Integrated profiling of phenotype and blood transcriptome for stress vulnerability and depression

Identification of core genes, critical signaling pathways, and potential drugs for countering BPA-induced hippocampal neurotoxicity in male mice

Although the neurotoxicity of the common chemical bisphenol A (BPA) to the mouse hippocampus has been often reported, the mechanism underlying BPA-induced depression-like behavior in mice remains unclear. We evaluated BPA's role in inducing depressive-like behavior by exposing male mice to different BPA concentrations (0, 0.01, 0.1, and 1 μg/mL) and using the forced swimming test (FST) and tail suspension test (TST). We aimed to identify critical gene and anti-BPA-neurotoxicity compounds using RNA sequencing combined with bioinformatics analysis. Our results showed that 1 μg/mL BPA exposure increased mouse immobility during the FST and TST. Based on BPA-induced hippocampal transcriptome changes, we identified NADH: ubiquinone oxidoreductase subunit AB1 (Ndufab1) as a critical and potential therapeutic target gene, and Ndufab1 mRNA and protein levels were downregulated in the BPA-exposed groups. Furthermore, molecular docking identified phenelzine as a compound that could counteract BPA-related neurotoxicity. Conclusively, our analyses confirmed that BPA triggers depressive behavior in male mice by downregulating Ndufab1 expression and suggested that phenelzine might reduce BPA-induced neurotoxicity.

Investigation of the shared molecular mechanisms and hub genes between myocardial infarction and depression

Background

The pathogenesis of myocardial infarction complicating depression is still not fully understood. Bioinformatics is an effective method to study the shared pathogenesis of multiple diseases and has important application value in myocardial infarction complicating depression.

Methods

The differentially expressed genes (DEGs) between control group and myocardial infarction group (M-DEGs), control group and depression group (D-DEGs) were identified in the training set. M-DEGs and D-DEGs were intersected to obtain DEGs shared by the two diseases (S-DEGs). The GO, KEGG, GSEA and correlation analysis were conducted to analyze the function of DEGs. The biological function differences of myocardial infarction and depression were analyzed by GSVA and immune cell infiltration analysis. Four machine learning methods, nomogram, ROC analysis, calibration curve and decision curve were conducted to identify hub S-DEGs and predict depression risk. The unsupervised cluster analysis was constructed to identify myocardial infarction molecular subtype clusters based on hub S-DEGs. Finally, the value of these genes was verified in the validation set, and blood samples were collected for RT-qPCR experiments to further verify the changes in expression levels of these genes in myocardial infarction and depression.

Results

A total of 803 M-DEGs, 214 D-DEGs, 13 S-DEGs and 6 hub S-DEGs (CD24, CSTA, EXTL3, RPS7, SLC25A5 and ZMAT3) were obtained in the training set and they were all involved in immune inflammatory response. The GSVA and immune cell infiltration analysis results also suggested that immune inflammation may be the shared pathogenesis of myocardial infarction and depression. The diagnostic models based on 6 hub S-DEGs found that these genes showed satisfactory combined diagnostic performance for depression. Then, two molecular subtypes clusters of myocardial infarction were identified, many differences in immune inflammation related-biological functions were found between them, and the hub S-DEGs had satisfactory molecular subtypes identification performance. Finally, the analysis results of the validation set further confirmed the value of these hub genes, and the RT-qPCR results of blood samples further confirmed the expression levels of these hub genes in myocardial infarction and depression.

Conclusion

Immune inflammation may be the shared pathogenesis of myocardial infarction and depression. Meanwhile, hub S-DEGs may be potential biomarkers for the diagnosis and molecular subtype identification of myocardial infarction and depression.

