Analyzing the genes and pathways related to major depressive disorder via a systems biology approach

Genome-wide association study of early-onset and late-onset postpartum depression: the IGEDEPP prospective study

Postpartum depression (PPD) appears at two peak periods: early-onset prior to 2 months after delivery and late-onset (2 months after delivery and beyond). The aim of our study is to evaluate the different genetic factors associated with early- and late-onset PPD. With the French multicenter interaction of gene and environment of depression during postpartum (IGEDEPP) cohort, we conducted a genome-wide association study (GWAS) on 234 women with early-onset PPD and 223 women with late-onset PPD, as well as 1,204 controls with no history of lifetime depression. We performed post-GWAS analyses: functional mapping and annotation of GWAS results using MAGMA thanks to Functional Mapping and Annotation of Genome-Wide Association Studies (FUMA), expression quantitative trait loci (QTL) analyses, mapping using data from the PsychENCODE and GTEx, and polygenic risk score (PRS) analysis based on published GWAS. We found two new significant candidate loci for early-onset PPD, rs6436132 in PTPRN gene on chromosome 2 and rs184644645 in RAD18 on chromosome 14, respectively, and one region of interest with five significant associated SNPs in chromosome 20 for late-onset PPD. Variant rs6436132 is the most significant associated with early-onset PPD, and it is a QTL that significantly modifies the expression and splicing of the PTPRN gene in different brain tissues. We also found an enrichment of uterus tissue in the early expression of PPD genes. PRS analysis showed a genetic overlap between both early and late-onset PPD and major depressive disorder, but only early-onset PPD overlaps with bipolar disorder. Our study presents two GWAS separately, highlighting two candidate loci for early-onset PPD and one different region of interest for late-onset PPD. These results have important consequences in our understanding of these disorders, especially since our data reinforce the hormonal pathophysiological hypotheses for early-onset PPD.

Links among genetic variants and hierarchical brain structural and functional networks for antidepressant treatment: A multivariate study

BACKGROUND

Antidepressant treatment effects are strongly heritable and have substantial effects on brain function and structure, but the underlying mechanisms are still poorly understood. In this research, we aimed to evaluate the factors of single nucleotide polymorphisms (SNPs) and hierarchical brain structural and functional networks that were associated with antidepressant treatment. Moreover, we further explored the correlations and mediation pattern among "brain structure-brain function-gene" in major depressive disorder (MDD).

METHODS

We analysed 405 SNPs and rich club/feeder/local connections of hierarchical structural and functional networks with three-way parallel independent component analysis in 179 MDD patients. The group-discriminative independent components of the three modalities between responders and non-responders of antidepressant treatment were identified. Pearson correlations and mediation analysis were further utilized to investigate the associations among SNPs and connections of the structural and functional networks.

RESULTS

Notably, correlations with antidepressant treatment outcomes were found in structural, functional and SNP modalities simultaneously. The features of group-discriminative independent components included the shared feeder connections of hub regions with the inferior frontal orbital gyrus and amygdala in structural and functional modalities and genes enriched in circadian rhythmic processes and dopaminergic synapse pathways. The structural feeder network displayed close correlations with SNPs and the functional feeder network. Furthermore, the structural feeder network could mediate the association between SNPs and the functional feeder network, implying that genetic variants might influence brain function by affecting brain structure in MDD.

CONCLUSIONS

These findings provide potential biomarkers for antidepressant therapy and provide a better grasp of the associations among SNPs and hierarchical structural and functional networks in MDD.

Pharmacological modulation of HIF-1 in the treatment of neuropsychiatric disorders

Hypoxia-inducible factor 1 has been identified as an important therapeutic target in psychiatric illnesses. Hypoxia is a condition in which tissues do not receive enough oxygen, resulting in less oxidative energy production. HIF-1, the master regulator of molecular response to hypoxia, is destabilized when oxygen levels fall. HIF-1, when activated, increases the gene transcription factors that promote adaptive response and longevity in hypoxia. HIF-regulated genes encode proteins involved in cell survival, energy metabolism, angiogenesis, erythropoiesis, and vasomotor control. Multiple genetic and environmental variables contribute to the pathophysiology of psychiatric disease. This review focuses on the most recent findings indicating the role of oxygen deprivation in CNS damage, with strong attention on HIF-mediated pathways. Several pieces of evidence suggested that, in the case of hypoxia, induction and maintenance of HIF-1 target genes may help reduce nerve damage. Major new insights into the molecular mechanisms that control HIF's sensitivity to oxygen are used to make drugs that can change the way HIF works as a therapeutic target for some CNS diseases.

