Abnormal gut microbiota and bile acids in patients with first-episode major depressive disorder and correlation analysis

Digestive characteristics of Gastrodia elata Blume polysaccharide and related impacts on human gut microbiota in vitro

ETHNOPHARMACOLOGICAL RELEVANCE

Gastrodia elata Blume is a traditional Chinese medicine with the effects of improving the deficiency of the body and maintaining health, and polysaccharide (GEP) is one of the effective ingredients to play these activities of G. elata. Traditionally, G. elata is orally administered, so the activities of GEP are associated with digestive and intestinal metabolism. However, the digestive behavior of GEP and its effects on the human gut microbiota are unclear and need to be fully studied.

AIM OF THE STUDY

This study aimed to investigate the changes in structural characteristics of GEP during digestion and the related impacts of its digestive product on gut microbiota in human fecal fermentation, and to explain the beneficial mechanism of GEP on human health from the perspective of digestive characteristics and "gut" axis.

MATERIALS AND METHODS

The changes of reducing sugars, free monosaccharides and physicochemical properties of GEP during digestion were investigated by GPC, HPLC, FT-IR, CD, NMR, SEM, and TGA. Moreover, polysaccharide consumption, pH value changes, SCFAs production, and changes in gut microbiota during fermentation were also discussed.

RESULTS

During digestion of GEP, glucose was partially released causing a decrease in molecular weight, and a change in monosaccharide composition. In addition, the characteristics of GEP before and after digestion, including configuration, morphology, and stability, were different. The digestive product of GEP was polysaccharide (GEP-I), which actively participated in the fecal fermentation process. As the fermentation time increased, the utilization of GEP-I by the microbiota gradually increased. The abundance of probiotics such as Bifidobacterium, Collinsella, Prevotella, and Faecalibacterium was significantly increased, and the abundance of pathogenic Shigella, Dorea, Desulfovibrio, and Blautia was significantly inhibited, thereby suggesting that GEP has the potential to maintain human health through the "gut" axis. In addition, the beneficial health effects of GEP-I have also been observed in the influence of microbial metabolites. During the fermentation of GEP-I, the pH value gradually decreased, and the contents of beneficial metabolites such as acetic acid, propionic acid, and caproic acid significantly increased.

CONCLUSION

The structure of GEP changed significantly during digestion, and its digestive product had the potential to maintain human health by regulating gut microbiota, which may be one of the active mechanisms of GEP.

Assessing causal associations of bile acids with obesity indicators: A Mendelian randomization study

Maintaining a balanced bile acids (BAs) metabolism is essential for lipid and cholesterol metabolism, as well as fat intake and absorption. The development of obesity may be intricately linked to BAs and their conjugated compounds. Our study aims to assess how BAs influence the obesity indicators by Mendelian randomization (MR) analysis. Instrumental variables of 5 BAs were obtained from public genome-wide association study databases, and 8 genome-wide association studies related to obesity indicators were used as outcomes. Causal inference analysis utilized inverse-variance weighted (IVW), weighted median, and MR-Egger methods. Sensitivity analysis involved MR-PRESSO and leave-one-out techniques to detect pleiotropy and outliers. Horizontal pleiotropy and heterogeneity were assessed using the MR-Egger intercept and Cochran Q statistic, respectively. The IVW analysis revealed an odds ratio of 0.94 (95% confidence interval: 0.88, 1.00; P = .05) for the association between glycolithocholate (GLCA) and obesity, indicating a marginal negative causal association. Consistent direction of the estimates obtained from the weighted median and MR-Egger methods was observed in the analysis of the association between GLCA and obesity. Furthermore, the IVW analysis demonstrated a suggestive association between GLCA and trunk fat percentage, with a beta value of -0.014 (95% confidence interval: -0.027, -0.0004; P = .04). Our findings suggest a potential negative causal relationship between GLCA and both obesity and trunk fat percentage, although no association survived corrections for multiple comparisons. These results indicate a trend towards a possible association between BAs and obesity, emphasizing the need for future studies.

Assessing the associations of 1,400 blood metabolites with major depressive disorder: a Mendelian randomization study

Background and objectives

Major Depressive Disorder (MDD) is one of the most prevalent and debilitating health conditions worldwide. Previous studies have reported a link between metabolic dysregulation and MDD. However, evidence for a causal relationship between blood metabolites and MDD is lacking.

