Multi-omics reveals specific host metabolism-microbiome associations in intracerebral hemorrhage

Unravelling the Gut Microbiome Role in Cardiovascular Disease: A Systematic Review and a Meta-Analysis

A notable shift in understanding the human microbiome's influence on cardiovascular disease (CVD) is underway, although the causal association remains elusive. A systematic review and meta-analysis were conducted to synthesise current knowledge on microbial taxonomy and metabolite variations between healthy controls (HCs) and those with CVD. An extensive search encompassing three databases identified 67 relevant studies (2012-2023) covering CVD pathologies from 4707 reports. Metagenomic and metabolomic data, both qualitative and quantitative, were obtained. Analysis revealed substantial variability in microbial alpha and beta diversities. Moreover, specific changes in bacterial populations were shown, including increased Streptococcus and Proteobacteria and decreased Faecalibacterium in patients with CVD compared with HC. Additionally, elevated trimethylamine N-oxide levels were reported in CVD cases. Biochemical parameter analysis indicated increased fasting glucose and triglycerides and decreased total cholesterol and low- and high-density lipoprotein cholesterol levels in diseased individuals. This study revealed a significant relationship between certain bacterial species and CVD. Additionally, it has become clear that there are substantial inconsistencies in the methodologies employed and the reporting standards adhered to in various studies. Undoubtedly, standardising research methodologies and developing extensive guidelines for microbiome studies are crucial for advancing the field.

Application of emerging technologies in ischemic stroke: from clinical study to basic research

Stroke is a primary cause of noncommunicable disease-related death and disability worldwide. The most common form, ischemic stroke, is increasing in incidence resulting in a significant burden on patients and society. Urgent action is thus needed to address preventable risk factors and improve treatment methods. This review examines emerging technologies used in the management of ischemic stroke, including neuroimaging, regenerative medicine, biology, and nanomedicine, highlighting their benefits, clinical applications, and limitations. Additionally, we suggest strategies for technological development for the prevention, diagnosis, and treatment of ischemic stroke.

The role of gut microbiota in cerebrovascular disease and related dementia

In recent years, increasing evidence suggests that commensal microbiota may play an important role not only in health but also in disease including cerebrovascular disease. Gut microbes impact physiology, at least in part, by metabolizing dietary factors and host-derived substrates and then generating active compounds including toxins. The purpose of this current review is to highlight the complex interplay between microbiota, their metabolites. and essential functions for human health, ranging from regulation of the metabolism and the immune system to modulation of brain development and function. We discuss the role of gut dysbiosis in cerebrovascular disease, specifically in acute and chronic stroke phases, and the possible implication of intestinal microbiota in post-stroke cognitive impairment and dementia, and we identify potential therapeutic opportunities of targeting microbiota in this context. LINKED ARTICLES: This article is part of a themed issue From Alzheimer's Disease to Vascular Dementia: Different Roads Leading to Cognitive Decline. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.6/issuetoc.

Effects of continuous intravenous infusion with propofol on intestinal metabolites in rats

Microbial metabolites play an important role in regulating intestinal homeostasis and immune responses. Propofol is a common anesthetic in clinic, but it is not clear whether it affects intestinal metabolites in rats. Tail vein puncture was performed after adaptive feeding for 1 month in eight 2-month-old rats and they were given continuous intravenous infusion of propofol for 3 h. The feces of rats were divided into different groups based on time periods, with before and after anesthesia with propofol on days 1, 3 and 7 labeled as groups P, A1, A3 and A7, respectively. The effect of continuous intravenous infusion with propofol on rat fecal metabolites was determined using the non-targeted metabolomics technique gas chromatography coupled with a time-of-flight mass spectrometer analysis. The types and contents of metabolites in rat feces were changed after continuous intravenous infusion with propofol, but the changes were not statistically significant. The contents of the metabolites 3-hydroxyphenylacetic acid and palmitic acid increased from day 3 to 7, and it was shown that the two metabolites were positively correlated at a statistically significant level. Linoleic acid decreased to its lowest level on day 3, and it returned to pre-anesthesia level on day 7. At the same time, linoleic acid metabolism was a metabolic pathway that was co-enriched 7 days after infusion with propofol. Spearman correlation analysis showed that there was significant correlation between some differential metabolites and differential microorganisms. It was observed that zymosterol 1, cytosin and elaidic acid were negatively correlated with Alloprevotella in the A3 vs. P group. In the A7 vs. P group, cortexolone 3 and coprostan-3-one were positively correlated with Faecalibacterium, whilst aconitic acid was negatively correlated with it. In conclusion, the present study revealed statistically insignificant effects of continuous intravenous propofol on the intestinal metabolites in rats.

