooke cell adenomas (CCA) and ACTH-producing carcinomas (CA). The molecular pathogenesis of these tumors is still poorly understood. To better understand the genomic landscape of all the lesions of the corticotroph lineage, we sequenced the whole exome of three SCA, one CCA, four ACTH-secreting PA causing CD, one corticotrophinoma occurring in a CD patient who developed Nelson syndrome after adrenalectomy and one patient with an ACTH-producing CA. The ACTH-producing CA was the lesion with the highest number of single nucleotide variants (SNV) in genes such as USP8, TP53, AURKA, EGFR, HSD3B1 and CDKN1A. The USP8 variant was found only in the ACTH-CA and in the corticotrophinoma occurring in a patient with Nelson syndrome. In CCA, SNV in TP53, EGFR, HSD3B1 and CDKN1A SNV were present. HSD3B1 and CDKN1A SNVs were present in all three SCA, whereas in two of these tumors SNV in TP53, AURKA and EGFR were found. None of the analyzed tumors showed SNV in USP48, BRAF, BRG1 or CABLES1. The amplification of 17q12 was found in all tumors, except for the ACTH-producing carcinoma. The four clinically functioning ACTH adenomas and the ACTH-CA shared the amplification of 10q11.22 and showed more copy-number variation (CNV) gains and single-nucleotide variations than the nonfunctioning tumors.

Integration of Transcriptome and Exome Genotyping Identifies Significant Variants with Autism Spectrum Disorder

Autism is a complex disease with genetic predisposition factors. Real factors for treatment and early diagnosis are yet to be defined. This study integrated transcriptome and exome genotyping for identifying functional variants associated with autism spectrum disorder and their impact on gene expression to find significant variations. More than 1800 patients were screened, and 70 (47 male/23 female) with an average age of 7.56 ± 3.68 years fulfilled the DSM-5 criteria for autism. Analysis revealed 682 SNPs of 589 genes significantly (p < 0.001) associated with autism among the putative functional exonic variants (n = 243,345) studied. Olfactory receptor genes on chromosome 6 were significant after Bonferroni correction (α = 0.05/243345 = 2.05 × 10−7) with a high degree of linkage disequilibrium on 6p22.1 (p = 6.71 × 10−9). The differentially expressed gene analysis of autistic patients compared to controls in whole RNA sequencing identified significantly upregulated (foldchange ≥ 0.8 and p-value ≤ 0.05; n = 125) and downregulated (foldchange ≤ −0.8 and p-value ≤ 0.05; n = 117) genes. The integration of significantly up- and downregulated genes and genes of significant SNPs identified regulatory variants (rs6657480, rs3130780, and rs1940475) associated with the up- (ITGB3BP) and downregulation (DDR1 and MMP8) of genes in autism spectrum disorder in people of Arab ancestries. The significant variants could be a biomarker of interest for identifying early autism among Arabs and helping to characterize the genes involved in the susceptibility mechanisms for autistic subjects.

CT-detected extramural venous invasion-related gene signature for the overall survival prediction in patients with gastric cancer

Background

Computed tomography (CT)‐detected extramural venous invasion (EMVI) has been identified as an independent factor that can be used for risk stratification and prediction of prognosis in patients with gastric cancer (GC). Overall survival (OS) is identified as the most important prognostic indicator for GC patients. However, the molecular mechanism of EMVI development and its potential relationship with OS in GC are not fully understood. In this radiogenomics‐based study, we sought to investigate the molecular mechanism underlying CT‐detected EMVI in patients with GC, and aimed to construct a genomic signature based on EMVI‐related genes with the goal of using this signature to predict the OS.