Morphometric similarity network alterations in COVID-19 survivors correlate with behavioral features and transcriptional signatures

OBJECTIVES

To explore the differences in the cortical morphometric similarity network (MSN) between COVID-19 survivors and healthy controls, and the correlation between these differences and behavioralfeatures and transcriptional signatures.

MATERIALS & METHODS

39 COVID-19 survivors and 39 age-, sex- and education years-matched healthy controls (HCs) were included. All participants underwent MRI and behavioral assessments (PCL-17, GAD-7, PHQ-9). MSN analysis was used to compute COVID-19 survivors vs. HCs differences across brain regions. Correlation analysis was used to determine the associations between regional MSN differences and behavioral assessments, and determine the spatial similarities between regional MSN differences and risk genes transcriptional activity.

RESULTS

COVID-19 survivors exhibited decreased regional MSN in insula, precuneus, transverse temporal, entorhinal, para-hippocampal, rostral middle frontal and supramarginal cortices, and increased regional MSN in pars triangularis, lateral orbitofrontal, superior frontal, superior parietal, postcentral, and inferior temporal cortices. Regional MSN value of lateral orbitofrontal cortex was positively associated with GAD-7 and PHQ-9 scores, and rostral middle frontal was negatively related to PHQ-9 scores. The analysis of spatial similarities showed that seven risk genes (MFGE8, MOB2, NUP62, PMPCA, SDSL, TMEM178B, and ZBTB11) were related to regional MSN values.

CONCLUSION

The MSN differences were associated with behavioral and transcriptional signatures, early psychological counseling or intervention may be required to COVID-19 survivors. Our study provided a new insight into understanding the altered coordination of structure in COVID-19 and may offer a new endophenotype to further investigate the brain substrate.

Gene Expression has Distinct Associations with Brain Structure and Function in Major Depressive Disorder

Major depressive disorder (MDD) is associated with structural and functional brain abnormalities. MDD as well as brain anatomy and function are influenced by genetic factors, but the role of gene expression remains unclear. Here, this work investigates how cortical gene expression contributes to structural and functional brain abnormalities in MDD. This work compares the gray matter volume and resting-state functional measures in a Chinese sample of 848 MDD patients and 749 healthy controls, and these case-control differences are then associated with cortical variation of gene expression. While whole gene expression is positively associated with structural abnormalities, it is negatively associated with functional abnormalities. This work observes the relationships of expression levels with brain abnormalities for individual genes, and found that transcriptional correlates of brain structure and function show opposite relations with gene dysregulation in postmortem cortical tissue from MDD patients. This work further identifies genes that are positively or negatively related to structural abnormalities as well as functional abnormalities. The MDD-related genes are enriched for brain tissue, cortical cells, and biological pathways. These findings suggest that distinct genetic mechanisms underlie structural and functional brain abnormalities in MDD, and highlight the importance of cortical gene expression for the development of cortical abnormalities.

Unsupervised cross-domain functional MRI adaptation for automated major depressive disorder identification

Resting-state functional magnetic resonance imaging (rs-fMRI) data have been widely used for automated diagnosis of brain disorders such as major depressive disorder (MDD) to assist in timely intervention. Multi-site fMRI data have been increasingly employed to augment sample size and improve statistical power for investigating MDD. However, previous studies usually suffer from significant inter-site heterogeneity caused for instance by differences in scanners and/or scanning protocols. To address this issue, we develop a novel discrepancy-based unsupervised cross-domain fMRI adaptation framework (called UFA-Net) for automated MDD identification. The proposed UFA-Net is designed to model spatio-temporal fMRI patterns of labeled source and unlabeled target samples via an attention-guided graph convolution module, and also leverage a maximum mean discrepancy constrained module for unsupervised cross-site feature alignment between two domains. To the best of our knowledge, this is one of the first attempts to explore unsupervised rs-fMRI adaptation for cross-site MDD identification. Extensive evaluation on 681 subjects from two imaging sites shows that the proposed method outperforms several state-of-the-art methods. Our method helps localize disease-associated functional connectivity abnormalities and is therefore well interpretable and can facilitate fMRI-based analysis of MDD in clinical practice.