The emerging role of long noncoding RNA in depression and its implications in diagnostics and therapeutic responses

Depression is one of the most common mental illnesses, affecting more than 350 million people worldwide. However, the occurrence of depression is a complex process involving genetic, physiological, psychological, and social factors, and the underlying mechanisms of its pathogenesis remain unclear. With advances in sequencing technology and epigenetic studies, increasing research evidence suggests that long noncoding RNAs (lncRNAs) play nonnegligible roles in the development of depression and may be involved in the pathogenesis of depression through multiple pathways, including regulating neurotrophic factors and other growth factors and affecting synaptic function. In addition, significant alterations in lncRNA expression profiles in peripheral blood and different brain regions of patients and model animals with depression suggest that lncRNAs may function as biomarkers for the differential diagnosis of depression and other psychiatric disorders and may also be potential therapeutic targets. In this paper, the biological functions of lncRNAs are briefly described, and the functional roles and abnormal expression of lncRNAs in the development, diagnosis and treatment of depression are reviewed.

NPAS4 in the medial prefrontal cortex mediates chronic social defeat stress-induced anhedonia-like behavior and reductions in excitatory synapses

Chronic stress can produce reward system deficits (i.e., anhedonia) and other common symptoms associated with depressive disorders, as well as neural circuit hypofunction in the medial prefrontal cortex (mPFC). However, the molecular mechanisms by which chronic stress promotes depressive-like behavior and hypofrontality remain unclear. We show here that the neuronal activity-regulated transcription factor, NPAS4, in the mPFC is regulated by chronic social defeat stress (CSDS), and it is required in this brain region for CSDS-induced changes in sucrose preference and natural reward motivation in the mice. Interestingly, NPAS4 is not required for CSDS-induced social avoidance or anxiety-like behavior. We also find that mPFC NPAS4 is required for CSDS-induced reductions in pyramidal neuron dendritic spine density, excitatory synaptic transmission, and presynaptic function, revealing a relationship between perturbation in excitatory synaptic transmission and the expression of anhedonia-like behavior in the mice. Finally, analysis of the mice mPFC tissues revealed that NPAS4 regulates the expression of numerous genes linked to glutamatergic synapses and ribosomal function, the expression of upregulated genes in CSDS-susceptible animals, and differentially expressed genes in postmortem human brains of patients with common neuropsychiatric disorders, including depression. Together, our findings position NPAS4 as a key mediator of chronic stress-induced hypofrontal states and anhedonia-like behavior.

Dulaglutide Improves Gliosis and Suppresses Apoptosis/Autophagy Through the PI3K/Akt/mTOR Signaling Pathway in Vascular Dementia Rats

Dulaglutide is a new type of hypoglycemic agent that agonizes glucagon-like peptide-1 receptor (GLP-1RA). It can be concluded from previous studies that a GLP-1RA can reduce apoptosis and regulate autophagy in the nervous system, while related research on dulaglutide in vascular dementia (VD) has not been reported. In our study, the VD rat model was established by bilateral carotid artery occlusion, and the results of the Morris water maze test (MWM) and open-field test showed that the application of dulaglutide could effectively reduce the cognitive decline of VD rats without changing the behavior in the open-field test, which was used to assess an anxiety-like phenotype. We applied HE staining and immunofluorescence labeling to show that dulaglutide treatment significantly alleviated neuronal damage in the hippocampal region of VD rats, and reduced microglial and astrocyte proliferation. Western blot results showed that dulaglutide reduced VD-induced neuronal apoptosis (BCL2/BAX, c-caspase3) and autophagy (P62, LC3B, Beclin-1), and upregulated phosphorylation of PI3K/Akt/mTOR signaling pathway. KEGG pathway analysis of RNA-Sequence results showed that the differentially expressed genes in the dulaglutide treatment group were significantly enriched in the mTOR signaling pathway, and the repressor of mTOR, Deptor, was down-regulated. In conclusion, this study suggested that dulaglutide may alleviate learning and memory impairment and neuron damage in VD rats by attenuating apoptosis, regulating autophagy, and activating the PI3K/Akt/mTOR signaling pathway in neurons, which may make it a promising candidate for the simultaneous treatment of VD and diabetes.