Materials and Methods

Whole mRNA genome sequencing of frozen tumor samples from 13 locally advanced GC patients was performed to identify EMVI‐related genes. EMVI‐prognostic hub genes were selected based on overlapping EMVI‐related differentially expressed genes and OS‐related genes, using a training cohort of 176 GC patients who were included in The Cancer Genome Atlas database. Another 174 GC patients from this database comprised the external validation cohort. A risk stratification model using a seven‐gene signature was constructed through the use of a least absolute shrinkage and selection operator Cox regression model.

Results

Patients with high risk score showed significantly reduced OS (training cohort, p = 1.143e‐04; validation cohort, p = 2.429e‐02). Risk score was an independent predictor of OS in multivariate Cox regression analyses (training cohort, HR = 2.758; 95% CI: 1.825–4.169; validation cohort, HR = 2.173; 95% CI: 1.347–3.505; p < 0.001 for both). Gene functions/pathways of the seven‐gene signature mainly included cell proliferation, cell adhesion, regulation of metal ion transport, and epithelial to mesenchymal transition.

Conclusions

A CT‐detected EMVI‐related gene model could be used to predict the prognosis in GC patients, potentially providing clinicians with additional information regarding appropriate therapeutic strategy and medical decision‐making.

Genome-wide gene expression changes in postpartum depression point towards an altered immune landscape

Maternal postpartum depression (PPD) is a significant public health concern due to the severe negative impact on maternal and child health and well-being. In this study, we aimed to identify genes associated with PPD. To do this, we investigated genome-wide gene expression profiles of pregnant women during their third trimester of pregnancy and tested the association of gene expression with perinatal depressive symptoms. A total of 137 women from a cohort from the University of North Carolina, USA were assessed. The main phenotypes analysed were Edinburgh Postnatal Depression Scale (EPDS) scores at 2 months postpartum and PPD (binary yes/no) based on an EPDS cutoff of 10. Illumina NextSeq500/550 transcriptomic sequencing from whole blood was analysed using the edgeR package. We identified 71 genes significantly associated with postpartum depression scores at 2 months, after correction for multiple testing at 5% FDR. These included several interesting candidates including TNFRSF17, previously reported to be significantly upregulated in women with PPD and MMP8, a matrix metalloproteinase gene, associated with depression in a genome-wide association study. Functional annotation of differentially expressed genes revealed an enrichment of immune response-related biological processes. Additional analysis of genes associated with changes in depressive symptoms from recruitment to 2 months postpartum identified 66 genes significant at an FDR of 5%. Of these genes, 33 genes were also associated with depressive symptoms at 2 months postpartum. Comparing the results with previous studies, we observed that 15.4% of genes associated with PPD in this study overlapped with 700 core maternal genes that showed significant gene expression changes across multiple brain regions (P = 7.9e-05) and 29-53% of the genes were also associated with estradiol changes in a pharmacological model of depression (P values range = 1.2e-4-2.1e-14). In conclusion, we identified novel genes and validated genes previously associated with oestrogen sensitivity in PPD. These results point towards the role of an altered immune transcriptomic landscape as a vulnerability factor for PPD.

Development and Clinical Validation of a Novel 4-Gene Prognostic Signature Predicting Survival in Colorectal Cancer

In this study, we collected genes related to energy metabolism, used gene expression data from public databases to classify molecular subtypes of colon cancer (COAD) based on the genes related to energy metabolism, and further evaluated the relationships between the molecular subtypes and prognosis and clinical characteristics. Differential expression analysis of the molecular subtypes yielded 1948 differentially expressed genes (DEGs), whose functions were closely related to the occurrence and development of cancer. Based on the DEGs, we constructed a 4-gene prognostic risk model and identified the high expression of FOXD4, ENPEP, HOXC6, and ALOX15B as a risk factor associated with a high risk of developing COAD. The 4-gene signature has strong robustness and a stable predictive performance in datasets from different platforms not only in patients with early COAD but also in all patients with colon cancer. The enriched pathways of the 4-gene signature in the high- and low-risk groups obtained by GSEA were significantly related to the occurrence and development of colon cancer. Moreover, the results of qPCR, immunohistochemistry staining and Western blot assay revealed that FOXD4, ENPEP, HOXC6, and ALOX15B are over expressed in CRC tissues and cells. These results suggesting that the signature could potentially be used as a prognostic marker for clinical diagnosis.

