Alterations of the Composition and Neurometabolic Profile of Human Gut Microbiota in Major Depressive Disorder

Alterations in fecal microbiota composition and cytokine expression profiles in adolescents with depression: a case-control study

Emerging evidence has highlighted that altered gut microbiota are associated with the onset and progression of depression via regulating the gut-brain axis. However, existing research has predominantly focused on children and adults, frequently neglecting adolescent depression. Given the rising prevalence and substantial impact of adolescent depression on functional impairment and suicidality, it is essential to focus more on this age group. In this study, we examined the fecal microbiota and inflammatory profiles of 99 depressed adolescents and 106 age-matched healthy controls using Illumina NovaSeq sequencing and multiplex immunoassays, respectively. Our findings revealed lower bacterial α-diversity and richness, alongside altered β-diversity in adolescents with depression. Gut dysbiosis associated with adolescent depression was characterized by increased pro-inflammatory genera such as Streptococcus and decreased anti-inflammatory genera like Faecalibacterium. These differential genera may serve as potential non-invasive biomarkers for adolescent depression, either individually or in combination. We also observed disruptions in the inferred microbiota functions in adolescent depression-associated microbiota, particularly in glycolysis and gluconeogenesis. Additionally, depressed adolescents exhibited systemic immune dysfunction, with elevated levels of pro-inflammatory cytokines and chemokines, which showed significant correlations with the differential genera. Our study bridges the gap between children and adults by providing new insights into the fecal microbiota characteristics and their links to immune system disruptions in depressed adolescents, which offer new targets for the diagnosis and treatment of depression in this age group.

Faecalibacterium prausnitzii, FOS and GOS loaded synbiotic reverses treatment-resistant depression in rats: Restoration of gut-brain crosstalk

Alterations in commensal gut microbiota, such as butyrate-producing bacteria and its metabolites, have been linked to stress-related brain disorders, including depression. Herein, we investigated the effect of Faecalibacterium prausnitzii (ATCC-27766) administered along with fructooligosaccharides (FOS) and galactooligosaccharides (GOS) in a rat model of treatment-resistant depression (TRD). The behavioral changes related to anxiety-, anhedonia- and despair-like phenotypes were recorded employing elevated plus maze, sucrose-preference test, and forced-swim test, respectively. Rats exposed to unpredictable chronic mild-stress (UCMS) and adrenocorticotropic hormone (ACTH) injections exhibited a TRD-like phenotype. Six-week administration of F. prausnitzii and FOS + GOS ameliorated TRD-like conditions in rats. This synbiotic treatment also restored the decreased levels of short-chain fatty acids (SCFAs) such as acetate, propionate, and butyrate in the fecal samples of TRD rats. Synbiotic-recipient TRD rats displayed an increased abundance of Lactobacillus helveticus, Lactobacillus hamsteri, and Ruminococcus flavefaciens. Moreover, more mucus-producing goblet cells were seen in the colon of synbiotic-treated rats, suggesting improved gut health. The synbiotic treatment effectively modulated neuroinflammation by reducing proinflammatory cytokines (IFN-γ, TNF-α, CRP, and IL-6). It normalized the altered levels of key neurotransmitters such as serotonin, gamma-aminobutyric acid, noradrenaline, and dopamine in the hippocampus and/or frontal cortex. The enhanced expression of brain-derived neurotrophic factor, tryptophan hydroxylase 1, and serotonin transporter-3 (SERT-3), and reduced levels of indoleamine 2,3-dioxygenase 1 (IDO-1) and kynurenine metabolite were observed in the synbiotic-treated group. We suggest that F. prausnitzii and FOS + GOS-loaded synbiotic may reverse the TRD-like symptoms in rats by positively impacting gut health, neuroinflammation, neurotransmitters, and gut microbial composition.

