A pilot exploration of multi-omics research of gut microbiome in major depressive disorders

Relationships between the gut microbiome and brain functional alterations in first-episode, drug-naïve patients with major depressive disorder

OBJECTIVE

Increasing evidence has shown that the microbiota-gut-brain axis (MGB) is involved in the mechanism of major depressive disorder (MDD). However, the relationship between the gut microbiome and brain function in MDD patients has not been determined. Here, we intend to identify specific changes in the gut microbiome and brain function in first-episode, drug-naïve MDD patients and then explore the associations between the two omics to elucidate how the MGB axis plays a role in MDD development.

METHODS

We recruited 38 first-episode, drug-naïve MDD patients and 37 healthy controls (HC). The composition of the fecal microbiome and neural spontaneous activity alterations were examined using 16S rRNA gene amplicon sequencing analysis and regional homogeneity (ReHo). Spearman correlation analyses were conducted to assess the associations between the gut microbiome and brain function.

RESULTS

Compared with HC, MDD patients exhibited distinct alterations in the gut microbiota and elevated ReHo in the frontal regions. In the MDD group, a positive relationship was noted between the relative abundance of Blautia and the HAMD-17 and HAMA scores, as well as between the relative abundance of Oxalobacteraceae and the HAMD-17 score. The relative abundances of Porphyromonadaceae and Parabacteroides were negatively correlated with the ReHo values of frontal regions.

LIMITATIONS

Our study utilized a cross-sectional design, and the number of subjects was relatively small.

CONCLUSION

We found that some specific gut microbiomes were associated with frontal function, and others were associated with clinical symptoms in MDD patients, which may support the role of the MGB axis underlying MDD.

Vitamin-mediated interaction between the gut microbiome and mitochondria in depression: A systematic review-based integrated perspective

Depression is one of the world's most prevalent mental disorders and its treatment remains suboptimal. Depression is a systemic disease with highly complex biological mechanisms. Emerging evidence points towards the involvement of mitochondria, microbiome and vitamins in its pathophysiology. Mitochondrial energy production was shown to be lowered in patients with depression. Mitochondrial energy production depends on vitamins, which are available from food, but are also synthesized by the gut microbiota. Several studies reported altered vitamin levels as well as changes in the gut microbiome composition and its vitamin metabolism in patients with depression. Therefore, the question of a connection between mitochondria and gut microbiome and vitamins influencing the mental health arises. This review aims to systematically investigate a combination of the topics - depression, mitochondria, microbiome, and vitamins - to generate an overview of a novel yet extremely complex and interconnected research field. A systematic literature search yielded 34 articles, and the results were summarized and bundled to develop this new integrative perspective on mitochondrial function mediated by the microbiome and microbiome-derived vitamins in depression. Furthermore, by discussing the research gaps this review aims to encourage innovative research approaches to better understand the biology of depression, which could result in optimized therapeutic approaches.

Dynamic Human Gut Microbiome and Immune Shifts During an Immersive Psychosocial Therapeutic Program

Background

Depression is a leading cause of disability worldwide yet its underlying factors, particularly microbial associations, are poorly understood.

Methods

We examined the longitudinal interplay between the microbiome and immune system in the context of depression during an immersive psychosocial intervention. 142 multi-omics samples were collected from 52 well-characterized participants before, during, and three months after a nine-day inquiry-based stress reduction program.

Results

We found that depression was associated with both an increased presence of putatively pathogenic bacteria and reduced microbial beta-diversity. Following the intervention, we observed reductions in neuroinflammatory cytokines and improvements in several mental health indicators. Interestingly, participants with a Prevotella -dominant microbiome showed milder symptoms when depressed, along with a more resilient microbiome and more favorable inflammatory cytokine profile, including reduced levels of CXCL-1.

Conclusions

Our findings reveal a protective link between the Prevotella-dominant microbiome and depression, associated with a less inflammatory environment and moderated symptoms. These insights, coupled with observed improvements in neuroinflammatory markers and mental health from the intervention, highlight potential avenues for microbiome-targeted therapies in depression management.