Methods

Using a two-sample bidirectional Mendelian randomization analysis (MR), we assessed the causal relationship between 1,400 serum metabolites and Major Depressive Disorder (MDD). The Inverse Variance Weighted method (IVW) was employed to estimate the causal association between exposures and outcomes. Additionally, MR-Egger regression, weighted median, simple mode, and weighted mode methods were used as supplementary approaches for a comprehensive appraisal of the causality between blood metabolites and MDD. Pleiotropy and heterogeneity tests were also conducted. Lastly, the relevant metabolites were subjected to metabolite function analysis, and a reverse MR was implemented to explore the potential influence of MDD on these metabolites.

Results

After rigorous screening, we identified 34 known metabolites, 13 unknown metabolites, and 18 metabolite ratios associated with Major Depressive Disorder (MDD). Among all metabolites, 33 were found to have positive associations, and 32 had negative associations. The top five metabolites that increased the risk of MDD were the Arachidonate (20:4n6) to linoleate (18:2n6) ratio, LysoPE(18:0/0:0), N-acetyl-beta-alanine levels, Arachidonate (20:4n6) to oleate to vaccenate (18:1) ratio, Glutaminylglutamine, and Threonine to pyruvate ratio. Conversely, the top five metabolites that decreased the risk of MDD were N6-Acetyl-L-lysine, Oleoyl-linoleoyl-glycerol (18:1 to 18:2) [2] to linoleoyl-arachidonoyl-glycerol (18:2 to 20:4) [2] ratio, Methionine to phosphate ratio, Pregnanediol 3-O-glucuronide, and 6-Oxopiperidine-2-carboxylic acid. Metabolite function enrichment was primarily concentrated in pathways such as Bile Acid Biosynthesis (FDR=0.177), Glutathione Metabolism (FDR=0.177), Threonine, and 2-Oxobutanoate Degradation (FDR=0.177). In addition, enrichment was noted in pathways like Valine, Leucine, and Isoleucine Biosynthesis (p=0.04), as well as Ascorbate and Aldarate Metabolism (p=0.04).

Discussion

Within a pool of 1,400 blood metabolites, we identified 34 known metabolites and 13 unknown metabolites, as well as 18 metabolite ratios associated with Major Depressive Disorder (MDD). Additionally, three functionally enriched groups and two metabolic pathways were selected. The integration of genomics and metabolomics has provided significant insights for the screening and prevention of MDD.

TGR5-mediated lateral hypothalamus-dCA3-dorsolateral septum circuit regulates depressive-like behavior in male mice

Although bile acids play a notable role in depression, the pathological significance of the bile acid TGR5 membrane-type receptor in this disorder remains elusive. Using depression models of chronic social defeat stress and chronic restraint stress in male mice, we found that TGR5 in the lateral hypothalamic area (LHA) predominantly decreased in GABAergic neurons, the excitability of which increased in depressive-like mice. Upregulation of TGR5 or inhibition of GABAergic excitability in LHA markedly alleviated depressive-like behavior, whereas down-regulation of TGR5 or enhancement of GABAergic excitability facilitated stress-induced depressive-like behavior. TGR5 also bidirectionally regulated excitability of LHA GABAergic neurons via extracellular regulated protein kinases-dependent Kv4.2 channels. Notably, LHA GABAergic neurons specifically innervated dorsal CA3 (dCA3) CaMKIIα neurons for mediation of depressive-like behavior. LHA GABAergic TGR5 exerted antidepressant-like effects by disinhibiting dCA3 CaMKIIα neurons projecting to the dorsolateral septum (DLS). These findings advance our understanding of TGR5 and the LHAGABA→dCA3CaMKIIα→DLSGABA circuit for the development of potential therapeutic strategies in depression.

Gut bacteria-driven homovanillic acid alleviates depression by modulating synaptic integrity

The gut-brain axis is implicated in depression development, yet its underlying mechanism remains unclear. We observed depleted gut bacterial species, including Bifidobacterium longum and Roseburia intestinalis, and the neurotransmitter homovanillic acid (HVA) in individuals with depression and mouse depression models. Although R. intestinalis does not directly produce HVA, it enhances B. longum abundance, leading to HVA generation. This highlights a synergistic interaction among gut microbiota in regulating intestinal neurotransmitter production. Administering HVA, B. longum, or R. intestinalis to mouse models with chronic unpredictable mild stress (CUMS) and corticosterone (CORT)-induced depression significantly improved depressive symptoms. Mechanistically, HVA inhibited synaptic autophagic death by preventing excessive degradation of microtubule-associated protein 1 light chain 3 (LC3) and SQSTM1/p62 proteins, protecting hippocampal neurons' presynaptic membrane. These findings underscore the role of the gut microbial metabolism in modulating synaptic integrity and provide insights into potential novel treatment strategies for depression.

