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CMS group displayed depressive symptom patterns in the behavioral tests. (A) Open space swimming test (OST). Mice performed the OST following exposure to CMS. The swimming distance was measured by recording movement with a digital video camera and analyzed using a computerized video-based tracking system. The results are expressed as the average values obtained from the CMS and C groups, and were analyzed by Student’s t-test (n = 9 for each group; *: p<0.001). (B) Tail suspension test (TST). The activity counts of the CMS group were measured using the Be-sensor system, which analyzed radiated heat energy. The mean values in CMS and C groups are presented. The activity counts of the CMS group were significantly lower than those of the controls in the first 3 minutes and the last minute of the test. The data were analyzed by Student’s t-test and a p value less than 0.05 was considered significant (n = 9 per each group; **: p<0.05).
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Major depressive disorder (MDD) is a common psychiatric disorder that involves marked disabilities in global functioning, anorexia, and severe medical comorbidities. MDD is associated with not only psychological and sociocultural problems, but also pervasive physical dysfunctions such as metabolic, neurobiological and immunological abnormalities. N...
Citations
... IPA was applied to analyze the functions of the DEGs, as previously described [18,19]. Of the tissue-specific DEGs, those associated with cancer, energy metabolism, and psychiatric and brain disorders (depression, dementia, Alzheimer's disease [AD], and cognitive impairment) were selected on the basis of behaviors observed in Il18 −/− mice [10]. ...
... These results suggest the possibility that IL18 may be an important cytokine in cancer treatment. 18, its receptor (Il18r), and other differentially expressed genes common to liver, brown adipose tissue, and brain in Il18 −/− mice. Only Casp4 was predicted to have a direct interaction with IL18. ...
Interleukin 18 (IL18) was originally identified as an inflammation-induced cytokine that is secreted by immune cells. An increasing number of studies have focused on its non-immunological functions, with demonstrated functions for IL18 in energy homeostasis and neural stability. IL18 is reportedly required for lipid metabolism in the liver and brown adipose tissue. Furthermore, IL18 (Il18) deficiency in mice leads to mitochondrial dysfunction in hippocampal cells, resulting in depressive-like symptoms and cognitive impairment. Microarray analyses of Il18−/− mice have revealed a set of genes with differential expression in liver, brown adipose tissue, and brain; however, the impact of IL18 deficiency in these tissues remains uncertain. In this review article, we discuss these genes, with a focus on their relationships with the phenotypic disease traits of Il18−/− mice.
... 68 Genomic studies proposed that HNF4α anti-depressive effects are linked to the regulation of gluconeogenesis, lipid homeostasis, and serotonin metabolism. 69,70 Moreover, it has been shown that binding of drugs to this transcription factors can impact its activity and consequently modulate cell functions. 71 Similarly, several studies also identified several molecules presenting high affinity for HNF4α affecting its activity. ...
Obesity is associated with increased occurrence of cognitive and mood disorders. While consumption of high-fat diets (HFD) and associated obesity could have a detrimental impact on the brain, dietary bioactives may mitigate these harmful effects. We previously observed that (-)-epicatechin (EC) can mitigate HFD-induced anxiety-associated behaviors in mice. The aim of our study is to investigate the molecular mechanisms of EC actions in the hippocampus which underlies its anti-anxiety effects in HFD-fed mice using a multi-genomic approach. Healthy eight-week old male C57BL/6J mice were fed for 24 weeks either: (A) a control diet containing 10% total calories from fat; (B) a HFD containing 45% total calories from fat; or (C) the HFD supplemented with 20 mg EC per kg body weight. Hippocampi were isolated for genomic analysis using Affymetrix arrays, followed by in-depth bioinformatic analyses. Genomic analysis demonstrated that EC induced significant changes in mouse hippocampal global gene expression. We observed changes in the expression of 1001 protein-coding genes, 241 miRNAs, and 167 long non-coding RNAs. Opposite gene expression profiles were observed when the gene expression profile obtained upon EC supplementation was compared to the profile obtained after consumption of the HFD. Functionality analysis revealed that the differentially expressed genes regulate processes involved in neurofunction, inflammation, endothelial function, cell-cell adhesion, and cell signaling. In summary, the capacity of EC to mitigate anxiety-related behaviors in HFD-induced obese mice can be in part explained by its capacity to exert complex genomic modifications in the hippocampus, counteracting changes driven by consumption of the HFD and/or associated obesity.
