Gut microbiome and serum metabolome alterations in isolated dystonia

Abstract Background Dystonia is a complex neurological movement disorder characterised by involuntary muscle contractions. The relationship between the gut microbiota and isolated dystonia remains poorly explored. Methods We collected faeces and blood samples to study the microbiome and the serum metabolome from a cohort of 57 drug-naïve isolated dystonia patients and 27 age- and environment-matched healthy individuals. We first sequenced the V4 regions of the 16S rDNA gene from all faeces samples. Further, we performed metagenomic sequencing of gut microbiome and non-targeted metabolomics profiling of serum from dystonia patients with significant dysbiosis. Results Gut microbial β-diversity was significantly different, with a more heterogeneous community structure among dystonia individuals than healthy controls, while no difference in α-diversity was found. Gut microbiota in dystonia patients was enriched with Blautia obeum, Dorea longicatena and Eubacterium hallii, but depleted with Bacteroides vulgatus and Bacteroides plebeius. Metagenomic sequencing revealed that genes related to the citrate cycle, vitamin B6 and glycan metabolism were less abundant in dystonia, while genes linked to purine and tryptophan biosynthesis were more abundant. Serum metabolome analysis revealed altered levels of tyrosine and glutamate. The integrative analysis of the gut microbiome and serum metabolomics identified dystonia-associated gut microbial species linked to changes in serum metabolites, reflecting the effect of the gut microbiome on metabolic activity in isolated dystonia. Conclusion This study is the first to reveal gut microbial dysbiosis in dystonia patients. Our findings identified previously unknown links between intestinal microbiota alterations, circulating amino acids and dystonia, providing new insight into the pathogenesis of isolated dystonia.

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Gut microbiota differs between children with Inflammatory Bowel Disease and healthy siblings in taxonomic and functional composition: a metagenomic analysis

AJP Gastrointestinal and Liver Physiology ◽

10.1152/ajpgi.00293.2016 ◽

2017 ◽

Vol 312 (4) ◽

pp. G327-G339 ◽

Cited By ~ 35

Author(s):

Rebecca L. Knoll ◽

Kristoffer Forslund ◽

Jens Roat Kultima ◽

Claudius U. Meyer ◽

Ulrike Kullmer ◽

...

Keyword(s):

Inflammatory Bowel Disease ◽

Gut Microbiota ◽

Bowel Disease ◽

Virulence Genes ◽

Metagenomic Sequencing ◽

Fecal Microbiome ◽

Microbial Dysbiosis ◽

Healthy Siblings ◽

Inflammatory Bowel ◽

Sibling Study

Current treatment for pediatric inflammatory bowel disease (IBD) patients is often ineffective, with serious side effects. Manipulating the gut microbiota via fecal microbiota transplantation (FMT) is an emerging treatment approach but remains controversial. We aimed to assess the composition of the fecal microbiome through a comparison of pediatric IBD patients to their healthy siblings, evaluating risks and prospects for FMT in this setting. A case-control (sibling) study was conducted analyzing fecal samples of six children with Crohn’s disease (CD), six children with ulcerative colitis (UC) and 12 healthy siblings by metagenomic sequencing. In addition, lifetime antibiotic intake was retrospectively determined. Species richness and diversity were significantly reduced in UC patients compared with control [Mann-Whitney U-test false discovery rate (MWU FDR) = 0.011]. In UC, bacteria positively influencing gut homeostasis, e.g., Eubacterium rectale and Faecalibacterium prausnitzii, were significantly reduced in abundance (MWU FDR = 0.05). Known pathobionts like Escherichia coli were enriched in UC patients (MWU FDR = 0.084). Moreover, E. coli abundance correlated positively with that of several virulence genes (SCC > 0.65, FDR < 0.1). A shift toward antibiotic-resistant taxa in both IBD groups distinguished them from controls [MWU Benjamini-Hochberg-Yekutieli procedure (BY) FDR = 0.062 in UC, MWU BY FDR = 0.019 in CD). The collected results confirm a microbial dysbiosis in pediatric UC, and to a lesser extent in CD patients, replicating associations found previously using different methods. Taken together, these observations suggest microbiotal remodeling therapy from family donors, at least for children with UC, as a viable option. NEW & NOTEWORTHY In this sibling study, prior reports of microbial dysbiosis in IBD patients from 16S rRNA sequencing was verified using deep shotgun sequencing and augmented with insights into the abundance of bacterial virulence genes and bacterial antibiotic resistance determinants, seen against the background of data on the specific antibiotic intake of each of the study participants. The observed dysbiosis, which distinguishes patients from siblings, highlights such siblings as potential donors for microbiotal remodeling therapy in IBD.