Omics approaches open new horizons in major depressive disorder: from biomarkers to precision medicine

Major depressive disorder (MDD) is a recurrent episodic mood disorder that represents the third leading cause of disability worldwide. In MDD, several factors can simultaneously contribute to its development, which complicates its diagnosis. According to practical guidelines, antidepressants are the first-line treatment for moderate to severe major depressive episodes. Traditional treatment strategies often follow a one-size-fits-all approach, resulting in suboptimal outcomes for many patients who fail to experience a response or recovery and develop the so-called "therapy-resistant depression". The high biological and clinical inter-variability within patients and the lack of robust biomarkers hinder the finding of specific therapeutic targets, contributing to the high treatment failure rates. In this frame, precision medicine, a paradigm that tailors medical interventions to individual characteristics, would help allocate the most adequate and effective treatment for each patient while minimizing its side effects. In particular, multi-omic studies may unveil the intricate interplays between genetic predispositions and exposure to environmental factors through the study of epigenomics, transcriptomics, proteomics, metabolomics, gut microbiomics, and immunomics. The integration of the flow of multi-omic information into molecular pathways may produce better outcomes than the current psychopharmacological approach, which targets singular molecular factors mainly related to the monoamine systems, disregarding the complex network of our organism. The concept of system biomedicine involves the integration and analysis of enormous datasets generated with different technologies, creating a "patient fingerprint", which defines the underlying biological mechanisms of every patient. This review, centered on precision medicine, explores the integration of multi-omic approaches as clinical tools for prediction in MDD at a single-patient level. It investigates how combining the existing technologies used for diagnostic, stratification, prognostic, and treatment-response biomarkers discovery with artificial intelligence can improve the assessment and treatment of MDD.

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.

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.

Potential effects of the most prescribed drugs on the microbiota-gut-brain-axis: A review

The link between drug-induced dysbiosis and its influence on brain diseases through gut-residing bacteria and their metabolites, named the microbiota-gut-brain axis (MGBA), remains largely unexplored. This review investigates the effects of commonly prescribed drugs (metformin, statins, proton-pump-inhibitors, NSAIDs, and anti-depressants) on the gut microbiota, comparing the findings with altered bacterial populations in major brain diseases (depression, multiple sclerosis, Parkinson's and Alzheimer's). The report aims to explore whether drugs can influence the development and progression of brain diseases via the MGBA. Central findings indicate that all explored drugs induce dysbiosis. These dysbiosis patterns were associated with brain disorders. The influence on brain diseases varied across different bacterial taxa, possibly mediated by direct effects or through bacterial metabolites. Each drug induced both positive and negative changes in the abundance of bacteria, indicating a counterbalancing effect. Moreover, the above-mentioned drugs exhibited similar effects, suggesting that they may counteract or enhance each other's effects on brain diseases when taken together by comorbid patients. In conclusion, the interplay of bacterial species and their abundances may have a greater impact on brain diseases than individual drugs or bacterial strains. Future research is needed to better understand drug-induced dysbiosis and the implications for brain disease pathogenesis, with the potential to develop more effective therapeutic options for patients with brain-related diseases.

Oral D-ribose causes depressive-like behavior by altering glycerophospholipid metabolism via the gut-brain axis

Our previous work has shown that D-ribose (RIB)-induced depressive-like behaviors in mice. However, the relationship between variations in RIB levels and depression as well as potential RIB participation in depressive disorder is yet unknown. Here, a reanalysis of metabonomics data from depressed patients and depression model rats is performed to clarify whether the increased RIB level is positively correlated with the severity of depression. Moreover, we characterize intestinal epithelial barrier damage, gut microbial composition and function, and microbiota-gut-brain metabolic signatures in RIB-fed mice using colonic histomorphology, 16 S rRNA gene sequencing, and untargeted metabolomics analysis. The results show that RIB caused intestinal epithelial barrier impairment and microbiota-gut-brain axis dysbiosis. These microbial and metabolic modules are consistently enriched in peripheral (fecal, colon wall, and serum) and central (hippocampus) glycerophospholipid metabolism. In addition, three differential genera (Lachnospiraceae_UCG-006, Turicibacter, and Akkermansia) and two types of glycerophospholipids (phosphatidylcholine and phosphatidylethanolamine) have greater contributions to the overall correlations between differential genera and glycerophospholipids. These findings suggest that the disturbances of gut microbiota by RIB may contribute to the onset of depressive-like behaviors via regulating glycerophospholipid metabolism, and providing new insight for understanding the function of microbiota-gut-brain axis in depression.