... Protein extraction from the mouse hippocampus and western blotting were performed as previously described [17,25]. Briefly, samples were K. Yamanishi et al. incubated in Laemmli sample buffer for 5 min at 95°C, electrophoresed on a 10-20% sodium dodecyl sulfate polyacrylamide gel, and transferred onto polyvinylidene difluoride membranes (Hybond-P, Amersham Bioscience, Little Chalfont, UK). ...
Interleukin-18 (IL18) is an inflammatory cytokine that is related to psychiatric disorders such as depression and cognitive impairment. We previously found that IL18 deficiency may cause hippocampal impairment, resulting in depression-like behavioral changes. However, the potential role of IL18 in stressful conditions remains uncertain. In the present study, we examined the effect of IL18 on neural inflammation and stress tolerance during acute stress. Littermate Il18+/+ and Il18−/− mice were exposed to a single restraint stress for 6 h, and all assessments were performed 18 h after the mice were released from the restraint. In Il18−/− mice exposed to acute stress, the immobility times in both the forced swim test and tail suspension test were decreased, although no difference was observed in Il18+/+ mice. Il1β, Il6, and Tnfα expression levels in the hippocampus of stressed Il18−/− mice were significantly higher than those in the other groups. Moreover, the numbers of astrocytes and microglia, including those in the active form, were also increased compared with those in other groups. Regarding the molecular mechanism, the HSF5 and TTR genes were specifically expressed in stressed Il18−/− mice. As a potential treatment, intracerebral administration of IL18 to Il18−/− mice resulted in partial recovery of changes in behavioral assessments. Our results revealed that IL18-deficient mice were more sensitive and had a longer response to acute stress than that in normal mice. In addition, neural inflammation and augmentation of glucocorticoid signals caused by stress were more intense and remained longer in Il18−/− mice, resulting in behavioral changes. In conclusion, IL18 might be an indispensable factor that modulates the stress response and maintains balance between neural inflammation and glucocorticoid signaling.
... Additional studies referring to the same dataset deposited in GEO are provided in Supplementary Table 1. The search of literature together with inclusion criteria resulted in 79 studies performed in laboratory animals (Stankiewicz et al., 2015;Stankiewicz et al., 2014;Zhang et al., 2015;Jeong et al., 2013;Lisowski et al., 2011;Hoban et al., 2018;Datson et al., 2012;Wang et al., 2017;Cathomas et al., 2019;Liu et al., 2010a;Tsolakidou et al., 2010;Lee et al., 2005;Lisowski et al., 2013;Skrzypiec et al., 2013;Li et al., 2014;Kim and Han, 2006;Yamanishi et al., 2015;Babenko et al., 2012;Wang et al., 2010;Laine et al., 2018;Jungke et al., 2011;Barreto et al., 2012;Orsetti et al., 2008;Wingo et al., 2018;Crews et al., 2012;Herve et al., 2017;Lehmann et al., 2018;Miyata et al., 2016;Yoshida et al., 2017;Muhie et al., 2015;Muhie et al., 2017;Nie et al., 2018;Hohoff et al., 2013;Keeley et al., 2006;Krishnan et al., 2007;Lehmann et al., 2017;Roszkowski et al., 2016;Bagot et al., 2016;Rimmerman et al., 2017;Bondar et al., 2018;Ejchel-Cohen et al., 2006;Wang et al., 2019;Pfau et al., 2016;Feldker et al., 2006;Karisetty et al., 2017;Gray et al., 2014;Shen et al., 2019;Joo et al., 2009;Stefanelli et al., 2018;Sun et al., 2018;Irwin, 2001;Ma et al., 2016;Jung et al., 2012;Peixoto et al., 2015;Kim et al., 2016;Datson et al., 2013;LaPlant et al., 2009;Spadaro et al., 2015;Karssen et al., 2007;Malki et al., 2014;Benatti et al., 2012;Cho et al., 2015;Kanarik et al., 2011;Brzozka et al., 2016;Mychasiuk et al., 2016;Floriou-Servou et al., 2018;Hlavacova et al., 2012;Aso et al., 2011;Nollet et al., 2019;Kohen et al., 2005;Burgdorf et al., 2015;Warren et al., 2013;Tomas-Roig et al., 2016;Engel et al., 2018;Labonte et al., 2017;Kwon et al., 2019;Hodes et al., 2015;Andrus et al., 2012;Poplawski et al., 2016) and three human studies (Girgenti et al., 2021;Licznerski et al., 2015;Su et al., 2008) presenting unique transcriptomic datasets that were used for retrieval of data for further analysis. The priority was given to transcriptomic data available in GEO repository provided that the study listed relevant accession numbers and the data could be retrieved with GEO2R tool. ...