Role of Inflammatory Mechanisms in Major Depressive Disorder: From Etiology to Potential Pharmacological Targets

The involvement of central and peripheral inflammation in the pathogenesis and prognosis of major depressive disorder (MDD) has been demonstrated. The increase of pro-inflammatory cytokines (interleukin (IL)-1β, IL-6, IL-18, and TNF-α) in individuals with depression may elicit neuroinflammatory processes and peripheral inflammation, mechanisms that, in turn, can contribute to gut microbiota dysbiosis. Together, neuroinflammation and gut dysbiosis induce alterations in tryptophan metabolism, culminating in decreased serotonin synthesis, impairments in neuroplasticity-related mechanisms, and glutamate-mediated excitotoxicity. This review aims to highlight the inflammatory mechanisms (neuroinflammation, peripheral inflammation, and gut dysbiosis) involved in the pathophysiology of MDD and to explore novel anti-inflammatory therapeutic approaches for this psychiatric disturbance. Several lines of evidence have indicated that in addition to antidepressants, physical exercise, probiotics, and nutraceuticals (agmatine, ascorbic acid, and vitamin D) possess anti-inflammatory effects that may contribute to their antidepressant properties. Further studies are necessary to explore the therapeutic benefits of these alternative therapies for MDD.

Confounder or Confederate? The Interactions Between Drugs and the Gut Microbiome in Psychiatric and Neurological Diseases

The gut microbiome is emerging as an important factor in signaling along the gut-brain axis. The intimate physiological connection between the gut and the brain allows perturbations in the microbiome to be directly transmitted to the central nervous system and thereby contribute to psychiatric and neurological diseases. Common microbiome perturbations result from the ingestion of xenobiotic compounds including pharmaceuticals such as psychotropic drugs. In recent years, a variety of interactions between these drug classes and the gut microbiome have been reported, ranging from direct inhibitory effects on gut bacteria to microbiome-mediated drug degradation or sequestration. Consequently, the microbiome may play a critical role in influencing the intensity, duration, and onset of therapeutic effects, as well as in influencing the side effects that patients may experience. Furthermore, because the composition of the microbiome varies from person to person, the microbiome may contribute to the frequently observed interpersonal differences in the response to these drugs. In this review, we first summarize the known interactions between xenobiotics and the gut microbiome. Then, for psychopharmaceuticals, we address the question of whether these interactions with gut bacteria are irrelevant for the host (i.e., merely confounding factors in metagenomic analyses) or whether they may even have therapeutic or adverse effects.

Untargeted Plasma Metabolomic Profiling in Patients with Depressive Disorders: A Preliminary Study

Depressive disorder is a multifactorial disease that is based on dysfunctions in mental and biological processes. The search for biomarkers can improve its diagnosis, personalize therapy, and lead to a deep understanding of the biochemical processes underlying depression. The purpose of this work was a metabolomic analysis of blood serum to classify patients with depressive disorders and healthy individuals using Compound Discoverer software. Using high-resolution mass spectrometry, blood plasma samples from 60 people were analyzed, of which 30 were included in a comparison group (healthy donors), and 30 were patients with a depressive episode (F32.11) and recurrent depressive disorder (F33.11). Differences between patient and control groups were identified using the built-in utilities in Compound Discoverer software. Compounds were identified by their accurate mass and fragment patterns using the mzCloud database and tentatively identified by their exact mass using the ChemSpider search engine and the KEGG, ChEBI, FDA UNII-NLM, Human Metabolome and LipidMAPS databases. We identified 18 metabolites that could divide patients with depressive disorders from healthy donors. Of these, only two compounds were tentatively identified using the mzCloud database (betaine and piperine) based on their fragmentation spectra. For three compounds ((4S,5S,8S,10R)-4,5,8-trihydroxy-10-methyl-3,4,5,8,9,10-hexahydro-2H-oxecin-2-one, (2E,4E)-N-(2-hydroxy-2-methylpropyl)-2,4-tetradecadienamide and 17α-methyl-androstan-3-hydroxyimine-17β-ol), matches were found in the mzCloud database but with low score, which could not serve as reliable evidence of their structure. Another 13 compounds were identified by their exact mass in the ChemSpider database, 9 (g-butyrobetaine, 6-diazonio-5-oxo-L-norleucine, 11-aminoundecanoic acid, methyl N-acetyl-2-diazonionorleucinate, glycyl-glycyl-argininal, dilaurylmethylamine, 12-ketodeoxycholic acid, dicetylamine, 1-linoleoyl-2-hydroxy-sn-glycero-3-PC) had only molecular formulas proposed, and 4 were unidentified. Thus, the use of Compound Discoverer software alone was not sufficient to identify all revealed metabolites. Nevertheless, the combination of the found metabolites made it possible to divide patients with depressive disorders from healthy donors.

