Blood and urinary metabolomic evidence validating traditional Chinese medicine diagnostic classification of major depressive disorder

Metabolomics in Depression: What We Learn from Preclinical and Clinical Evidences

Depression is one of the predominant common mental illnesses that affects millions of people of all ages worldwide. Random mood changes, loss of interest in routine activities, and prevalent unpleasant senses often characterize this common depreciated mental illness. Subjects with depressive disorders have a likelihood of developing cardiovascular complications, diabesity, and stroke. The exact genesis and pathogenesis of this disease are still questionable. A significant proportion of subjects with clinical depression display inadequate response to antidepressant therapies. Hence, clinicians often face challenges in predicting the treatment response. Emerging reports have indicated the association of depression with metabolic alterations. Metabolomics is one of the promising approaches that can offer fresh perspectives into the diagnosis, treatment, and prognosis of depression at the metabolic level. Despite numerous studies exploring metabolite profiles post-pharmacological interventions, a quantitative understanding of consistently altered metabolites is not yet established. The article gives a brief discussion on different biomarkers in depression and the degree to which biomarkers can improve treatment outcomes. In this review article, we have systemically reviewed the role of metabolomics in depression along with current challenges and future perspectives.

Deciphering the Metabolome under Stress: Insights from Rodent Models

Despite intensive research efforts to understand the molecular underpinnings of psychological stress and stress responses, the underlying molecular mechanisms remain largely elusive. Towards this direction, a plethora of stress rodent models have been established to investigate the effects of exposure to different stressors. To decipher affected molecular pathways in a holistic manner in these models, metabolomics approaches addressing altered, small molecule signatures upon stress exposure in a high-throughput, quantitative manner provide insightful information on stress-induced systemic changes in the brain. In this review, we discuss stress models in mice and rats, followed by mass spectrometry (MS) and nuclear magnetic resonance (NMR) metabolomics studies. We particularly focus on acute, chronic and early life stress paradigms, highlight how stress is assessed at the behavioral and molecular levels and focus on metabolomic outcomes in the brain and peripheral material such as plasma and serum. We then comment on common metabolomics patterns across different stress models and underline the need for unbiased -omics methodologies and follow-up studies of metabolomics outcomes to disentangle the complex pathobiology of stress and pertinent psychopathologies.

An integrated targeted metabolomics and network pharmacology approach to exploring the mechanism of ellagic acid against sleep deprivation-induced memory impairment and anxiety

Background

As a neuroprotective agent, ellagic acid (EA) is extremely beneficial. Our previous study found that EA can alleviate sleep deprivation (SD)-induced abnormal behaviors, although the mechanisms underlying this protective effect have not yet been fully elucidated.

Objective

An integrated network pharmacology and targeted metabolomics approach was utilized in this study to investigate the mechanism of EA against SD-induced memory impairment and anxiety.

Methods

Behavioral tests were conducted on mice after 72 h of SD. Hematoxylin and eosin staining and nissl staining were then carried out. Integration of network pharmacology and targeted metabolomics was performed. Eventually, the putative targets were further verified using molecular docking analyses and immunoblotting assays.

Results

The present study findings confirmed that EA ameliorated the behavioral abnormalities induced by SD and prevented histopathological and morphological damage to hippocampal neurons. Through multivariate analysis, clear clustering was obtained among different groups, and potential biomarkers were identified. Four key targets, catechol-O-methyltransferase (COMT), cytochrome P450 1B1 (CYP1B1), glutathione S-transferase A2 (GSTA2), and glutathione S-transferase P1 (GSTP1), as well as the related potential metabolites and metabolic pathways, were determined by further integrated analysis. Meanwhile, in-silico studies revealed that EA is well located inside the binding site of CYP1B1 and COMT. The experimental results further demonstrated that EA significantly reduced the increased expression of CYP1B1 and COMT caused by SD.