Identifying Antidepressant Effects of Brain-Derived Neurotrophic Factor and IDO1 in the Mouse Model Based on RNA-Seq Data

Deletion of brain-derived neurotrophic factor (BDNF) and upregulation of indoleamine 2,3-dioxygenase 1 (IDO1) are associated with depression severity in animals. The neurotransmitter hypothesis of depression at the transcriptomic level can be tested using BDNF- and IDO1-knockout mouse models and RNA-seq. In this study, BDNF^+/−, IDO1^−/−, and chronic ultra-mild stress (CUMS)-induced depression mouse models and controls were developed, and the differentially expressed genes were analyzed. Furthermore, the ceRNA package was used to search the lncRNA2Target database for potential lncRNAs. Finally, a protein–protein interaction (PPI) network was constructed using STRINGdb. By comparing the control and CUMS model groups, it was found that pathway enrichment analysis and ceRNA network analysis revealed that most differentially expressed genes (DEGs) were associated with protection of vulnerable neuronal circuits. In addition, we found the enriched pathways were associated with nervous system development and synapse organization when comparing the control and BDNF^+/−model groups. When replicating the neurotransmitter disruption features of clinical patients, such comparisons revealed the considerable differences between CUMS and knockdown BDNF models, and the BDNF^+/−model may be superior to the classic CUMS model. The data obtained in the present study implicated the potential DEGs and their enriched pathway in three mouse models related to depression and the regulation of the ceRNA network-mediated gene in the progression of depression. Together, our findings may be crucial for uncovering the mechanisms underlying the neurotransmitter hypothesis of depression in animals.

A Systematic Review of Candidate Genes for Major Depression

Background and Objectives: The aim of this systematic review was to analyse which candidate genes were examined in genetic association studies and their association with major depressive disorder (MDD). Materials and Methods: We searched PUBMED for relevant studies published between 1 July 2012 and 31 March 2019, using combinations of keywords: “major depressive disorder” OR “major depression” AND “gene candidate”, “major depressive disorder” OR “major depression” AND “polymorphism”. Synthesis focused on assessing the likelihood of bias and investigating factors that may explain differences between the results of studies. For selected gene list after literature overview, functional enrichment analysis and gene ontology term enrichment analysis were conducted. Results: 141 studies were included in the qualitative review of gene association studies focusing on MDD. 86 studies declared significant results (p < 0.05) for 172 SNPs in 85 genes. The 13 SNPs associations were confirmed by at least two studies. The 18 genetic polymorphism associations were confirmed in both the previous and this systematic analysis by at least one study. The majority of the studies (68.79 %) did not use or describe power analysis, which may have had an impact over the significance of their results. Almost a third of studies (N = 54) were conducted in Chinese Han population. Conclusion: Unfortunately, there is still insufficient data on the links between genes and depression. Despite the reported genetic associations, most studies were lacking in statistical power analysis, research samples were small, and most gene polymorphisms have been confirmed in only one study. Further genetic research with larger research samples is needed to discern whether the relationship is random or causal. Summations: This systematic review had summarized all reported genetic associations and has highlighted the genetic associations that have been replicated. Limitations: Unfortunately, most gene polymorphisms have been confirmed only once, so further studies are warranted for replicating these genetic associations. In addition, most studies included a small number of MDD cases that could be indicative for false positive. Considering that polymorphism loci and associations with MDD is also vastly dependent on interpersonal variation, extensive studies of gene interaction pathways could provide more answers to the complexity of MDD.

A Systematic Review of Circulatory microRNAs in Major Depressive Disorder: Potential Biomarkers for Disease Prognosis

Major depressive disorder (MDD) is a neuropsychiatric disorder, which remains challenging to diagnose and manage due to its complex endophenotype. In this aspect, circulatory microRNAs (cimiRNAs) offer great potential as biomarkers and may provide new insights for MDD diagnosis. Therefore, we systemically reviewed the literature to explore various cimiRNAs contributing to MDD diagnosis and underlying molecular pathways. A comprehensive literature survey was conducted, employing four databases from 2012 to January 2021. Out of 1004 records, 157 reports were accessed for eligibility criteria, and 32 reports meeting our inclusion criteria were considered for in-silico analysis. This study identified 99 dysregulated cimiRNAs in MDD patients, out of which 20 cimiRNAs found in multiple reports were selected for in-silico analysis. KEGG pathway analysis indicated activation of ALS, MAPK, p53, and P13K-Akt signaling pathways, while gene ontology analysis demonstrated that most protein targets were associated with transcription. In addition, chromosomal location analysis showed clustering of dysregulated cimiRNAs at proximity 3p22-p21, 9q22.32, and 17q11.2, proposing their coregulation with specific transcription factors primarily involved in MDD physiology. Further analysis of transcription factor sites revealed the existence of HIF-1, REST, and TAL1 in most cimiRNAs. These transcription factors are proposed to target genes linked with MDD, hypothesizing that first-wave cimiRNA dysregulation may trigger the second wave of transcription-wide changes, altering the protein expressions of MDD-affected cells. Overall, this systematic review presented a list of dysregulated cimiRNAs in MDD, notably miR-24-3p, let 7a-5p, miR-26a-5p, miR135a, miR-425-3p, miR-132, miR-124 and miR-16-5p as the most prominent cimiRNAs. However, various constraints did not permit us to make firm conclusions on the clinical significance of these cimiRNAs, suggesting the need for more research on single blood compartment to identify the biomarker potential of consistently dysregulated cimiRNAs in MDD, as well as the therapeutic implications of these in-silico insights.