Comparative profiling of gut microbiota and metabolome in diet-induced obese and insulin-resistant C57BL/6J mice

Diet-based models are commonly used to investigate obesity and related disorders. We conducted a comparative profiling of three obesogenic diets HFD, high fat diet; HFHF, high fat high fructose diet; and HFCD, high fat choline deficient diet to assess their impact on the gut microbiome and metabolome. After 20 weeks, we analyzed the gut microbiota and metabolomes of liver, plasma, cecal, and fecal samples. Fecal and plasma bile acids (BAs) and fecal short-chain fatty acids (SCFAs) were also examined. Significant changes were observed in fecal and cecal metabolites, with increased Firmicutes and decreased Bacteroidetes in the HFD, HFHF, and HFCD-fed mice compared to chow and LFD (low fat diet)-fed mice. Most BAs were reduced in plasma and fecal samples of obese groups, except taurocholic acid, which increased in HFCD mice's plasma. SCFAs like acetate and butyrate significantly decreased in obesogenic diet groups, while propionic acid specifically decreased in the HFCD group. Pathway analysis revealed significant alterations in amino acid, carbohydrate metabolism, and nucleic acid biosynthesis pathways in obese mice. Surprisingly, even LFD-fed mice showed distinct changes in microbiome and metabolite profiles compared to the chow group. This study provides insights into gut microbiome dysbiosis and metabolite alterations induced by obesogenic and LFD diets in various tissues. These findings aid in selecting suitable diet models to study the role of the gut microbiome and metabolites in obesity and associated disorders, with potential implications for understanding similar pathologies in humans.

Depression-associated gut microbes, metabolites and clinical trials

Depression is one of the most prevalent mental disorders today. Over the past decade, there has been considerable attention given to the field of gut microbiota associated with depression. A substantial body of research indicates a bidirectional communication pathway between gut microbiota and the brain. In this review, we extensively detail the correlation between gut microbiota, including Lactobacillus acidophilus and Bifidobacterium longum, and metabolites such as short-chain fatty acids (SCFAs) and 5-hydroxytryptamine (5-HT) concerning depression. Furthermore, we delve into the potential health benefits of microbiome-targeted therapies, encompassing probiotics, prebiotics, and synbiotics, in alleviating depression. Lastly, we underscore the importance of employing a constraint-based modeling framework in the era of systems medicine to contextualize metabolomic measurements and integrate multi-omics data. This approach can offer valuable insights into the complex metabolic host-microbiota interactions, enabling personalized recommendations for potential biomarkers, novel drugs, and treatments for depression.

Lipids in Psychiatric Disorders: Functional and Potential Diagnostic Role as Blood Biomarkers

Lipids are a crucial component of the human brain, serving important structural and functional roles. They are involved in cell function, myelination of neuronal projections, neurotransmission, neural plasticity, energy metabolism, and neuroinflammation. Despite their significance, the role of lipids in the development of mental disorders has not been well understood. This review focused on the potential use of lipids as blood biomarkers for common mental illnesses, such as major depressive disorder, anxiety disorders, bipolar disorder, and schizophrenia. This review also discussed the impact of commonly used psychiatric medications, such as neuroleptics and antidepressants, on lipid metabolism. The obtained data suggested that lipid biomarkers could be useful for diagnosing psychiatric diseases, but further research is needed to better understand the associations between blood lipids and mental disorders and to identify specific biomarker combinations for each disease.

Alterations in gut microbiota caused by major depressive disorder or a low FODMAP diet and where they overlap

Beneficial changes in microbiota observed in individuals with a major depressive disorder (MDD) may be initiated with a low fermentable oligosaccharide, disaccharide, monosaccharide, and polyol (FODMAP) elimination diet. Academic Search Ultimate, APA PsychINFO, Cochrane Library, MEDLINE, Scopus and Web of Science were searched for original research documenting differences in microbiota in MDD or changes with a low FODMAP diet in adults (age 18 years +). Studies with fecal microbiota, 16 s RNA sequencing and QIIME pipelines were included. Studies using antibiotics, probiotics, and medications such as antidepressants were excluded. Additionally, studies based on a single gender were excluded as gender impacts microbiota changes in MDD. Four studies addressed differences in microbiota with MDD and another four assessed shifts occurring with a low FODMAP diet. The abundance of Bacteroidetes, Bacteroidaceae and Bacteroides were lower in individuals with MDD but increased with a low FODMAP diet. Abundance of Ruminoccaceae was lower and Bilophila was higher with both a low FODMAP diet and MDD. These results provide preliminary evidence that a low FODMAP diet might drive changes in microbiota that also benefit people with MDD. Further research to assess whether a low FODMAP diet can treat MDD through modification of targeted microbiota is warranted.