The protective effect of S-adenosylmethionine on chronic adolescent stress-induced depression-like behaviors by regulating gut microbiota

The efficacy and tolerability of current antidepressants for adolescent depression are inadequate. S-adenosylmethionine (SAMe), known for its effectiveness and minimal side effects in adult depression, remains unstudied in adolescents. This study explored the potential of SAMe to address depression-like behaviors in juvenile rats induced by chronic unpredictable mild stress (CUMS), with a focus on gut microbiome interactions. Adolescent male Wistar rats were subjected to a 4-week CUMS regimen and received daily intraperitoneal injections of 300 mg/kg SAMe. Behavioral assessments included the sucrose preference test, elevated plus maze test, open field test, and Y-maze test. Histopathological changes of the hippocampus and colon were observed by Nissl staining and hematoxylin and eosin staining, respectively. Gut microbiome composition was analyzed using Accurate 16S absolute quantification sequencing. The results showed that SAMe significantly improved behavioral outcomes, reduced histopathological damages in hippocampal neurons and colon tissues, and modulated the gut microbiota of depressed rats. It favorably altered the ratio of Bacteroidetes to Firmicutes, decreased the absolute abundance of Deferribacteres, and adjusted levels of key microbial genera associated with depression-like behaviors. These results suggested that SAMe could effectively counter depression-like behaviors in CUMS-exposed adolescent rats by mitigating hippocampal neuronal and colon damage and modulating the gut microbiota. This supports SAMe as a viable and tolerable treatment option for adolescent depression, highlighting the importance of the gut-brain axis in therapeutic strategies.

Association between major depressive disorder and gut microbiota dysbiosis

OBJECTIVE

Major depressive disorder (MDD) affects 300 million people globally. Because dysbiosis may alter the central nervous system, it plays a potential role in this disorder. Dysbiosis is characterized by a decrease in microbial diversity and an increase in proinflammatory species. The human gut microbiota refers to the trillions of microbes, such as bacteria, that live in the human gut. The purpose of this study was to compare the gut microbiota of patients with MDD with that of healthy controls.

METHODS

This case-control study involved 35 MDD cases and 35 healthy age- and sex-matched controls. Stool samples were collected and subjected to quantitative real-time PCR. Four intestinal bacterial phyla (firmicutes, bacteroidetes, actinobacteria, and proteobacteria) were investigated by 16SrRNA analysis.

RESULTS

The findings indicated a relative abundance of bacteroidetes to firmicutes in the control and case groups was 0.66 vs. 1.33, respectively (p < .05). There were no significant differences in actinobacteria or proteobacteria among those in the MDD group compared to the healthy control group.

CONCLUSIONS

Gut microbiota dysbiosis may contribute to the onset of depression, underscoring the importance of understanding the relationship between MDD and gut microbiota. Firmicutes, which produce short-chain fatty acids, are crucial for intestinal health. However, dysbiosis can disrupt the gut microbiota, impacting the central nervous system and contributing to the onset of depression.

Associations between specific dietary patterns, gut microbiome composition, and incident subthreshold depression in Chinese young adults

INTRODUCTION

The interplay between influential factors and the incidence of subthreshold depression (SD) in young adults remains poorly understood.

OBJECTIVES

This study sought to understand the dietary habits, gut microbiota composition, etc. among individuals with SD in young adults and to investigate their association with SD occurrence.

METHODS

Employing a cross-sectional approach, 178 individuals with SD, aged 18-32 years, were matched with 114 healthy counterparts. SD status was evaluated using the Zung Self-rating Depression Scale (SDS), Zung Self-rating Anxiety Scale (SAS), Beck Depression Inventory 2nd version (BDI-II), the 17-item Hamilton Rating Scales of Depression (HAMD-17), and Pittsburgh Sleep Quality Index (PSQI). Metagenomic sequencing was utilized to identify fecal microbial profiles. Dietary patterns were discerned via factor analysis of a 25-item food frequency questionnaire (FFQ). Logistic regression analysis and mediation analysis were performed to explore the potential links between gut microbiota, dietary patterns, and incident SD.

RESULTS

Data on dietary habits were available for 292 participants (mean [SD] age, 22.1 [2.9] years; 216 [73.9 %] female). Logistic regression analysis revealed that dietary patterns Ⅰ (odds ratio [OR], 0.34; 95 % CI, 0.15-0.75) and IV (OR, 0.39; 95 % CI, 0.17-0.86 and OR, 0.39; 95 % CI, 0.18-0.84) were associated with reduced risk of SD. Distinct microbial profiles were observed in young adults with SD, marked by increased microbial diversity and taxonomic alterations. Moreover, mediation analysis suggested Veillonella atypica as a potential mediator linking SDS or BDI-II scores with a healthy dietary pattern rich in bean products, coarse grains, nuts, fruits, mushrooms, and potatoes (β = 0.25, 95 % CI: 0.02-0.78 and β = 0.18, 95 % CI: 0.01-0.54).

