Cohabiting with ulcerative colitis patients decreases differences of gut microbiome between healthy individuals and the patients.

Background: Ulcerative colitis (UC), which is characterized by chronic relapsing inflammation of the colon, results from a complex interaction of factors involving the host, environment, and microbiome. The present study aimed to investigate the gut microbial composition and metabolic variations in patients with UC and their spouses. Materials and Methods: Fecal samples were collected from 13 healthy spouses and couples with UC. 16S rRNA gene amplicon sequencing and metagenomics sequencing were used to analyze gut microbiota composition, pathways, gene expression, and enzyme activity, followed by the Kyoto Encyclopedia of Genes and Genomes. Results: We found that the microbiome diversity of couples with UC decreased, especially that of UC patients. Bacterial composition, such as Firmicutes, was altered between UC patients and healthy controls, but was not significantly different between UC patients and their spouses. This has also been observed in pathways, such as metabolism, genetic information processing, organismal systems, and human diseases. However, the genes and enzymes of spouses with UC were not significantly different from those of healthy individuals. Furthermore, the presence of Faecalibacterium correlated with oxidative phosphorylation, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, and the bacterial secretion system, showed a marked decline in the UC group compared with their spouses, but did not vary between healthy couples. Conclusion: Our study revealed that cohabitation with UC patients decreased differences in the gut microbiome between healthy individuals and patients. Not only was the composition and diversity of the microbiota diminished, but active pathways also showed some decline. Furthermore, Firmicutes, Faecalibacterium, and the four related pathways may be associated with the pathological state of the host rather than with human behavior.

The causal relationship between gut microbiota and biliary tract cancer: comprehensive bidirectional Mendelian randomization analysis.

Background: Growing evidence has shown that gut microbiome composition is associated with Biliary tract cancer (BTC), but the causality remains unknown. This study aimed to explore the causal relationship between gut microbiota and BTC, conduct an appraisal of the gut microbiome's utility in facilitating the early diagnosis of BTC. Methods: We acquired the summary data for Genome-wide Association Studies (GWAS) pertaining to BTC (418 cases and 159,201 controls) from the Biobank Japan (BBJ) database. Additionally, the GWAS summary data relevant to gut microbiota (N = 18,340) were sourced from the MiBioGen consortium. The primary methodology employed for the analysis consisted of Inverse Variance Weighting (IVW). Evaluations for sensitivity were carried out through the utilization of multiple statistical techniques, encompassing Cochrane's Q test, the MR-Egger intercept evaluation, the global test of MR-PRESSO, and a leave-one-out methodological analysis. Ultimately, a reverse Mendelian Randomization analysis was conducted to assess the potential for reciprocal causality. Results: The outcomes derived from IVW substantiated that the presence of Family Streptococcaceae (OR = 0.44, P = 0.034), Family Veillonellaceae (OR = 0.46, P = 0.018), and Genus Dorea (OR = 0.29, P = 0.041) exerted a protective influence against BTC. Conversely, Class Lentisphaeria (OR = 2.21, P = 0.017), Genus Lachnospiraceae FCS020 Group (OR = 2.30, P = 0.013), and Order Victivallales (OR = 2.21, P = 0.017) were associated with an adverse impact. To assess any reverse causal effect, we used BTC as the exposure and the gut microbiota as the outcome, and this analysis revealed associations between BTC and five different types of gut microbiota. The sensitivity analysis disclosed an absence of empirical indicators for either heterogeneity or pleiotropy. Conclusion: This investigation represents the inaugural identification of indicative data supporting either beneficial or detrimental causal relationships between gut microbiota and the risk of BTC, as determined through the utilization of MR methodologies. These outcomes could hold significance for the formulation of individualized therapeutic strategies aimed at BTC prevention and survival enhancement.

Similarities and differences: species and diet impact gut microbiota of captive pheasants.