A Systematic Analysis on the Genes and Their Interaction Underlying the Comorbidity of Alzheimer's Disease and Major Depressive Disorder

Background

During the past years, clinical and epidemiological studies have indicated a close relationship between Alzheimer's disease (AD) and other mental disorders like major depressive disorder (MDD). At the same time, a number of genes genetically associated with AD or MDD have been detected. However, our knowledge on the mechanisms that link the two disorders is still incomplete, and controversies exist. In such a situation, a systematic analysis on these genes could provide clues to understand the molecular features of two disorders and their comorbidity.

Methods

In this study, we compiled the genes reported to be associated with AD or MDD by a comprehensive search of human genetic studies and genes curated in disease-related database. Then, we investigated the features of the shared genes between AD and MDD using the functional enrichment analysis. Furthermore, the major biochemical pathways enriched in the AD- or MDD-associated genes were identified, and the cross talks between the pathways were analyzed. In addition, novel candidate genes related to AD and MDD were predicted in the context of human protein-protein interactome.

Results

We obtained 650 AD-associated genes, 447 MDD-associated genes, and 77 shared genes between AD and MDD. The functional analysis revealed that biological processes involved in cognition, neural development, synaptic transmission, and immune-related processes were enriched in the common genes, indicating a complex mechanism underlying the comorbidity of the two diseases. In addition, we conducted the pathway enrichment analysis and found 102 shared pathways between AD and MDD, which involved in neuronal development, endocrine, cell growth, and immune response. By using the pathway cross-talk analysis, we found that these pathways could be roughly clustered into four modules, i.e., the immune response-related module, the neurodevelopmental module, the cancer or cell growth module, and the endocrine module. Furthermore, we obtained 37 novel candidate genes potentially related to AD and MDD with node degrees > 5.0 by mapping the shared genes to human protein-protein interaction network (PPIN). Finally, we found that 37 novel candidate genes are significantly expressed in the brain.

Conclusion

These results indicated shared biological processes and pathways between AD and MDD and provided hints for the comorbidity of AD and MDD.

GABAA subunit single nucleotide polymorphisms show sex-specific association to alcohol consumption and mental distress in a Norwegian population-based sample

Little is known about genetic influences on the relationship between alcohol consumption and mental distress in the general population, where the majority report consumption and distress far below diagnostic thresholds. This study investigated single nucleotide polymorphisms (SNPs) from candidate gene studies on alcohol use disorder and depressive disorders, for association with alcohol consumption and with mental distress in a population-based sample from the Cohort of Norway (n = 1978, 49% women). The relationship between alcohol consumption and mental distress was further examined for genotype modification. There was a positive correlation between mental distress and alcohol consumption in men, as well as an association between SNPs and mental distress in men (GABRG1, GABRA2, DRD2, ANKK1, MTHFR) and women (CHRM2, MTHFR) and between SNPs and alcohol consumption in women (GABRA2, MTHFR). No modification by SNP genotype was found on the relationship between alcohol consumption and mental distress. The association between mental distress and GABRG1 in men remained significant after correcting for multiple comparisons. The results indicate that alcohol consumption and mental distress are associated in the general population even at levels below clinical thresholds and point to SNPs in genes related to GABAergic signalling for level of mental distress in men.