CONCLUSIONS

Our findings highlight the complex interplay between dietary patterns, gut microbiota, and the risk of developing SD in young adults, underscoring the potential for dietary interventions and microbiome modulation in mental health promotion.

Multi-omics analysis of gut-brain axis reveals novel microbial and neurotransmitter signatures in patients with arteriosclerotic cerebral small vessel disease

Arteriosclerotic cerebral small vessel disease (aCSVD) is a major cause of stroke and dementia. Although its underlying pathogenesis remains poorly understood, both inflammaging and gut microbiota dysbiosis have been hypothesized to play significant roles. This study investigated the role of gut microbiota in the pathogenesis of aCSVD through a comparative analysis of the gut microbiome and metabolome between CSVD patients and healthy controls. The results showed that patients with aCSVD exhibited a marked reduction in potentially beneficial bacterial species, such as Faecalibacterium prausnitzli and Roseburia intestinalis, alongside an increase in taxa from Bacteroides and Proteobacteria. Integrated metagenomic and metabolomic analyses revealed that alterations in microbial metabolic pathways, including LPS biosynthesis and phenylalanine-tyrosine metabolism, were associated with the status of aCSVD. Our findings indicated that microbial LPS biosynthesis and phenylalanine-tyrosine metabolism potentially influenced the symptoms and progression of aCSVD via pro-inflammatory effect and modulation of systemic neurotransmitters, respectively. These results imply that gut microbiota characteristics may serve as indicators for early detection of aCSVD and as potential gut-directed therapeutic intervention target.

Exploring the gut-brain Axis: Potential therapeutic impact of Psychobiotics on mental health

One of the most challenging and controversial issues in microbiome research is related to gut microbial metabolism and neuropsychological disorders. Psychobiotics affect human behavior and central nervous system processes via the gut-brain axis, involving neuronal, immune, and metabolic pathways. They have therapeutic potential in the treatment of several neurodegenerative and neurodevelopmental disorders such as depression, anxiety, autism, attention deficit hyperactivity disorder, Alzheimer's disease, Parkinson's disease, schizophrenia, Huntington's disease, anorexia nervosa, and multiple sclerosis. However, the mechanisms underlying the interaction between psychobiotics and the abovementioned diseases need further exploration. This review focuses on the relationship between gut microbiota and its impact on neurological and neurodegenerative disorders, examining the potential of psychobiotics as a preventive and therapeutic approach, summarising recent research on the gut-brain axis and the potential beneficial effects of psychobiotics, highlighting the need for further research and investigation in this area.

The use of omics technologies in creating LBP and postbiotics based on the Limosilactobacillus fermentum U-21

In recent years, there has been an increasing tendency to create drugs based on certain commensal bacteria of the human microbiota and their ingredients, primarily focusing on live biotherapeutics (LBPs) and postbiotics. The creation of such drugs, termed pharmacobiotics, necessitates an understanding of their mechanisms of action and the identification of pharmacologically active ingredients that determine their target properties. Typically, these are complexes of biologically active substances synthesized by specific strains, promoted as LBPs or postbiotics (including vesicles): proteins, enzymes, low molecular weight metabolites, small RNAs, etc. This study employs omics technologies, including genomics, proteomics, and metabolomics, to explore the potential of Limosilactobacillus fermentum U-21 for innovative LBP and postbiotic formulations targeting neuroinflammatory processes. Proteomic techniques identified and quantified proteins expressed by L. fermentum U-21, highlighting their functional attributes and potential applications. Key identified proteins include ATP-dependent Clp protease (ClpL), chaperone protein DnaK, protein GrpE, thioredoxin reductase, LysM peptidoglycan-binding domain-containing protein, and NlpC/P60 domain-containing protein, which have roles in disaggregase, antioxidant, and immunomodulatory activities. Metabolomic analysis provided insights into small-molecule metabolites produced during fermentation, revealing compounds with anti-neuroinflammatory activity. Significant metabolites produced by L. fermentum U-21 include GABA (γ-aminobutyric acid), niacin, aucubin, and scyllo-inositol. GABA was found to stabilize neuronal activity, potentially counteracting neurodegenerative processes. Niacin, essential for optimal nervous system function, was detected in vesicles and culture fluid, and it modulates cytokine production, maintaining immune homeostasis. Aucubin, an iridoid glycoside usually secreted by plants, was identified as having antioxidant properties, addressing issues of bioavailability for therapeutic use. Scyllo-inositol, identified in vesicles, acts as a chemical chaperone, reducing abnormal protein clumps linked to neurodegenerative diseases. These findings demonstrate the capability of L. fermentum U-21 to produce bioactive substances that could be harnessed in the development of pharmacobiotics for neurodegenerative diseases, contributing to their immunomodulatory, anti-neuroinflammatory, and neuromodulatory activities. Data of the HPLC-MS/MS analysis are available via ProteomeXchange with identifier PXD050857.