The fecal microbiota plays an important role in maintaining animal health and is closely related to host life activities. In recent years, there have been an increasing number of studies on the fecal microbiota from birds. An exploration of the effects of species and living environments on the composition of gut microbiota will provide better protection for wildlife. In this study, non-injury sampling and 16S rDNA high-throughput sequencing were used to investigate the bacterial composition and diversity of the fecal microbiota in silver pheasants (Lophura nycthemera) and golden pheasants (Chrysolophus pictus) from Tianjin Zoo and Beijing Wildlife Park. The results showed that the abundance of Firmicutes was the highest in all fecal samples. At the genus level, Bacteroides was the common dominant bacteria, while there were some differences in other dominant bacteria genera. There were significant differences in fecal microbial composition between the golden pheasants from Tianjin Zoo and Beijing Wildlife Park. The metabolic analysis and functional prediction suggested that the gut microbiota composition and host metabolism were influenced by dietary interventions and living conditions. The results of this study provide the basis for further research of intestinal microbial of L. nycthemera and C. pictus, and valuable insights for conservation of related species.

Comparative characterization of the infant gut microbiome and their maternal lineage by a multi-omics approach.

The human gut microbiome establishes and matures during infancy, and dysregulation at this stage may lead to pathologies later in life. We conducted a multi-omics study comprising three generations of family members to investigate the early development of the gut microbiota. Fecal samples from 200 individuals, including infants (0-12 months old; 55% females, 45% males) and their respective mothers and grandmothers, were analyzed using two independent metabolomics platforms and metagenomics. For metabolomics, gas chromatography and capillary electrophoresis coupled to mass spectrometry were applied. For metagenomics, both 16S rRNA gene and shotgun sequencing were performed. Here we show that infants greatly vary from their elders in fecal microbiota populations, function, and metabolome. Infants have a less diverse microbiota than adults and present differences in several metabolite classes, such as short- and branched-chain fatty acids, which are associated with shifts in bacterial populations. These findings provide innovative biochemical insights into the shaping of the gut microbiome within the same generational line that could be beneficial in improving childhood health outcomes.

Association between gut microbiota and onset of type 2 diabetes mellitus: a two-sample Mendelian randomization study.

Aim: Mendelian randomization (MR) analysis has been used in the exploration of the role of gut microbiota (GM) in type 2 diabetes mellitus (T2DM); however, it was limited to the genus level. This study herein aims to investigate the relationship of GM, especially at the species level, with T2DM in order to provide some evidence for further exploration of more specific GM taxa and pathway abundance in T2DM. Methods: This two-sample MR study was based on the summary statistics of GM from the available genome-wide association study (GWAS) meta-analysis conducted by the MiBioGen consortium as well as the Dutch Microbiome Project (DMP), whereas the summary statistics of T2DM were obtained from the FinnGen consortium released data. Inverse variance weighted (IVW), MR-Egger, strength test (F), and weighted median methods were used to examine the causal association between GM and the onset of T2DM. Cochran's Q statistics was employed to quantify the heterogeneity of instrumental variables. Bonferroni's correction was conducted to correct the bias of multiple testing. We also performed reverse causality analysis. Results: The corrected IVW estimates suggested the increased relative abundance of family Oxalobacteraceae (OR = 1.0704) and genus Oxalobacter (OR = 1.0874), respectively, were associated with higher odds of T2DM, while that of species faecis (OR = 0.9460) had a negative relationship with T2DM. The relationships of class Betaproteobacteria, family Lactobacillaceae, species finegoldii, and species longum with T2DM were also significant according to the IVW results (all P < 0.05). Conclusions: GM had a potential causal association with T2DM, especially species faecis, finegoldii, and longum. Further studies are still needed to clarify certain results that are contradictory with previous findings.

Alteration of the intestinal microbiota and serum metabolites in a mouse model of Pon1 gene ablation.