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Integrative analysis of the gut microbiome and metabolome in a rat model with stress induced irritable bowel syndrome

Scientific Reports ◽

10.1038/s41598-021-97083-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yue Hu ◽

Fang Chen ◽

Haiyong Ye ◽

Bin Lu

Keyword(s):

Irritable Bowel Syndrome ◽

Gut Microbiota ◽

Rat Model ◽

Gut Microbiome ◽

16S Rrna Gene Sequencing ◽

Metabolic Phenotype ◽

Control Group ◽

Rrna Gene ◽

Microbial Dysbiosis ◽

Irritable Bowel

AbstractStress is one of the major causes of irritable bowel syndrome (IBS), which is well-known for perturbing the microbiome and exacerbating IBS-associated symptoms. However, changes in the gut microbiome and metabolome in response to colorectal distention (CRD), combined with restraint stress (RS) administration, remains unclear. In this study, CRD and RS stress were used to construct an IBS rat model. The 16S rRNA gene sequencing was used to characterize the microbiota in ileocecal contents. UHPLC-QTOF-MS/MS assay was used to characterize the metabolome of gut microbiota. As a result, significant gut microbial dysbiosis was observed in stress-induced IBS rats, with the obvious enrichment of three and depletion of 11 bacterial taxa in IBS rats, when compared with those in the control group (q < 0.05). Meanwhile, distinct changes in the fecal metabolic phenotype of stress-induced IBS rats were also found, including five increased and 19 decreased metabolites. Furthermore, phenylalanine, tyrosine and tryptophan biosynthesis were the main metabolic pathways induced by IBS stress. Moreover, the altered gut microbiota had a strong correlation with the changes in metabolism of stress-induced IBS rats. Prevotella bacteria are correlated with the metabolism of 1-Naphthol and Arg.Thr. In conclusion, the gut microbiome, metabolome and their interaction were altered. This may be critical for the development of stress-induced IBS.

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Yoghurt Consumption is Associated With Transient Changes in the Composition of the Human Gut Microbiome

10.21203/rs.3.rs-99718/v1 ◽

2020 ◽

Author(s):

Caroline Ivanne Le Roy ◽

Alexander Kurilshikov ◽

Emily Leeming ◽

Alessia Visconti ◽

Ruth Bowyer ◽

...

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

Visceral Fat ◽

Gut Microbiome ◽

Body Weight Gain ◽

Healthy Eating Index ◽

Rrna Gene ◽

Metagenomic Sequencing ◽

Sequencing Data ◽

Shotgun Metagenomic Sequencing

Abstract Background: Yoghurt contains live bacteria that could contribute via modulation of the gut microbiota to its reported beneficial effects such as reduced body weight gain and lower incidence of type 2 diabetes. To date, the association between yoghurt consumption and the composition of the gut microbiota is underexplored. Here we used clinical variables, metabolomics, 16S rRNA and shotgun metagenomic sequencing data collected on over 1000 predominantly female UK twins to define the link between the gut microbiota and yoghurt-associated health benefits. Results: According to food frequency questionnaires (FFQ), 73% of subjects consumed yoghurt. Consumers presented a healthier diet pattern (healthy eating index: beta = 2.17±0.34; P = 2.72x10-10) and improved metabolic health characterised by reduced visceral fat (beta = -28.18±11.71 g; P = 0.01). According to 16S rRNA gene analyses and whole shotgun metagenomic sequencing approach consistent taxonomic variations were observed with yoghurt consumption. More specifically, we identified higher abundance of species used as yoghurt starters Streptococcus thermophilus (beta = 0.41±0.051; P = 6.14x10-12) and sometimes added Bifidobacterium animalis subsp. lactis (beta = 0.30±0.052; P = 1.49x10-8) in the gut of yoghurt consumers. Replication in 1103 volunteers from the LifeLines-DEEP cohort confirmed the increase of S. thermophilus among yoghurt consumers. Using food records collected the day prior to faecal sampling we showed that increase in these two yoghurt bacteria could be transient. Metabolomics analysis revealed that B. animalis subsp. lactis was associated with 13 faecal metabolites including a 3-hydroxyoctanoic acid, known to be involved in the regulation of gut inflammation.Conclusions: Yoghurt consumption is associated with reduced visceral fat mass and changes in gut microbiome including transient increase of yoghurt-contained species (i.e. S. thermophilus and B. lactis).

