Does decreased autophagy and dysregulation of LC3A in astrocytes play a role in major depressive disorder?

Astrocytic dysfunction contributes to the molecular pathogenesis of major depressive disorder (MDD). However, the astrocytic subtype that mainly contributes to MDD etiology and whether dysregulated autophagy in astrocytes is associated with MDD remain unknown. Using a single-nucleus RNA sequencing (snRNA-seq) atlas, three astrocyte subtypes were identified in MDD, while C2 State-1Q astrocytes showed aberrant changes in both cell proportion and most differentially expressed genes compared with other subtypes. Moreover, autophagy pathways were commonly inhibited in astrocytes in the prefrontal cortices (PFCs) of patients with MDD, especially in C2 State-1Q astrocytes. Furthermore, by integrating snRNA-seq and bulk transcriptomic data, we found significant reductions in LC3A expression levels in the PFC region of CUMS-induced depressed mice, as well as in postmortem PFC tissues and peripheral blood samples from patients with MDD. These results were further validated by qPCR using whole-blood samples from patients with MDD and healthy controls. Finally, LC3A expression in the whole blood of patients with MDD was negatively associated with the severity of depressive symptoms. Overall, our results underscore autophagy inhibition in PFC astrocytes as a common molecular characteristic in MDD and might reveal a novel potential diagnostic marker LC3A.

Plasma biomarker panel for major depressive disorder by quantitative proteomics using ensemble learning algorithm: A preliminary study.

Major depressive disorder (MDD) is a major international public health issue; thus, investigating its underlying mechanisms and identifying suitable biomarkers to enable its early detection are imperative. Using data-independent acquisition-mass spectrometry-based proteomics, the plasma of 44 patients with MDD and 25 healthy controls was studied to detect differentially expressed proteins. Bioinformatics analyses, such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, Protein-Protein Interaction network, and weighted gene co-expression network analysis were employed. Moreover, an ensemble learning technique was used to build a prediction model. A panel of two biomarkers, L-selectin and an isoform of the Ras oncogene family was identified. With an area under the receiver operating characteristic curve of 0.925 and 0.901 for the training and test sets, respectively, the panel was able to distinguish MDD from the controls. Our investigation revealed numerous potential biomarkers and a diagnostic panel based on several algorithms, which may contribute to the future development of a plasma-based diagnostic approach and better understanding of the molecular mechanisms of MDD.

miR-124 Exacerbates depressive-like behavior by targeting Ezh2 to induce autophagy.

On the basis of our previous research, miR-124 and autophagy have been shown to be associated with depression and antidepressant treatment, respectively. However, whether miR-124 is involved in depressive-like behavior and antidepressant efficacy through regulating autophagy remains poorly understood. The chronic unpredictable mild stress (CUMS) depression model in mice was established, and then intraperitoneal fluoxetine injections (10 mg/kg) were administered for a duration of 4 weeks. The behavioral changes induced by CUMS were evaluated by the tail suspension test, open field test, sucrose preference test, and elevated plus maze test. Quantitative real-time PCR was used to detect expression levels of miR-124 and its three precursor genes in hippocampus of mice. Western blotting was used to detect the expressions of Ezh2 and autophagy proteins (P62, Atg3, Atg7, LC3-I, and LC3- II) in hippocampus of mice. Depression-like behaviors were successfully induced in CUMS models and reversed by SSRI treatments. The expression levels of miR-124 and its precursor gene ( miR-124-3 ) were significantly increased in the hippocampus of CUMS mice, while the expression levels were significantly decreased after 4 weeks of fluoxetine treatment. The mRNA and protein expressions of Ezh2, a validated target of miR-124, were decreased in the hippocampus of CUMS mice, and the fluoxetine treatment could reverse the expressions. A correlation analysis suggested that miR-124 had a significant negative correlation with Ezh2 mRNA expression. The protein levels of LC3-II/I, P62, and Atg7, which were found to be regulated by Ezh2, were increased in the hippocampus of CUMS mice and decreased after fluoxetine treatment. We speculated that autophagy was enhanced in the CUMS model of depression and might be mediated by miR-124 targeting Ezh2.

The influence of TNIK gene polymorphisms on risperidone response in a Chinese Han population.