Mutations in the Paraoxonase 1 (Pon1) gene underlie aging, cardiovascular disease, and impairments of the nervous and gastrointestinal systems and are linked to the intestinal microbiome. The potential role of Pon1 in modulating the intestinal microbiota and serum metabolites is poorly understood. The present study demonstrated that mice with genomic excision of Pon1 by a multiplexed guide RNA CRISPR/Cas9 approach exhibited disrupted gut microbiota, such as significantly depressed alpha-diversity and distinctly separated beta diversity, accompanied by varied profiles of circulating metabolites. Furthermore, genomic knock in of Pon1 exerted a distinct effect on the intestinal microbiome and serum metabolome, including dramatically enriched Aerococcus, linoleic acid and depleted Bacillus, indolelactic acid. Specifically, a strong correlation was established between bacterial alterations and metabolites in Pon1 knockout mice. In addition, we identified metabolites related to gut bacteria in response to Pon1 knock in. Thus, the deletion of Pon1 affects the gut microbiome and functionally modifies serum metabolism, which can lead to dysbiosis, metabolic dysfunction, and infection risk. Together, these findings put forth a role for Pon1 in microbial alterations that contribute to metabolism variations. The function of Pon1 in diseases might at least partially depend on the microbiome.

Intestinal microbiome profiles in broiler chickens raised without antibiotics exhibit altered microbiome dynamics relative to conventionally raised chickens.

The present study was undertaken to profile and compare the cecal microbial communities in conventionally (CONV) grown and raised without antibiotics (RWA) broiler chickens. Three hundred chickens were collected from five CONV and five RWA chicken farms on days 10, 24, and 35 of age. Microbial genomic DNA was extracted from cecal contents, and the V4-V5 hypervariable regions of the 16S rRNA gene were amplified and sequenced. Analysis of 16S rRNA sequence data indicated significant differences in the cecal microbial diversity and composition between CONV and RWA chickens on days 10, 24, and 35 days of age. On days 10 and 24, CONV chickens had higher richness and diversity of the cecal microbiome relative to RWA chickens. However, on day 35, this pattern reversed such that RWA chickens had higher richness and diversity of the cecal microbiome than the CONV groups. On days 10 and 24, the microbiomes of both CONV and RWA chickens were dominated by members of the phylum Firmicutes. On day 35, while Firmicutes remained dominant in the RWA chickens, the microbiome of CONV chickens exhibited am abundance of Bacteroidetes. The cecal microbiome of CONV chickens was enriched with the genus Faecalibacterium, Pseudoflavonifractor, unclassified Clostridium_IV, Bacteroides, Alistipes, and Butyricimonas, whereas the cecal microbiome of RWA chickens was enriched with genus Anaerofilum, Butyricicoccu, Clostridium_XlVb and unclassified Lachnospiraceae. Overall, the cecal microbiome richness, diversity, and composition were greatly influenced by the management program applied in these farms. These findings provide a foundation for further research on tailoring feed formulation or developing a consortium to modify the gut microbiome composition of RWA chickens.

Causal effects of PM2.5 exposure on neuropsychiatric disorders and the mediation via gut microbiota: A Mendelian randomization study.