Identification of transcriptome alterations in the prefrontal cortex, hippocampus, amygdala and hippocampus of suicide victims

Suicide is one of the leading causes of death globally for all ages, and as such presents a very serious problem for clinicians worldwide. However, the underlying neurobiological pathology remains to a large extent unknown. In order to address this gap, we have carried out a genome-wide investigation of the gene expression in the amygdala, hippocampus, prefrontal cortex and thalamus in post-mortem brain samples obtained from 20 suicide completers and 7 control subjects. By KEGG enrichment analysis indicated we identified novel clusters of downregulated pathways involved in antigen neutralization and autoimmune thyroid disease (amygdala, thalamus), decreased axonal plasticity in the hippocampus. Two upregulated pathways were involved in neuronal death in the hippocampus and olfactory transduction in the thalamus and the prefrontal cortex. Autoimmune thyroid disease pathway was downregulated only in females. Metabolic pathways involved in Notch signaling amino acid metabolism and unsaturated lipid synthesis were thalamus-specific. Suicide-associated changes in the expression of several genes and pseudogenes that point to various functional mechanisms possibly implicated in the pathology of suicide. Two genes (SNORA13 and RNU4-2) involved in RNA processing were common to all brain regions analyzed. Most of the identified gene expression changes were related to region-specific dysregulated manifestation of genetic and epigenetic mechanisms underlying neurodevelopmental disorders (SNORD114-10, SUSd1), motivation, addiction and motor disorders (CHRNA6), long-term depression (RAB3B), stress response, major depression and schizophrenia (GFAP), signal transduction at the neurovascular unit (NEXN) and inhibitory neurotransmission in spatial learning, neural plasticity (CALB2; CLIC6, ENPP1). Some of the differentially expressed genes were brain specific non-coding RNAs involved in the regulation of translation (SNORA13). One, (PARM1) is a potential oncogene and prognostic biomarker for colorectal cancer with no known function in the brain. Disturbed gene expression involved in antigen neutralization, autoimmunity, neural plasticity, stress response, signal transduction at the neurovascular unit, dysregulated nuclear RNA processing and translation and epigenetic imprinting signatures is associated with suicide and point to regulatory non-coding RNAs as potential targets of new drugs development.

Integrative DNA Methylation and Gene Expression Analysis in the Prefrontal Cortex of Mexicans Who Died by Suicide

BACKGROUND

Suicide represents a major health concern, especially in developing countries. While many demographic risk factors have been proposed, the underlying molecular pathology of suicide remains poorly understood. A body of evidence suggests that aberrant DNA methylation and expression is involved. In this study, we examined DNA methylation profiles and concordant gene expression changes in the prefrontal cortex of Mexicans who died by suicide.

METHODS

In collaboration with the coroner's office in Mexico City, brain samples of males who died by suicide (n = 35) and age-matched sudden death controls (n = 13) were collected. DNA and RNA were extracted from prefrontal cortex tissue and analyzed with the Infinium Methylation480k and the HumanHT-12 v4 Expression Beadchips, respectively.

RESULTS

We report evidence of altered DNA methylation profiles at 4430 genomic regions together with 622 genes characterized by differential expression in cases vs controls. Seventy genes were found to have concordant methylation and expression changes. Metacore-enriched analysis identified 10 genes with biological relevance to psychiatric phenotypes and suicide (ADCY9, CRH, NFATC4, ABCC8, HMGA1, KAT2A, EPHA2, TRRAP, CD22, and CBLN1) and highlighted the association that ADCY9 has with various pathways, including signal transduction regulated by the cAMP-responsive element modulator, neurophysiological process regulated by the corticotrophin-releasing hormone, and synaptic plasticity. We therefore went on to validate the observed hypomethylation of ADCY9 in cases vs control through targeted bisulfite sequencing.

CONCLUSION

Our study represents the first, to our knowledge, analysis of DNA methylation and gene expression associated with suicide in a Mexican population using postmortem brain, providing novel insights for convergent molecular alterations associated with suicide.

Dysregulation of Myt1 expression acts as a potential peripheral biomarker for major depressive disorder and bipolar disorder

Major depressive disorder (MDD) and bipolar disorder (BPD) are among the most debilitating mental conditions. Diagnostic criteria for MDD include psychological and physical symptoms, such as low mood and changes in appetite or sleep, respectively. BPD in addition to periods of depression represents episodes of mania or hypomania, and elevation in mood and energy levels are associated with this condition. Dysregulation in adult neurogenesis and myelination have been reported in psychiatric disorders. As a key factor in neurogenesis, it was hypothesized that Myt1 gene expression may be altered in these conditions. Using Real-time PCR, Myt1 expression level in 100 MDD patients and 100 BPD patients, compared with healthy control (HC) individuals was evaluated. Results demonstrate significant downregulation of Myt1 in MDD and BPD. Logistic regression analysis and binary classification evaluation reveal potential risk factor and biomarker characteristics of Myt1, respectively. Moreover, forward and backward digit span results denote a significant reduction in the function of working memory (WM) of MDD and BPD subjects. Correlation analysis revealed a significant association between Myt1 downregulation and WM disruption in the affected individuals. In conclusion, due to its altered role in neurogenesis, downregulation of Myt1 can be associated with the pathology of MDD and BPD.