... To confirm proper calculation of the ratio (stress/ control) we compared the transcriptomic data (ratio or log fold change) with an expression level in individual groups using data available in tables, figures or visualization of expression of individual genes retrieved from GEO repository with the GEO2R tool. Such data showing expression in individual groups used for transcriptomic analyses were available in 56 studies (Stankiewicz et al., 2015;Stankiewicz et al., 2014;Zhang et al., 2015;Jeong et al., 2013;Lisowski et al., 2011;Hoban et al., 2018;Datson et al., 2012;Wang et al., 2017;Cathomas et al., 2019;Liu et al., 2010a;Tsolakidou et al., 2010;Lee et al., 2005;Lisowski et al., 2013;Skrzypiec et al., 2013;Li et al., 2014;Kim and Han, 2006;Yamanishi et al., 2015;Babenko et al., 2012;Wang et al., 2010;Laine et al., 2018;Barreto et al., 2012;Orsetti et al., 2008;Wingo et al., 2018;Crews et al., 2012;Herve et al., 2017;Lehmann et al., 2018;Miyata et al., 2016;Yoshida et al., 2017;Muhie et al., 2015;Muhie et al., 2017;Nie et al., 2018;Hohoff et al., 2013;Keeley et al., 2006;Krishnan et al., 2007;Lehmann et al., 2017;Roszkowski et al., 2016;Bagot et al., 2016;Rimmerman et al., 2017;Bondar et al., 2018;Ejchel-Cohen et al., 2006;Wang et al., 2019;Pfau et al., 2016;Feldker et al., 2006;Karisetty et al., 2017;Gray et al., 2014;Shen et al., 2019;Joo et al., 2009;Stefanelli et al., 2018;Sun et al., 2018;Irwin, 2001;Ma et al., 2016;Jung et al., 2012;Peixoto et al., 2015;Kim et al., 2016;Spadaro et al., 2015;Su et al., 2008), and in 5 of them (Lisowski et al., 2011;Hoban et al., 2018;Datson et al., 2012;Wang et al., 2017;Cathomas et al., 2019) we found that the expression ratio in transcriptomic data was calculated in the reversed way (control/stress). Therefore, in these cases (Lisowski et al., 2011;Hoban et al., 2018;Datson et al., 2012;Wang et al., 2017;Cathomas et al., 2019) we reversed the signs of expression values. ...
Interpretation of transcriptomic experiments is hindered by many problems including false positives/negatives inherent to big-data methods and changes in gene nomenclature. To find the most consistent effect of stress on brain transcriptome, we retrieved data from 79 studies applying animal models and 3 human studies investigating post-traumatic stress disorder (PTSD). The analyzed data were obtained either with microarrays or RNA sequencing applied to samples collected from more than 1887 laboratory animals and from 121 human subjects.
Based on the initial database containing a quarter million differential expression effect sizes representing transcripts in three species, we identified the most frequently reported genes in 223 stress-control comparisons. Additionally, the analysis considers sex, individual vulnerability and contribution of glucocorticoids. We also found an overlap between gene expression in PTSD patients and animals which indicates relevance of laboratory models for human stress response. Our analysis points to genes that, as far as we know, were not specifically tested for their role in stress response (Pllp, Arrdc2, Midn, Mfsd2a, Ccn1, Htra1, Csrnp1, Tenm4, Tnfrsf25, Sema3b, Fmo2, Adamts4, Gjb1, Errfi1, Fgf18, Galnt6, Slc25a42, Ifi30, Slc4a1, Cemip, Klf10, Tom1, Dcdc2c, Fancd2, Luzp2, Trpm1, Abcc12, Osbpl1a, Ptp4a2). Provided transcriptomic resource will be useful for guiding the new research.