Causal association between 637 human metabolites and ovarian cancer: a mendelian randomization study

BACKGROUND

Current evidence suggests a significant association between metabolites and ovarian cancer (OC); however, the causal relationship between the two remains unclear. This study employs Mendelian randomization (MR) to investigate the causal effects between different metabolites and OC.

METHODS

In this study, a total of 637 metabolites were selected as the exposure variables from the Genome-wide Association Study (GWAS) database ( http://gwas.mrcieu.ac.uk/datasets/ ). The OC related GWAS dataset (ieu-b-4963) was chosen as the outcome variable. R software and the TwoSampleMR package were utilized for the analysis in this study. MR analysis employed the inverse variance-weighted method (IVW), MR-Egger and weighted median (WM) for regression fitting, taking into consideration potential biases caused by linkage disequilibrium and weak instrument variables. Metabolites that did not pass the tests for heterogeneity and horizontal pleiotropy were considered to have no significant causal effect on the outcome. Steiger's upstream test was used to determine the causal direction between the exposure and outcome variables.

RESULTS

The results from IVW analysis revealed that a total of 31 human metabolites showed a significant causal effect on OC (P < 0.05). Among them, 9 metabolites exhibited consistent and stable causal effects, which were confirmed by Steiger's upstream test (P < 0.05). Among these 9 metabolites, Androsterone sulfate, Propionylcarnitine, 5alpha-androstan-3beta,17beta-diol disulfate, Total lipids in medium VLDL and Concentration of medium VLDL particles demonstrated a significant positive causal effect on OC, indicating that these metabolites promote the occurrence of OC. On the other hand, X-12,093, Octanoylcarnitine, N2,N2-dimethylguanosine, and Cis-4-decenoyl carnitine showed a significant negative causal association with OC, suggesting that these metabolites can inhibit the occurrence of OC.

CONCLUSIONS

The study revealed the complex effect of metabolites on OC through Mendelian randomization. As promising biomarkers, these metabolites are worthy of further clinical validation.

Genetically predicted causality between gut microbiota, blood metabolites, and intracerebral hemorrhage: a bidirectional Mendelian randomization study

Background

Recent research linked changes in the gut microbiota and serum metabolite concentrations to intracerebral hemorrhage (ICH). However, the potential causal relationship remained unclear. Therefore, the current study aims to estimate the effects of genetically predicted causality between gut microbiota, serum metabolites, and ICH.

Methods

Summary data from genome-wide association studies (GWAS) of gut microbiota, serum metabolites, and ICH were obtained separately. Gut microbiota GWAS (N = 18,340) were acquired from the MiBioGen study, serum metabolites GWAS (N = 7,824) from the TwinsUK and KORA studies, and GWAS summary-level data for ICH from the FinnGen R9 (ICH, 3,749 cases; 339,914 controls). A two-sample Mendelian randomization (MR) study was conducted to explore the causal effects between gut microbiota, serum metabolites, and ICH. The random-effects inverse variance-weighted (IVW) MR analyses were performed as the primary results, together with a series of sensitivity analyses to assess the robustness of the results. Besides, a reverse MR was conducted to evaluate the possibility of reverse causation. To validate the relevant findings, we further selected data from the UK Biobank for analysis.

Results

MR analysis results revealed a nominal association (p < 0.05) between 17 gut microbial taxa, 31 serum metabolites, and ICH. Among gut microbiota, the higher level of genus Eubacterium xylanophilum (odds ratio (OR): 1.327, 95% confidence interval (CI):1.154-1.526; Bonferroni-corrected p = 7.28 × 10-5) retained a strong causal relationship with a higher risk of ICH after the Bonferroni corrected test. Concurrently, the genus Senegalimassilia (OR: 0.843, 95% CI: 0.778-0.915; Bonferroni-corrected p = 4.10 × 10-5) was associated with lower ICH risk. Moreover, after Bonferroni correction, only two serum metabolites remained out of the initial 31 serum metabolites. One of the serum metabolites, Isovalerate (OR: 7.130, 95% CI: 2.648-19.199; Bonferroni-corrected p = 1.01 × 10-4) showed a very strong causal relationship with a higher risk of ICH, whereas the other metabolite was unidentified and excluded from further analysis. Various sensitivity analyses yielded similar results, with no heterogeneity or directional pleiotropy observed.

Conclusion

This two-sample MR study revealed the significant influence of gut microbiota and serum metabolites on the risk of ICH. The specific bacterial taxa and metabolites engaged in ICH development were identified. Further research is required in the future to delve deeper into the mechanisms behind these findings.

Metagenomic analysis reveals a dynamic microbiome with diversified adaptive functions that respond to ovulation regulation in the mouse endometrium

Understanding the microflora inhabiting the reproductive tract is important for a better understanding of female physiology and reproductive health. The endometrial fluid from mice in three reproductive stages (A: Unproductive mice; B: Postovulatory mice; C: Postpartum mice) was extracted for microbial DNA extraction and sequencing. Phenotypic and functional analyses of endometrial microbial enrichment was undertaken using LefSe. The results showed 95 genera and 134 species of microorganisms in the uteri of mice. There were differentially distributed genera, among which Lactobacillus, Enterococcus, and Streptococcus were more abundant in the endometrial fluid of mice in the unproductive group. That of mice in the postovulatory group was colonized with Salmonella enterica and Campylobacter and was mainly enriched in metabolic pathways and steroid biosynthesis. The presence of Chlamydia, Enterococcus, Pseudomonadales, Acinetobacter, and Clostridium in the endometrial fluid of postpartum mice, in addition to the enrichment of the endocrine system and the Apelin and FoxO signaling pathways, resulted in a higher number of pathogenic pathways than in the other two groups. The results showed that the microbial diversity characteristics in the endometrium of mice in different reproductive states differed and that they could be involved in the regulation of animal reproduction through metabolic pathways and steroid biosynthesis, suggesting that reproductive diseases induced by microbial diversity alterations in the regulation of animal reproduction cannot be ignored.

Serum lipidome unravels a diagnostic potential in bile acid diarrhoea

OBJECTIVE

Bile acid diarrhoea (BAD) is debilitating yet treatable, but it remains underdiagnosed due to challenging diagnostics. We developed a blood test-based method to guide BAD diagnosis.

DESIGN

We included serum from 50 treatment-naive patients with BAD diagnosed by gold standard 75selenium homotaurocholic acid test, 56 feature-matched controls and 37 patients with non-alcoholic fatty liver disease (NAFLD). Metabolomes were generated using mass spectrometry covering 1295 metabolites and compared between groups. Machine learning was used to develop a BAD Diagnostic Score (BDS).

RESULTS

Metabolomes of patients with BAD significantly differed from controls and NAFLD. We detected 70 metabolites with a discriminatory performance in the discovery set with an area under receiver-operating curve metric above 0.80. Logistic regression modelling using concentrations of decanoylcarnitine, cholesterol ester (22:5), eicosatrienoic acid, L-alpha-lysophosphatidylinositol (18:0) and phosphatidylethanolamine (O-16:0/18:1) distinguished BAD from controls with a sensitivity of 0.78 (95% CI 0.64 to 0.89) and a specificity of 0.93 (95% CI 0.83 to 0.98). The model was independent of covariates (age, sex, body mass index) and distinguished BAD from NAFLD irrespective of fibrosis stage. BDS outperformed other blood test-based tests (7-alpha-hydroxy-4-cholesten-3-one and fibroblast growth factor 19) currently under development.

CONCLUSIONS

BDS derived from serum metabolites in a single-blood sample showed robust identification of patients with BAD with superior specificity and sensitivity compared with current blood test-based diagnostics.

Intracranial hemorrhage management in the multi-omics era

Intracranial hemorrhage (ICH) is a devastating disorder. Neuroprotective strategies that prevent tissue injury and improve functional outcomes have been identified in multiple animal models of ICH. However, these potential interventions in clinical trials produced generally disappointing results. With progress in omics, studies of omics data, including genomics, transcriptomics, epigenetics, proteomics, metabolomics, and the gut microbiome, may help promote precision medicine. In this review, we focused on introducing the applications of all omics in ICH and shed light on all of the considerable advantages to systematically analyze the necessity and importance of multiple omics technology in ICH.