Transcriptomic Studies of Antidepressant Action in Rodent Models of Depression: A First Meta-Analysis

Antidepressants (ADs) are, for now, the best everyday treatment we have for moderate to severe major depressive episodes (MDEs). ADs are among the most prescribed drugs in the Western Hemisphere; however, the trial-and-error prescription strategy and side-effects leave a lot to be desired. More than 60% of patients suffering from major depression fail to respond to the first AD they are prescribed. For those who respond, full response is only observed after several weeks of treatment. In addition, there are no biomarkers that could help with therapeutic decisions; meanwhile, this is already true in cancer and other fields of medicine. For years, many investigators have been working to decipher the underlying mechanisms of AD response. Here, we provide the first systematic review of animal models. We thoroughly searched all the studies involving rodents, profiling transcriptomic alterations consecutive to AD treatment in naïve animals or in animals subjected to stress-induced models of depression. We have been confronted by an important heterogeneity regarding the drugs and the experimental settings. Thus, we perform a meta-analysis of the AD signature of fluoxetine (FLX) in the hippocampus, the most studied target. Among genes and pathways consistently modulated across species, we identify both old players of AD action and novel transcriptional biomarker candidates that warrant further investigation. We discuss the most prominent transcripts (immediate early genes and activity-dependent synaptic plasticity pathways). We also stress the need for systematic studies of AD action in animal models that span across sex, peripheral and central tissues, and pharmacological classes.

Effects of Psychotropic Drugs on Ribosomal Genes and Protein Synthesis

Altered protein synthesis has been implicated in the pathophysiology of several neuropsychiatric disorders, particularly schizophrenia. Ribosomes are the machinery responsible for protein synthesis. However, there remains little information on whether current psychotropic drugs affect ribosomes and contribute to their therapeutic effects. We treated human neuronal-like (NT2-N) cells with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), valproate (0.5 mM) or vehicle control for 24 h. Transcriptomic and gene set enrichment analysis (GSEA) identified that the ribosomal pathway was altered by these drugs. We found that three of the eight drugs tested significantly decreased ribosomal gene expression, whilst one increased it. Most changes were observed in the components of cytosolic ribosomes and not mitochondrial ribosomes. Protein synthesis assays revealed that aripiprazole, clozapine and lithium all decreased protein synthesis. Several currently prescribed psychotropic drugs seem to impact ribosomal gene expression and protein synthesis. This suggests the possibility of using protein synthesis inhibitors as novel therapeutic agents for neuropsychiatric disorders.

Identification of Key Modules and Genes Associated with Major Depressive Disorder in Adolescents

Major depressive disorder (MDD) is a leading cause of disability worldwide. Adolescence is a crucial period for the occurrence and development of depression. There are essential distinctions between adolescent and adult depression patients, and the etiology of depressive disorder is unclear. The interactions of multiple genes in a co-expression network are likely to be involved in the physiopathology of MDD. In the present study, RNA-Seq data of mRNA were acquired from the peripheral blood of MDD in adolescents and healthy control (HC) subjects. Co-expression modules were constructed via weighted gene co-expression network analysis (WGCNA) to investigate the relationships between the underlying modules and MDD in adolescents. In the combined MDD and HC groups, the dynamic tree cutting method was utilized to assign genes to modules through hierarchical clustering. Moreover, functional enrichment analysis was conducted on those co-expression genes from interested modules. The results showed that eight modules were constructed by WGCNA. The blue module was significantly associated with MDD after multiple comparison adjustment. Several Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with stress and inflammation were identified in this module, including histone methylation, apoptosis, NF-kappa β signaling pathway, and TNF signaling pathway. Five genes related to inflammation, immunity, and the nervous system were identified as hub genes: CNTNAP3, IL1RAP, MEGF9, UBE2W, and UBE2D1. All of these findings supported that MDD was associated with stress, inflammation, and immune responses, helping us to obtain a better understanding of the internal molecular mechanism and to explore biomarkers for the diagnosis or treatment of depression in adolescents.