BACKGROUND: Growing evidence has revealed the impacts of exposure to fine particulate matter (PM2.5) and dysbiosis of gut microbiota on neuropsychiatric disorders, but the causal inference remains controversial due to residual confounders in observational studies. METHODS: This study aimed to examine the causal effects of exposure to PM2.5 on 4 major neuropsychiatric disorders (number of cases = 18,381 for autism spectrum disorder [ASD], 38,691 for attention deficit hyperactivity disorder [ADHD], 67,390 for schizophrenia, and 21,982 cases for Alzheimer's disease [AD]), and the mediation pathway through gut microbiota. Two-sample Mendelian randomization (MR) analyses were performed, in which genetic instruments were identified from genome-wide association studies (GWASs). The included GWASs were available from (1) MRC Integrative Epidemiology Unit (MRC-IEU) for PM2.5, PMcoarse, PM10, and NOX; (2) the Psychiatric Genomics Consortium (PGC) for ASD, ADHD, and schizophrenia; (3) MRC-IEU for AD; and (4) MiBioGen for gut microbiota. Multivariable MR analyses were conducted to adjust for exposure to NOX, PMcoarse, and PM10. We also examined the mediation effects of gut microbiota in the associations between PM2.5 exposure levels and neuropsychiatric disorders, using two-step MR analyses. RESULTS: Each 1 standard deviation (1.06 ug/m3) increment in PM2.5 concentrations was associated with elevated risk of ASD (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.00-2.02), ADHD (1.51, 1.15-1.98), schizophrenia (1.47, 1.15-1.87), and AD (1.57, 1.16-2.12). For all the 4 neurodevelopmental disorders, the results were robust under various sensitivity analyses, while the MR-Egger method yielded non-significant outcomes. The associations remained significant for all the 4 neuropsychiatric disorders after adjusting for PMcoarse, while non-significant after adjusting for NOX and PM10. The effects of PM2.5 exposure on ADHD and schizophrenia were partially mediated by Lachnospiraceae and Barnesiella, with the proportions ranging from 8.31% to 15.77%. CONCLUSIONS: This study suggested that exposure to PM2.5 would increase the risk of neuropsychiatric disorders, partially by influencing the profile of gut microbiota. Comprehensive regulations on air pollutants are needed to help prevent neuropsychiatric disorders.

Characterization of the gut bacterial and viral microbiota in latent autoimmune diabetes in adults.

Latent autoimmune diabetes in adults (LADA) is a heterogeneous disease characterized by autoantibodies against insulin producing pancreatic beta cells and initial lack of need for insulin treatment. The aim of the present study was to investigate if individuals with LADA have an altered gut microbiota relative to non-diabetic control subjects, individuals with type 1 diabetes (T1D), and individuals with type 2 diabetes (T2D). Bacterial community profiling was performed with primers targeting the variable region 4 of the 16S rRNA gene and sequenced. Amplicon sequence variants (ASVs) were generated with DADA2 and annotated to the SILVA database. The gut virome was sequenced, using a viral particle enrichment and metagenomics approach, assembled, and quantified to describe the composition of the viral community. Comparison of the bacterial alpha- and beta-diversity measures revealed that the gut bacteriome of individuals with LADA resembled that of individuals with T2D. Yet, specific genera were found to differ in abundance in individuals with LADA compared with T1D and T2D, indicating that LADA has unique taxonomical features. The virome composition reflected the stability of the most dominant order Caudovirales and the families Siphoviridae, Podoviridae, and Inoviridae, and the dominant family Microviridae. Further studies are needed to confirm these findings.

A digital twin of the infant microbiome to predict neurodevelopmental deficits.

Despite the recognized gut-brain axis link, natural variations in microbial profiles between patients hinder definition of normal abundance ranges, confounding the impact of dysbiosis on infant neurodevelopment. We infer a digital twin of the infant microbiome, forecasting ecosystem trajectories from a few initial observations. Using 16S ribosomal RNA profiles from 88 preterm infants (398 fecal samples and 32,942 abundance estimates for 91 microbial classes), the model (Q-net) predicts abundance dynamics with R2 = 0.69. Contrasting the fit to Q-nets of typical versus suboptimal development, we can reliably estimate individual deficit risk (Mδ) and identify infants achieving poor future head circumference growth with ≈76% area under the receiver operator characteristic curve, 95% ± 1.8% positive predictive value at 98% specificity at 30 weeks postmenstrual age. We find that early transplantation might mitigate risk for ≈45.2% of the cohort, with potentially negative effects from incorrect supplementation. Q-nets are generative artificial intelligence models for ecosystem dynamics, with broad potential applications.

NURECON: A Novel Online System for Determining Nutrition Requirements Based on Microbial Composition.