TGR5 deficiency-induced anxiety and depression-like behaviors: The role of gut microbiota dysbiosis

BACKGROUND AND PURPOSE

Anxiety and depression have been associated with imbalances in the gut microbiota and bile acid metabolism. Takeda G protein-coupled receptor 5 (TGR5), a bile acid receptor involved in metabolism, is influenced by the gut microbiota. This study aimed to investigate the relationship between anxiety, depression, and microbiota using TGR5 knockout mice.

METHODS

We employed the following methods: (1) Assessment of behavioral changes, (2) Measurement of 5-HT levels and protein expression, (3) Analysis of stool samples, (4) Utilization of gene sequencing and statistical analysis to identify microbial signatures, (5) Examination of correlations between microbial signatures and 5-HT levels, and (6) Fecal microbiota transplantation experiments of TGR5-/- mice.

RESULTS

The deletion of TGR5 was found to result in increased anxiety- and depression-like behaviors in mice. TGR5 knockout mice exhibited significant reductions in 5-hydroxytryptamine (5-HT) levels in both serum and hippocampus, accompanied by a decrease in the expression of 5-HT1A receptor in the hippocampus. Moreover, TGR5 deficiency was associated with a decrease in the species richness of the gut microbiota. Specifically, the gut microbiota compositions of TGR5 knockout mice displayed distinct differences compared to their littermates, characterized by higher abundances of Anaeroplasma, Prevotella, Staphylococcus, Jeotgalicoccus, and Helicobacter, and a lower abundance of Bifidobacterium. Notably, a strong association between Jeotgalicoccus as well as Staphylococcus and serum 5-HT levels was observed in co-occurrence network. Furthermore, mice that received fecal microbiota transplants from TGR5-/- mice displayed anxiety and depression -like behaviors, accompanied by alterations in 5-HT levels in the hippocampus and serum.

LIMITATIONS

Study limitations for gut bacteria were analyzed at the genus level only.

CONCLUSION

TGR5 deletion in mice induces anxiety and depression-like behaviors, linked to reduced 5-HT levels in serum and the hippocampus. Gut microbiota changes play a direct role in these behaviors and serotonin alterations. This implicates TGR5 and gut bacteria in mood regulation, with potential therapeutic implications.

Stress in the microbiome-immune crosstalk

The gut microbiota exerts a mutualistic interaction with the host in a fragile ecosystem and the host intestinal, neural, and immune cells. Perturbations of the gastrointestinal track composition after stress have profound consequences on the central nervous system and the immune system. Reciprocally, brain signals after stress affect the gut microbiota highlighting the bidirectional communication between the brain and the gut. Here, we focus on the potential role of inflammation in mediating stress-induced gut-brain changes and discuss the impact of several immune cells and inflammatory molecules of the gut-brain dialogue after stress. Understanding the impact of microbial changes on the immune system after stress might provide new avenues for therapy.

A Pilot Interaction Analysis of Gut Microbiota and Peripheral Markers of Aging in Severe Psychiatric Disorders: A Role for Lachnoclostridium?

Excessive predominance of pathological species in the gut microbiota could increase the production of inflammatory mediators at the gut level and, via modification of the gut-blood barrier, at the systemic level. This pro-inflammatory state could, in turn, increase biological aging that is generally proxied by telomere shortening. In this study, we present findings from a secondary interaction analysis of gut microbiota, aging, and inflammatory marker data from a cohort of patients with different diagnoses of severe mental disorders. We analyzed 15 controls, 35 patients with schizophrenia (SCZ), and 31 patients with major depressive disorder (MDD) recruited among those attending a community mental health center (50 males and 31 females, mean and median age 46.8 and 46.3 years, respectively). We performed 16S rRNA sequencing as well as measurement of telomere length via quantitative fluorescence in situ hybridization and high-sensitivity C-reactive protein. We applied statistical modeling with logistic regression to test for interaction between gut microbiota and these markers. Our results showed statistically significant interactions between telomere length and gut microbiota pointing to the genus Lachnostridium, which remained significantly associated with a reduced likelihood of MDD even after adjustment for a series of covariates. Although exploratory, these findings show that specific gut microbiota signatures overexpressing Lachnoclostridium and interacting with biological aging could modulate the liability for MDD.