Multi-omic approaches for host-microbiome data integration

The gut microbiome interacts with the host through complex networks that affect physiology and health outcomes. It is becoming clear that these interactions can be measured across many different omics layers, including the genome, transcriptome, epigenome, metabolome, and proteome, among others. Multi-omic studies of the microbiome can provide insight into the mechanisms underlying host-microbe interactions. As more omics layers are considered, increasingly sophisticated statistical methods are required to integrate them. In this review, we provide an overview of approaches currently used to characterize multi-omic interactions between host and microbiome data. While a large number of studies have generated a deeper understanding of host-microbiome interactions, there is still a need for standardization across approaches. Furthermore, microbiome studies would also benefit from the collection and curation of large, publicly available multi-omics datasets.

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.

Adverse childhood experiences and reoccurrence of illness impact the gut microbiome, which affects suicidal behaviours and the phenome of major depression: towards enterotypic phenotypes

The first publication demonstrating that major depressive disorder (MDD) is associated with alterations in the gut microbiota appeared in 2008 (Maes et al., 2008). The purpose of the present study is to delineate a) the microbiome signature of the phenome of depression, including suicidal behaviours (SB) and cognitive deficits; the effects of adverse childhood experiences (ACEs) and recurrence of illness index (ROI) on the microbiome; and the microbiome signature of lowered high-density lipoprotein cholesterol (HDLc). We determined isometric log-ratio abundances or prevalences of gut microbiome phyla, genera, and species by analysing stool samples from 37 healthy Thai controls and 32 MDD patients using 16S rDNA sequencing. Six microbiome taxa accounted for 36% of the variance in the depression phenome, namely Hungatella and Fusicatenibacter (positive associations) and Butyricicoccus, Clostridium, Parabacteroides merdae, and Desulfovibrio piger (inverse association). This profile (labelled enterotype 1) indicates compositional dysbiosis, is strongly predicted by ACE and ROI, and is linked to SB. A second enterotype was developed that predicted a decrease in HDLc and an increase in the atherogenic index of plasma (Bifidobacterium, P. merdae, and Romboutsia were positively associated, while Proteobacteria and Clostridium sensu stricto were negatively associated). Together, enterotypes 1 and 2 explained 40.4% of the variance in the depression phenome, and enterotype 1 in conjunction with HDLc explained 39.9% of the variance in current SB. In conclusion, the microimmuneoxysome is a potential new drug target for the treatment of severe depression and SB and possibly for the prevention of future episodes.

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.

The putatively high-altitude adaptation of macaque monkeys: Evidence from the fecal metabolome and gut microbiome

Animals living in high-altitude environments, such as the Tibetan Plateau, must face harsh environmental conditions (e.g., hypoxia, cold, and strong UV radiation). These animals' physiological adaptations (e.g., increased red cell production and turnover rate) might also be associated with the gut microbial response. Bilirubin is a component of red blood cell turnover or destruction and is excreted into the intestine and reduced to urobilinoids and/or urobilinogen by gut bacteria. Here, we found that the feces of macaques living in high-altitude regions look significantly browner (with a high concentration of stercobilin, a component from urobilinoids) than those living in low-altitude regions. We also found that gut microbes involved in urobilinogen reduction (e.g., beta-glucuronidase) were enriched in the high-altitude mammal population compared to the low-altitude population. Moreover, the spatial-temporal change in gut microbial function was more profound in the low-altitude macaques than in the high-altitude population, which might be attributed to profound changes in food resources in the low-altitude regions. Therefore, we conclude that a high-altitude environment's stress influences living animals and their symbiotic microbiota.