Conclusion

The findings of this study extended our understanding of the underlying mechanisms by which EA treats SD-induced memory impairment and anxiety, and suggested a novel approach to address the increased health risks associated with sleep loss.

Metabolomics- and systems toxicology-based hepatotoxicity mechanism of Sophorae Tonkinensis Radix et Rhizoma in rats

Drug-induced liver injury (DILI) is a major challenge to the development and clinical application of drugs, especially limits the global application of Chinese herbal medicines, because the material basis and mechanisms of some Chinese herbal medicines are not well clear. In this study, a comprehensive method integrating metabolomics and systems toxicology (SysT) was used to investigate how the main substances in Sophorae TonkinensisRadix et Rhizoma (STRER) influence the metabolic pathways and molecular mechanisms of hepatotoxicity. Through a 28-day continuous oral administration toxicity study combined with serum metabolomics analyses, the aqueous, ethanol-precipitation and dichloromethane extracts of STRER exhibited significant hepatotoxic effects. In addition, 19 differential metabolites with a time-dose-effect relationship were identified in rats. The primary bile acid biosynthesis pathway was significantly altered, which was consistent with the findings of the SysT analysis. Furthermore, through the quantification of bile acids in serum, 16 differential bile acids were identified as being significantly changed; moreover, 21 relevant targets which intersected with the hepatotoxic targets of STRER were identified. Molecular docking was used to confirm the validation of bindings between targets and corresponding compounds, and finally, six important compounds and 14 potential targets were identified to be involved in STRER-induced liver injury in relation to bile acid metabolism.

Metabolomics of Major Depressive Disorder: A Systematic Review of Clinical Studies

Although the understanding of the pathophysiology of major depressive disorder (MDD) has advanced greatly, this has not been translated into improved outcomes. To date, no biomarkers have been identified for the diagnosis, prognosis, and therapeutic management of MDD. Thus, we aim to review the biomarkers that are differentially expressed in MDD. A systematic review was conducted in January 2022 in the PubMed/MEDLINE, Scopus, Embase, PsycINFO, and Gale Academic OneFile databases for clinical studies published from January 2001 onward using the following terms: “Depression” OR “Depressive disorder” AND “Metabolomic.” Multiple metabolites were found at altered levels in MDD, demonstrating the involvement of cellular signaling metabolites, components of the cell membrane, neurotransmitters, inflammatory and immunological mediators, hormone activators and precursors, and sleep controllers. Kynurenine and acylcarnitine were identified as consistent with depression and response to treatment. The most consistent evidence found was regarding kynurenine and acylcarnitine. Although the data obtained allow us to identify how metabolic pathways are affected in MDD, there is still not enough evidence to propose changes to current diagnostic and therapeutic actions. Some limitations are the heterogeneity of studies on metabolites, methods for detection, analyzed body fluids, and treatments used. The experiments contemplated in the review identified increased or reduced levels of metabolites, but not necessarily increased or reduced the activity of the associated pathways. The information acquired through metabolomic analyses does not specify whether the changes identified in the metabolites are a cause or a consequence of the pathology.

Alteration of the Intestinal Permeability Are Reflected by Changes in the Urine Metabolome of Young Autistic Children: Preliminary Results

Several metabolomics-based studies have provided evidence that autistic subjects might share metabolic abnormalities with gut microbiota dysbiosis and alterations in gut mucosal permeability. Our aims were to explore the most relevant metabolic perturbations in a group of autistic children, compared with their healthy siblings, and to investigate whether the increased intestinal permeability may be mirrored by specific metabolic perturbations. We enrolled 13 autistic children and 14 unaffected siblings aged 2–12 years; the evaluation of the intestinal permeability was estimated by the lactulose:mannitol test. The urine metabolome was investigated by proton nuclear magnetic resonance (1H-NMR) spectroscopy. The lactulose:mannitol test unveiled two autistic children with altered intestinal permeability. Nine metabolites significantly discriminated the urine metabolome of autistic children from that of their unaffected siblings; however, in the autistic children with increased permeability, four additional metabolites—namely, fucose, phenylacetylglycine, nicotinurate, and 1-methyl-nicotinamide, strongly discriminated their urine metabolome from that of the remaining autistic children. Our preliminary data suggest the presence of a specific urine metabolic profile associated with the increase in intestinal permeability.