An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case

In addition to the psychological depressive phenotype, major depressive disorder (MDD) patients are also associated with underlying immune dysregulation that correlates with metabolic syndrome prevalent in depressive patients. A robust integrative analysis of biological pathways underlying the dysregulated neural connectivity and systemic inflammatory response will provide implications in the development of effective strategies for the diagnosis, management and the alleviation of associated comorbidities. In the current study, focusing on MDD, we explored an integrative network analysis methodology to analyze transcriptomic data combined with the meta-analysis of biomarker data available throughout public databases and published scientific peer-reviewed articles. Detailed gene set enrichment analysis and complex protein–protein, gene regulatory and biochemical pathway analysis has been undertaken to identify the functional significance and potential biomarker utility of differentially regulated genes, proteins and metabolite markers. This integrative analysis method provides insights into the molecular mechanisms along with key glycosylation dysregulation underlying altered neutrophil-platelet activation and dysregulated neuronal survival maintenance and synaptic functioning. Highlighting the significant gap that exists in the current literature, the network analysis framework proposed reduces the impact of data gaps and permits the identification of key molecular signatures underlying complex disorders with multiple etiologies such as within MDD and presents multiple treatment options to address their molecular dysfunction.

Can Molecular Biology Propose Reliable Biomarkers for Diagnosing Major Depression?

BACKGROUND

Modern medicine has provided considerable knowledge of the pathophysiology of mental disorders at the body, systemic, organ and neurochemical levels of the biological organization of the body. Modern clinical diagnostics of depression have some problems, that is why psychiatric society makes use of diagnostics and taxonomy of different types of depression by implemention of modern molecular biomarkers in diagnostic procedures. But up to now, there are no reliable biomarkers of major depressive disorder (MDD) and other types of depression.

OBJECTIVE

The purpose of this review is to find fundamentals in pathological mechanisms of depression, which could be a basis for development of molecular and genetic biomarkers, being the most feasible for clinical use.

METHOD

This review summarizes the published data using PubMed, Science Direct, Google Scholar and Scopus.

RESULTS

In this review, we summarized and discussed findings in molecular biology, genetics, neuroplasticity, neurotransmitters, and neuroimaging that could increase our understanding of the biological foundations of depression and show new directions for the development of reliable biomarkers. We did not find any molecular and genetic biomarker approved for the clinic. But the Genome-Wide Association Study method promises some progress in the development of biomarkers based on SNP in the future. Epigenetic factors also are a promising target for biomarkers. We have found some differences in the etiology of different types of atypical and melancholic depression. This knowledge could be the basis for development of biomarkers for clinical practice in diagnosis, prognosis and selection of treatment.

CONCLUSION

Depression is not a monoetiological disease. Many pathological mechanisms are involved in depression, thus up to now, there is no approved and reliable biomarker for diagnosis, prognosis and correction of treatment of depression. The structural and functional complexity of the brain, the lack of invasive technology, poor correlations between genetic and clinical manifestation of depression, imperfect psychiatric classification and taxonomy of subtypes of disease are the main causes of this situation. One of the possible ways to come over this situation can be to pay attention to the trigger mechanism of disease and its subtypes. Researchers and clinicians should focus their efforts on searching the trigger mechanism of depression and different types of it . HPA axis can be a candidate for such trigger in depression caused by stress, because it influences the main branches of disease: neuroinflammation, activity of biogenic amines, oxidative and nitrosative stress, epigenetic factors, metabolomics, etc. But before we shall find any trigger mechanism, we need to create complex biomarkers reflecting genetic, epigenetic, metabolomics and other pathological changes in different types of depression. Recently the most encouraging results have been obtained from genetics and neuroimaging. Continuing research in these areas should be forced by using computational, statistical and systems biology approaches, which can allow to obtain more knowledge about the neurobiology of depression. In order to obtain clinically useful tests, search for biomarkers should use appropriate research methodologies with increasing samples and identifying more homogeneous groups of depressed patients.