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Prospective correlation between the patient microbiome with response to and development of immune-mediated adverse effects to immunotherapy in lung cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e21024 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e21024-e21024

Author(s):

Justin Chau ◽

Meeta Yadav ◽

Ben Liu ◽

Muhammad Furqan ◽

Qun Dai ◽

...

Keyword(s):

Lung Cancer ◽

Gut Microbiota ◽

Treatment Response ◽

Gut Microbiome ◽

Operational Taxonomic Unit ◽

Geographic Region ◽

Organ Function ◽

Immune Mediated ◽

Α Diversity ◽

Clinical Trial Information

e21024 Background: Though the gut microbiome has been associated with immunotherapy (ICI) efficacy in certain cancers, similar correlations between microbiomes at other body sites with treatment response and immune related adverse events (irAEs) in lung cancer (LC) patients receiving ICIs have not been made. We designed a prospective cohort study conducted from 2018-2020 at a single-center academic institution to assess for correlations between the microbiome in various body sites with treatment response and development of irAEs in LC patients treated with ICIs. Methods: Patients with histopathologically confirmed, unresectable/advanced/metastatic LC planned to undergo ICI-based therapy were enrolled between September 2018 and June 2019. Patients must have had measurable disease, ECOG 0-2, and good organ function to be included. Data was collected for analysis from January 2019 to October 2020. Nasal, buccal and gut microbiome samples were obtained prior to ICI initiation, at development of irAEs, improvement of irAEs to grade 1 or less, and at disease progression. 16S rRNA sequenced data was mapped to the SILVA 13.2 database; operational taxonomic unit clusters were analyzed using MicrobiomeAnalyst and METAGENassist. Results: 37 patients were enrolled, and 34 patients were evaluable for this report. 32 healthy controls (HC) from the same geographic region were included to compare baseline gut microbiota. Compared to HC, LC gut microbiota exhibited significantly lower α-diversity. The gut microbiome of patients who did not suffer irAEs were found to have relative enrichment of Bifidobacterium ( p = 0.001) and Desulfovibrio ( p = 0.0002). Responders to combined chemoimmunotherapy exhibited increased Clostridiales ( p = 0.018) but reduced Rikenellaceae ( p = 0.016). In responders to chemoimmunotherapy we also observed enrichment of Finegoldia in nasal microbiome, and increased Megasphaera but reduced Actinobacillus in buccal samples. Longitudinal samples exhibited a trend of α-diversity and certain microbial changes during the development and resolution of irAEs. Conclusions: This pilot study identified significant differences in the gut microbiome between HC and LC patients, and correlates specific bacterial genera to ICI response and irAEs in LC. In addition, it suggests potential predictive utility in nasal and buccal microbiomes, warranting further validation with a larger cohort and mechanistic dissection using preclinical models. Clinical trial information: NCT03688347.

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Duration of Persistent Atrial Fibrillation Is Associated with Alterations in Human Gut Microbiota and Metabolic Phenotypes

mSystems ◽

10.1128/msystems.00422-19 ◽

2019 ◽

Vol 4 (6) ◽

Cited By ~ 4

Author(s):

Kun Zuo ◽

Jing Li ◽

Pan Wang ◽

Ye Liu ◽

Zheng Liu ◽

...