... After confirming shallow or absent breathing or a lack of response to pain stimulation, blood from their heart was collected immediately. The serum and brain regions (PFC, hypothalamus, and hippocampus) were removed as previously described, immediately placed in liquid nitrogen, and stored at −80°C until required [24,25] 2.4. Immunofluorescence Staining. ...
... Microarray data from the PFC of CMS model mice [28] and from the hippocampus of Il18 −/− mice were obtained in our previous studies [20,24]. ...
... and Il18 −/− Mice. We previously isolated a total of 494 and 294 genes whose expression was increased more than twofold or decreased by more than half from CMS and Il18 −/− mice, respectively [20,24]. To examine which genes were responsible for causing depression under IL-18-deficit conditions, we searched for molecules expressed in both CMS and Il18 −/− mice. ...
Interleukin-18 (IL-18) is an inflammatory cytokine that has been linked to energy homeostasis and psychiatric symptoms such as depression and cognitive impairment. We previously revealed that deficiency in IL-18 led to hippocampal abnormalities and resulted in depression-like symptoms. However, the impact of IL-18 deficiency on other brain regions remains to be clarified. In this study, we first sought to confirm that IL-18 expression in neural cells can be found in human brain tissue. Subsequently, we examined the expression of genes in the prefrontal cortex of Il18−/− mice and compared it with gene expression in mice subjected to a chronic mild stress model of depression. Extracted genes were further analyzed using Ingenuity® Pathway Analysis, in which 18 genes common to both the chronic mild stressed model and Il18−/− mice were identified. Of those, 16 were significantly differentially expressed between Il18+/+ and Il18−/− mice. We additionally measured protein expression of α-2-HS-glycoprotein (AHSG) and transthyretin (TTR) in serum and the brain. In the prefrontal cortex of Il18−/− mice, TTR but not AHSG was significantly decreased. Conversely, in the serum of Il18−/− mice, AHSG was significantly increased but not TTR. Therefore, our results suggest that in IL-18-deficit conditions, TTR in the brain is one of the mediators causally related to depression, and AHSG in peripheral organs is one of the regulators inducing energy imbalance. Moreover, this study suggests a possible “signpost” to clarify the molecular mechanisms commonly underlying the immune system, energy metabolism, neural function, and depressive disorders.
... Another study using microarray analysis showed that CMS affects several genes in the cerebral cortex and hippocampus, and that these genes are involved in multiple functions, such as the regulation of neurotransmitters and growth factors [14]. Further to this, using microarray analysis, Yamanishi et al. reported that Hnf4a directly affects various genes associated with several metabolic processes in the prefrontal cortex [15]. Therefore, a comprehensive, systemic, and comparative analysis of different brain areas involved in emotion and the stress response should be conducted. ...
Background:
Accumulations of stressful life events result in the onset of major depressive disorder (MDD). Comprehensive genomic analysis is required to elucidate pathophysiological changes and identify applicable biomarkers.
Methods:
Transcriptomic analysis was performed on different brain parts of a chronic mild stress (CMS)-induced MDD mouse model followed by systemic analysis. QPCR and ELISA were utilized for validation in mice and patients.
Results:
The highest numbers of genes with significant changes induced by CMS were 505 in the amygdala followed by 272 in the hippocampus (twofold changes; FDR, p < 0.05). Enrichment analysis indicated that the core-enriched genes in CMS-treated mice were positively enriched for IFN-γ response genes in the amygdala, and hedgehog signaling in the hippocampus. Transthyretin (TTR) was severely reduced in CMS-treated mice. In patients with diagnosed MDD, serum concentrations of TTR were reduced by 48.7% compared to controls (p = 0.0102). Paired samples from patients with MDD demonstrated a further 66.3% increase in TTR at remission compared to the acute phase (p = 0.0339).