Dietary habits have been proven to have an impact on the microbial composition and health of the human gut. Over the past decade, researchers have discovered that gut microbiota can use nutrients to produce metabolites that have major implications for human physiology. However, there is no comprehensive system that specifically focuses on identifying nutrient deficiencies based on gut microbiota, making it difficult to interpret and compare gut microbiome data in the literature. This study proposes an analytical platform, NURECON, that can predict nutrient deficiency information in individuals by comparing their metagenomic information to a reference baseline. NURECON integrates a next-generation bacterial 16S rRNA analytical pipeline (QIIME2), metabolic pathway prediction tools (PICRUSt2 and KEGG), and a food compound database (FooDB) to enable the identification of missing nutrients and provide personalized dietary suggestions. Metagenomic information from total number of 287 healthy subjects was used to establish baseline microbial composition and metabolic profiles. The uploaded data is analyzed and compared to the baseline for nutrient deficiency assessment. Visualization results include gut microbial composition, related enzymes, pathways, and nutrient abundance. NURECON is a user-friendly online platform that provides nutritional advice to support dietitians' research or menu design.

Altered microbiome of serum exosomes in patients with acute and chronic cholecystitis.

BACKGROUND: This study aimed to investigate the differences in the microbiota composition of serum exosomes from patients with acute and chronic cholecystitis. METHOD: Exosomes were isolated from the serum of cholecystitis patients through centrifugation and identified and characterized using transmission electron microscopy and nano-flow cytometry. Microbiota analysis was performed using 16S rRNA sequencing. RESULTS: Compared to patients with chronic cholecystitis, those with acute cholecystitis exhibited lower richness and diversity. Beta diversity analysis revealed significant differences in the microbiota composition between patients with acute and chronic cholecystitis. The relative abundance of Proteobacteria was significantly higher in exosomes from patients with acute cholecystitis, whereas Actinobacteria, Bacteroidetes, and Firmicutes were significantly more abundant in exosomes from patients with chronic cholecystitis. Furthermore, functional predictions of microbial communities using Tax4Fun analysis revealed significant differences in metabolic pathways such as amino acid metabolism, carbohydrate metabolism, and membrane transport between the two patient groups. CONCLUSIONS: This study confirmed the differences in the microbiota composition within serum exosomes of patients with acute and chronic cholecystitis. Serum exosomes could serve as diagnostic indicators for distinguishing acute and chronic cholecystitis.

Landscapes of gut bacterial and fecal metabolic signatures and their relationship in severe preeclampsia.

BACKGROUND: Preeclampsia is a pregnancy-specific disease leading to maternal and perinatal morbidity. Hypertension and inflammation are the main characteristics of preeclampsia. Many factors can lead to hypertension and inflammation, including gut microbiota which plays an important role in hypertension and inflammation in humans. However, alterations to the gut microbiome and fecal metabolome, and their relationships in severe preeclampsia are not well known. This study aims to identify biomarkers significantly associated with severe preeclampsia and provide a knowledge base for treatments regulating the gut microbiome. METHODS: In this study, fecal samples were collected from individuals with severe preeclampsia and healthy controls for shotgun metagenomic sequencing to evaluate changes in gut microbiota composition. Quantitative polymerase chain reaction analysis was used to validate the reliability of our shotgun metagenomic sequencing results. Additionally, untargeted metabolomics analysis was performed to measure fecal metabolome concentrations. RESULTS: We identified several Lactobacillaceae that were significantly enriched in the gut of healthy controls, including Limosilactobacillus fermentum, the key biomarker distinguishing severe preeclampsia from healthy controls. Limosilactobacillus fermentum was significantly associated with shifts in KEGG Orthology (KO) genes and KEGG pathways of the gut microbiome in severe preeclampsia, such as flagellar assembly. Untargeted fecal metabolome analysis found that severe preeclampsia had higher concentrations of Phenylpropanoate and Agmatine. Increased concentrations of Phenylpropanoate and Agmatine were associated with the abundance of Limosilactobacillus fermentum. Furthermore, all metabolites with higher abundances in healthy controls were enriched in the arginine and proline metabolism pathway. CONCLUSION: Our research indicates that changes in metabolites, possibly due to the gut microbe Limosilactobacillus fermentum, can contribute to the development of severe preeclampsia. This study provides insights into the interaction between gut microbiome and fecal metabolites and offers a basis for improving severe preeclampsia by modulating the gut microbiome.