Human Gut Microbiota for Diagnosis and Treatment of Depression

Nowadays, depressive disorder is spreading rapidly all over the world. Therefore, attention to the studies of the pathogenesis of the disease in order to find novel ways of early diagnosis and treatment is increasing among the scientific and medical communities. Special attention is drawn to a biomarker and therapeutic strategy through the microbiota-gut-brain axis. It is known that the symbiotic interactions between the gut microbes and the host can affect mental health. The review analyzes the mechanisms and ways of action of the gut microbiota on the pathophysiology of depression. The possibility of using knowledge about the taxonomic composition and metabolic profile of the microbiota of patients with depression to select gene compositions (metagenomic signature) as biomarkers of the disease is evaluated. The use of in silico technologies (machine learning) for the diagnosis of depression based on the biomarkers of the gut microbiota is given. Alternative approaches to the treatment of depression are being considered by balancing the microbial composition through dietary modifications and the use of additives, namely probiotics, postbiotics (including vesicles) and prebiotics as psychobiotics, and fecal transplantation. The bacterium Faecalibacterium prausnitzii is under consideration as a promising new-generation probiotic and auxiliary diagnostic biomarker of depression. The analysis conducted in this review may be useful for clinical practice and pharmacology.

Gut microbiota: A potential player in psychiatric symptoms during COVID-19

OBJECTIVES

This study aims to explore the potential interconnections among gut microbiota, COVID-19 infection, depression and anxiety disorder. Additionally, it tries to assess potential therapeutic interventions that may improve the dysbiosis of gut microbiota.

METHODS

To achieve these objectives, we reviewed existing literature, encompassing studies and critical reviews that intersect the domains of gut microbiota, COVID-19, depression and anxiety disorders.

RESULTS

The findings highlight a notable correlation between the dysbiosis of gut microbiota and psychiatric symptoms in the context of COVID-19. Specifically, there is a marked reduction in the populations of bacteria that generate anti-inflammatory short-chain fatty acids (SCFAs), alongside a rise in the prevalence of gut bacterial clusters linked to inflammatory processes. Furthermore, several potential treatment strategies were summarised for improving the dysbiosis.

CONCLUSIONS

Gut microbiota plays a significant role in psychiatric symptoms during COVID-19, which has significant implications for the study and prevention of psychiatric symptoms in major epidemic diseases.

Oral and gut microbial profiling in periodontitis and Parkinson's disease

Objectives

We tested the hypothesis that Parkinson's disease (PA) alters the periodontitis-associated oral microbiome.

Method

Patients with periodontitis with Parkinson's disease (PA+P) and without PA (P) and systemically and periodontally healthy individuals (HC) were enrolled. Clinical, periodontal and neurological parameters were recorded. The severity of PA motor functions was measured. Unstimulated saliva samples and stool samples were collected. Next-generation sequencing of 16S ribosomal RNA (V1-V3 regions) was performed.

Results

PA patients had mild-to-moderate motor dysfunction and comparable plaque scores as those without, indicating that oral hygiene was efficient in the PA+P group. In saliva, there were statistically significant differences in beta diversity between HC and PA+P (p = 0.001), HC and P (p = 0.001), and P and PA+P (p = 0.028). The microbial profiles of saliva and fecal samples were distinct. Mycoplasma faucium, Tannerella forsythia, Parvimonas micra, and Saccharibacteria (TM7) were increased in P; Prevotella pallens, Prevotella melaninogenica, Neisseria multispecies were more abundant in PA+P group, Ruthenibacterium lactatiformans, Dialister succinatiphilus, Butyrivibrio crossotus and Alloprevotella tannerae were detected in fecal samples in P groups compared to healthy controls.