Conclusions:
This study provides comprehensive information on molecular networks related to MDD as a basis for further investigation and identifies TTR for MDD monitoring and management. A clinical trial with bigger patient cohort should be conducted to validate this translational study.
... SP1 expression was also increased in cortex subjected to brain I/R insult and in primary neurons subjected to OGD/R treatment (Sun et al., 2015). Hnf4a is a TF belonging to the nuclear receptor superfamily and is expressed in the intestine, kidney, liver, and pancreas (including β-cells) (Yamanishi et al., 2015;Sato et al., 2017). It has been proved that Hnf4a was a key TF which showed specific binding at enhancer and super-enhancer sites during ischemic acute kidney injury (Wilflingseder et al., 2020). ...
Background
Spinal cord ischemia/reperfusion injury (SCII) is a catastrophic complication involved with cardiovascular, spine, and thoracic surgeries and can lead to paraplegia. Nevertheless, the molecular mechanism of SCII remain ill-defined.
Methods
Expression profiling (GSE138966) data were obtained from GEO database. Then, differentially expressed (DE) lncRNAs and DEmRNAs were screened out with p < 0.05, and | fold change| > 1.5. Aberrant miRNAs expression in SCII was obtained from PubMed. Functional enrichment analysis of overlapping DEmRNAs between predicted mRNAs in miRDB database and DEmRNAs obtained from GSE138966 was performed using cluster Profiler R package. The lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network was established in light of ceRNA theory. The key lncRNAs in the ceRNA network were identified by topological analysis. Subsequently, key lncRNAs related ceRNA-pathway network and transcription factors (TFs)-mRNAs network were constructed. Simultaneously, the expression levels of hub genes were measured via qRT-PCR.
Results
The results in this study indicated that 76 miRNAs, 1373 lncRNAs, and 4813 mRNAs were differentially expressed in SCII. A SCII-related ceRNA network was constructed with 154 ncRNAs, 139 mRNAs, and 51 miRNAs. According topological analysis, six lncRNAs (NONRATT019236.2, NONRATT009530.2, NONRATT026999.2, TCONS_00032391, NONRATT023112.2, and NONRATT021956.2) were selected to establish the ceRNA-pathway network, and then two candidate hub lncRNAs (NONRATT009530.2 and NONRATT026999.2) were identified. Subsequently, two lncRNA-miRNA-mRNA regulatory axes were identified. NONRATT026999.2 and NONRATT009530.2 might involve SCII via miR-20b-5p/Map3k8 axis based on the complex ceRNA network. SP1 and Hnf4a acting as important TFs might regulate Map3k8. Furthermore, qRT-PCR results showed that the NONRATT009530.2, NONRATT026999.2, Map3k8, Hfn4a, and SP1 were significantly upregulated in SCII of rats, while the miR-20b-5p was downregulated.
Conclusion
Our results offer a new insight to understand the ceRNA regulation mechanism in SCII and identify highlighted lncRNA-miRNA-mRNA axes and two key TFs as potential targets for prevention and treatment of SCII.
... Thirty minutes before the tail suspension tests, mice were intraperitoneally injected with saline or physostigmine (0.2 mg/kg; Tokyo Chemical Industry, Tokyo, Japan). Tail suspension test was performed using an infrared ray sensor system (Taiyo Electric Co. Ltd., Osaka, Japan), which showed activity counts but did not provide immobility time 18 . We performed TST with another system by analyzing images captured with CCD camera (O'Hara & Co., Tokyo, Japan), which provided immobility time as well as activity counts 19 . ...
Previously, we reported a family in which bipolar disorder (BD) co-segregates with a Mendelian kidney disorder linked to 1q22. The causative renal gene was later identified as MUC1. Genome-wide linkage analysis of BD in the family yielded a peak at 1q22 that encompassed the NTRK1 and MUC1 genes. NTRK1 codes for TrkA (Tropomyosin-related kinase A) which is essential for development of the cholinergic nervous system. Whole genome sequencing of the proband identified a damaging missense mutation, E492K, in NTRK1. Induced pluripotent stem cells were generated from family members, and then differentiated to neural stem cells (NSCs). E492K NSCs had reduced neurite outgrowth. A conditional knock-in mouse line, harboring the point mutation in the brain, showed depression-like behavior in the tail suspension test following challenge by physostigmine, a cholinesterase inhibitor. These results are consistent with the cholinergic hypothesis of depression. They imply that the NTRK1 E492K mutation, impairs cholinergic neurotransmission, and may convey susceptibility to bipolar disorder.