Gut microbiota and gut tissue metabolites involved in development and prevention of depression

Depression is a prevalent, life-threatening, and highly recurrent psychiatric illness. Several studies have shown that depression is associated with endogenous metabolites and the gut microbiota. However, it is unclear whether metabolites in different gut tissues play a role in the pathogenesis of depression and whether the gut microbiota has an impact on depression. Here, we investigated the metabolic signatures in the jejunum, ileum, and colorectum using metabolomics and explored the influence of the gut microbiota on both the development of chronic variable stress (CVS)-induced depression rat model and variations in gut tissue metabolites using a gnotobiotic rat model. The results showed that CVS induced disturbances in gut metabolites (29 differential metabolites) and had different effects on the different segments. When CVS rats were treated with antibiotics, depression-like ethological disorders disappeared, and the decreased catecholamine levels almost normalized. The depression recovery was attributed to the influence of antibiotics on the gut microbiota, especially inhibiting Clostridiaceae (F1), Candidatus arthromitus (G2), Lactobacillus (G6), and elevating Pseudomonadaceae (F6). Moreover, 16 of 29 varied metabolites in CVS rats were reversed with antibiotic treatment. Among them, 12 increased metabolites were decreased, suggesting a trigger for depression. However, four decreased metabolites were increased, indicating a potential therapeutic effect on depression. Based on the Pearson's correlation analysis, hypoxanthine, 3-hydroxypristanic acid, threonic acid, and L-carnitine were strongly associated with F6, F1, G2, and G6, which are involved in the development and prevention of depression. These findings provide a possibility for further exploration of the pathogenesis and prevention of depression.

Clinical efficacy of Tiaoqi Jiangni decoction in the treatment of functional dyspepsia and its influence on life quality

OBJECTIVE

To observe clinical effects of Tiaoqi Jiangni Decoction combined with mosapride citrate tablets in the treatment of functional dyspepsia and its impact on quality of life.

METHODS

Seventy-six patients with functional dyspepsia were admitted to Cangzhou Central Hospital of Hebei Province from September 2019 to June 2020. They were selected and randomized into a treatment group and a control group (38 cases in each group). Both groups received mosapride citrate tablets (5 mg/time, 3 times/d). The treatment group was additionally given Tiaoqi Jiangni Decoction.

RESULTS

The total effective rate of the treatment group was higher than that of the control group (P < 0.05). After treatment, the sub-scores of each symptom and the overall score of traditional Chinese medicine (TCM) syndrome in the treatment group were significantly lower than those in the control group (all P < 0.05). The overall and sub-item scores of the Functional Digestive Disorders Quality of Life Questionnaire (FDDQL) of both groups saw an increase after treatment (all P < 0.05). There was no significant disparity in sleep and stress between the two groups. The treatment group presented a better performance in other aspects than the control group (all P < 0.05). Before treatment, the two groups showed no significant disparity in the gastric emptying rate of barium bar and mental and psychological state. The two indexes were observed with a rise after treatment, with superior results in the treatment group to those in the control group (P < 0.05). No adverse reactions were observed in the two groups. One month after treatment, the treatment group obtained a lower recurrence rate as compared to the control group (P < 0.05).

CONCLUSION

Tiaoqi Jiangni Decoction in combination with mosapride citrate tablets in the treatment of FD yields a significant clinical effect by substantially alleviating patients' clinical symptoms and improving their quality of life, with no adverse reactions, high safety, and low recurrence rate, which merits further clinical application.

