Dataset Information

Gut Microbiome and Metabolome Were Altered and Strongly Associated With Platelet Count in Adult Patients With Primary Immune Thrombocytopenia.

ABSTRACT: Gut microbiota has been implicated in the pathogenesis of many autoimmune diseases. This is still an area of active research given that the role of gut microbiota on the primary immune thrombocytopenia (ITP) remains unclear. In this study, fecal samples of 30 untreated adult primary ITP patients and 29 healthy controls (HCs) were used to investigate the gut microbial community and metabolite profiles. Our results show that fecal bacteria such as Blautia, Streptococcus, and Lactobacillus are enriched, whereas bacteria such as Bacteroides are depleted in ITP patients. Notably, fecal metabolites such as fatty acyls and glycerophospholipids are enriched and strongly correlate with discrepant gut microbiota. Furthermore, combinations of Weissella and Streptococcus anginosus, or Cer (t18:0/16:0), Cer (d18:1/17:0), and 13-hydroxyoctadecanoic acid could provide good diagnostic markers for ITP. Moreover, a strong negative correlation was found between platelet count and altered gut microbiota such as S. anginosus and gut metabolites such as Cer (t18:0/16:0) in ITP. In conclusion, dysbiosis of both gut microbiota and metabolome develops in ITP patients compared to HCs. Several ITP-altered gut bacteria and metabolites can be diagnostic biomarkers for ITP, and are highly correlated with platelet count, suggesting that they may also play a role in ITP pathogenesis.

SUBMITTER: Zhang X

PROVIDER: S-EPMC7360729 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Gut Microbiome and Metabolome Were Altered and Strongly Associated With Platelet Count in Adult Patients With Primary Immune Thrombocytopenia.

Zhang Xuewu X Gu Silan S You Liangshun L Xu Yu Y Zhou De Chen Yunbo Y Yan Ren R Jiang Huiyong H Li Yating Y Lv Longxian L Qian Wenbin W

Frontiers in microbiology 20200708

Gut microbiota has been implicated in the pathogenesis of many autoimmune diseases. This is still an area of active research given that the role of gut microbiota on the primary immune thrombocytopenia (ITP) remains unclear. In this study, fecal samples of 30 untreated adult primary ITP patients and 29 healthy controls (HCs) were used to investigate the gut microbial community and metabolite profiles. Our results show that fecal bacteria such as Blautia, Streptococcus, and Lacto ...[more]

PMID: 32733424

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Project description:BACKGROUND:Fibromyalgia is a complex, relatively unknown disease characterised by chronic, widespread musculoskeletal pain. The gut-brain axis connects the gut microbiome with the brain through the enteric nervous system (ENS); its disruption has been associated with psychiatric and gastrointestinal disorders. To gain an insight into the pathogenesis of fibromyalgia and identify diagnostic biomarkers, we combined different omics techniques to analyse microbiome and serum composition. METHODS:We collected faeces and blood samples to study the microbiome, the serum metabolome and circulating cytokines and miRNAs from a cohort of 105 fibromyalgia patients and 54 age- and environment-matched healthy individuals. We sequenced the V3 and V4 regions of the 16S rDNA gene from faeces samples. UPLC-MS metabolomics and custom multiplex cytokine and miRNA analysis (FirePlex™ technology) were used to examine sera samples. Finally, we combined the different data types to search for potential biomarkers. RESULTS:We found that the diversity of bacteria is reduced in fibromyalgia patients. The abundance of the Bifidobacterium and Eubacterium genera (bacteria participating in the metabolism of neurotransmitters in the host) in these patients was significantly reduced. The serum metabolome analysis revealed altered levels of glutamate and serine, suggesting changes in neurotransmitter metabolism. The combined serum metabolomics and gut microbiome datasets showed a certain degree of correlation, reflecting the effect of the microbiome on metabolic activity. We also examined the microbiome and serum metabolites, cytokines and miRNAs as potential sources of molecular biomarkers of fibromyalgia. CONCLUSIONS:Our results show that the microbiome analysis provides more significant biomarkers than the other techniques employed in the work. Gut microbiome analysis combined with serum metabolomics can shed new light onto the pathogenesis of fibromyalgia. We provide a list of bacteria whose abundance changes in this disease and propose several molecules as potential biomarkers that can be used to evaluate the current diagnostic criteria.

Project description:BackgroundThe infant intestinal microbiome plays an important role in metabolism and immune development with impacts on lifelong health. The linkage between the taxonomic composition of the microbiome and its metabolic phenotype is undefined and complicated by redundancies in the taxon-function relationship within microbial communities. To inform a more mechanistic understanding of the relationship between the microbiome and health, we performed an integrative statistical and machine learning-based analysis of microbe taxonomic structure and metabolic function in order to characterize the taxa-function relationship in early life.ResultsStool samples collected from infants enrolled in the New Hampshire Birth Cohort Study (NHBCS) at approximately 6-weeks (n = 158) and 12-months (n = 282) of age were profiled using targeted and untargeted nuclear magnetic resonance (NMR) spectroscopy as well as DNA sequencing of the V4-V5 hypervariable region from the bacterial 16S rRNA gene. There was significant inter-omic concordance based on Procrustes analysis (6 weeks: p = 0.056; 12 months: p = 0.001), however this association was no longer significant when accounting for phylogenetic relationships using generalized UniFrac distance metric (6 weeks: p = 0.376; 12 months: p = 0.069). Sparse canonical correlation analysis showed significant correlation, as well as identifying sets of microbe/metabolites driving microbiome-metabolome relatedness. Performance of machine learning models varied across different metabolites, with support vector machines (radial basis function kernel) being the consistently top ranked model. However, predictive R2 values demonstrated poor predictive performance across all models assessed (avg: - 5.06% -- 6 weeks; - 3.7% -- 12 months). Conversely, the Spearman correlation metric was higher (avg: 0.344-6 weeks; 0.265-12 months). This demonstrated that taxonomic relative abundance was not predictive of metabolite concentrations.ConclusionsOur results suggest a degree of overall association between taxonomic profiles and metabolite concentrations. However, lack of predictive capacity for stool metabolic signatures reflects, in part, the possible role of functional redundancy in defining the taxa-function relationship in early life as well as the bidirectional nature of the microbiome-metabolome association. Our results provide evidence in favor of a multi-omic approach for microbiome studies, especially those focused on health outcomes.

Dataset Information

Gut Microbiome and Metabolome Were Altered and Strongly Associated With Platelet Count in Adult Patients With Primary Immune Thrombocytopenia.

Publications

Gut Microbiome and Metabolome Were Altered and Strongly Associated With Platelet Count in Adult Patients With Primary Immune Thrombocytopenia.

Similar Datasets

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