... Hepatocyte nuclear factor 4, HNF4A, is a transcription factor known to play a major role in liver and gastrointestinal diseases (46). While HNF4A has never before been associated specifically with ASD, it has been reported to be involved in Parkinson's disease (47) and major depressive disorder (48) as well as in regulation of circadian rhythm (49). Notably, circadian rhythm and sleep disorders have previously been associated with ASD by clinical, genetics, and transcriptomic analyses (7,26,(50)(51)(52). ...
Autism spectrum disorder (ASD) describes a collection of neurodevelopmental disorders characterized by core symptoms that include social communication deficits and repetitive, stereotyped behaviors often coupled with restricted interests. Primary challenges to understanding and treating ASD are the genetic and phenotypic heterogeneity of cases that complicates all omics analyses as well as a lack of information on relationships among genes, pathways, and autistic traits. In this study, we re-analyze existing transcriptomic data from simplex families by subtyping individuals with ASD according to multivariate cluster analyses of clinical ADI-R scores that encompass a broad range of behavioral symptoms. We also correlate multiple ASD traits, such as deficits in verbal and non-verbal communication, play and social skills, ritualistic behaviors, and savant skills, with expression profiles using Weighted Gene Correlation Network Analyses (WGCNA). Our results show that subtyping greatly enhances the ability to identify differentially expressed genes involved in specific canonical pathways and biological functions associated with ASD within each phenotypic subgroup. Moreover, using WGCNA, we identify gene modules that correlate significantly with specific ASD traits. Network prediction analyses of the genes in these modules reveal canonical pathways as well as neurological functions and disorders relevant to the pathobiology of ASD. Finally, we compare the WGCNA-derived data on autistic traits in simplex families with analogous data from multiplex families using transcriptomic data from our previous studies. The comparison reveals overlapping trait-associated pathways as well as upstream regulators of the module-associated genes that may serve as useful targets for a precision medicine approach to ASD.
... HNF4 , a gene associated with maturity-onset diabetes of the young (MODY, a form of non-insulin-dependent diabetes mellitus (32)), is primarily expressed in the liver (reviewed in (33)) and has been reported to play roles in gluconeogenesis (34) and cholesterol homeostasis (35). Yamanishi and colleagues (36) reported that HNF4 is also expressed in the brains of mice where it appears to drive transcriptomic changes when the mice are housed under stressful conditions. Expression of hnf4 itself in the brains of our zebrafish was very low so that its transcripts were excluded during the pre-processing preceding our differentially gene Enrichment testing of all the detectable genes in the RNA-seq experiment identified subtle changes to expression of genes involved in energy production and protein translation. ...
The early cellular stresses which eventually lead to Alzheimer’s disease (AD) remain poorly understood because we cannot access living, asymptomatic human AD brains for detailed molecular analyses. Sortilin-related receptor 1 ( SORL1 ) encodes a multi-domain receptor protein genetically associated with both rare, early-onset familial AD (EOfAD) and common, sporadic late-onset AD (LOAD). SORL1 has been shown to play a role in the trafficking of the amyloid β A4 precursor protein (APP) which is cleaved proteolytically to form one of the pathological hallmarks of AD, amyloid β (Aβ) peptide. However, the other functions of SORL1 are less well understood. Here, we employed a reverse genetics approach to characterise the effect of an EOfAD mutation in SORL1 using zebrafish as a model organism. We performed targeted mutagenesis to generate an EOfAD-like mutation in the zebrafish orthologue of SORL1 , and performed RNA-sequencing on mRNA isolated from a family of fish either heterozygous for the EOfAD-like mutation or their wild type siblings and identified subtle effects on the expression of genes which likely indicate changes in mitochondrial and ribosomal function. These changes appear to be independent of changes to expression of APP-related proteins in zebrafish, and mitochondrial content.