Gut microbiota's influence on erysipelas: evidence from a two-sample Mendelian randomization analysis.

Background: Previous studies have suggested a link between gut microbiota and skin diseases, including erysipelas, an inflammatory skin condition. Despite this, the precise nature of the relationship between erysipelas and gut microbiota remains unclear and subject to debate. Methods: We conducted a Mendelian Randomization (MR) analysis using publicly available summary data from genome-wide association studies (GWAS) to explore the potential causal relationship between gut microbiota and erysipelas. Instrumental variables (IVs) were identified using a comprehensive set of screening methods. We then performed MR analyses primarily using the Inverse Variance Weighted (IVW) method, complemented by alternative approaches such as MR Egger, weighted median, simple mode, and weighted mode. A series of sensitivity analyses, including Cochran's Q test, MR-Egger intercept test, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test, and a leave-one-out test, were executed to ensure the robustness and validity of our findings. Results: We identified potential associations between erysipelas and various gut microbiota, including Alcaligenaceae (OR 1.23; 95% CI 1.06-1.43; p=0.006), Rikenellaceae (OR 0.77; 95% CI 0.67-0.90; p=0.001), and others. Notably, associations with Actinomyces, Lachnospiraceae NC2004 group, Ruminiclostridium 9, Ruminococcaceae UCG014, Odoribacter, and Actinobacteria were also observed. Sensitivity analyses confirmed the robustness of these associations. Conclusion: Our MR analysis suggests both potentially beneficial and harmful causal relationships between various gut microbiota and the incidence of erysipelas. This study provides new theoretical and empirical insights into the pathogenesis of erysipelas and underscores the potential for innovative preventive and therapeutic approaches.

Jian Gan powder ameliorates immunological liver injury in mice by modulating the gut microbiota and metabolic profiles.

BACKGROUND: Immunological liver injury (ILI) is a common liver disease associated with the microbiota-gut-liver axis. Jian Gan powder (JGP) exhibits both protective and therapeutic effects on hepatitis virus-induced ILI in the clinic. However, the underlying mechanisms remain elusive. The aim of this study is to investigate the hepatoprotective effects and associated mechanisms of JGP in the context of gut microbiota, utilizing a mouse model of ILI. METHODS: The mouse model was established employing Bacillus Calmette-Guérin (BCG) plus lipopolysaccharide (LPS). Following treatment with JGP (7.5, 15, or 30 g/kg), serum, liver, and fresh fecal samples were analyzed. 16S rRNA gene sequencing and untargeted metabolomics profiling were performed to assess the role of JGP on the gut microbiota and its metabolites. RESULTS: JGP treatment markedly reduced serum IFN-γ, IL-6, IL-22, and hepatic p-STAT3 (phosphorylated transducer and activator of transcription-3) expression. In contrast, JGP increased the percentage of proliferating cell nuclear antigen-positive liver cells in treated mice. Fecal 16S rRNA gene sequencing revealed that JGP treatment restored the levels of Alloprevotella, Burkholderia-Caballeronia-Paraburkholderia, Muribaculum, Streptococcus, and Stenotrophomonas. Additionally, metabolomics analysis of fecal samples showed that JGP restored the levels of allylestrenol, eplerenone, phosphatidylethanolamine (PE) (P-20:0/0:0), sphingomyelin (SM) d27:1, soyasapogenol C, chrysin, and soyasaponin I. CONCLUSIONS: JGP intervention improves ILI by restoring gut microbiota and modifying its metabolic profiles. These results provide a novel insight into the mechanism of JGP in treating ILI and the scientific basis to support its clinical application.

Blood lipids mediate the effects of gut microbiome on endometriosis: a mendelian randomization study.