From-Toilet-to-Freezer: A Review on Requirements for an Automatic Protocol to Collect and Store Human Fecal Samples for Research Purposes

The composition, viability and metabolic functionality of intestinal microbiota play an important role in human health and disease. Studies on intestinal microbiota are often based on fecal samples, because these can be sampled in a non-invasive way, although procedures for sampling, processing and storage vary. This review presents factors to consider when developing an automated protocol for sampling, processing and storing fecal samples: donor inclusion criteria, urine-feces separation in smart toilets, homogenization, aliquoting, usage or type of buffer to dissolve and store fecal material, temperature and time for processing and storage and quality control. The lack of standardization and low-throughput of state-of-the-art fecal collection procedures promote a more automated protocol. Based on this review, an automated protocol is proposed. Fecal samples should be collected and immediately processed under anaerobic conditions at either room temperature (RT) for a maximum of 4 h or at 4 °C for no more than 24 h. Upon homogenization, preferably in the absence of added solvent to allow addition of a buffer of choice at a later stage, aliquots obtained should be stored at either -20 °C for up to a few months or -80 °C for a longer period-up to 2 years. Protocols for quality control should characterize microbial composition and viability as well as metabolic functionality.

Fructo-oligofructose ameliorates 2,4-dinitrofluorobenzene-induced atopic dermatitis-like skin lesions and psychiatric comorbidities in mice

BACKGROUND

Atopic dermatitis (AD) is a chronic inflammatory skin disorder characterized by pruritus and eczema lesions and psychiatric comorbidities. The gut-brain-skin axis plays a pivotal role during AD development, which might suggest a novel therapeutic strategy for AD. The present study aims to uncover the protective effects and underlying mechanisms of fructo-oligofructose (FOS), a type of prebiotic, on AD-like skin manifestations and comorbid anxiety and depression in AD mice.

RESULTS

Female Kunming mice were treated topically with 2,4-dinitrofluorobenzene (DNFB) to induce AD-like symptoms and FOS was administered daily for 14 days. The results showed that FOS could alleviate AD-like skin lesions markedly as evidenced by dramatic decreases in severity score, scratching bouts, the levels of immunoglobulin E (IgE) and T helper 1(Th1)/Th2-related cytokines, and the infiltration of inflammatory cells and mast cells to the dermal tissues. The comorbid anxiety and depressive-like behaviors, estimated by the forced swimming test (FST), the tail-suspension test (TST), the open-field test (OFT), and the zero maze test (ZMT) in AD mice, were significantly attenuated by FOS. Fructo-oligofructose significantly upregulated brain neurotransmitters levels of 5-hydroxytryptamine (5-HT) and dopamine (DA). Furthermore, FOS treatment increased the relative abundance of gut microbiota, such as Prevotella and Lactobacillus and the concentrations of short-chain fatty acids (SCFAs), especially acetate and iso-butyrate in the feces of AD mice. The correlation analysis indicated that the reshaped gut microbiome composition and enhanced SCFAs formation are associated with skin inflammation and behavioral alteration.

CONCLUSION

Collectively, these data identify FOS as a promising microbiota-targeted treatment for AD-like skin inflammation and comorbid anxiety and depressive-like behaviors. © 2023 Society of Chemical Industry.

Young adults with major depression show altered microbiome

There is growing basic and clinical evidence that major depressive disorder (MDD) is associated with gut microbiome alterations, but clinical studies have tended not to adjust for confounding factors. And few studies on the gut microbiome focused on young adults with MDD. Here we performed a pilot study to compare the gut microbiome of young adults with MDD with healthy controls. Shotgun metagenomic sequencing was performed on stool samples obtained from 40 young adults with MDD and 42 healthy controls. After controlling for confounding factors including sex, age, BMI, alcohol or cigarette consumption, bowel movement quality, exercise or defecation frequency, we compared microbiome diversity between groups, identified differentially abundant taxa, and further compared functional differences through gut-brain and gut-metabolic module analysis. There were no significant differences in overall gut microbiome structure and function in young adults with MDD compared with controls. Abundance of Sutterellaceae and species belonging to Clostridium, Eubacterium, and Ruminococcus were significantly different between groups. The cysteine degradation I pathway was increased in MDD. After controlling for most confounding factors, this pilot study provides new evidence on the specific, often subtle gut dysbiosis affecting young adults with depression.

