Gene expression alterations in the medial prefrontal cortex and blood cells in a mouse model of depression during menopause

A Perspective on Evaluating Life Stage Differences in Drug Dosages for Drug Labeling and Instructions

Drug labeling and instructions provide essential information for patients regarding the usage of drugs. Instructions for the dosage of drug usage are critical for the effectiveness of the drug and the safety of patients. The dosage of many drugs varies depending on the patient's age. However, as our understanding of human biology deepens, we believe that these instructions need to be modified to incorporate different life stages. This is because human biology and metabolism differ significantly among different life stages, and their responses to drugs also vary. Additionally, the same age of different persons may fall into different life stages. Therefore, our group from multiple institutes and countries proposes a reexamination of whether incorporating life stages in all or any drug instructions will greatly enhance drug efficiency and patients' health.

A mitochondrial nexus in major depressive disorder: Integration with the psycho-immune-neuroendocrine network

Nervous system processes, including cognition and affective state, fundamentally rely on mitochondria. Impaired mitochondrial function is evident in major depressive disorder (MDD), reflecting cumulative detrimental influences of both extrinsic and intrinsic stressors, genetic predisposition, and mutation. Glucocorticoid 'stress' pathways converge on mitochondria; oxidative and nitrosative stresses in MDD are largely mitochondrial in origin; both initiate cascades promoting mitochondrial DNA (mtDNA) damage with disruptions to mitochondrial biogenesis and tryptophan catabolism. Mitochondrial dysfunction facilitates proinflammatory dysbiosis while directly triggering immuno-inflammatory activation via released mtDNA, mitochondrial lipids and mitochondria associated membranes (MAMs), further disrupting mitochondrial function and mitochondrial quality control, promoting the accumulation of abnormal mitochondria (confirmed in autopsy studies). Established and putative mechanisms highlight a mitochondrial nexus within the psycho-immune neuroendocrine (PINE) network implicated in MDD. Whether lowering neuronal resilience and thresholds for disease, or linking mechanistic nodes within the MDD pathogenic network, impaired mitochondrial function emerges as an important risk, a functional biomarker, providing a therapeutic target in MDD. Several treatment modalities have been demonstrated to reset mitochondrial function, which could benefit those with MDD.

Evaluating the interaction between 3'aQTL and alcohol consumption/smoking on anxiety and depression: 3'aQTL-by-environment interaction study in UK Biobank cohort

BACKGROUND

Smoking and alcohol consumption were associated with the development of depression and anxiety. 3'UTR APA quantitative trait loci (3'aQTLs) have been associated with multiple health states and conditions. Our aim is to evaluate the interactive effects of 3'aQTLs-alcohol consumption/tobacco smoking on the risk of anxiety and depression.

METHODS

The 3'aQTL data of 13 brain regions were extracted from the large-scale 3'aQTL atlas. The phenotype data (frequency of cigarette smoking and alcohol drinking, anxiety score, self-reported anxiety, depression score and self-reported depression) of 90,399-103,011 adults aged 40-69 years living in the UK and contributing to the UK Biobank during 2006-2010, were obtained from the UK Biobank cohort. The frequency of cigarette smoking and alcohol drinking of each subject were defined by the amount of smoking and alcohol drinking of self-reported, respectively. The continuous alcohol consumption/smoking terms were further categorized in tertiles. 3'aQTL-by-environmental interaction analysis was then performed to evaluate the associations of gene-smoking/alcohol consumption interactions with anxiety and depression using generalized linear model (GLM) of PLINK 2.0 with an additive mode of inheritance. Furthermore, GLM was also used to explore the relationship between alcohol consumption/smoking with hazard of anxiety/depression stratified by allele for the significant genotyped SNPs that modified the alcohol consumption/smoking-anxiety/depression association.

RESULTS

The interaction analysis identified several candidate 3'aQTLs-alcohol consumption interactions, such as rs7602638 located in PPP3R1 (β = 0.08, P = 6.50 × 10-6) for anxiety score; rs10925518 located in RYR2 (OR = 0.95, P = 3.06 × 10-5) for self-reported depression. Interestingly, we also observed that the interactions between TMOD1 (β = 0.18, P = 3.30 × 10-8 for anxiety score; β = 0.17, P = 1.42 × 10-6 for depression score), ZNF407 (β = 0.17, P = 2.11 × 10-6 for anxiety score; β = 0.15, P = 4.26 × 10-5 for depression score) and alcohol consumption was not only associated with anxiety, but related to depression. Besides, we found that relationship between alcohol consumption and hazard of anxiety/depression was significantly different for different SNPs genotypes, such as rs34505550 in TMOD1 (AA: OR = 1.03, P = 1.79 × 10-6; AG: OR = 1.00, P = 0.94; GG: OR = 1.00, P = 0.21) for self-reported anxiety.

LIMITATIONS

The identified 3'aQTLs-alcohol consumption/smoking interactions were associated with depression and anxiety, and its potential biological mechanisms need to be further revealed.

CONCLUSIONS

Our study identified important interactions between candidate 3'aQTL and alcohol consumption/smoking on depression and anxiety, and found that the 3'aQTL may modify the associations between consumption/smoking with depression and anxiety. These findings may help to further explore the pathogenesis of depression and anxiety.

Stress and the brain transcriptome: Identifying commonalities and clusters in standardized data from published experiments

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.

Alteration in the mRNA expression profile of the autophagy-related mTOR pathway in schizophrenia patients treated with olanzapine

BACKGROUND

The mammalian target of rapamycin protein (mTOR) signaling pathway is involved in the pathogenesis of schizophrenia and the mechanism of extrapyramidal adverse reactions to antipsychotic drugs, which might be mediated by an mTOR-dependent autophagy impairment. This study aimed to examine the expression of mTOR pathway genes in patients with schizophrenia treated with olanzapine, which is considered an mTOR inhibitor and autophagy inducer.

METHODS

Thirty-two patients with acute schizophrenia who had been treated with olanzapine for four weeks (average dose 14.24 ± 4.35 mg/d) and 32 healthy volunteers were recruited. Before and after olanzapine treatment, the Positive and Negative Syndrome Scale (PANSS) was used to evaluate the symptoms of patients with schizophrenia, and the mRNA expression levels of mTOR pathway-related genes, including MTOR, RICTOR, RAPTOR, and DEPTOR, were detected in fasting venous blood samples from all subjects using real-time quantitative PCR.

RESULTS

The MTOR and RICTOR mRNA expression levels in patients with acute schizophrenia were significantly decreased compared with those of healthy controls and further significantly decreased after four weeks of olanzapine treatment. The DEPTOR mRNA expression levels in patients with acute schizophrenia were not significantly different from those of healthy controls but were significantly increased after treatment. The expression levels of the RAPTOR mRNA were not significantly different among the three groups. The pairwise correlations of MTOR, DEPTOR, RAPTOR, and RICTOR mRNA expression levels in patients with acute schizophrenia and healthy controls were significant. After olanzapine treatment, the correlations between the expression levels of the DEPTOR and MTOR mRNAs and between the DEPTOR and RICTOR mRNAs disappeared.

CONCLUSIONS

Abnormalities in the mTOR pathway, especially DEPTOR and mTORC2, might play important roles in the autophagy mechanism underlying the pathophysiology of schizophrenia and effects of olanzapine treatment.

Translational Identification of Transcriptional Signatures of Major Depression and Antidepressant Response

Major depressive disorder (MDD) is a highly prevalent mental illness whose therapy management remains uncertain, with more than 20% of patients who do not achieve response to antidepressants. Therefore, identification of reliable biomarkers to predict response to treatment will greatly improve MDD patient medical care. Due to the inaccessibility and lack of brain tissues from living MDD patients to study depression, researches using animal models have been useful in improving sensitivity and specificity of identifying biomarkers. In the current study, we used the unpredictable chronic mild stress (UCMS) model and correlated stress-induced depressive-like behavior (n = 8 unstressed vs. 8 stressed mice) as well as the fluoxetine-induced recovery (n = 8 stressed and fluoxetine-treated mice vs. 8 unstressed and fluoxetine-treated mice) with transcriptional signatures obtained by genome-wide microarray profiling from whole blood, dentate gyrus (DG), and the anterior cingulate cortex (ACC). Hierarchical clustering and rank-rank hypergeometric overlap (RRHO) procedures allowed us to identify gene transcripts with variations that correlate with behavioral profiles. As a translational validation, some of those transcripts were assayed by RT-qPCR with blood samples from 10 severe major depressive episode (MDE) patients and 10 healthy controls over the course of 30 weeks and four visits. Repeated-measures ANOVAs revealed candidate trait biomarkers (ARHGEF1, CMAS, IGHMBP2, PABPN1 and TBC1D10C), whereas univariate linear regression analyses uncovered candidates state biomarkers (CENPO, FUS and NUBP1), as well as prediction biomarkers predictive of antidepressant response (CENPO, NUBP1). These data suggest that such a translational approach may offer new leads for clinically valid panels of biomarkers for MDD.