Cortical structural differences in major depressive disorder correlate with cell type-specific transcriptional signatures

Major depressive disorder (MDD) has been shown to be associated with structural abnormalities in a variety of spatially diverse brain regions. However, the correlation between brain structural changes in MDD and gene expression is unclear. Here, we examine the link between brain-wide gene expression and morphometric changes in individuals with MDD, using neuroimaging data from two independent cohorts and a publicly available transcriptomic dataset. Morphometric similarity network (MSN) analysis shows replicable cortical structural differences in individuals with MDD compared to control subjects. Using human brain gene expression data, we observe that the expression of MDD-associated genes spatially correlates with MSN differences. Analysis of cell type-specific signature genes suggests that microglia and neuronal specific transcriptional changes account for most of the observed correlation with MDD-specific MSN differences. Collectively, our findings link molecular and structural changes relevant for MDD.

The correlation between brain structural changes in major depressive disorder (MDD) and gene expression is unclear. Here, the authors explore the correlation between cell type-specific gene expression changes and cortical structural difference in individuals with major depressive disorder.

Integrative Genomic-Epigenomic Analysis of Clozapine-Treated Patients with Refractory Psychosis

Clozapine (CLZ) is the only antipsychotic drug that has been proven to be effective in patients with refractory psychosis, but it has also been proposed as an effective mood stabilizer; however, the complex mechanisms of action of CLZ are not yet fully known. To find predictors of CLZ-associated phenotypes (i.e., the metabolic ratio, dosage, and response), we explore the genomic and epigenomic characteristics of 44 patients with refractory psychosis who receive CLZ treatment based on the integration of polygenic risk score (PRS) analyses in simultaneous methylome profiles. Surprisingly, the PRS for bipolar disorder (BD-PRS) was associated with the CLZ metabolic ratio (pseudo-R2 = 0.2080, adjusted p-value = 0.0189). To better explain our findings in a biological context, we assess the protein-protein interactions between gene products with high impact variants in the top enriched pathways and those exhibiting differentially methylated sites. The GABAergic synapse pathway was found to be enriched in BD-PRS and was associated with the CLZ metabolic ratio. Such interplay supports the use of CLZ as a mood stabilizer and not just as an antipsychotic. Future studies with larger sample sizes should be pursued to confirm the findings of this study.

[6S]-5-Methyltetrahydrofolic Acid and Folic Acid Pregnancy Diets Differentially Program Metabolic Phenotype and Hypothalamic Gene Expression of Wistar Rat Dams Post-Birth

[6S]-5-methyltetrahydrofolic acid (MTHF) is a proposed replacement for folic acid (FA) in diets and prenatal supplements. This study compared the effects of these two forms on maternal metabolism and hypothalamic gene expression. Pregnant Wistar rats received an AIN-93G diet with recommended FA (1X, 2 mg/kg, control), 5X-FA or equimolar levels of MTHF. During lactation they received the control diet and then a high fat diet for 19-weeks post-weaning. Body weight, adiposity, food intake, energy expenditure, plasma hormones, folate, and 1-carbon metabolites were measured. RNA-sequencing of the hypothalamus was conducted at parturition. Weight-loss from weaning to 1-week post-weaning was less in dams fed either form of the 5X vs. 1X folate diets, but final weight-gain was higher in 5X-MTHF vs. 5X-FA dams. Both doses of the MTHF diets led to 8% higher food intake and associated with lower plasma leptin at parturition, but higher leptin at 19-weeks and insulin resistance at 1-week post-weaning. RNA-sequencing revealed 279 differentially expressed genes in the hypothalamus in 5X-MTHF vs. 5X-FA dams. These findings indicate that MTHF and FA differ in their programing effects on maternal phenotype, and a potential adverse role of either form when given at the higher doses.

Metabolomic analysis of the hippocampus in a rat model of chronic mild unpredictable stress-induced depression based on a pathway crosstalk and network module approach

BACKGROUND

The molecular alterations underlying the pathogenesis of depression have not been systematically defined. Increasing evidence suggests that hippocampus metabolism is strongly involved in the pathogenesis of chronic mild unpredictable stress (CUMS)-induced depression. The principal objective of this study was to reveal important information concerning the pathogenesis of depression through a comprehensive analysis of metabolites in the hippocampus in a CUMS rat model.

METHODS

Metabolites related to metabolic changes in the hippocampus in the CUMS model were collected from a depression-specific database and published literature. Potential metabolite pathways were identified by the Omicsolution tool. Then, crosstalk analysis was carried out to investigate the relationship between different important pathways. In addition, MetaboAnalyst was used to analyze potential metabolites for drug-related metabolite enrichment analysis, which was used to study hippocampus metabolite-related drug pathways in a CUMS model. Then, a metabolite-protein interaction (MPI) network was constructed and analyzed to identify important metabolites and proteins. The functional modules were extracted using the CNM network decomposition algorithm. Finally, neurotransmitters in the hippocampus of rats with CUMS depression were detected to verify the important pathways.