C2H2-Type Zinc Finger Proteins in Brain Development, Neurodevelopmental, and Other Neuropsychiatric Disorders: Systematic Literature-Based Analysis

Neurodevelopmental disorders (NDDs) are multifaceted pathologic conditions manifested with intellectual disability, autistic features, psychiatric problems, motor dysfunction, and/or genetic/chromosomal abnormalities. They are associated with skewed neurogenesis and brain development, in part through dysfunction of the neural stem cells (NSCs) where abnormal transcriptional regulation on key genes play significant roles. Recent accumulated evidence highlights C₂H₂-type zinc finger proteins (C₂H₂-ZNFs), the largest transcription factor family in humans, as important targets for the pathologic processes associated with NDDs. In this review, we identified their significant accumulation (74 C₂H₂-ZNFs: ~10% of all human member proteins) in brain physiology and pathology. Specifically, we discuss their physiologic contribution to brain development, particularly focusing on their actions in NSCs. We then explain their pathologic implications in various forms of NDDs, such as morphological brain abnormalities, intellectual disabilities, and psychiatric disorders. We found an important tendency that poly-ZNFs and KRAB-ZNFs tend to be involved in the diseases that compromise gross brain structure and human-specific higher-order functions, respectively. This may be consistent with their characteristic appearance in the course of species evolution and corresponding contribution to these brain activities.

Genetics Factors in Major Depression Disease

Depressive disorders (DDs) are one of the most widespread forms of psychiatric pathology. According to the World Health Organization, about 350 million people in the world are affected by this condition. Family and twin studies have demonstrated that the contribution of genetic factors to the risk of the onset of DDs is quite large. Various methodological approaches (analysis of candidate genes, genome-wide association analysis, genome-wide sequencing) have been used, and a large number of the associations between genes and different clinical DD variants and DD subphenotypes have been published. However, in most cases, these associations have not been confirmed in replication studies, and only a small number of genes have been proven to be associated with DD development risk. To ascertain the role of genetic factors in DD pathogenesis, further investigations of the relevant conditions are required. Special consideration should be given to the polygenic characteristics noted in whole-genome studies of the heritability of the disorder without a pronounced effect of the major gene. These observations accentuate the relevance of the analysis of gene-interaction roles in DD development and progression. It is important that association studies of the inherited variants of the genome should be supported by analysis of dynamic changes during DD progression. Epigenetic changes that cause modifications of a gene's functional state without changing its coding sequence are of primary interest. However, the opportunities for studying changes in the epigenome, transcriptome, and proteome during DD are limited by the nature of the disease and the need for brain tissue analysis, which is possible only postmortem. Therefore, any association studies between DD pathogenesis and epigenetic factors must be supplemented through the use of different animal models of depression. A threefold approach comprising the combination of gene association studies, assessment of the epigenetic state in DD patients, and analysis of different "omic" changes in animal depression models will make it possible to evaluate the contribution of genetic, epigenetic, and environmental factors to the development of different forms of depression and to help develop ways to decrease the risk of depression and improve the treatment of DD.

DNA methylation signatures of educational attainment

Educational attainment is a key behavioural measure in studies of cognitive and physical health, and socioeconomic status. We measured DNA methylation at 410,746 CpGs (N = 4152) and identified 58 CpGs associated with educational attainment at loci characterized by pleiotropic functions shared with neuronal, immune and developmental processes. Associations overlapped with those for smoking behaviour, but remained after accounting for smoking at many CpGs: Effect sizes were on average 28% smaller and genome-wide significant at 11 CpGs after adjusting for smoking and were 62% smaller in never smokers. We examined sources and biological implications of education-related methylation differences, demonstrating correlations with maternal prenatal folate, smoking and air pollution signatures, and associations with gene expression in cis, dynamic methylation in foetal brain, and correlations between blood and brain. Our findings show that the methylome of lower-educated people resembles that of smokers beyond effects of their own smoking behaviour and shows traces of various other exposures.