Keyword(s):

Atrial Fibrillation ◽

Gut Microbiota ◽

Early Stage ◽

Persistent Atrial Fibrillation ◽

Metabolic Profiles ◽

Metagenomic Sequencing ◽

Microbial Function ◽

Distinct Structure ◽

The Common ◽

The Relationship

ABSTRACT Atrial fibrillation (AF) has been shown to be associated with disordered gut microbiota (GM). The underlying factors governing persistent AF (psAF) are not well understood, and the association between AF duration and GM profiles remains to be characterized. Thus, the present study aimed at investigating the dysbiosis of GM in patients with short and long psAF duration and illuminating the relationship between the GM and psAF maintenance. Based on metagenomic sequencing and metabolomic analyses, we assessed the metabolic and GM signature in 12 patients with psAF of <12 months (Pers<12m), eight patients with psAF of >12 months (Pers>12m), and 20 controls. We found that the GM in patients with both Pers<12m and Pers>12m was significantly perturbed, with an elevated microbial diversity, distinct structure, and discrepant composition. Although Pers<12m and Pers>12m patients shared a large number of common bacteria with controls, including 84 genera and 404 species, certain bacteria were differently enriched at different AF durations. Furthermore, disturbance in gut microbial function and GM-linked metabolic alterations were detected in both the Pers<12m and Pers>12m groups. The connection of GM and metabolites with psAF is consistent with interaction and potential modulation of host metabolic pathways due to GM dysbiosis with AF persistence. Our results showed that patients of the Pers<12m and Pers>12m groups shared many common disordered GM and metabolic features, which might occur in early disease, while prolonged psAF duration was related to certain unique alterations. Preventative strategies targeting GM and microbial metabolites for early intervention to treat AF patients are highly warranted. IMPORTANCE Atrial fibrillation was associated with a disordered gut microbiota in previous research. However, the gut microbiota signature of patients at different stages of atrial fibrillation remains largely unknown. We sought to determine whether the shift in the gut microbiota and metabolic profiles occurs early and remains stable or develops gradually during atrial fibrillation. We found that patients with persistent atrial fibrillation of <12 months and persistent atrial fibrillation of >12 months shared most of the common features of gut microbiota dysbiosis. However, some distinctive and progressive alterations in the gut microbiota and metabolic structure, which may contribute to the progression of atrial fibrillation, were identified. The present study provides a comprehensive description of the dysbiotic gut microbiota and metabolic profiles in patients of short and long persistent atrial fibrillation, and our findings may help identify therapeutic strategies targeting the gut microbiota to treat atrial fibrillation at an early stage.

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The Effect of Probiotics Supplementation on the Gut Microbiome of Healthy Dogs Assessed Using Metagenomic Sequencing: A Randomized Control Trial

Current Developments in Nutrition ◽

10.1093/cdn/nzaa062_048 ◽

2020 ◽

Vol 4 (Supplement_2) ◽

pp. 1591-1591

Author(s):

Jirayu Tanprasertsuk ◽

Justin Shmalberg ◽

Aashish Jha ◽

LeeAnn Perry ◽

Ryan Honaker

Keyword(s):