Gut microbiota composition in depressive disorder: a systematic review, meta-analysis, and meta-regression

Studies investigating gut microbiota composition in depressive disorder have yielded mixed results. The aim of our study was to compare gut microbiome between people with depressive disorder and healthy controls. We did a meta-analysis and meta-regression of studies by searching PubMed, Web of Science, Embase, Scopus, Ovid, Cochrane Library, ProQuest, and PsycINFO for articles published from database inception to March 07, 2022. Search strategies were then re-run on 12 March 2023 for an update. We undertook meta-analyses whenever values of alpha diversity and Firmicutes, Bacteroidetes (relative abundance) were available in two or more studies. A random-effects model with restricted maximum-likelihood estimator was used to synthesize the effect size (assessed by standardized mean difference [SMD]) across studies. We identified 44 studies representing 2091 patients and 2792 controls. Our study found that there were no significant differences in patients with depressive disorder on alpha diversity indices, Firmicutes and Bacteroidetes compared with healthy controls. In subgroup analyses with regional variations(east/west) as a predictor, patients who were in the West had a lower Chao1 level (SMD -0.42[-0.74 to -0.10]). Subgroup meta-analysis showed Firmicutes level was decreased in patients with depressive disorder who were medication-free (SMD -1.54[-2.36 to -0.72]), but Bacteroidetes level was increased (SMD -0.90[0.07 to 1.72]). In the meta-regression analysis, six variables cannot explain the 100% heterogeneity of the studies assessing by Chao1, Shannon index, Firmicutes, and Bacteroidetes. Depleted levels of Butyricicoccus, Coprococcus, Faecalibacterium, Fusicatenibacter, Romboutsia, and enriched levels of Eggerthella, Enterococcus, Flavonifractor, Holdemania, Streptococcus were consistently shared in depressive disorder. This systematic review and meta-analysis found that psychotropic medication and dietary habit may influence microbiota. There is reliable evidence for differences in the phylogenetic relationship in depressive disorder compared with controls, however, method of measurement and method of patient classification (symptom vs diagnosis based) may affect findings. Depressive disorder is characterized by an increase of pro-inflammatory bacteria, while anti-inflammatory butyrate-producing genera are depleted.

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.

Ginkgo biloba extract protects against depression-like behavior in mice through regulating gut microbial bile acid metabolism

Depression is a mental disorder with high morbidity, disability and relapse rates. Ginkgo biloba extract (GBE), a traditional Chinese medicine, has a long history of clinical application in the treatment of cerebral and mental disorders, but the key mechanism remains incompletely understood. Here we showed that GEB exerted anti-depressant effect in mice through regulating gut microbial metabolism. GBE protected against unpredictable mild stress (UMS)-induced despair, anxiety-like and social avoidance behavior in mice without sufficient brain distribution. Fecal microbiome transplantation transmitted, while antibiotic cocktail abrogated the protective effect of GBE. Spatiotemporal bacterial profiling and metabolomics assay revealed a potential involvement of Parasutterella excrementihominis and the bile acid metabolite ursodeoxycholic acid (UDCA) in the effect of GBE. UDCA administration induced depression-like behavior in mice. Together, these findings suggest that GBE acts on gut microbiome-modulated bile acid metabolism to alleviate stress-induced depression.

Liver function test indices-based prediction model for post-stroke depression: a multicenter, retrospective study

BACKGROUND

Post-stroke depression (PSD) was one of the most prevalent and serious neuropsychiatric effects after stroke. Nevertheless, the association between liver function test indices and PSD remains elusive, and there is a lack of effective prediction tools. The purpose of this study was to explore the relationship between the liver function test indices and PSD, and construct a prediction model for PSD.

METHODS

All patients were selected from seven medical institutions of Chongqing Medical University from 2015 to 2021. Variables including demographic characteristics and liver function test indices were collected from the hospital electronic medical record system. Univariate analysis, least absolute shrinkage and selection operator (LASSO) and logistic regression analysis were used to screen the predictors. Subsequently, logistic regression, random forest (RF), extreme gradient boosting (XGBoost), gradient boosting decision tree (GBDT), categorical boosting (CatBoost) and support vector machine (SVM) were adopted to build the prediction model. Furthermore, a series of evaluation indicators such as area under curve (AUC), sensitivity, specificity, F1 were used to assess the performance of the prediction model.

RESULTS

A total of 464 PSD and 1621 stroke patients met the inclusion criteria. Six liver function test items, namely AST, ALT, TBA, TBil, TP, ALB/GLB, were closely associated with PSD, and included for the construction of the prediction model. In the test set, logistic regression model owns the AUC of 0.697. Compared with the other four machine learning models, the GBDT model has the best predictive performance (F1 = 0.498, AUC = 0.761) and was chosen to establish the prediction tool.

CONCLUSIONS

The prediction model constructed using these six predictors with GBDT algorithm displayed a promising prediction ability, which could be used for the participating hospital units or individuals by mobile phone or computer.