Aim: To investigate whether the TNIK gene affects risperidone treatment outcomes in the Chinese population. Methods: A total of 148 unrelated inpatients who received risperidone for six weeks were enrolled. The selected single nucleotide polymorphisms (SNPs; rs2088885, rs7627954 and rs13065441) were genotyped using the MassARRAY® SNP IPLEX platform. Results: The analysis showed that one novel SNP of TNIK, rs7627954, had a significant association with the response to risperidone (χ2 = 4.472; p = 0.034). This work also identified rs2088885 as significantly associated with risperidone response (χ2 = 5.257; p = 0.022). The result revealed that the rs2088885-rs7627954 C-T haplotype was more prevalent in good responders than in poor responders (p = 0.0278). Conclusion: This study revealed that the rs2088885 and rs7627954 SNPs of TNIK are associated with risperidone treatment response.

Sex differences between serum total bilirubin levels and cognition in patients with schizophrenia.

BACKGROUND: Cognitive deficits are common in patients with schizophrenia (SCZ). Abnormal serum total bilirubin (TBIL) levels have been involved in cognitive deficits associated with neuropsychiatric diseases such as mild cognitive impairment and subcortical ischemic vascular disease. However, this relationship has not yet been fully investigated in patients with SCZ. Therefore, the aim of this study was to investigate the association between the serum TBIL concentration and cognitive deficits in SCZ patients and to determine whether a sex difference exists in the association. METHODS: A total of 455 participants were eligible and included in this cross-sectional study. Cognition was evaluated using the Montreal Cognitive Assessment. Serum TBIL concentration was measured with an automatic biochemistry analyzer according to the routine protocol in the hospital medical laboratory. RESULTS: Serum TBIL levels were lower in the cognition impairment group than in the cognition normal group in male patients. In contrast, serum TBIL levels tended to be increased in the cognition impairment group in female patients, although the difference was not significant. Further stepwise multiple regression analysis stratified by sex showed that serum TBIL was independently and positively associated with cognitive function in male patients but not in female patients. Moreover, the association between serum TBIL level and cognitive function was also identified by the propensity score matching (PSM) method in male patients, but not in female patients. CONCLUSION: These findings suggest that lower serum TBIL levels may be associated with cognitive impairment in male SCZ patients.

Signatures of 4 autophagy-related genes as diagnostic markers of MDD and their correlation with immune infiltration.

BACKGROUND: Major depressive disorder (MDD) is a debilitating mental illness and one of the primary causes of suicide. This study attempted to develop and validate a multigene joint signature for diagnosing MDD based on autophagy-related genes (ARGs) and to explore their biological role in MDD. METHODS: We downloaded data from the Gene Expression Omnibus (GEO) database and retrieved ARGs from the Human Autophagy Database. The limma package in R software was used to identify differentially expressed genes (DEGs). We used CIBERSORT to analyze differences in the immune microenvironment between MDD patients and controls. Finally, we examined the correlation between diagnostic markers and infiltrating immune cells to better understand the molecular immune mechanism. RESULTS: In this study, we identified 20 differentially expressed ARGs in MDD compared to controls. A signature of 4 autophagy-related genes (GPR18, PDK4, NRG1 and EPHB2) was obtained. ROC analysis showed that our model has good diagnostic performance (AUC=0.779, 95% CI=0.709-0.848). Bioinformatics analysis validated that GPR18 may represent a new candidate gene for MDD. Correlation analysis revealed that GPR18 was positively correlated with regulatory T cells (Treg), CD8+ T cells, naive B cells, and memory B cells and negatively correlated with M0 macrophages and neutrophils in MDD. LIMITATIONS: This was a second mining of previously published data sets. Independent studies are warranted to validate and improve the clinical utility of the identified signature. CONCLUSIONS: We identified a novel four-ARG gene signature that has good diagnostic performance and identified an association between ARG genes and the immune microenvironment in MDD.

Promoter Hypomethylation of miR-124 Gene Is Associated With Major Depressive Disorder.

Based on our previous studies and other evidence, miR-124 is an important biomarker and therapeutic target for major depressive disorder (MDD). The aim of this study was to clarify the role of miR-124 methylation in MDD and antidepressant effects from the perspective of epigenetics. MethylTarget™ was used to detect methylation levels of the three miR-124 precursor genes (MIR124-1, MIR124-2, and MIR124-3) in 33 pre- and post-treatment MDD patients and 33 healthy controls. A total of 11 cytosine-phosphate-guanine (CpG) islands in the three miR-124 precursor genes, including 222 CpG sites, were detected. All CpG islands were hypomethylated in MDD patients when compared to healthy controls and seven CpG regions were still identified with a statistically significant difference after Bonferroni correction. In addition, 137 of 222 CpG sites were found a statistical difference between MDD patients and controls, and 40 CpG sites were still statistically significant after Bonferroni correction. After performing the LASSO regression model, seven biomarkers with differential methylation among 40 CpG sites were identified. Mean methylation score was lower in MDD patients (z = -5.84, p = 5.16E-9). The AUC value reached 0.917 (95% CI: 0.854-0.981) to discriminate MDD and controls. No changes in methylation of the three miR-124 precursor genes were found in MDD patients following antidepressant treatment. The methylation of miR-124 could be a promising diagnostic biomarker for MDD.