Exploration of the mechanism by which icariin modulates hippocampal neurogenesis in a rat model of depression

Icariin (ICA) has a significant capacity to protect against depression and hippocampal injury, but it cannot effectively cross the blood-brain barrier and accumulate in the brain. Therefore, the mechanism by which ICA protects against hippocampal injury in depression remains unclear. In this study, we performed proteomics analysis of cerebrospinal fluid to investigate the mechanism by which ICA prevents dysfunctional hippocampal neurogenesis in depression. A rat model of depression was established through exposure to chronic unpredictable mild stress for 6 weeks, after which 120 mg/kg ICA was administered subcutaneously every day. The results showed that ICA alleviated depressive symptoms, learning and memory dysfunction, dysfunctional neurogenesis, and neuronal loss in the dentate gyrus of rats with depression. Neural stem cells from rat embryonic hippocampi were cultured in media containing 20% cerebrospinal fluid from each group of rats and then treated with 100 μM corticosterone. The addition of cerebrospinal fluid from rats treated with ICA largely prevented the corticosterone-mediated inhibition of neuronal proliferation and differentiation. Fifty-two differentially expressed proteins regulated by chronic unpredictable mild stress and ICA were identified through proteomics analysis of cerebrospinal fluid. These proteins were mainly involved in the ribosome, PI3K-Akt signaling, and interleukin-17 signaling pathways. Parallel reaction monitoring mass spectrometry showed that Rps4x, Rps12, Rps14, Rps19, Hsp90b1, and Hsp90aa1 were up-regulated by chronic unpredictable mild stress and down-regulated by ICA. In contrast, HtrA1 was down-regulated by chronic unpredictable mild stress and up-regulated by ICA. These findings suggest that ICA can prevent depression and dysfunctional hippocampal neurogenesis through regulating the expression of certain proteins found in the cerebrospinal fluid. The study was approved by the Experimental Animal Ethics Committee of Guangzhou University of Chinese Medicine of China in March 2017.

Cerebrospinal fluid proteomics reveal potential protein targets of JiaWeiSiNiSan in preventing chronic psychological stress damage

CONTEXT

Chinese herbal formula JiaWeiSiNiSan (JWSNS) has been widely used to prevent stress-induced neuropsychiatric ailments in clinics and proven to have therapeutic anti-stress effects on rats. However, the mechanism remains unclear.

OBJECTIVE

Based on the proteomics of cerebrospinal fluid (CSF), this study explores the possible mechanism and target proteins of JiaWeiSiNiSan raising stress resilience and preventing stress damage.

MATERIALS AND METHODS

A 6-week Chronic Unpredictable Mild Stress (CUMS) model was applied on adult Wistar male rats to observe the effects of JWSNS on improving mental stress resilience. Tandem Mass Tag (TMT) proteomics and bioinformatics analysis were used to screen and analyze differentially expressed proteins (DEPs) in CSF. Parallel Reaction Monitoring (PRM) was used to validate target DEPs.

RESULTS

Significantly decreased sucrose preference, locomotion activity level and accuracy of T-maze, as well as increased immobility time, were observed in CUMS rats compared to CON rats while JWSNS improved above depression-like behaviours. The quantitative proteomics and bioinformatics analysis showed that JWSNS decreased the expression of Rps4x, HSP90AA1, Rps12, Uba1, Rsp14, Tuba1b in CUMS rats CSF (p < 0.05, FDR < 0.5). Immunofluorescence results showed that the number of BrdU/DCX positive cells (p < 0.01) and the relative number of neurons (p < 0.01) in the hippocampus dentate gyrus (DG) of the JSWNS group significantly increased, compared with the CUMS group.

CONCLUSIONS

JWSNS could increase mental stress resilience and prevent stress damage by regulating proteins in CSF. This study provides a scientific basis for further study on Chinese formulas preventing mental illness.

Distinct epigenetic signatures between adult-onset and late-onset depression

The heterogeneity of major depressive disorder (MDD) is attributed to the fact that diagnostic criteria (e.g., DSM-5) are only based on clinical symptoms. The discovery of blood biomarkers has the potential to change the diagnosis of MDD. The purpose of this study was to identify blood biomarkers of DNA methylation by strategically subtyping patients with MDD by onset age. We analyzed genome-wide DNA methylation of patients with adult-onset depression (AOD; age ≥ 50 years, age at depression onset < 50 years; N = 10) and late-onset depression (LOD; age ≥ 50 years, age at depression onset ≥ 50 years; N = 25) in comparison to that of 30 healthy subjects. The methylation profile of the AOD group was not only different from that of the LOD group but also more homogenous. Six identified methylation CpG sites were validated by pyrosequencing and amplicon bisulfite sequencing as potential markers for AOD in a second set of independent patients with AOD and healthy control subjects (N = 11). The combination of three specific methylation markers achieved the highest accuracy (sensitivity, 64%; specificity, 91%; accuracy, 77%). Taken together, our findings suggest that DNA methylation markers are more suitable for AOD than for LOD patients.