Genetic Contributions of Inflammation to Depression

This paper describes the effects of immune genes genetic variants and mRNA expression on depression's risk, severity, and response to antidepressant treatment, through a systematic review on all papers published between 2000 and 2016. Our results, based largely on case-control studies, suggest that common genetic variants and gene-expression pathways are involved in both immune activation and depression. The most replicated and relevant genetic variants include polymorphisms in the genes for interleukin (IL)-1β, IL-6, IL-10, monocyte chemoattractant protein-1, tumor necrosis factor-alpha, C-reactive protein, and phospholipase A2. Moreover, increased blood cytokines mRNA expression (especially of IL-1β) identifies patients that are less likely to respond to conventional antidepressants. However, even for the most replicated findings there are inconsistent results, not only between studies, but also between the immune effects of the genetic variants and the resulting effects on depression. We find evidence that these discrepant findings may be explained, at least in part, by the heterogeneity of the depression immunophenotype, by environmental influences and gene × environment interactions, and by the complex interfacing of genetic variants with gene expression. Indeed, some of the most robust findings have been obtained in patients developing depression in the context of treatment with interferon-alpha, a widely used model to mimic depression in the context of inflammation. Further 'omics' approaches, through GWAS and transcriptomics, will finally shed light on the interaction between immune genes, their expression, and the influence of the environment, in the pathogenesis of depression.

Meta-analysis of the COMT Val158Met polymorphism in major depressive disorder: the role of gender

OBJECTIVES

Many studies have reported an association of the COMT Val158Met polymorphism and major depressive disorder (MDD), although with conflicting results. The role of gender is a possible modulator. To overcome the problem of poor sample size detecting genes of small effect, we perform a meta-analysis of the current literature, investigating the influence of the COMT Val158Met polymorphism on the pathogenesis of MDD, with a major focus on the effect of gender.

METHODS

Out of 977 retrieved articles, 21 included case-control studies allowed the analysis of 9005 patients with MDD and 12,095 controls. Allelic and genotypic pooled odds ratios (OR) were calculated for the total sample and gender-subgroups.

RESULTS

In the absence of publication bias, allelic and genotypic analyses showed no significant association in the total sample, as well as in gender-specific subgroups. Sensitivity analysis did not alter the ORs.

CONCLUSIONS

The results imply a complex nature of the genotype × phenotype interaction. Further studies of the COMT gene or the locus remain to be justified given the important positional and functional relevance and the plethora of gender-specific findings. A possible way to further dissect this topic is shifting the focus to gene-based or genome-wide analyses of intermediate phenotypes.

Alterations of microRNA-124 expression in peripheral blood mononuclear cells in pre- and post-treatment patients with major depressive disorder

Recently, increasing evidence has indicated that dysfunction of microRNA-124 (miR-124) might be involved in the pathophysiology and treatment of major depressive disorder (MDD) in some animal models of depression. However, the role of miR-124 in MDD patients remains unclear. The objective of this study was to investigate whether the miR-124 expression levels in peripheral blood mononuclear cells (PBMCs) were associated with MDD and to evaluate the effects of antidepressant treatment on miR-124 levels. Quantitative real-time PCR was applied to detect miR-124 expression in 32 pre- and post-treatment MDD patients and 30 healthy controls. Our results showed that expression levels of miR-124 from PBMCs in MDD patients were significantly higher than those in healthy controls (p < 0.001), and that the area under the curve of miR-124 from ROC analysis was 0.762 with a sensitivity of 83.33% and specificity of 66.67% in distinguishing MDD patients from healthy controls. In addition, the expression levels of miR-124 were significantly down-regulated after eight weeks of treatment (p < 0.001). MiRNA target gene prediction and functional annotation analysis indicated that altered miR-124 was involved in affecting some important biological processes and pathways related to MDD. These results provide new information on miR-124 involvement in the biological alterations of MDD and in antidepressant effects.