Network-based approach to identify molecular signatures in the brains of depressed suicides.

BACKGROUND: Suicide is a serious and global health problem that has a strong association with major depressive disorder (MDD). Weighted gene co-expression network analysis (WGCNA) was performed for the construction of a co-expression network to get important gene modules associated with depressed suicide. METHODS: Transcriptome sequencing data from dorsolateral prefrontal cortex was used, which included 29 non-psychiatric controls (CON), 21 MDD suicides (MDD-S) and 9 MDD non-suicides (MDD-NS) of medication-free sudden death individuals. RESULTS: The highest correlation in the module-traits relationship was discovered between the black module and suicide (r = -0.30, p = 0.024) as well as MDD (r = -0.34, p = 0.010).Furthermore, the expression levels of genes decreased progressively across the three groups (CON>MDD-NS>MDD-S). Therefore, the genes in the black module was selected for subsequent analyses. Protein-Protein Interaction Network found that the top 10 hub genes were somehow involved in depressed suicide including JUN, FOS, ATF3, MYC, EGR1, FOSB, DUSP1, NFKBIA, TLR2, NR4A1. Most of the GO terms were enriched in cell death and apoptosis and KEGG was mainly enriched in MAPK pathway. Cell Type-Specific Analysis found these genes were significantly enriched in endothelial and microglia (p<0.000) cell types. In addition, 92 genes in this module had at least one highly significant differentially methylated positions between MDD-S and controls. CONCLUSION: Cell death and apoptosis may participate in the interplay between depressed suicide and neuro-inflammation system.

Two Novel Loci of RELN Associated With Antipsychotics Response in Chinese Han Population.

BACKGROUND: There are great individual differences in the drug responses; however, there are few prognostic drug response biomarkers available. RELN is one of the more extensively examined schizophrenia candidate genes. The purpose of this study was to determine whether RELN can affect antipsychotics response in the Chinese population. This may lead to the discovery of relevant novel drug response markers. METHODS: The unrelated 260 Chinese Han inpatients with schizophrenia were enrolled in the present study. The enrolled subjects have been prescribed antipsychotic medication during the study. A total of 15 SNPs of RELN were genotyped by MassARRAY® platform. The association of the RELN gene with therapeutic response to antipsychotics was analyzed based on sex and age at onset. RESULTS: Two novel SNPs of RELN were found to be associated with antipsychotic treatment response (rs155333, p = 0.010 and rs6465938, p = 0.049) at nominal significance threshold, but not after multiple correction. Our study also revealed highly significant association of a haplotype consisting of three SNPs (rs362814-rs362626-rs2237628) with antipsychotic treatment response. Even after permutation, the p-value indicated significant association (rs362814-rs362626-rs2237628: ACT, χ2 = 6.353, p = 0.0117, permuted p = 0.04). Furthermore, a novel SNP, rs2535764, was found to be associated with antipsychotic response under overdominant genetic model at a marginal significant level of 0.046 (C/T vs. C/C + T/T: p = 0.046, AIC = 314.7, BIC = 321.6). CONCLUSION: Our data indicated that RELN can affect antipsychotic treatment outcomes in the Chinese population. SNPs of RELN could be used as predictive biomarkers for future personalized medicine of antipsychotic drug treatment. However, none of the three novel SNPs (rs155333, rs6465938, and rs2535764) remained significant after Bonferroni correction. Therefore, validation is needed in larger pharmacogenetic studies.

Co-Expression Network Analysis Revealed That the ATP5G1 Gene Is Associated With Major Depressive Disorder.