BACKGROUND: There is evidence for an association between the gut microbiome and endometriosis. However, their causal relationship and the mediating role of lipid metabolism remain unclear. METHODS: Using genome-wide association study (GWAS) data, we conducted a bidirectional Mendelian randomization (MR) analysis to investigate the causal relationships between gut microbiome and endometriosis. The inverse variance weighted (IVW) method was used as the primary model, with other MR models used for comparison. Sensitivity analysis based on different statistical assumptions was used to evaluate whether the results were robust. A two-step MR analysis was further conducted to explore the mediating effects of lipids, by integrating univariable MR and the multivariate MR method based on the Bayesian model averaging method (MR-BMA). RESULTS: We identified four possible intestinal bacteria genera associated with the risk of endometriosis through the IVW method, including Eubacterium ruminantium group (odds ratio [OR] = 0.881, 95% CI: 0.795-0.976, P = 0.015), Anaerotruncus (OR = 1.252, 95% CI: 1.028-1.525, P = 0.025), Olsenella (OR = 1.110, 95% CI: 1.007-1.223, P = 0.036), and Oscillospira (OR = 1.215, 95% CI: 1.014-1.456, P = 0.035). The further two-step MR analysis identified that the effect of Olsenella on endometriosis was mediated by triglycerides (proportion mediated: 3.3%; 95% CI = 1.5-5.1%). CONCLUSION: This MR study found evidence for specific gut microbiomes associated with the risk of endometriosis, which might partially be mediated by triglycerides.

Association between gut microbiota and pan-dermatological diseases: a bidirectional Mendelian randomization research.

Background: Gut microbiota has been associated with dermatological problems in earlier observational studies. However, it is unclear whether gut microbiota has a causal function in dermatological diseases. Methods: Thirteen dermatological diseases were the subject of bidirectional Mendelian randomization (MR) research aimed at identifying potential causal links between gut microbiota and these diseases. Summary statistics for the Genome-Wide Association Study (GWAS) of gut microbiota and dermatological diseases were obtained from public datasets. With the goal of evaluating the causal estimates, five acknowledged MR approaches were utilized along with multiple testing corrections, with inverse variance weighted (IVW) regression serving as the main methodology. Regarding the taxa that were causally linked with dermatological diseases in the forward MR analysis, reverse MR was performed. A series of sensitivity analyses were conducted to test the robustness of the causal estimates. Results: The combined results of the five MR methods and sensitivity analysis showed 94 suggestive and five significant causal relationships. In particular, the genus Eubacterium_fissicatena_group increased the risk of developing psoriasis vulgaris (odds ratio [OR] = 1.32, pFDR = 4.36 × 10-3), family Bacteroidaceae (OR = 2.25, pFDR = 4.39 × 10-3), genus Allisonella (OR = 1.42, pFDR = 1.29 × 10-2), and genus Bacteroides (OR = 2.25, pFDR = 1.29 × 10-2) increased the risk of developing acne; and the genus Intestinibacter increased the risk of urticaria (OR = 1.30, pFDR = 9.13 × 10-3). A reverse MR study revealed insufficient evidence for a significant causal relationship. In addition, there was no discernible horizontal pleiotropy or heterogeneity. Conclusion: This study provides novel insights into the causality of gut microbiota in dermatological diseases and therapeutic or preventive paradigms for cutaneous conditions.

Atherosclerosis, gut microbiome, and exercise in a meta-omics perspective: a literature review.

Background: Cardiovascular diseases are the leading cause of death worldwide, significantly impacting public health. Atherosclerotic cardiovascular diseases account for the majority of these deaths, with atherosclerosis marking the initial and most critical phase of their pathophysiological progression. There is a complex relationship between atherosclerosis, the gut microbiome's composition and function, and the potential mediating role of exercise. The adaptability of the gut microbiome and the feasibility of exercise interventions present novel opportunities for therapeutic and preventative approaches. Methodology: We conducted a comprehensive literature review using professional databases such as PubMed and Web of Science. This review focuses on the application of meta-omics techniques, particularly metagenomics and metabolomics, in studying the effects of exercise interventions on the gut microbiome and atherosclerosis. Results: Meta-omics technologies offer unparalleled capabilities to explore the intricate connections between exercise, the microbiome, the metabolome, and cardiometabolic health. This review highlights the advancements in metagenomics and metabolomics, their applications in research, and examines how exercise influences the gut microbiome. We delve into the mechanisms connecting these elements from a metabolic perspective. Metagenomics provides insight into changes in microbial strains post-exercise, while metabolomics sheds light on the shifts in metabolites. Together, these approaches offer a comprehensive understanding of how exercise impacts atherosclerosis through specific mechanisms. Conclusions: Exercise significantly influences atherosclerosis, with the gut microbiome serving as a critical intermediary. Meta-omics technology holds substantial promise for investigating the gut microbiome; however, its methodologies require further refinement. Additionally, there is a pressing need for more extensive cohort studies to enhance our comprehension of the connection among these element.