CLINICAL TRIAL REGISTRATION

The name of the registry: Chinese Registry of Clinical Trials.

TRIAL REGISTRATION NUMBER

ChiCTR2100063542. Trial URL: http://www.chictr.org.cn/showproj.aspx?proj=6354283.

Antidepressant Monotherapy and Combination Therapy with Acupuncture in Depressed Patients: A Resting-State Functional Near-Infrared Spectroscopy (fNIRS) Study

Depression is a common psychiatric illness affecting over 300 million people globally. Acupuncture has been reported to be a safe complementary treatment for depression. This study is aimed to investigate the efficacy and mechanism of combining acupuncture with antidepressants in treating depression compared to the sole use of antidepressants. Seventy depression patients were randomly assigned to the treatment group (n = 50) and control group (n = 20). The treatment group received acupuncture combined antidepressants treatment for 3 weeks, while the control group took antidepressants monotherapy for 3 weeks. Among the 70 patients, 40 participants (20 control; 20 treatment) were randomized for studying functional connectivity (FC) of the dorsolateral prefrontal cortex (DLPFC) measured by the functional near-infrared spectroscopy. The primary outcome was HAMD-17 and secondary outcomes were PHQ-9, and the relationships of resting-state FC (rsFC) with the depression severity. PHQ-9 and HAMD-17 scores in the treatment group were significantly lower than those in the control group at Week 3 (p = 0.01) with effect sizes of -0.4 and -0.61 respectively. The rsFC in F1, F3, AF3, AF7, FC3, FC5 (left DLPFC, 10-20 system), AF8, and F6 (right DLPFC) in the treatment group had significant temporal correlation (p < 0.05, FDR corrected) in DLPFC compared to the channels in the control group. No significant correlation was found between the changes of rsFC and depression severity. In conclusion, depressed patients receiving acupuncture combined with antidepressants have improvement of depressive symptoms and the stronger rsFC in the DLPFC compared to those using antidepressants alone.

Blood Plasma Metabolic Profile of Newborns with Hypoxic-Ischaemic Encephalopathy by GC-MS

Background

Early diagnosis of hypoxic-ischaemic encephalopathy (HIE) is crucial in preventing neurodevelopmental disabilities and reducing morbidity and mortality. The study was to investigate the plasma metabolic signatures in the peripheral blood of HIE newborns and explore the potential diagnostic biomarkers.

Method

In the present study, 24 newborns with HIE and 24 healthy controls were recruited. The plasma metabolites were measured by gas chromatography-mass spectrometry (GC-MS), and the raw data was standardized by the EigenMS method. Significantly differential metabolites were identified by multivariate statistics. Pathway enrichment was performed by bioinformatics analysis. Meanwhile, the diagnostic value of candidate biomarkers was evaluated.

Result

The multivariate statistical models showed a robust capacity to distinguish the HIE cases from the controls. 52 metabolites were completely annotated. 331 significantly changed pathways were enriched based on seven databases, including 33 overlapped pathways. Most of them were related to amino acid metabolism, energy metabolism, neurotransmitter biosynthesis, pyrimidine metabolism, the regulation of HIF by oxygen, and GPCR downstream signaling. 14 candidate metabolites showed great diagnostic potential on HIE. Among them, alpha-ketoglutaric acid has the potential to assess the severity of HIE in particular.

Conclusion

The blood plasma metabolic profile could comprehensively reflect the metabolic disorders of the whole body under hypoxia-ischaemic injury. Several candidate metabolites may serve as promising biomarkers for the early diagnosis of HIE. Further validation based on large clinical samples and the establishment of guidelines for the clinical application of mass spectrometry data standardization methods are imperative in the future.

Gut Microbiome: A Potential Indicator for Differential Diagnosis of Major Depressive Disorder and General Anxiety Disorder

Background: Major depressive disorder (MDD) and general anxiety disorder (GAD) share many common features, leading to numerous challenges in their differential diagnosis. Given the importance of the microbiota-gut-brain axis, we investigated the differences in gut microbiota between representative cases of these two diseases and sought to develop a microbiome-based approach for their differential diagnosis. Methods: We enrolled 23 patients with MDD, 21 with GAD, and 10 healthy subjects (healthy crowd, HC) in the present study. We used 16S rRNA gene-sequencing analysis to determine the microbial compositions of the gut microbiome based on Illumina Miseq and according to the standard protocol. Results: GAD showed a significant difference in microbiota richness and diversity as compared with HC. Additionally, Otu24167, Otu19140, and Otu19751 were significantly decreased in MDD relative to HC, and Otu2581 and Otu10585 were significantly increased in GAD relative to MDD. At the genus level, the abundances of Sutterella and Fusicatenibacter were significantly lower in MDD relative to HC, and the abundances of Fusicatenibacter and Christensenellaceae_R7_group were significantly lower in GAD than in HC. The abundance of Sutterella was significantly higher whereas that of Faecalibacterium was significantly lower in GAD relative to MDD. Moreover, we observed that Christensenellaceae_R7_group negatively correlated with the factor score (Limited to Hopelessness) and total score of HAMD-24 (p < 0.05), whereas Fusicatenibacter negatively correlated with FT4 (p < 0.05). Furthermore, the GAD group showed significant differences at the genus level for Faecalibacterium, which negatively correlated with PTC (p < 0.05). Conclusions: This study elucidated a unique gut-microbiome signature associated with MDD and GAD that could facilitate differential diagnosis and targeted therapy.

Self-Designed Ningxin Anshen Formula for Treatment of Post-ischemic Stroke Insomnia: A Randomized Controlled Trial

This study aimed to assess the efficacy and safety of self-designed Ningxin Anshen (NXAS) Formula for post-ischemic stroke insomnia of blood-deficient and liver-heat syndrome. Ninety patients were randomized into NXAS group, Placebo group and Zopiclone group. Patients in the NXAS group, Placebo group and Zopiclone group were treated with Ningxin Anshen Formula, placebo and zopiclone for 4 weeks, respectively. The scores of the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI) and traditional Chinese Medicine (TCM) Syndromes of self-designed scale and the number of adverse events (AEs) were determined. Results showed that the overall effective rate in the NXAS group and Placebo group was 76.67 and 30.00%, respectively, showing significant difference (P < 0.01). There was no marked difference between Zopiclone group (80.00%) and NXAS group. In both NXAS group and Zopiclone group, the scores of PSQI, ISI, and TCM Syndromes of self-designed scale after 4-week treatment were significantly different from those before treatment (P < 0.01). After 4-week treatment, the scores of PSQI, ISI, and TCM Syndromes of self-designed score were comparable between NXAS group and Zopiclone group (P > 0.05). Only one patient in the NXAS group developed gastrointestinal discomfort, which resolved without treatment discontinuation. In conclusion, self-designed NXAS Formula is effective and safe and has little adverse effect in treating post-stroke insomnia of blood-deficient and liver-heat syndrome.

Altered Default Mode Network and Salience Network Functional Connectivity in Patients with Generalized Anxiety Disorders: An ICA-Based Resting-State fMRI Study

This study aimed to explore the role of the default mode network (DMN) and salience network (SN) in the assessment of pathophysiology of generalized anxiety disorder (GAD) through analyzing the characteristics of internal function connectivity (FC) and to investigate the relationship of FC with Hamilton anxiety (HAMA) scale scores in untreated GAD patients during a resting-state functional magnetic resonance imaging (rs-fMRI). Rs-fMRI and HAMA scale scoring were performed in 51 GAD patients (31 GAD patients with liver stagnation transforming into fire type and 20 GAD patients with stagnation of liver-Qi syndrome type) and 20 healthy controls. Spearman correlation analysis was performed to assess the association between HAMA scores and abnormal brain FC. Compared with healthy controls, the FC of the right medial prefrontal gyrus of the DMN and the right superior temporal gyrus of the SN increased significantly in the GAD patients (P < 0.001). However, the FC of the left middle frontal gyrus and bilateral medial superior frontal gyrus of the SN reduced significantly in the GAD patients with stagnation of liver-Qi syndrome type as compared with healthy controls and GAD patients with liver stagnation transforming into fire type (P < 0.001). There was no relationship between abnormal brain FC and HAMA scores. In conclusion, the FC of the DMN and SN may be abnormal in the GAD patients at the resting state. The aberrant FC of some crucial brain regions of these networks may contribute to the pathophysiology of GAD.

Metabolomic Biomarkers in Anxiety Disorders

Anxiety disorders range among the most prevalent psychiatric disorders and belong to the leading disorders in the study of the total global burden of disease. Anxiety disorders are complex conditions, with not fully understood etiological mechanisms. Numerous factors, including psychological, genetic, biological, and chemical factors, are thought to be involved in their etiology. Although the diagnosis of anxiety disorders is constantly evolving, diagnostic manuals rely on symptom lists, not on objective biomarkers and treatment effects are small to moderate. The underlying biological factors that drive anxiety disorders may be better suited to serve as biomarkers for guiding personalized medicine, as they are objective and can be measured externally. Therefore, the incorporation of novel biomarkers into current clinical methods might help to generate a classification system for anxiety disorders that can be linked to the underlying dysfunctional pathways. The study of metabolites (metabolomics) in a large-scale manner shows potential for disease diagnosis, for stratification of patients in a heterogeneous patient population, for monitoring therapeutic efficacy and disease progression, and for defining therapeutic targets. All of these are important properties for anxiety disorders, which is a multifactorial condition not involving a single-gene mutation. This review summarizes recent investigations on metabolomics studies in anxiety disorders.

Metabolic linkages between indoor negative air ions, particulate matter and cardiorespiratory function: A randomized, double-blind crossover study among children

BACKGROUND

Ionization air purifiers, which purify particulate matter (PM) by producing vast number of negative air ions (NAI), are widely used. Recent study implied that ionization air purification could bring respiratory benefits but deterioration of heart rate variability (HRV). However, its underlying molecular mechanisms remain unclear.

OBJECTIVES

To explore the molecular linkages between indoor NAI, decreased PM and the cardiorespiratory effect after purification.

METHODS

Urine samples were collected from 44 healthy children three times of each study period (real and sham purification) in an existing randomized, double-blind crossover study. Ultra-high performance liquid chromatography/mass spectrometry was conducted in metabolomics analysis, the associations between indoor NAI, decreased PM and the cardiorespiratory function were investigated via the meet-in-metabolite approach (MIMA) based on statistical and metabolic pathway analysis. Mixed-effect models were used to establish associations between exposure, health parameters and metabolites.

RESULTS

Twenty-eight and fourteen metabolites were identified with significant correlations to NAI and PM, respectively. Besides, eight and eighteen metabolites were separately associated with respiratory function and HRV. The increased NAI and decreased PM improved respiratory function mainly with eight pathways, promoting energy production, anti-inflammation and anti-oxidation capacity. Decreased PM ameliorated HRV with six main pathways, increasing energy production and anti-inflammation capacity while increased NAI deteriorated HRV with five main pathways, lowering energy generation and anti-oxidation capacity.

CONCLUSIONS

Increased NAI and decreased PM ameliorated respiratory function by increasing energy production, improving anti-inflammation and anti-oxidation capacity. Decreased PM improved cardiac autonomic function by increasing energy production and anti-inflammation capacity, while these benefits were overcast by massive NAI via lowering energy generation and anti-oxidation capacity with different metabolic pathways.

Metabolomics in Psychiatric Disorders: What We Learn from Animal Models

Biomarkers are a recent research target within biological factors of psychiatric disorders. There is growing evidence for deriving biomarkers within psychiatric disorders in serum or urine samples in humans, however, few studies have investigated this differentiation in brain or cerebral fluid samples in psychiatric disorders. As brain samples from humans are only available at autopsy, animal models are commonly applied to determine the pathogenesis of psychiatric diseases and to test treatment strategies. The aim of this review is to summarize studies on biomarkers in animal models for psychiatric disorders. For depression, anxiety and addiction disorders studies, biomarkers in animal brains are available. Furthermore, several studies have investigated psychiatric medication, e.g., antipsychotics, antidepressants, or mood stabilizers, in animals. The most notable changes in biomarkers in depressed animal models were related to the glutamate-γ-aminobutyric acid-glutamine-cycle. In anxiety models, alterations in amino acid and energy metabolism (i.e., mitochondrial regulation) were observed. Addicted animals showed several biomarkers according to the induced drugs. In summary, animal models provide some direct insights into the cellular metabolites that are produced during psychiatric processes. In addition, the influence on biomarkers due to short- or long-term medication is a noticeable finding. Further studies should combine representative animal models and human studies on cerebral fluid to improve insight into mental disorders and advance the development of novel treatment strategies.

Advances and challenges in development of precision psychiatry through clinical metabolomics on mood and psychotic disorders

Metabolomics is defined as the study of the global metabolite profile in a system under a given set of conditions. The objective of this review is to comprehensively assess the literature on metabolomics in mood disorders and schizophrenia and provide data for mental health researchers about the challenges and potentials of metabolomics. The majority of studies in metabolomics in Psychiatry uses peripheral blood or urine. The most widely used analytical techniques in metabolomics research are nuclear magnetic resonance (NMR) and mass spectrometry (MS). They are multiparametric and provide extensive structural and conformational information on multiple chemical classes. NMR is useful in untargeted analysis, which focuses on biosignatures or 'metabolic fingerprints' of illnesses. MS targeted metabolomics approach focuses on the identification and quantification of selected metabolites known to be involved in a particular metabolic pathway. The available studies of metabolomics in Schizophrenia, Bipolar Disorder and Major Depressive Disorder suggest a potential in investigating metabolic pathways involved in these diseases' pathophysiology and response to treatment, as well as its potential in biomarkers identification.

Brain connectomic associations with traditional Chinese medicine diagnostic classification of major depressive disorder: a diffusion tensor imaging study

Background

Major depressive disorder (MDD) is highly heterogeneous in pathogenesis and manifestations. Further classification may help characterize its heterogeneity. We previously have shown differential metabolomic profiles of traditional Chinese medicine (TCM) diagnostic subtypes of MDD. We further determined brain connectomic associations with TCM subtypes of MDD.

Methods

In this naturalistic study, 44 medication-free patients with a recurrent depressive episode were classified into liver qi stagnation (LQS, n = 26) and Heart and Spleen Deficiency (HSD, n = 18) subtypes according to TCM diagnosis. Healthy subjects (n = 28) were included as controls. Whole-brain white matter connectivity was analyzed on diffusion tensor imaging.

Results

The LQS subtype showed significant differences in multiple network metrics of the angular gyrus, middle occipital gyrus, calcarine sulcus, and Heschl's gyrus compared to the other two groups. The HSD subtype had markedly greater regional connectivity of the insula, parahippocampal gyrus, and posterior cingulate gyrus than the other two groups, and microstructural abnormalities of the frontal medial orbital gyrus and middle temporal pole. The insular betweenness centrality was strongly inversely correlated with the severity of depression and dichotomized the two subtypes at the optimal cutoff value with acceptable sensitivity and specificity.

Conclusions

The LQS subtype is mainly characterized by aberrant connectivity of the audiovisual perception-related temporal-occipital network, whereas the HSD subtype is more closely associated with hyperconnectivity and microstructural abnormalities of the limbic-paralimbic network. Insular connectivity may serve a biomarker for TCM-based classification of depression.Trial registration Registered at http://www.clinicaltrials.gov (NCT02346682) on January 27, 2015.

Chronic paradoxical sleep deprivation-induced depression-like behavior, energy metabolism and microbial changes in rats

AIMS

Given the lasting impact of chronic paradoxical sleep deprivation (PSD) on behavior and organism metabolic alternations, along with the role of the microbiome in neurobehavioral development and metabolism, we sought to examine the relationship between the microbiota and chronic PSD-induced behavioral and metabolic changes.

MATERIALS AND METHODS

Psychological status of 7-day PSD (7d-PSD) male rats was tested by behavioral method, serum inflammatory cytokines and hypothalamic-pituitary-adrenal (HPA) axis-related hormones. In addition, GC-MS based urine metabolomics and 16S rRNA gene sequencing approaches were applied to estimate the influences of chronic PSD on host metabolism and gut-microbiota. Furtherly, microbial functional prediction and Spearman's correlation analysis were implemented to manifest the relations between the differential urinary metabolites and gut microbiota.

KEY FINDINGS

7d-PSD rats displayed depression-like behavior, metabolic and microbial changes. By integrating differential gut bacteria with indicators of depression and differential metabolites, we found that the alterations of Akkermansia, Oscillospira, Ruminococcus, Parabacteroides, Aggregatibacter and Phascolarctobacterium were closely related to abnormalities of depression symptoms and inflammatory cytokines. These bacteria also had close connections with host energy metabolism concerning arginine and proline metabolism, glycine, serine and threonine metabolism, and glyoxylate and dicarboxylate metabolism, pyruvate metabolism, which overlapped with the results of 16S rRNA gene function annotation.

SIGNIFICANCE

These data suggest that a specific situation of circadian disturbance, chronic PSD-induced alterations in gut microbiota and related host changes in metabolism may be the pathogenesis of depression.

Systems biology approaches in the study of Chinese herbal formulae

Systems biology is an academic field that attempts to integrate different levels of information to understand how biological systems function. It is the study of the composition of all components of a biological system and their interactions under specific conditions. The core of systems biology is holistic and systematic research, which is different from the manner of thinking and research of all other branches of biology to date. Chinese herbal formulae (CHF) are the main form of Chinese medicine and are composed of single Chinese herbal medicines (CHMs) with pharmacological and pharmacodynamic compatibility. When single CHMs are combined into CHF, the result is different from the original effect of a single drug and can be better adapted to more diseases with complex symptoms. CHF represent a complex system with multiple components, targets and effects. Therefore, the use of systems biology is conducive to revealing the complex characteristics of CHF. With the rapid development of omics technologies, systems biology has been widely and increasingly applied to the study of the basis of the pharmacological substances, action targets and mechanisms of CHF. To meet the challenges of multiomics synthesis-intensive studies and system dynamics research in CHF, this paper reviews the common techniques of genomics, transcriptomics, proteomics, metabolomics, and metagenomics and their applications in research on CHF.

Application of metabolomics in toxicity evaluation of traditional Chinese medicines

Traditional Chinese medicines (TCM) have a long history of use because of its potential complementary therapy and fewer adverse effects. However, the toxicity and safety issues of TCM have drawn considerable attention in the past two decades. Metabolomics is an “omics” approach that aims to comprehensively analyze all metabolites in biological samples. In agreement with the holistic concept of TCM, metabolomics has shown great potential in efficacy and toxicity evaluation of TCM. Recently, a large amount of metabolomic researches have been devoted to exploring the mechanism of toxicity induced by TCM, such as hepatotoxicity, nephrotoxicity, and cardiotoxicity. In this paper, the application of metabolomics in toxicity evaluation of bioactive compounds, TCM extracts and TCM prescriptions are reviewed, and the potential problems and further perspectives for application of metabolomics in toxicological studies are also discussed.