Major depressive disorder (MDD) is a leading cause of disability worldwide, although its etiology and mechanism remain unknown. The aim of our study was to identify hub genes associated with MDD and to illustrate the underlying mechanisms. A weighted gene co-expression network analysis (WGCNA) was performed to identify significant gene modules and hub genes associated with MDD in peripheral blood mononuclear cells (PBMCs) (n = 45). In the blue module (R 2 = 0.95), five common hub genes in both co-expression network and protein-protein interaction (PPI) network were regarded as "real" hub genes. In another independent dataset, GSE52790, four genes were still significantly down-regulated in PBMCs from MDD patients compared with the controls. Furthermore, these four genes were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in PBMCs from 33 MDD patients and 41 healthy controls. The qRT-PCR analysis showed that ATP synthase membrane subunit c locus 1 (ATP5G1) was significantly down-regulated in samples from MDD patients than in control samples (t = -2.89, p-value = 0.005). Moreover, this gene was significantly differentially expressed between patients and controls in the prefrontal cortex (z = -2.83, p-value = 0.005). Highly significant differentially methylated positions were identified in the Brodmann area 25 (BA25), with probes in the ATP5G1 gene being significantly associated with MDD: cg25495775 (t = 2.82, p-value = 0.008), cg25856120 (t = -2.23, p-value = 0.033), and cg23708347 (t = -2.24, p-value = 0.032). These findings indicate that the ATP5G1 gene is associated with the pathogenesis of MDD and that it could serve as a peripheral biomarker for MDD.

Baseline Serum Levels of Beclin-1, but Not Inflammatory Factors, May Predict Antidepressant Treatment Response in Chinese Han Patients With MDD: A Preliminary Study.

Currently, the choice of medical treatment for major depressive disorder (MDD) is primarily based on a trial-and-error process. Thus, identification of individual factors capable of predicting treatment response is of great clinical relevance. Recent work points towards beclin-1 and inflammatory factors as potential biomarkers of antidepressant treatment response. The primary aim of the study was to investigate whether pre-treatment serum levels of beclin-1 and inflammatory factors could predict antidepressant treatment response in Chinese Han patients with MDD. Forty patients with MDD were treated with either a selective serotonin reuptake inhibitor (SSRI) (paroxetine in 20 cases) or a serotonin-norepinephrine reuptake inhibitor (SNRI) (duloxetine in 13 cases and venlafaxine in 7 cases). Depression scores and serum levels of beclin-1 were measured at the baseline and after 8 weeks of antidepressant treatment. Serum C-reactive protein (CRP), interleukin (IL)-1B, and IL-6 levels were determined using enzyme-linked immunosorbent assay kits at the baseline. Twenty-seven patients were identified as treatment responders, whereas 13 were identified as non-responders after 8 weeks of antidepressant treatment. Baseline serum beclin-1 levels were significantly higher in non-responders than in responders (p = 0.001), whereas no differences were found in baseline serum CRP, IL-1B, or IL-6 levels between responders and non-responders. There were no significant correlations between baseline levels of beclin-1 and baseline IL-1ß, IL-6, and CRP levels-neither in the total sample nor in responder and non-responder groups. Moreover, logistic regression models and a random forest model showed that baseline serum beclin-1, but not inflammatory factors, was an independent and the most important predictor for antidepressant treatment response. Furthermore, serum beclin-1 levels were significantly increased in responders (p = 0.027) but not in non-responders after 8 weeks of treatment (p = 0.221). Baseline serum beclin-1 levels may be a predictive biomarker of antidepressant response in patients with MDD. Moreover, beclin-1 may be involved in the therapeutic effect of antidepressant drugs.

Analysis of the association of MIR124-1 and its target gene RGS4 polymorphisms with major depressive disorder and antidepressant response.

BACKGROUND: Increasing evidence has indicated that dysfunction of miR-124 and target gene regulator of G protein signaling 4 (RGS4) may be involved in the etiology and treatment of major depressive disorder (MDD). However, the molecular mechanisms are not fully understood. This study aimed to investigate whether common genetic variations in these two genes are associated with MDD and therapeutic response to antidepressants in the Chinese population. METHODS: Three polymorphisms including rs531564 (a functional single-nucleotide polymorphism [SNP] in MIR124-1), rs10759 (a microRNA-binding site SNP in RGS4), and rs951436 (a promoter SNP in RGS4) were genotyped in 225 Chinese MDD patients and 436 controls. Among the MDD patients, 147 accepted antidepressant treatment for 8 weeks with therapeutic evaluation at baseline, week 2, week 4, week 6, and week 8 using the 17-item Hamilton Rating Scale for Depression. Multifactor dimensionality reduction (MDR) was used to identify gene-gene interactions. RESULTS: No significant association with MDD was discovered in single-SNP analyses. However, by MDR analysis, the three-locus model of gene-gene interaction was the best for predicting MDD risk. In pharmacogenetic study, a significant association was found in genotypic frequencies of rs951436 between the remitter and non-remitter groups (p=0.026, correction p=0.078). For further analysis, the rs951436 heterozygote carriers had threefold probabilities of achieving clinical complete remission (odds ratio =3.00, 95% confidence interval =1.33-6.76, p=0.007, correction p=0.021) as compared with rs951436 homozygotes (AA+CC) after 8 weeks of treatment. CONCLUSION: An interaction effect of MIR124-1 and RGS4 polymorphisms may play a more important role than individual factors for MDD development. Moreover, RGS4 gene polymorphisms may be associated with antidepressant response among the Han population.