Integrative metagenomic analysis reveals distinct gut microbial signatures related to obesity.

Obesity is a metabolic disorder closely associated with profound alterations in gut microbial composition. However, the dynamics of species composition and functional changes in the gut microbiome in obesity remain to be comprehensively investigated. In this study, we conducted a meta-analysis of metagenomic sequencing data from both obese and non-obese individuals across multiple cohorts, totaling 1351 fecal metagenomes. Our results demonstrate a significant decrease in both the richness and diversity of the gut bacteriome and virome in obese patients. We identified 38 bacterial species including Eubacterium sp. CAG:274, Ruminococcus gnavus, Eubacterium eligens and Akkermansia muciniphila, and 1 archaeal species, Methanobrevibacter smithii, that were significantly altered in obesity. Additionally, we observed altered abundance of five viral families: Mesyanzhinovviridae, Chaseviridae, Salasmaviridae, Drexlerviridae, and Casjensviridae. Functional analysis of the gut microbiome indicated distinct signatures associated to obesity and identified Ruminococcus gnavus as the primary driver for function enrichment in obesity, and Methanobrevibacter smithii, Akkermansia muciniphila, Ruminococcus bicirculans, and Eubacterium siraeum as functional drivers in the healthy control group. Additionally, our results suggest that antibiotic resistance genes and bacterial virulence factors may influence the development of obesity. Finally, we demonstrated that gut vOTUs achieved a diagnostic accuracy with an optimal area under the curve of 0.766 for distinguishing obesity from healthy controls. Our findings offer comprehensive and generalizable insights into the gut bacteriome and virome features associated with obesity, with the potential to guide the development of microbiome-based diagnostics.

Longitudinal multi-omics analysis uncovers the altered landscape of gut microbiota and plasma metabolome in response to high altitude.

BACKGROUND: Gut microbiota is significantly influenced by altitude. However, the dynamics of gut microbiota in relation to altitude remains undisclosed. METHODS: In this study, we investigated the microbiome profile of 610 healthy young men from three different places in China, grouped by altitude, duration of residence, and ethnicity. We conducted widely targeted metabolomic profiling and clinical testing to explore metabolic characteristics. RESULTS: Our findings revealed that as the Han individuals migrated from low altitude to high latitude, the gut microbiota gradually converged towards that of the Tibetan populations but reversed upon returning to lower altitude. Across different cohorts, we identified 51 species specifically enriched during acclimatization and 57 species enriched during deacclimatization to high altitude. Notably, Prevotella copri was found to be the most enriched taxon in both Tibetan and Han populations after ascending to high altitude. Furthermore, significant variations in host plasma metabolome and clinical indices at high altitude could be largely explained by changes in gut microbiota composition. Similar to Tibetans, 41 plasma metabolites, such as lactic acid, sphingosine-1-phosphate, taurine, and inositol, were significantly elevated in Han populations after ascending to high altitude. Germ-free animal experiments demonstrated that certain species, such as Escherichia coli and Klebsiella pneumoniae, which exhibited altitude-dependent variations in human populations, might play crucial roles in host purine metabolism. CONCLUSIONS: This study provides insights into the dynamics of gut microbiota and host plasma metabolome with respect to altitude changes, indicating that their dynamics may have implications for host health at high altitude and contribute to host adaptation. Video Abstract.