Stress, inflammation, microbiome and depression

Psychiatric disorders are mental illnesses involving changes in mood, cognition and behavior. Their prevalence has rapidly increased in the last decades. One of the most prevalent psychiatric disorders is major depressive disorder (MDD), a debilitating disease lacking efficient treatments. Increasing evidence shows that microbial and immunological changes contribute to the pathophysiology of depression and both are modulated by stress. This bidirectional relationship constitutes the brain-gut axis involving various neuroendocrine, immunological, neuroenterocrine and autonomic pathways. The present review covers the most recent findings on the relationships between stress, the gut microbiome and the inflammatory response and their contribution to depression.

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.

YY1 (Yin-Yang 1), a transcription factor regulating systemic inflammation, is involved in cognitive impairment of depression

AIM

Clinical and preclinical studies suggest that alterations in the peripheral and brain immune system are associated with the pathophysiology of depression, also leading to changes in local glucose metabolism in the brain. Here, the authors identified Yin-Yang 1 (YY1), a transcription factor closely associated with central and peripheral inflammation.

METHODS

Plasma levels of YY1, interleukin (IL) 6, and IL-1β in major depressive disorder (MDD) were collected before and after treatment with vortioxetine, and correlation with clinical and cognitive scores was studied. Chronic unpredictable mild stress was treated with vortioxetine. Micropositron emission tomography (microPET) was used to analyze glucose metabolism and mRNA, and the protein level of the YY1-nuclear factor κB (NF-κB)-IL-1β inflammatory pathway were measured in related brain regions.

RESULTS

Plasma levels of YY1 and IL-1β were significantly increased in MDD and decreased after treatment with vortioxetine. Meanwhile, the level of YY1 in plasma was negatively correlated with cognitive functions in patients with MDD and positively correlated with the level of IL-1β in plasma. Compared with the control group, in chronic unpredictable mild stress rats, (microPET) analysis showed that the decrease of glucose metabolism in the hippocampus, entorhinal cortex, amygdala, striatum, and medial prefrontal cortex was reversed after treatment. mRNA and protein level of related molecular in YY1-NF-κB-IL-1β inflammatory pathway decreased in the hippocampus and was reversed by vortioxetine.

CONCLUSION

The current study suggests that the YY1-NF-κB-IL-1β inflammatory pathway may play an essential role in both mood changes and cognitive impairment in depression, and may be associated with changes in glucose metabolism in emotion regulation and cognition. These findings provide new evidence for the inflammatory mechanisms of depression.

Microbiota-immune-brain interactions: A lifespan perspective

There is growing appreciation of key roles of the gut microbiota in maintaining homeostasis and influencing brain and behaviour at critical windows across the lifespan. Mounting evidence suggests that communication between the gut and the brain could be the key to understanding multiple neuropsychiatric disorders, with the immune system coming to the forefront as an important mechanistic mediator. Throughout the lifespan, the immune system exchanges continuous reciprocal signals with the central nervous system. Intestinal microbial cues alter immune mediators with consequences for host neurophysiology and behaviour. Several factors challenge the gut microbiota composition, which in response release molecules with neuro- and immuno-active potential that are crucial for adequate neuro-immune interactions. In this review, multiple factors contributing to the upkeep of the fine balance between health and disease of these systems are discussed, and we elucidate the potential mechanistic implications for the gut microbiota inputs on host brain and behaviour across the lifespan.

Integrated Module of Multidimensional Omics for Peripheral Biomarkers (iMORE) in patients with major depressive disorder: rationale and design of a prospective multicentre cohort study

INTRODUCTION

Major depressive disorder (MDD) represents a worldwide burden on healthcare and the response to antidepressants remains limited. Systems biology approaches have been used to explore the precision therapy. However, no reliable biomarker clinically exists for prognostic prediction at present. The objectives of the Integrated Module of Multidimensional Omics for Peripheral Biomarkers (iMORE) study are to predict the efficacy of antidepressants by integrating multidimensional omics and performing validation in a real-world setting. As secondary aims, a series of potential biomarkers are explored for biological subtypes.