Transcriptomics Analysis Reveals Shared Pathways in Peripheral Blood Mononuclear Cells and Brain Tissues of Patients With Schizophrenia

Background: Schizophrenia is a serious mental disorder with complicated biological mechanisms. Few studies explore the transcriptional features that are shared in brain tissue and peripheral blood. In the present study, we aimed to explore the biological pathways with similar expression patterns in both peripheral blood mononuclear cells (PBMCs) and brain tissues. Methods: The present study used transcriptomics technology to detect mRNA expression of PBMCs of 10 drug-naïve patients with schizophrenia and 20 healthy controls. Transcriptome data sets of brain tissue of patients with schizophrenia downloaded from public databases were also analyzed in our study. The biological pathways with similar expression patterns in the PBMCs and brain tissues were uncovered by differential expression analysis, weighted gene co-expression network analysis (WGCNA), and pathway analysis. Finally, the expression levels of differential expressed genes (DEGs) were validated by real-time fluorescence quantitative polymerase chain reaction (qPCR) in another 12 drug-naïve patients with schizophrenia and 12 healthy controls. Results: We identified 542 DEGs, 51 DEGs, 732 DEGs, and 104 DEGs in PBMCs, dorsolateral prefrontal cortex, anterior cingulate gyrus, and nucleus accumbent, respectively. Five DEG clusters were recognized as having similar gene expression patterns in PBMCs and brain tissues by WGCNA. The pathway analysis illustrates that these DEG clusters are mainly enriched in several biological pathways that are related to phospholipid metabolism, ribosome signal transduction, and mitochondrial oxidative phosphorylation. The differential significance of PLAAT3, PLAAT4, PLD2, RPS29, RPL30, COX7C, COX7A2, NDUFAF2, and ATP5ME were confirmed by qPCR. Conclusions: This study finds that the pathways associated with phospholipid metabolism, ribosome signal transduction, and energy metabolism have similar expression patterns in PBMCs and brain tissues of patients with schizophrenia. Our results supply a novel insight for revealing the pathogenesis of schizophrenia and might offer a new approach to explore potential biological markers of peripheral blood in schizophrenia.

Equivalent change enrichment analysis: assessing equivalent and inverse change in biological pathways between diverse experiments

Background

In silico functional genomics have become a driving force in the way we interpret and use gene expression data, enabling researchers to understand which biological pathways are likely to be affected by the treatments or conditions being studied. There are many approaches to functional genomics, but a number of popular methods determine if a set of modified genes has a higher than expected overlap with genes known to function as part of a pathway (functional enrichment testing). Recently, researchers have started to apply such analyses in a new way: to ask if the data they are collecting show similar disruptions to biological functions compared to reference data. Examples include studying whether similar pathways are perturbed in smokers vs. users of e-cigarettes, or whether a new mouse model of schizophrenia is justified, based on its similarity in cytokine expression to a previously published model. However, there is a dearth of robust statistical methods for testing hypotheses related to these questions and most researchers resort to ad hoc approaches. The goal of this work is to develop a statistical approach to identifying gene pathways that are equivalently (or inversely) changed across two experimental conditions.

Results

We developed Equivalent Change Enrichment Analysis (ECEA). This is a new type of gene enrichment analysis based on a statistic that we call the equivalent change index (ECI). An ECI of 1 represents a gene that was over or under-expressed (compared to control) to the same degree across two experiments. Using this statistic, we present an approach to identifying pathways that are changed in similar or opposing ways across experiments. We compare our approach to current methods on simulated data and show that ECEA is able to recover pathways exhibiting such changes even when they exhibit complex patterns of regulation, which other approaches are unable to do. On biological data, our approach recovered pathways that appear directly connected to the condition being studied.