RESULTS

In the current study, 53 significantly enriched pathways related to the 107 identified metabolites were selected, and the top ranked enriched pathways included arginine and proline metabolism, neuroactive ligand-receptor interaction, phenylalanine metabolism, bile secretion, and glutathione metabolism. Pathway crosstalk analysis showed that the significantly enriched pathways were divided into two interrelated modules, which were mainly involved in metabolism, signal transduction, neurotransmitters, and the endocrine system. Enrichment analysis of drug-related metabolic KEGG pathways identified the antibiotic pathways as the most important pathways. In the MPI network, the hub metabolites were phosphate, arachidonic acid, oxoglutaric acid, l-glutamic acid, and glutathione, and the hub proteins were Got1, Got2, Tat, Ccbl1, Ccbl2, Il4i1. A total of 16 functional modules were extracted from the MPI network by using the CNM algorithm. Finally, metabolites related to serotonergic synapses, dopaminergic synapses, and glutamatergic synapses were found to be involved in the pathology of depression.

CONCLUSION

We found that neurotransmitter pathways (serotonergic synapses, dopaminergic synapses and glutamatergic synapses) in the hippocampus play a crucial role in the underlying molecular mechanism of depression, which provides useful clues for identifying the detailed depression-associated metabolic profiles.

Maternal age at delivery and risk of allergy and asthma in the offspring: a systematic review and meta-analysis protocol

INTRODUCTION

While several perinatal factors have been linked to the risk of developing asthma and allergy in childhood, the role of maternal age at delivery remains uncertain. Some studies suggest that young maternal age at delivery may increase the risk, while other studies suggested a reduced risk. To provide a clearer appreciation of the underlying evidence, we plan to undertake a systematic review to synthesise previous studies that have investigated the association between maternal age at delivery and the risk of asthma and allergy in the offspring.

METHODS AND ANALYSIS

We will search PubMed, EMBASE, ISI Web of Science, Scopus and Google Scholar to identify relevant studies on the topic published in the databases from inception until October 2020. We will search databases of proceedings of international conferences, contact authors who have published on the topic and search the reference lists of the included studies in order to identify additional studies. Two investigators will independently screen the identified studies, perform data extraction and examine the risk of bias in the studies; a third investigator will arbitrate throughout these processes. We will use the Effective Public Health Practice Project tool for assessment of the risk of bias in included studies. We will perform random-effects meta-analysis to combine effect estimates from included studies judged to be homogeneous.

ETHICS AND DISSEMINATION

Only data from the published literature will be included in this study, therefore no ethics approval is required. Our findings will be published in a peer-reviewed journal.

PROTOCOL REGISTRATION

The protocol has been submitted for registration on PROSPERO, University of York, and Centre for Review and Dissemination, now awaiting the assignment of a registration number.

Analyzing the genes and pathways related to major depressive disorder via a systems biology approach

INTRODUCTION

Major depressive disorder (MDD) is a mental disorder caused by the combination of genetic, environmental, and psychological factors. Over the years, a number of genes potentially associated with MDD have been identified. However, in many cases, the role of these genes and their relationship in the etiology and development of MDD remains unclear. Under such situation, a systems biology approach focusing on the function correlation and interaction of the candidate genes in the context of MDD will provide useful information on exploring the molecular mechanisms underlying the disease.

METHODS

We collected genes potentially related to MDD by screening the human genetic studies deposited in PubMed (https://www.ncbi.nlm.nih.gov/pubmed). The main biological themes within the genes were explored by function and pathway enrichment analysis. Then, the interaction of genes was analyzed in the context of protein-protein interaction network and a MDD-specific network was built by Steiner minimal tree algorithm.

RESULTS

We collected 255 candidate genes reported to be associated with MDD from available publications. Functional analysis revealed that biological processes and biochemical pathways related to neuronal development, endocrine, cell growth and/or survivals, and immunology were enriched in these genes. The pathways could be largely grouped into three modules involved in biological procedures related to nervous system, the immune system, and the endocrine system, respectively. From the MDD-specific network, 35 novel genes potentially associated with the disease were identified.

CONCLUSION

By means of network- and pathway-based methods, we explored the molecular mechanism underlying the pathogenesis of MDD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular features of MDD.