Health Outcomes ◽

Gut Microbiome ◽

Randomized Control Trial ◽

Gastrointestinal Diseases ◽

Metagenomic Sequencing ◽

Β Diversity ◽

Α Diversity ◽

Stool Samples ◽

Healthy Dogs ◽

Randomized Control

Abstract Objectives Dogs share similar gut microbiome (GM) with humans, making them a great model for investigating the effects of probiotics (PR) on GM and health. This randomized control trial examined changes in MB and health outcomes in household dogs after PR supplementation. Methods All dogs recruited were fed human grade cooked food ≥ 1 mo, not fed any cultured food, PR, prebiotics, or on antibiotics ≥ 3 mo, and absent of major diseases. Dogs were randomized to receive a daily dose of PR (20 billion CFU of L. reuteri, P. acidilactici, E. faecium, L. acidophilus, B. animalis, L. fermentum, L. rhamnosus) or placebo (PL) for 4 weeks. Owners completed a health survey and collected stool samples at baseline and 4 weeks after the intervention in both groups. Additional stool samples were collected 2 weeks after stopping the PR in the PR group. GM profiling was performed with metagenomic sequencing. Results Twenty three dogs in the PR and 19 dogs in the PL group completed the trial (5.6 ± 3.0 y, 69% male). PR had no effect on α-diversity. As compared to baseline, changes in β-diversity at the species level in 4.3% of GM were significantly affected by PR at week 4 (P < 0.001) but not at week 6. A significant increase (adj P < 0.01) for ≥ 2-fold in abundance was observed at week 4 as compared to baseline for 41 bacterial taxa, 29 (71%) of which belong in the Lactobacillus genus. The abundance of E. coli also decreased at week 4 in the PR group (2.8 folds, adj P < 0.01). The abundance of these taxa returned to baseline at week 6. Such changes in diversity or abundance were not observed with PL. Dogs fed PR tended to be at a lower risk of diarrhea during the trial (0% vs 16%, P = 0.08). No change in other health outcomes was observed. Conclusions Oral PR supplementation has a small but significant effect on GM in healthy dogs. Findings warrant further investigation with longer duration in populations at a higher risk of gastrointestinal diseases. Funding Sources NomNomNow Inc.

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Dysbiosis of gut microbiota and its correlation with dysregulation of cytokines in psoriasis patients

10.21203/rs.3.rs-50642/v2 ◽

2021 ◽

Author(s):

Xinyue Zhang ◽

Kun Guo ◽

Linjing Shi ◽

Ting Sun ◽

Songmei Geng

Keyword(s):

Gut Microbiota ◽

Relative Abundance ◽

Gut Microbiome ◽

High Throughput Sequencing ◽

Interleukin 2 ◽

Negative Relationship ◽

Healthy Individuals ◽

Microbial Composition ◽

Microbiome Composition ◽

The Relationship

Abstract Background: Psoriasis is an inflammatory skin disease associated with multiple comorbidities and substantially diminishes patients’ quality of life. The gut microbiome has become a hot topic in psoriasis as it has been shown to affect both allergy and autoimmunity diseases in recent studies. Our objective was to identify differences in the fecal microbial composition of patients with psoriasis compared with healthy individuals to unravel the microbiota profiling in this autoimmune disease.Results: We collected fecal samples from 30 psoriasis patients and 30 healthy controls, sequenced them by 16S rRNA high-throughput sequencing, and identified the gut microbial composition using bioinformatic analyses including Quantitative Insights into Microbial Ecology (QIIME) and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). Our results showed that different relative abundance of certain bacterial taxa between psoriasis patients and healthy individuals, including Faecalibacterium and Megamonas, were increased in patients with psoriasis. It’s also implicated that many cytokines act as main effect molecules in the pathology of psoriasis. We selected the inflammation-related indicators that were abnormal in psoriasis patients and found the microbiome variations were associated with the level of them, especially interleukin-2 receptor showed a positive relationship with Phascolarctobacterium and a negative relationship with the dialister. The relative abundance of Phascolarctobacterium and dialister can be regard as predictors of psoriasis activity. The correlation analysis based on microbiota and Inflammation-related indicators showed that microbiota dysbiosis might induce an abnormal immune response in psoriasis. Conclusions: We concluded that the gut microbiome composition in psoriasis patients has been altered markedly and provides evidence to understand the relationship between gut microbiota and psoriasis. More mechanistic experiments are needed to determine whether the differences observed in gut microbiota are the cause or consequences of psoriasis and whether the relationship between gut microbiota and cytokines was involved.

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An online atlas of human plasma metabolite signatures of gut microbiome composition

10.1101/2021.12.23.21268179 ◽

2021 ◽

Author(s):

Koen F. Dekkers ◽

Sergi Sayols-Baixeras ◽

Gabriel Baldanzi ◽

Christoph Nowak ◽

Ulf Hammar ◽

...