The Genetics of Stress-Related Disorders: PTSD, Depression, and Anxiety Disorders

Research into the causes of psychopathology has largely focused on two broad etiologic factors: genetic vulnerability and environmental stressors. An important role for familial/heritable factors in the etiology of a broad range of psychiatric disorders was established well before the modern era of genomic research. This review focuses on the genetic basis of three disorder categories-posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and the anxiety disorders-for which environmental stressors and stress responses are understood to be central to pathogenesis. Each of these disorders aggregates in families and is moderately heritable. More recently, molecular genetic approaches, including genome-wide studies of genetic variation, have been applied to identify specific risk variants. In this review, I summarize evidence for genetic contributions to PTSD, MDD, and the anxiety disorders including genetic epidemiology, the role of common genetic variation, the role of rare and structural variation, and the role of gene-environment interaction. Available data suggest that stress-related disorders are highly complex and polygenic and, despite substantial progress in other areas of psychiatric genetics, few risk loci have been identified for these disorders. Progress in this area will likely require analysis of much larger sample sizes than have been reported to date. The phenotypic complexity and genetic overlap among these disorders present further challenges. The review concludes with a discussion of prospects for clinical translation of genetic findings and future directions for research.

Systems Genomics Support for Immune and Inflammation Hypothesis of Depression

BACKGROUND

Immune system plays an important role in brain development and function. With the discovery of increased circulating inflammatory cytokine levels in depression over two decades ago, evidence implicating immune system alterations in the disease has increasingly accumulated.

OBJECTIVE

To assess the underlying etiology and pathophysiology, a brief overview of the hypothesis free genomic, transcriptomic and proteomic studies in depression is presented here in order to specifically examine if the immune and inflammation hypothesis of depression is supported.

RESULTS

It is observed that genes identified in genome-wide association studies, and genes showing differential expression in transcriptomic studies in human depression do separately overrepresent processes related to both development as well as functioning of the immune system, and inflammatory response. These processes are also enriched in differentially expressed genes reported in animal models of antidepressant treatment. It is further noted that some of the genes identified in genome sequencing and proteomic analyses in human depression, and transcriptomic studies in chronic social defeat stress, an established animal model of depression, relate to immune and inflammatory pathways.

CONCLUSION

In conclusion, integrative genomics evidence supports the immune and inflammation hypothesis of depression.

The role of ventral striatal cAMP signaling in stress-induced behaviors

The cAMP and cAMP-dependent protein kinase A (PKA) signaling cascade is a ubiquitous pathway acting downstream of multiple neuromodulators. We found that the phosphorylation of phosphodiesterase-4 (PDE4) by cyclin-dependent protein kinase 5 (Cdk5) facilitated cAMP degradation and homeostasis of cAMP/PKA signaling. In mice, loss of Cdk5 throughout the forebrain elevated cAMP levels and increased PKA activity in striatal neurons, and altered behavioral responses to acute or chronic stressors. Ventral striatum- or D1 dopamine receptor-specific conditional knockout of Cdk5, or ventral striatum infusion of a small interfering peptide that selectively targeted the regulation of PDE4 by Cdk5, produced analogous effects on stress-induced behavioral responses. Together, our results demonstrate that altering cAMP signaling in medium spiny neurons of the ventral striatum can effectively modulate stress-induced behavioral states. We propose that targeting the Cdk5 regulation of PDE4 could be a new therapeutic approach for clinical conditions associated with stress, such as depression.