Conclusions

No significant differences were detected between Parkinson's and non-Parkinson's gut microbiomes, suggesting that Parkinson's disease modifies the oral microbiome in periodontitis subjects independent of the gut microbiome.

Prenatal metal exposures and childhood gut microbial signatures are associated with depression score in late childhood

BACKGROUND

Childhood depression is a major public health issue worldwide. Previous studies have linked both prenatal metal exposures and the gut microbiome to depression in children. However, few, if any, have studied their interacting effect in specific subgroups of children.

OBJECTIVES

Using an interpretable machine-learning method, this study investigates whether children with specific combinations of prenatal metals and childhood microbial signatures (cliques or groups of metals and microbes) were more likely to have higher depression scores at 9-11 years of age.

METHODS

We leveraged data from a well-characterized pediatric longitudinal birth cohort in Mexico City and its microbiome substudy (n = 112). Eleven metal exposures were measured in maternal whole blood samples in the second and third trimesters of pregnancy. The gut microbial abundances were measured at 9-11-year-olds using shotgun metagenomic sequencing. Depression symptoms were assessed using the Child Depression Index (CDI) t-scores at 9-11 years of age. We used Microbial and Chemical Exposure Analysis (MiCxA), which combines interpretable machine-learning into a regression framework to identify and estimate joint associations of metal-microbial cliques in specific subgroups. Analyses were adjusted for relevant covariates.

RESULTS

We identified a subgroup of children (11.6 % of the sample) characterized by a four-component metal-microbial clique that had a significantly high depression score (15.4 % higher than the rest) in late childhood. This metal-microbial clique consisted of high Zinc in the second trimester, low Cobalt in the third trimester, a high abundance of Bacteroides fragilis, a high abundance of Faecalibacterium prausnitzii. All combinations of cliques (two-, three-, and four-components) were significantly associated with increased log-transformed t-scored CDI (β = 0.14, 95%CI = [0.05,0.23], P < 0.01 for the four-component clique).

SIGNIFICANCE

This study offers a new approach to chemical-microbial analysis and a novel demonstration that children with specific gut microbiome cliques and metal exposures during pregnancy may have a higher likelihood of elevated depression scores.

Systematic identification of the role of gut microbiota in mental disorders: a TwinsUK cohort study

Mental disorders are complex disorders influenced by multiple genetic, environmental, and biological factors. Specific microbiota imbalances seem to affect mental health status. However, the mechanisms by which microbiota disturbances impact the presence of depression, stress, anxiety, and eating disorders remain poorly understood. Currently, there are no robust biomarkers identified. We proposed a novel pyramid-layer design to accurately identify microbial/metabolomic signatures underlying mental disorders in the TwinsUK registry. Monozygotic and dizygotic twins discordant for mental disorders were screened, in a pairwise manner, for differentially abundant bacterial genera and circulating metabolites. In addition, multivariate analyses were performed, accounting for individual-level confounders. Our pyramid-layer study design allowed us to overcome the limitations of cross-sectional study designs with significant confounder effects and resulted in an association of the abundance of genus Parabacteroides with the diagnosis of mental disorders. Future research should explore the potential role of Parabacteroides as a mediator of mental health status. Our results indicate the potential role of the microbiome as a modifier in mental disorders that might contribute to the development of novel methodologies to assess personal risk and intervention strategies.

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.

Unveiling the Connection between Microbiota and Depressive Disorder through Machine Learning

In the last few years, investigation of the gut-brain axis and the connection between the gut microbiota and the human nervous system and mental health has become one of the most popular topics. Correlations between the taxonomic and functional changes in gut microbiota and major depressive disorder have been shown in several studies. Machine learning provides a promising approach to analyze large-scale metagenomic data and identify biomarkers associated with depression. In this work, machine learning algorithms, such as random forest, elastic net, and You Only Look Once (YOLO), were utilized to detect significant features in microbiome samples and classify individuals based on their disorder status. The analysis was conducted on metagenomic data obtained during the study of gut microbiota of healthy people and patients with major depressive disorder. The YOLO method showed the greatest effectiveness in the analysis of the metagenomic samples and confirmed the experimental results on the critical importance of a reduction in the amount of Faecalibacterium prausnitzii for the manifestation of depression. These findings could contribute to a better understanding of the role of the gut microbiota in major depressive disorder and potentially lead the way for novel diagnostic and therapeutic strategies.