METHODS AND ANALYSIS

iMore is an observational cohort study in patients with MDD with a multistage design in China. The study is performed by three mental health centres comprising an observation phase and a validation phase. A total of 200 patients with MDD and 100 healthy controls were enrolled. The protocol-specified antidepressants are selective serotonin reuptake inhibitors and serotonin-norepinephrine reuptake inhibitors. Clinical visits (baseline, 4 and 8 weeks) include psychiatric rating scales for symptom assessment and biospecimen collection for multiomics analysis. Participants are divided into responders and non-responders based on treatment response (>50% reduction in Montgomery-Asberg Depression Rating Scale). Antidepressants' responses are predicted and biomarkers are explored using supervised learning approach by integration of metabolites, cytokines, gut microbiomes and immunophenotypic cells. The accuracy of the prediction models constructed is verified in an independent validation phase.

ETHICS AND DISSEMINATION

The study was approved by the ethics committee of Shanghai Mental Health Center (approval number 2020-87). All participants need to sign a written consent for the study entry. Study findings will be published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT04518592.

Gut microbiota and major depressive disorder: A bidirectional Mendelian randomization

BACKGROUND

Observational studies showed an association between gut microbiota and depression, but the causality relationship between them is unclear. We aimed to determine whether there is a bidirectional causal relationship between the composition of gut microbiota and major depressive disorders (MDD) and explore the role of gut microbiota in decreasing the risk of MDD.

METHODS

Our two-sample Mendelian randomization (MR) study acquired top SNPs associated with the composition of gut microbiota (n = 18,340) and with MDDs (n = 480,359) from publicly available genome-wide association studies (GWAS). The SNPs estimates were pooled using inverse-variance weighted meta-analysis, with sensitivity analyses-weighted median, MR Egger, and MR Pleiotropy Residual Sum and Outlier (PRESSO).

RESULTS

The Actinobacteria class had protective causal effects on MDD (OR 0.88, 95%CI 0.87 to 0.9). The Bifidobacterium (OR 0.89, 95%CI 0.88 to 0.91) were further found to have similar effects as the Actinobacteria class. The genus Ruminococcus1 had a protective effect on MDD (OR 0.88, 95%CI 0.76 to 0.99) while the Streptococcaceae family and its genus had an anti-protective effect on MDD (OR 1.07, 95%CI 1.01 to 1.13), but these findings were not supported by the MR-Egger analysis. Bidirectional MR showed no effect of MDD on gut microbiota composition.

LIMITATIONS

The use of summary-level data, the risk of sample overlap and low statistical power are the major limiting factors.

CONCLUSIONS

Our MR analysis showed a protective effect of Actinobacteria, Bifidobacterium, and Ruminococcus and a potentially anti-protective effect of Streptococcaceae on MDD pathogenesis. Further studies are needed to transform the findings into practice.

Possible metabolic interplay between quality of life and fecal microbiota in a presenior population-Preliminary results

OBJECTIVES

The number of people aged ≥60 y is increasing worldwide, so establishing a relationship between lifestyle and health-associated factors, such as gut microbiota in an older population, is important. This study aimed to characterize the gut microbiota of a presenior population, and analyze the association between some bacteria and quality of life with the Short Form (SF) 36 questionnaire.

METHODS

Participants were adult men and women ages 50 to 80 y (n = 74). In addition to the SF-36 questionnaire, fecal samples were collected in cryotubes, and 16S RNA gene sequencing was performed to characterize microbial features. Participants were classified into two groups according to SF-36 punctuation. Linear and logistic regression models were performed to assess the possible association between any bacterial bowl and SF-36 score. Receiver operating characteristics curves were fitted to define the relative diagnostic strength of different bacterial taxa for the correct determination of quality of life.

RESULTS

A positive relationship was established between SF-36 score and Actinobacteria (P = 0.0310; R = 0.2510) compared with Peptostreptococcaceae (P = 0.0259; R = -0.2589), which increased with decreasing quality of life. Logistic regressions models and receiver operating characteristics curves showed that the relative abundance of Actinobacteria and Peptostreptococcaceae may be useful to predict quality of life in a presenior population (area under the curve: 0.71).

CONCLUSIONS

Quality of life may be associated with the relative abundance of certain bacteria, especially Actinobacteria and Peptostreptococcaceae, which may have a specific effect on certain markers and health care, which is important to improve quality of life in older populations.

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

AIM

Gut microbiota and its metabolite bile acids may play a significant role in the occurrence and development of major depressive disorder (MDD). Therefore, this study analyzes gut microbiota and bile acids, as well as their correlation in patients.

METHODS

Thirty-one patients with MDD and 29 healthy controls (HCs) were enrolled in this study. We collected their both blood and feces. Plasma bile acid content was determined by liquid chromatography-mass spectrometry and gut microbiota was detected by 16SrRNA gene sequencing and subsequently analyzed. We also analyzed the correlation between different gut microbiota, bile acids, and Hamilton Depression (HAMD) score.

RESULTS

The α-diversity analysis found that Simpson and Pielou evenness index was much higher in HCs than in the patients with MDD. The β-diversity of the two groups were differences by nonmetric multidimensional scaling analysis. Linear discriminant analysis effect size analysis identified 16 different strains. Bile acids detection showed that 23-nordeoxycholic acid in patients with MDD was significantly higher than in HCs, whereas taurolithocholic acid (TLCA), glycolithocholic acid (GLCA), and lithocholic acid 3-sulfate were significantly lower. Spearman correlation analysis showed that Turicibacteraceae, Turicibacterales, and Turicibacter were positively related with TLCA, GLCA, glycodeoxycholic acid (GDCA), and taurodeoxycholic acid, and were negatively correlated with HAMD score. At the same time, TLCA, GLCA, and GDCA were negatively correlated with HAMD score.

CONCLUSIONS

Gut microbiota and bile acids metabolism are disturbances in MDD, and there exists a correlation between gut microbiota and bile acids metabolism. Moreover, their interaction may be related to the pathophysiological mechanism of MDD.

Alzheimer's disease and depression in the elderly: A trajectory linking gut microbiota and serotonin signaling

The occurrence of neuropsychiatric symptoms in the elderly is viewed as an early sign of subsequent cognitive deterioration and conversion from mild cognitive impairment to Alzheimer's disease. The prognosis in terms of both the severity and progression of clinical dementia is generally aggravated by the comorbidity of neuropsychiatric symptoms and decline in cognitive function. Undeniably, aging and in particular unhealthy aging, is a silent "engine of neuropathology" over which multiple changes take place, including drastic alterations of the gut microbial ecosystem. This narrative review evaluates the role of gut microbiota changes as a possible unifying concept through which the comorbidity of neuropsychiatric symptoms and Alzheimer's disease can be considered. However, since the heterogeneity of neuropsychiatric symptoms, it is improbable to describe the same type of alterations in the bacteria population observed in patients with Alzheimer's disease, as well as it is improbable that the variety of drugs used to treat neuropsychiatric symptoms might produce changes in gut bacterial diversity similar to that observed in the pathophysiology of Alzheimer's disease. Depression seems to be another very intriguing exception, as it is one of the most frequent neuropsychiatric symptoms in dementia and a mood disorder frequently associated with brain aging. Antidepressants (i.e., serotonin reuptake inhibitors) or tryptophan dietary supplementation have been shown to reduce Amyloid β-loading, reinstate microbial diversity and reduce the abundance of bacterial taxa dominant in depression and Alzheimer's disease. This review briefly examines this trajectory by discussing the dysfunction of gut microbiota composition, selected bacterial taxa, and alteration of tryptophan and serotonin metabolism/neurotransmission as overlapping in-common mechanisms involved with depression, Alzheimer's disease, and unhealthy aging.