Keyword(s):

Gut Microbiota ◽

Gut Microbiome ◽

High Performance ◽

Alpha Diversity ◽

Plasma Metabolites ◽

Uremic Toxin ◽

Metagenomic Sequencing ◽

Microbiome Composition ◽

Plasma Metabolite

The human gut microbiota produces a variety of small compounds, some of which enter the bloodstream and impact host health. Conversely, various exogenous nutritional and pharmaceutical compounds affect the gut microbiome composition before entering circulation. Characterization of the gut microbiota—host plasma metabolite interactions is an important step towards understanding the effects of the gut microbiota on human health. However, studies involving large and deeply phenotyped cohorts that would reveal such meaningful interactions are scarce. Here, we used deep metagenomic sequencing and ultra-high-performance liquid chromatography linked to mass spectrometry for detailed characterization of the fecal microbiota and plasma metabolome, respectively, of 8,584 participants invited at age 50 to 64 of the Swedish CArdioPulmonary bioImage Study (SCAPIS). After adjusting for multiple comparisons, we identified 1,008 associations between species alpha diversity and plasma metabolites, and 318,944 associations between specific gut metagenomic species and plasma metabolites. The gut microbiota explained up to 50% of the variance of individual plasma metabolites (mean of 4.7%). We present all results as the searchable association atlas "GUTSY" as a rich resource for mining associations, and exemplify the potential of the atlas by presenting novel associations between oral medication and the gut microbiome, and microbiota species strongly associated with levels of the uremic toxin p-cresol sulfate. The association atlas can be used as the basis for targeted studies of perturbation of specific bacteria and for identification of candidate plasma biomarkers of gut flora composition.

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Analyzing Type 2 Diabetes Associations with the Gut Microbiome in Individuals from Two Ethnic Backgrounds Living in the Same Geographic Area

Nutrients ◽

10.3390/nu13093289 ◽

2021 ◽

Vol 13 (9) ◽

pp. 3289

Author(s):

Manon Balvers ◽

Mélanie Deschasaux ◽

Bert-Jan van den Born ◽

Koos Zwinderman ◽

Max Nieuwdorp ◽

...

Keyword(s):

Type 2 Diabetes ◽

Gut Microbiota ◽

South Asian ◽

Gut Microbiome ◽

Geographical Area ◽

Microbiota Composition ◽

Α Diversity ◽

Functional Pathways ◽

Gut Microbiota Composition

It is currently unknown whether associations between gut microbiota composition and type 2 diabetes (T2D) differ according to the ethnic background of individuals. Thus, we studied these associations in participants from two ethnicities characterized by a high T2D prevalence and living in the same geographical area, using the Healthy Life In Urban Settings (HELIUS) study. We included 111 and 128 T2D participants on metformin (Met-T2D), 78 and 49 treatment-naïve T2D (TN-T2D) participants, as well as a 1:1 matched group of healthy controls from, respectively, African Surinamese and South-Asian Surinamese descent. Fecal microbiome profiles were obtained through 16S rRNA gene sequencing. Univariate and machine learning analyses were used to explore the associations between T2D and the composition and function of the gut microbiome in both ethnicities, comparing Met-T2D and TN-T2D participants to their respective healthy control. We found a lower α-diversity for South-Asian Surinamese TN-T2D participants but no significant associations between TN-T2D status and the abundance of bacterial taxa or functional pathways. In African Surinamese participants, we did not find any association between TN-T2D status and the gut microbiome. With respect to Met-T2D participants, we identified several bacterial taxa and functional pathways with a significantly altered abundance in both ethnicities. More alterations were observed in South-Asian Surinamese. Some altered taxa and pathways observed in both ethnicities were previously related to metformin use. This included a strong negative association between the abundance of Romboutsia and Met-T2D status. Other bacterial taxa were consistent with previous observations in T2D, including reduced butyrate producers such as Anaerostipes hadrus. Hence, our results highlighted both shared and unique gut microbial biomarkers of Met-T2D in individuals from different ethnicities but living in the same geographical area. Future research using higher-resolution shotgun sequencing is needed to clarify the role of ethnicity in the association between T2D and gut microbiota composition.