Aberrant expression of SIRT3 is conversely correlated with the progression and prognosis of human gastric cancer.

SIRT3 is a NAD(+)-dependent histone deacetylaseand and plays a critical role in various human carcinomas. However, its precise role in the pathogenesis of gastric cancer (GC) is still unclear. Western blot and Real-Time PCR were used to detect the protein and mRNA level of SIRT3 in freshly collected samples from GC patients. Immunohistochemistry staining was adopted to determine the expression of SIRT3 in 65 formalin-fixed, paraffin-embedded samples from GC patients. In addition, western blot was used to detect the protein levels of SIRT3 and HIF-1α in gastric cancer cells MGC-803 transfected with SIRT3 or control siRNA. Western blot analysis of 25 samples from GC patients showed that 64% (16/25) of patients exhibited decreased expression of SIRT3, whereas 4.0% (1/25) of patients displayed complete loss. In addition, Real-Time PCR analysis showed that GC patients had decreased expression of SIRT3 mRNA. Furthermore, immunohistochemistry analysis of 65 formalin-fixed, paraffin-embedded samples from GC patients showed that 67.7% (44/65) had decreased SIRT3 staining in the cancer tissues. Notably, the expression level of SIRT3 was inversely correlated with clinicopathological variable, including tumor infiltration, tumor differentiation and tumor stage and 5-year survival of these patients. In vitro experiment showed that knockdown of SIRT3 in MGC-803 gastric cancer cells significantly increased the expression of HIF-1α. Our results provide the first evidence showing that an aberrantly decreased expression of SIRT3 occurred in GC patients, suggesting that SIRT3 might function as a mitochondrial tumor suppressor in GC. Furthermore, the possible mechanism by which SIRT3 affect the progress of GC is its direct control of HIF-1α.

PAK4 confers cisplatin resistance in gastric cancer cells via PI3K/Akt- and MEK/ERK-dependent pathways.

CDDP [cisplatin or cis-diamminedichloroplatinum(II)] and CDDP-based combination chemotherapy have been confirmed effective against gastric cancer. However, CDDP efficiency is limited because of development of drug resistance. In this study, we found that PAK4 (p21-activated kinase 4) expression and activity were elevated in gastric cancer cells with acquired CDDP resistance (AGS/CDDP and MKN-45/CDDP) compared with their parental cells. Inhibition of PAK4 or knockdown of PAK4 expression by specific siRNA (small interfering RNA)-sensitized CDDP-resistant cells to CDDP and overcome CDDP resistance. Combination treatment of LY294002 [the inhibitor of PI3K (phosphoinositide 3-kinase)/Akt (protein kinase B or PKB) pathway] or PD98509 {the inhibitor of MEK [MAPK (mitogen-activated protein kinase)/ERK (extracellular-signal-regulated kinase) kinase] pathway} with PF-3758309 (the PAK4 inhibitor) resulted in increased CDDP efficacy compared with LY294002 or PD98509 alone. However, after the concomitant treatment of LY294002 and PD98509, PF-3758309 administration exerted no additional enhancement of CDDP cytotoxicity in CDDP-resistant cells. Inhibition of PAK4 by PF-3758309 could significantly suppress MEK/ERK and PI3K/Akt signalling in CDDP-resistant cells. Furthermore, inhibition of PI3K/Akt pathway while not MEK/ERK pathway could inhibit PAK4 activity in these cells. The in vivo results were similar with those of in vitro In conclusion, these results indicate that PAK4 confers CDDP resistance via the activation of MEK/ERK and PI3K/Akt pathways. PAK4 and PI3K/Akt pathways can reciprocally activate each other. Therefore, PAK4 may be a potential target for overcoming CDDP resistance in gastric cancer.