[Predictive factors of depression and its therapy]

Predictive factors of for the occurrence of depressive episodes include psychosocial and biological risk factors. These factors reflect the heterogeneity and complexity of the disease. They can identify groups that would benefit from preventive measures and provide indications for suitable preventive strategies. In recent decades considerable scientific effort, for example in the field of psychiatric genetics, has been undertaken to identify predictive factors for individual antidepressant therapy response and as an aid for individual treatment decisions. However, no clinically usable conclusions could yet be drawn from the respective findings. In practice clinical factors, such as symptom cluster of the depressive disorder and specific properties of the antidepressant, individual factors and contextual factors, such as the type of treatment facility, decision support and economic aspects, are factors influencing the choice of a specific antidepressant. Early clinical improvement under antidepressant medication in the first 2 weeks of treatment is one of the best predictors for the long-term treatment outcome in patients with major depressive disorder.

Coordinated messenger RNA/microRNA changes in fibroblasts of patients with major depression

BACKGROUND

Peripheral biomarkers for major psychiatric disorders have been an elusive target for the last half a century. Dermal fibroblasts are a simple, relevant, and much underutilized model for studying molecular processes of patients with affective disorders, as they share considerable similarity of signal transduction with neuronal tissue.

METHODS

Cultured dermal fibroblast samples from patients with major depressive disorder (MDD) and matched control subjects (n = 16 pairs, 32 samples) were assayed for genome-wide messenger RNA (mRNA) expression using microarrays. In addition, a simultaneous quantitative polymerase chain reaction-based assessment of >1000 microRNA (miRNA) species was performed. Finally, to test the relationship between the mRNA-miRNA expression changes, the two datasets were correlated with each other.

RESULTS

Our data revealed that MDD fibroblasts, when compared with matched control subjects, showed a strong mRNA gene expression pattern change in multiple molecular pathways, including cell-to-cell communication, innate/adaptive immunity, and cell proliferation. Furthermore, the same patient fibroblasts showed altered expression of a distinct panel of 38 miRNAs, which putatively targeted many of the differentially expressed mRNAs. The miRNA-mRNA expression changes appeared to be functionally connected, as the majority of the miRNA and mRNA changes were in the opposite direction.

CONCLUSIONS

Our data suggest that combined miRNA-mRNA assessments are informative about the disease process and that analyses of dermal fibroblasts might lead to the discovery of promising peripheral biomarkers of MDD that could be potentially used to aid the diagnosis and allow mechanistic testing of disturbed molecular pathways.

Large scale analysis of phenotype-pathway relationships based on GWAS results

The widely used pathway-based approach for interpreting Genome Wide Association Studies (GWAS), assumes that since function is executed through the interactions of multiple genes, different perturbations of the same pathway would result in a similar phenotype. This assumption, however, was not systemically assessed on a large scale. To determine whether SNPs associated with a given complex phenotype affect the same pathways more than expected by chance, we analyzed 368 phenotypes that were studied in >5000 GWAS. We found 216 significant phenotype-pathway associations between 70 of the phenotypes we analyzed and known pathways. We also report 391 strong phenotype-phenotype associations between phenotypes that are affected by the same pathways. While some of these associations confirm previously reported connections, others are new and could shed light on the molecular basis of these diseases. Our findings confirm that phenotype-associated SNPs cluster into pathways much more than expected by chance. However, this is true for <20% (70/368) of the phenotypes. Different types of phenotypes show markedly different tendencies: Virtually all autoimmune phenotypes show strong clustering of SNPs into pathways, while most cancers and metabolic conditions, and all electrophysiological phenotypes, could not be significantly associated with any pathway despite being significantly associated with a large number of SNPs. While this may be due to missing data, it may also suggest that these phenotypes could result only from perturbations of specific genes and not from other perturbations of the same pathway. Further analysis of pathway-associated versus gene-associated phenotypes is, therefore, needed in order to understand disease etiology and in order to promote better drug target selection.