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Machine-Learning Model for Resistance/Relapse Prediction in Immune Thrombocytopenia Using Gut Microbiota and Function Signatures

Blood ◽

10.1182/blood-2021-148987 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 18-18

Author(s):

Feng-Qi Liu ◽

Qi Chen ◽

Qingyuan Qu ◽

Xueyan Sun ◽

Qiu-Sha Huang ◽

...

Keyword(s):

Machine Learning ◽

Gut Microbiota ◽

Corticosteroid Therapy ◽

Gut Microbiome ◽

Immune Thrombocytopenia ◽

Corticosteroid Treatment ◽

Metagenomic Sequencing ◽

Chronic Itp ◽

Microbial Biomarkers ◽

And Function

Abstract Introduction Growing evidence has implicated gut microbiota in the pathogenesis of immune thrombocytopenia (ITP). In a previous research study, we found dysbiosis in the phylogenetic composition and function of gut microbiome in ITP and that corticosteroid treatment may have a strong effect on gut microbiota [Sci China Life Sci, 2020]. Corticosteroids have been widely used in the initial treatment of newly diagnosed ITP patients, but most adult patients relapse upon cessation of steroid treatment. Patients on agents in subsequent therapy may improve at any time, but which patients improve and when is unpredictable. The gut microbiome has been increasingly used in the assessment and prediction of immunomodulatory therapy in autoimmune diseases and cellular immunotherapy in cancers. Here, we provide evidence that gut microbiota and function signatures can be used to predict immune thrombocytopenia patients at high risk of relapse/resistance after corticosteroid treatment and to identify patients that are more likely to benefit from TPO-RAs in subsequent therapy. Methods Seventy-five fecal samples from 60 patients with newly diagnosed ITP (60 specimens before corticosteroid therapy and 15 specimens after corticosteroid therapy) and 41 samples from persistent/chronic ITP before and after treatment with TPO-RAs, including eltrombopag and avatrombopag were collected for deep shotgun metagenomic sequencing. To identify the microbial biomarkers related to relapse/resistance after corticosteroid treatment, we constructed a random forest classifier using machine learning to determine the risk of relapse/resistance of a training cohort of 30 patients from baseline samples and validated the classifier for 30 patients. Patients with persistent/chronic ITP were divided into responders and nonresponders according to their response to TPO-RA treatment in subsequent therapy. After identifying the microbial species and functional biomarkers related to the response to TPO-RA therapy, a random forest classifier was constructed using a training set of 20 patients and validated using a validation set of 21 patients. Results We used a metagenomic sequencing technique to investigate the differences among gut microbiota associated with relapse within 3 months of corticosteroid treatment. We observed that the diversity and composition of the microbial community in ITP patients after corticosteroid therapy (Post-C) changed significantly from the baseline (Pre-C), whereas the gut microbiota of the remission group was similar to that of the HC group, which implies that a shift in the gut microbiome could represent a return to homeostasis. To identify the microbial biomarkers related to early relapse after corticosteroid treatment, the Pre-C samples were divided into a remission group and a resistant/relapse group according to the response to corticosteroid therapy within 3 months. Nine significant associations with the microbial species and function were identified between the remission and resistant/relapse groups. A risk index built from this panel of microbes and functional pathways was used to differentiate remission from resistant/relapsed patients based on the baseline characteristics. The receiver operating characteristic (ROC) curve demonstrated that the risk index was a strong predictor of treatment response, with an area under the curve (AUC) of 0.87. Furthermore, to predict the response to TPO-RAs in subsequent therapy, the baseline gut microbiomes of responders and nonresponders before TPO-RA treatment were compared. Patients who responded to treatment exhibited an increase in Ruminococcaceae, Clostridiaceae and Bacteroides compared to nonresponders, with elevated abundance of the phosphotransferase system, tyrosine metabolism and secondary bile acid biosynthesis pathways according to KEGG analysis. Our prediction model based on the gut microbiome for TPO-RA response was robust across the cohorts and showed 89.5% and 79.2% prediction accuracy for persistent/chronic ITP patients in the training and validation sets, respectively. