Targeting hippocampal phospholipid and tryptophan metabolism for antidepressant-like effects of albiflorin

Advances in biosensors for major depressive disorder diagnostic biomarkers

Depression is one of the most common mental disorders and is mainly characterized by low mood or lack of interest and pleasure. It can be accompanied by varying degrees of cognitive and behavioral changes and may lead to suicide risk in severe cases. Due to the subjectivity of diagnostic methods and the complexity of patients' conditions, the diagnosis of major depressive disorder (MDD) has always been a difficult problem in psychiatry. With the discovery of more diagnostic biomarkers associated with MDD in recent years, especially emerging non-coding RNAs (ncRNAs), it is possible to quantify the condition of patients with mental illness based on biomarker levels. Point-of-care biosensors have emerged due to their advantages of convenient sampling, rapid detection, miniaturization, and portability. After summarizing the pathogenesis of MDD, representative biomarkers, including proteins, hormones, and RNAs, are discussed. Furthermore, we analyzed recent advances in biosensors for detecting various types of biomarkers of MDD, highlighting representative electrochemical sensors. Future trends in terms of new biomarkers, new sample processing methods, and new detection modalities are expected to provide a complete reference for psychiatrists and biomedical engineers.

Targeting autophagy to counteract neuroinflammation: A novel antidepressant strategy

Depression is a common disease that affects physical and mental health and imposes a considerable burden on afflicted individuals and their families worldwide. Depression is associated with a high rate of disability and suicide. It causes a severe decline in productivity and quality of life. Unfortunately, the pathophysiological mechanisms underlying depression have not been fully elucidated, and the risk of its treatment is still presented. Studies have shown that the expression of autophagic markers in the brain and peripheral inflammatory mediators are dysregulated in depression. Autophagy-related genes regulate the level of autophagy and change the inflammatory response in depression. Depression is related to several aspects of immunity. The regulation of the immune system and inflammation by autophagy may lead to the development or deterioration of mental disorders. This review highlights the role of autophagy and neuroinflammation in the pathophysiology of depression, sumaries the autophagy-targeting small moleculars, and discusses a novel therapeutic strategy based on anti-inflammatory mechanisms that target autophagy to treat the disease.

Progress of depression mechanism based on Omics method

Depression is a very common disabling mental disorder, which is typically characterized by high rates of disability and mortality. Although research into the various mechanisms of depression was still underway, its physiopathology remains uncertain. The rapid developments in new technologies and the combined use of a variety of techniques will help to understand the pathogenesis of depression and explore effective treatment methods. In this review, we focus on the combination of proteomic and metabolomic approaches to analyze metabolites and proteins in animal models of depression induced by different modeling approaches, with the aim of broadening the understanding of the physiopathological mechanisms of depression using complementary "omics" strategy.

The physicochemical characteristics and antidepressant-like effects of a polysaccharide-rich fraction from Schisandra chinensis (Turcz.) Baill in behavioral despair mice and olfactory bulbectomy-induced depression-like mice

ETHNOPHARMACOLOGICAL RELEVANCE

The dried fruit of Schisandra chinensis (Turcz.) Baill (S. chinensis) is widely used in treating central nervous system disorders. Increasing evidence has suggested that alcohol-soluble extracts and lignans from S. chinensis could significantly ameliorate depression-like behaviors in animal models, while there was little research on the potential of alcohol-insoluble polysaccharides as a candidate in the treatment of depression.

AIM OF THE STUDY

Our research was designed to explore both the physicochemical characteristics and antidepressant-like effects of an alcohol-insoluble polysaccharide-rich fraction named SCP from S. chinensis. Simultaneously, the underlying mechanisms were elucidated in the study.

MATERIALS AND METHODS

The physicochemical characteristics were accomplished by colorimetric assays, CE, HPGPC, and FT-IR. Behavioral despair testing accompanied by LAT were processed to promptly assess the antidepressant-like effects of SCP in mice. Then OBX-induced mice were established to explore the impacts of chronic co-treatments with SCP. Furthermore, effects of SCP on the HPA axis, oxidant/antioxidant system, neurotrophic and synaptic factors, and gut microbiota in OBX-induced mice were detected through ELISA and 16S rDNA (V3 + V4 regions) gene sequencing.

RESULTS

SCP is a polysaccharide-rich fraction mainly comprised of xylose, glucose, rhamnose, galactose, mannose, and galacturonic acid in ratios of 0.27, 5.09, 0.24, 1.00, 0.63, and 2.86, of which the MW distribution ranges from 681 to 3232 Da. Acute pre-treatment with SCP (200 mg/kg, i.g.) remarkably reduced mice's immobility in the FST without motor stimulation. Prolonged pre-treatments effectively enhanced the effects of SCP on the behavioral despair testing in mice. Chronic co-treatments with SCP (50, 200, and 800 mg/kg, i.g.) could ameliorate the slow increase of body weight and behavioral abnormality of OBX-induced mice in systemic behavioral testing. SCP (200 mg/kg) also successfully restored hyperactivity of the HPA axis, oxidative damage in the liver, neurotrophic disturbance and abnormal synaptic plasticity in the hippocampus, and dysregulation of gut microbiota in OBX-induced mice.

CONCLUSION

SCP exerts noteworthy antidepressant-like impacts on behavioral despair mice and OBX-induced mice via multiple targets, indicating a potential therapeutic candidate in depression therapy.

MetDIT: Transforming and Analyzing Clinical Metabolomics Data with Convolutional Neural Networks

Clinical metabolomics is growing as an essential tool for precision medicine. However, classical machine learning algorithms struggle to comprehensively encode and analyze the metabolomics data due to their high dimensionality and complex intercorrelations. This article introduces a new method called MetDIT, designed to analyze intricate metabolomics data effectively using deep convolutional neural networks (CNN). MetDIT comprises two components: TransOmics and NetOmics. Since CNN models have difficulty in processing one-dimensional (1D) sequence data efficiently, we developed TransOmics, a framework that transforms sequence data into two-dimensional (2D) images while maintaining a one-to-one correspondence between the sequences and images. NetOmics, the second component, leverages a CNN architecture to extract more discriminative representations from the transformed samples. To overcome the overfitting due to the small sample size and class imbalance, we introduced a feature augmentation module (FAM) and a loss function to improve the model performance. Furthermore, we systematically optimized the model backbone and image resolution to balance the model parameters and computational costs. To demonstrate the performance of the proposed MetDIT, we conducted extensive experiments using three different clinical metabolomics data sets and achieved better classification performance than classical machine learning methods used in metabolomics, including Random Forest, SVM, XGBoost, and LightGBM. The source code is available at the GitHub repository at https://github.com/Li-OmicsLab/MetDIT, and the WebApp can be found at http://metdit.bioinformatics.vip/.

Exploring the mechanism of Si-Ni-San against depression by UPLC-Q-TOF-MS/MS integrated with network pharmacology: experimental research

Background

Depression is becoming an urgent mental health problem. Si-Ni-San has been widely used to treat depression, yet its underlying pharmacological mechanism is poorly understood. Thus, we aim to explore the antidepressant mechanism of Si-Ni-San by chemical analysis and in-silico methods.

Methods

Compounds in Si-Ni-San were determined by ultra-high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS). Then, bioactive compounds were obtained from Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform and SwissADME, and the potential targets of which were acquired from SwissTargetPrediction. Depression-related targets were collected from GeneCards. The intersection between compound-related targets and depression-related targets were screened out, and the overlapped targets were further performed protein-protein interaction, biological functional and pathway enrichment analysis. Finally, networks of Si-Ni-San against depression were constructed and visualized by Cytoscape.

Results

One hundred nineteen compounds in Si-Ni-San were determined, of which 24 bioactive compounds were obtained. Then, 137 overlapped targets of Si-Ni-San against depression were collected. AKT1, PIK3R1, PIK3CA, mTOR, MAPK1 and MAPK8 were the key targets. Furthermore, PI3K-Akt signalling pathway, serotonergic synapse, MAPK signalling pathway and neurotrophin signalling pathway were involved in the antidepressant mechanism of Si-Ni-San. It showed that components like sinensetin, hesperetin, liquiritigenin, naringenin, quercetin, albiflorin and paeoniflorin were the mainly key active compounds for the antidepressant effect of Si-Ni-San.

Conclusions

This study demonstrated the key components, key targets and potential pharmacological mechanisms of Si-Ni-San against depression. These results indicate that Si-Ni-San is a promising therapeutic approach for treatment of depression, and may provide evidence for the research and development of drugs for treating depression.

Recent Progress in Mass Spectrometry-Based Metabolomics in Major Depressive Disorder Research

Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

Effects of albiflorin on oxidative stress and inflammatory responses in rats with acute spinal cord injury

INTRODUCTION

Oxidative stress and inflammatory responses are often the predominant detrimental factors associated with spinal cord injury (SCI). This study investigates the potential therapeutic effects of albiflorin (AF) on alleviating inflammation and oxidative stress in the rat model with SCI.

METHODS

Initially, the behavior of SCI-induced rats is examined by Basso-Beattie-Bresnahan score and the inclined plane examination. Then, the immunohistochemical staining of inflammasome-related protein (for instance, NACHT, LRR, and PYD domains-containing protein 3, NLRP3) is performed in combination with enzyme-linked immunosorbent assay (ELISA) of corresponding proinflammatory factors to assess the immunomodulatory effects of AF. Further, the markers involved in oxidative stress are examined by ELISA and western blot analysis analyses.

RESULTS

These findings indicated that AF could alleviate motor dysfunction and the loss of neuron cells in SCI-induced rats. Mechanistically, AF could attenuate the inflammatory responses by reducing oxidative stress and activating nuclear erythroid-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) pathway in SCI rats. Depleting the antioxidant capacity by inhibiting glutathione biosynthesis could counteract the anti-inflammatory activity of AF in SCI rats.

CONCLUSIONS

Together, our data suggested that AF could serve as a potential therapeutic agent against the aggravation of SCI in rats.

Exosome-sheathed ROS-responsive nanogel to improve targeted therapy in perimenopausal depression

The development of natural membranes as coatings for nanoparticles to traverse the blood-brain barrier (BBB) presents an effective approach for treating central nervous system (CNS) disorders. In this study, we have designed a nanogel loaded with PACAP and estrogen (E2), sheathed with exosomes and responsive to reactive oxygen species (ROS), denoted as HA NGs@exosomes. The objective of this novel design is to serve as a potent drug carrier for the targeted treatment of perimenopausal depression. The efficient cellular uptake and BBB penetration of HA NGs@exosomes has been demonstrated in vitro and in vivo. Following intranasal intervention with HA NGs@exosomes, ovariectomized mice under chronic unpredictable mild stress (CUMS) have shown improved behavioral performance, indicating that HA NGs@exosomes produced a rapid-onset antidepressant effect. Moreover, HA NGs@exosomes exhibit notable antioxidant and anti-inflammatory properties and may regulate the expression of pivotal proteins in the PACAP/PAC1 pathway to promote synaptic plasticity. Our results serve as a proof-of-concept for the utility of exosome-sheathed ROS-responsive nanogel as a promising drug carrier for the treatment of perimenopausal depression.

Quantitative proteomics reveals the therapeutic effects of RFAP against depression via pathway regulation of long-term depression and potentiation

Ethnopharmacological relevance

RFAP is a compound extraction complex of four Traditional Chinese Medicine (TCM), including the dry bark of Paeonia lactiflora Pall. (Radix Paeoniae Alba), Gardenia jasminoides J. Ellis (Fructus Gardeniae), Albizia julibrissin Durazz. (Albizia julibrissin Durazz), and Paeonia × suffruticosa Andrews (Peony bark). Not only RFAP but also the individual ingredients have been commonly used for the treatment of depression in the clinic. However, the underlying mechanism of pharmacology is difficult to interpret since its holistic and multidrug nature.

Aim of the study

This study aimed to elucidate the potential antidepressant mechanism of RFAP in the treatment of chronic unpredictable mild stress (CUMS) rats' model via the quantitative proteomics approach.

Materials and methods

We established the CUMS rats' model and evaluated the efficacy of RFAP using multiple behavior assays, including the sugar preference test, open field test, and forced swimming test. Then label-free quantitative proteomics analyses were performed to evaluate the integrated changes of proteome profiling in control, CUMS, RFAP low dose, and RFAP high dose groups. Finally, we validated the critical changed proteins in the pathways of long-term depression and potentiation via RT-PCR and Western blotting assays.

Results

We successfully established the CUMS rats' model. The behavior assays indicated that the rats demonstrated a tendency to behavioral despair after four weeks. Label-free quantitative proteomics showed that 107 proteins were significantly upregulated and 163 proteins were downregulated in the CUMS group compared to the control group. These differentially expressed proteins were involved in long-term potentiation, long-term depression, nervous system development, neuronal synaptic structural constituent of ribosome, ATP metabolic process, learning or memory, and cellular lipid metabolic process. RFAP treatment partially restored the differentially expressed protein profile. The protective effect of RFAP on behavioral assessment were consistent with the results of proteomics.

Conclusions

The results indicated that RFAP exerted a synergistic effect on CUMS by regulating long-term inhibition and potentiation-related proteins.

Antidepressant effects of the traditional Chinese herbal formula Xiao-Yao-San and its bioactive ingredients

BACKGROUND

Depression is one of the most debilitating and severe psychiatric disorders and a serious public health concern. Currently, many treatments are indicated for depression, including traditional Chinese medicinal formulae such as Xiao-Yao-San (XYS), which has effective antidepressant effects in clinical and animal studies.

PURPOSE

To summarize current evidence of XYS in terms of the preclinical and clinical studies and to identify the multi-level, multi-approach, and multi-target potential antidepressant mechanisms of XYS and active components of XYS by a comprehensive search of the related electronic databases.

METHODS

The following electronic databases were searched from the beginning to April 2022: PubMed, MEDLINE, Web of Science, Google Scholar, and China National Knowledge Infrastructure.

RESULTS

This review summarizes the antidepressant mechanisms of XYS and its active ingredients, which are reportedly correlated with monoamine neurotransmitter regulation, synaptic plasticity, and hypothalamic-pituitary-adrenal axis, etc. CONCLUSION: XYS plays a critical role in the treatment of depression by the regulation of several factors, including the monoaminergic systems, hypothalamic-pituitary-adrenal axis, synaptic plasticity, inflammation, brain-derived neurotrophic factor levels, brain-gut axis, and other pathways. However, more clinical and animal studies should be conducted to further investigate the antidepressant function of XYS and provide more evidence and recommendations for its clinical application. Our review provides an overview of XYS and guidance for future research direction.

Tryptophan-5-HT pathway disorder was uncovered in the olfactory bulb of a depression mice model by metabolomic analysis

Major depression (MD) is a severe mental illness that creates a heavy social burden, and the potential molecular mechanisms remain largely unknown. Lots of research demonstrate that the olfactory bulb is associated with MD. Recently, gas chromatography-mass spectrometry-based metabolomic studies on depressive rats indicated that metabolisms of purine and lipids were disordered in the olfactory bulb. With various physicochemical properties and extensive concentration ranges, a single analytical technique could not completely cover all metabolites, hence it is necessary to adopt another metabolomic technique to seek new biomarkers or molecular mechanisms for depression. Therefore, we adopted a liquid chromatography-mass spectrometry metabonomic technique in the chronic mild stress (CMS) model to investigate significant metabolic changes in the olfactory bulb of the mice. We discovered and identified 16 differential metabolites in the olfactory bulb of the CMS treatments. Metabolic pathway analysis by MetaboAnalyst 5.0 was generated according to the differential metabolites, which indicated that the tryptophan metabolism pathway was the core pathogenesis in the olfactory bulb of the CMS depression model. Further, the expressions of tryptophan hydroxylase (TpH) and aromatic amino acid decarboxylase (AAAD) were detected by western blotting and immunofluorescence staining. The expression of TpH was increased after CMS treatment, and the level of AAAD was unaltered. These results revealed that abnormal metabolism of the tryptophan pathway in the olfactory bulb mediated the occurrence of MD.

Novel targets for ameliorating energy metabolism disorders in depression through stable isotope-resolved metabolomics

The severe harm of depression to human health and life has attracted global attention, but the exact mechanism is not yet known due to the complicated pathogenesis. The existing antidepressants are far from ideal, indicating it is urgently needed to seek safe and effective drugs from a unique perspective. Based on the hypothesis of "mitochondrial dysfunction" proposed recently, we attempt to focus on the substrates supply of energy metabolism. We applied stable isotope-resolved metabolomics, and revealed that significantly decreased TCA cycle and abnormally increased gluconeogenesis pathway in CUMS rats. Pyruvate dehydrogenase (PDH) and pyruvate carboxylase (PC) maybe the key metabolic enzymes. This metabolic reprogramming was confirmed through ELISA assays and Western blot analysis. To explore the causes of substrates supply disorder in depression, we conducted the mitochondrial structure-function evaluation. Interestingly, the levels of the mitochondrial pyruvate carrier (MPC) decreased significantly, which is essential for the entry of pyruvic acid into the TCA cycle. Together, MPC, PDH and PC are expected to become potential novel therapeutic targets for treating depressive disorders. This research provides a unique insight for re-cognizing the pathological mechanisms of depression, the novel targets for development of ideal antidepressants, as well as a paradigm for deciphering abnormal metabolic pathways in other metabolic diseases.

Study of Antidepressant-Like Effects of Albiflorin and Paeoniflorin Through Metabolomics From the Perspective of Cancer-Related Depression

Mental health has become a new challenge in cancer treatment, with a high prevalence of depression in patients with cancer. Albiflorin (AF) and paeoniflorinn (PF) are isomers extracted from the root of Paeoniae Radix Alba (Baishao in Chinese), belonging to the monoterpene glycosides, and multiple studies have been conducted on their antidepression and anti-cancer effects. However, the effects of AF and PF on cancer-related depression are unclear. Therefore, the current study aims to investigate whether the two isomers are able to exert antidepressant-like effects and understand the underlying mechanisms in a rat model, established by combining irradiation with chronic restraint stress and solitary confinement. Our results demonstrate a significant regulation of AF and PF in the pharmacodynamic index, including the peripheral blood, organ index, behavioral traits, and HPA axis, relative to control rats. In serum and cerebral cortex metabonomics analysis, AF and PF showed a significantly restorative trend in abnormal biomarkers and regulating ether lipid metabolism, alanine, aspartate, glutamate metabolism, tryptophan metabolism, carnitine metabolism, arachidonic acid metabolism, arginine and proline metabolism pathway. Eight potential biomarkers were further screened by means of receiver operating characteristic (ROC) analysis. The data indicate that AF and PF could effectively ameliorate a depression-like state in the model rats, and the mechanism may be associated with the regulation of the neuroendocrine immune system and disrupted metabolic pathways. Further experiments are warranted to comprehensively evaluate the antidepressant effects of AF and PF in cancer-related depression. This study provides a better insight into the action mechanisms of antidepression of TCM, and provides a new perspective for the therapy of cancer-related depression.

Understanding complex functional wiring patterns in major depressive disorder through brain functional connectome

Brain function relies on efficient communications between distinct brain systems. The pathology of major depressive disorder (MDD) damages functional brain networks, resulting in cognitive impairment. Here, we reviewed the associations between brain functional connectome changes and MDD pathogenesis. We also highlighted the utility of brain functional connectome for differentiating MDD from other similar psychiatric disorders, predicting recurrence and suicide attempts in MDD, and evaluating treatment responses. Converging evidence has now linked aberrant brain functional network organization in MDD to the dysregulation of neurotransmitter signaling and neuroplasticity, providing insights into the neurobiological mechanisms of the disease and antidepressant efficacy. Widespread connectome dysfunctions in MDD patients include multiple, large-scale brain networks as well as local disturbances in brain circuits associated with negative and positive valence systems and cognitive functions. Although the clinical utility of the brain functional connectome remains to be realized, recent findings provide further promise that research in this area may lead to improved diagnosis, treatments, and clinical outcomes of MDD.

Alginate nanogels-based thermosensitive hydrogel to improve antidepressant-like effects of albiflorin via intranasal delivery

Depression is a primary public health problem. However, current antidepressants work slowly, and together with side effects. Herein, the alginate nanogels were constructed to load albiflorin (albiflorin nanogels), which further formed albiflorin nanogel loaded self-assembled thermosensitive hydrogel system (albiflorin-NGSTH) and were used to improve its antidepressant effects. The nanogel showed a nano-scaled particle size and stronger antioxidant activity. Rheological studies showed that albiflorin-NGSTH had a sol-gel transition at approximately 28 °C. Albiflorin-NGSTH quickly entered the brain by intranasal delivery, and had a continuously release for albiflorin. Preliminary results of mice behavioral despair tests found that albiflorin-NGSTH had no effects on independent exploratory behavior and anxiety of the mice, and significantly decreased immobility duration of the mice in tail suspension test (TST). Moreover, the intranasally administrated albiflorin-NGSTH at a low dose improved depressive behavior, decreased levels of proinflammatory cytokines, and repaired neuronal damage of chronic unpredictable mild stress (CUMS) rats, which indicated an excellent potential for depression therapy. The treatment of albiflorin-NGSTH on depressive disorder was achieved by regulating signal pathway related to depression. Therefore, albiflorin-NGSTH has an excellent potential for clinical application in intranasal drug delivery systems.