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.

Gut Dysbiosis: A New Avenue for Stroke Prevention and Therapeutics

A stroke is a serious life-threatening condition and a leading cause of death and disability that happens when the blood vessels to part of the brain are blocked or burst. While major advances in the understanding of the ischemic cascade in stroke was made over several decades, limited therapeutic options and high mortality and disability have caused researchers to extend the focus toward peripheral changes beyond brain. The largest proportion of microbes in human body reside in the gut and the interaction between host and microbiota in health and disease is well known. Our study aimed to explore the gut microbiota in patients with stroke with comparison to control group. Fecal samples were obtained from 51 subjects: 25 stroke patients (18 hemorrhagic, 7 ischemic) and 26 healthy control subjects. The variable region V3-V4 of the 16S rRNA gene was sequenced using the Illumina MiSeq platform. PICRUSt2 was used for prediction of metagenomics functions. Our results show taxonomic dysbiosis in stroke patients in parallel with functional dysbiosis. Here, we show that stroke patients have (1) increased Parabacteroides and Escherichia_Shigella, but decreased Prevotella and Fecalibacterium; (2) higher transposase and peptide/nickel transport system substrate-binding protein, but lower RNA polymerase sigma-70 factor and methyl-accepting chemotaxis protein, which are suggestive of malnutrition. Nutrients are essential regulators of both host and microbial physiology and function as key coordinators of host-microbe interactions. Manipulation of nutrition is expected to alleviate gut dysbiosis and prognosis and improve disability and mortality in the management of stroke.

Glucose and Lipid Profiles Predict Anthropometric Changes in Drug-Naïve Adolescents Starting Treatment with Risperidone or Sertraline: A Pilot Study

Psychiatric disorders are associated with cardiometabolic diseases, partly due to adverse drug effects with individual risk variabilities. Risperidone and sertraline are widely used for youths. Although they may be exposed to anthropometric changes, few data about this population exist. We evaluated the correlation between several blood parameters and body changes in a very small group of drug-naïve adolescents who had started risperidone or sertraline. We examined weight, waist circumference (WC), WC/height ratio and body mass index (BMI) at baseline (T0) and after at least three months of therapy (T1), and blood glucose and lipid profiles at T0. Here, we show significant increases in several anthropometric parameters in both groups, a negative correlation between HDL and ΔWC in the risperidone group and positive correlations between insulin and ΔBMI and between HOMA-IR and ΔBMI in the sertraline group. Despite the sample size, these results are important because it is difficult to study adolescents who are long-term-compliant with psychotropic drugs. This pilot study supports the importance of future large-scale investigations to understand the metabolic risk profiles of psychotropic drugs, their individual vulnerabilities and their underlying mechanisms. Simultaneous guideline-based psychiatric and metabolic interventions should be part of daily practice.

Stimulated Parotid Saliva Is a Better Method for Depression Prediction

BACKGROUND

Saliva cortisol is considered to be a biomarker of depression prediction. However, saliva collection methods can affect the saliva cortisol level.

OBJECTIVE

This study aims to determine the ideal saliva collection method and explore the application value of saliva cortisol in depression prediction.

METHODS

30 depressed patients and 30 healthy controls were instructed to collect saliva samples in the morning with six collection methods. Simultaneous venous blood was collected. Enzyme-linked immunosorbent assay was used to determine the cortisol level. The 24-observerrated Hamilton depression rating scale (HAMD-24) was used to assess the severity of depression.

RESULTS

The significant differences in saliva cortisol levels depend on the saliva collection methods. The level of unstimulated whole saliva cortisol was most correlated with blood (r = 0.91). The stimulated parotid saliva cortisol can better predict depression. The area under the curve was 0.89. In addition, the saliva cortisol level of the depression patients was significantly higher than the healthy controls. The correlation between the cortisol level and the HAMD-24 score was highly significant. The higher the saliva cortisol level, the higher the HAMD-24 score.

CONCLUSIONS

All the above findings point to an exciting opportunity for non-invasive monitoring of cortisol through saliva.