The Brain-Gut-Microbiota Interplay in Depression: a key to design innovative therapeutic approaches

Depression is the most prevalent mental disorder in the world associated with huge socio-economic consequences. While depressive-related symptoms are well known, the molecular mechanisms underlying disease pathophysiology and progression remain largely unknown. The gut microbiota (GM) is emerging as a key regulator of the central nervous system homeostasis by exerting fundamental immune and metabolic functions. In turn, the brain influences the intestinal microbial composition through neuroendocrine signals, within the so-called gut microbiota-brain axis. The balance of this bidirectional crosstalk is important to ensure neurogenesis, preserve the integrity of the blood-brain barrier and avoid neuroinflammation. Conversely, dysbiosis and gut permeability negatively affect brain development, behavior, and cognition. Furthermore, although not fully defined yet, changes in the GM composition in depressed patients are reported to influence the pharmacokinetics of common antidepressants by affecting their absorption, metabolism, and activity. Similarly, neuropsychiatric drugs may shape in turn the GM with an impact on the efficacy and toxicity of the pharmacological intervention itself. Consequently, strategies aimed at re-establishing the correct homeostatic gut balance (i.e., prebiotics, probiotics, fecal microbiota transplantation, and dietary interventions) represent an innovative approach to improve the pharmacotherapy of depression. Among these, probiotics and the Mediterranean diet, alone or in combination with the standard of care, hold promise for clinical application. Therefore, the disclosure of the intricate network between GM and depression will give precious insights for innovative diagnostic and therapeutic approaches towards depression, with profound implications for drug development and clinical practice.

Probiotics and Commensal Bacteria Metabolites Trigger Epigenetic Changes in the Gut and Influence Beneficial Mood Dispositions

The effect of the intestinal microbiome on the gut-brain axis has received considerable attention, strengthening the evidence that intestinal bacteria influence emotions and behavior. The colonic microbiome is important to health and the pattern of composition and concentration varies extensively in complexity from birth to adulthood. That is, host genetics and environmental factors are complicit in shaping the development of the intestinal microbiome to achieve immunological tolerance and metabolic homeostasis from birth. Given that the intestinal microbiome perseveres to maintain gut homeostasis throughout the life cycle, epigenetic actions may determine the effect on the gut-brain axis and the beneficial outcomes on mood. Probiotics are postulated to exhibit a range of positive health benefits including immunomodulating capabilities. Lactobacillus and Bifidobacterium are genera of bacteria found in the intestines and so far, the benefits afforded by ingesting bacteria such as these as probiotics to people with mood disorders have varied in efficacy. Most likely, the efficacy of probiotic bacteria at improving mood has a multifactorial dependency, relying namely on several factors that include the agents used, the dose, the pattern of dosing, the pharmacotherapy used, the characteristics of the host and the underlying luminal microbial environment (e.g., gut dysbiosis). Clarifying the pathways linking probiotics with improvements in mood may help identify the factors that efficacy is dependent upon. Adjunctive therapies with probiotics for mood disorders could, through DNA methylation molecular mechanisms, augment the intestinal microbial active cohort and endow its mammalian host with important and critical co-evolutionary redox signaling metabolic interactions, that are embedded in bacterial genomes, and that in turn can enhance beneficial mood dispositions.

Effects of ultrasound-induced stress on gut microbiota of mice

Background and Aim

Prolonged stress causes deleterious effects on both the organism and its microbiota. In this study, we examined the effects of exposure to variable frequency ultrasound (US) on the gut microbiota-liver-brain axis of mice.

Materials and Methods

This study was conducted on 20 mature clinically healthy sexually naive C57BL/6J male mice (42-45 days old). Group 1 (Normal) consisted of healthy intact mice (n = 10). Group 2 (Stress) consisted of mice subjected to US-induced stress (n = 10) for 20 days with alternating frequencies (20-45 kHz). Stool samples were collected on days 0, 10, and 20, and the corresponding DNA was later subjected to 16SrRNA sequencing. After mice were sacrificed on day 21, the leukocyte count, blood serum biochemical parameters, and liver and brain antioxidant status were measured. Behavioral testing was performed on days 17, 18, and 19.

Results

Ultrasound lead to higher stress and anxiety levels; increase in creatinine by 8.29% and gamma-glutamyltransferase activity by 5 times, a decrease in alkaline phosphatase activity by 38.23%, increase of de Ritis coefficient by 21.34%; increased liver and brain superoxide dismutase level by 20.8% and 21.5%, respectively; the stress-related changes in the gut microbiota composition - Bacteroidaceae and Firmicutes.

Conclusion

Subjecting mice to 20 days of US-induced stress leads to systemic disorders due to oxidative stress and a decrease in the diversity of the gut microbiota.

Exploration of the Gut Microbiome in Thai Patients with Major Depressive Disorder Shows a Specific Bacterial Profile with Depletion of the Ruminococcus Genus as a Putative Biomarker

Maes et al. (2008) published the first paper demonstrating that major depressive disorder (MDD) is accompanied by abnormalities in the microbiota-gut-brain axis, as evidenced by elevated serum IgM/IgA to lipopolysaccharides (LPS) of Gram-negative bacteria, such as Morganella morganii and Klebsiella Pneumoniae. The latter aberrations, which point to increased gut permeability (leaky gut), are linked to activated neuro-immune and oxidative pathways in MDD. To delineate the profile and composition of the gut microbiome in Thai patients with MDD, we examined fecal samples of 32 MDD patients and 37 controls using 16S rDNA sequencing, analyzed α- (Chao1 and Shannon indices) and β-diversity (Bray-Curtis dissimilarity), and conducted linear discriminant analysis (LDA) effect size (LEfSe) analysis. Neither α- nor β-diversity differed significantly between MDD and controls. Rhodospirillaceae, Hungatella, Clostridium bolteae, Hungatella hathewayi, and Clostridium propionicum were significantly enriched in MDD, while Gracillibacteraceae family, Lutispora, and Ruminococcus genus, Ruminococcus callidus, Desulfovibrio piger, Coprococcus comes, and Gemmiger were enriched in controls. Contradictory results have been reported for all these taxa, with the exception of Ruminococcus, which is depleted in six different MDD studies (one study showed increased abundance), many medical disorders that show comorbidities with MDD, and animal MDD models. Our results may suggest a specific profile of compositional gut dysbiosis in Thai MDD patients, with increases in some pathobionts and depletion of some beneficial microbiota. The results suggest that depletion of Ruminococcus may be a more universal biomarker of MDD that may contribute to increased enteral LPS load, LPS translocation, and gut-brain axis abnormalities.

Gut microbiota and its metabolites in depression: from pathogenesis to treatment

Major depressive disorder is one of the most disabling mental disorders worldwide. Increasing preclinical and clinical studies have highlighted that compositional and functional (e.g., metabolite) changes in gut microbiota, known as dysbiosis, are associated with the onset and progression of depression via regulating the gut-brain axis. However, the gut microbiota and their metabolites present a double-edged sword in depression. Dysbiosis is involved in the pathogenesis of depression while, at the same time, offering a novel therapeutic target. In this review, we describe the association between dysbiosis and depression, drug-microbiota interactions in antidepressant treatment, and the potential health benefits of microbial-targeted therapeutics in depression, including dietary interventions, fecal microbiota transplantation, probiotics, prebiotics, synbiotics, and postbiotics. With the emergence of microbial research, we describe a new direction for future research and clinical treatment of depression.

Impact of nonalcoholic fatty liver disease-related metabolic state on depression

Nonalcoholic fatty liver disease (NAFLD), also recently referred as metabolic (dysfunction)-associated fatty liver disease (MAFLD), is characterized by hepatocyte steatosis in the setting of metabolic risk conditions and in the absence of an underlying precursor, for instance alcohol consumption, hepatotropic viruses and hepatotoxic drugs. A possible association between NAFLD and depression has been proposed, owing to intersecting pathophysiological pathways. This narrative review aimed to summarize the current evidence that illustrate the potential pathophysiological and clinical linkage between NAFLD-related metabolic state and depression. Prefrontal cortex lesions are suggested to be a consequence of liver steatosis-associated systematic hyperinflammatory state, a phenomenon also occurring in depression. In addition, depressive symptoms are present in neurotransmitter imbalances. These abnormalities seem to be correlated with NAFLD/MAFLD, in terms of insulin resistance (IR), ammonia and gut dysbiosis' impact on serotonin, dopamine, noradrenaline levels and gamma aminobutyric acid receptors. Furthermore, reduced levels of nesfatin-1 and copine-6-associated BDNF (brain-derived neurotrophic factor) levels have been considered as a probable link between NAFLD and depression. Regarding NAFLD-related gut dysbiosis, it stimulates mediators including lipopolysaccharides, short-chain fatty acids and bile acids, which play significant role in depression. Finally, western diet and IR, which are mainstay components of NAFLD/MAFLD, are, also, substantiated to affect neurotransmitters in hippocampus and produce neurotoxic lipids that contribute to neurologic dysfunction, and thus trigger emotional disturbances, mainly depressive symptoms.