Conclusions

ECEA provides a new way to perform gene enrichment analysis that allows researchers to compare their data to existing datasets and determine if a treatment will cause similar or opposing genomic perturbations.

Evaluation of the Severity of Major Depression Using a Voice Index for Emotional Arousal

Recently, the relationship between emotional arousal and depression has been studied. Focusing on this relationship, we first developed an arousal level voice index (ALVI) to measure arousal levels using the Interactive Emotional Dyadic Motion Capture database. Then, we calculated ALVI from the voices of depressed patients from two hospitals (Ginza Taimei Clinic (H1) and National Defense Medical College hospital (H2)) and compared them with the severity of depression as measured by the Hamilton Rating Scale for Depression (HAM-D). Depending on the HAM-D score, the datasets were classified into a no depression (HAM-D < 8) and a depression group (HAM-D ≥ 8) for each hospital. A comparison of the mean ALVI between the groups was performed using the Wilcoxon rank-sum test and a significant difference at the level of 10% (p = 0.094) at H1 and 1% (p = 0.0038) at H2 was determined. The area under the curve (AUC) of the receiver operating characteristic was 0.66 when categorizing between the two groups for H1, and the AUC for H2 was 0.70. The relationship between arousal level and depression severity was indirectly suggested via the ALVI.

Strain Differences in Responsiveness to Repeated Restraint Stress Affect Remote Contextual Fear Memory and Blood Transcriptomics

The role of stress in altering fear memory is not well understood. Since individual variations in stress reactivity exist, and stress alters fear memory, exposing individuals with differing stress-reactivity to repeated stress would affect their fear memory to various degrees. We explored this question using the average stress-reactive Fisher 344 (F344) rat strain and the Wistar-Kyoto (WKY) strain with its heightened stress-reactivity. Male F344 and WKY rats were exposed to the contextual fear conditioning (CFC) paradigm and then chronic restraint stress (CRS) or no stress (NS) was administered for two weeks before a second CFC. Both recent and reinstated fear memory were greater in F344s than WKYs, regardless of the stress status. In contrast, remote memory was attenuated only in F344s after CRS. In determining whether this strain-specific response to CRS was mirrored by transcriptomic changes in the blood, RNA sequencing was carried out. Overlapping differentially expressed genes (DEGs) between NS and CRS in the blood of F344 and WKY suggest a convergence of stress-related molecular mechanisms, independent of stress-reactivity. In contrast, DEGs unique to the F344 and the WKY stress responses are divergent in their functionality and networks, beyond that of strain differences in their non-stressed state. These results suggest that in some individuals chronic or repeated stress, different from the original fear memory-provoking stress, can attenuate prior fear memory. Furthermore, the novel blood DEGs can report on the general state of stress of the individual, or can be associated with individual variation in stress-responsiveness.

iTRAQ-Based Protein Profiling in CUMS Rats Provides Insights into Hippocampal Ribosome Lesion and Ras Protein Changes Underlying Synaptic Plasticity in Depression

Hippocampal atrophy is one of the key changes in the brain implicated in the biology of depression. However, the precise molecular mechanism remains poorly understood due to a lack of biomarkers. In this research, we used behavioral experiments to evaluate anxiety and anhedonia levels in depressed rats using chronic unpredictable mild stress (CUMS) modeling. We also used isobaric tag for relative and absolute quantitation (iTRAQ) to identify the differentially expressed hippocampal proteins between depressed and normal rats. Bioinformatics analyses were also performed for a better understanding. The results showed that CUMS rats had higher anxiety and anhedonia levels than control rats, along with hippocampal lesions. Through iTRAQ and bioinformatics analyses, we found that ribosome proteins were significantly downregulated and Ras proteins exhibited a mixed change in the hippocampus of depressed rats. These findings suggest that the expression of hippocampal ribosome lesions and Ras proteins is significantly different in depressed rats than in control rats, providing new insights into the neurobiology of depression.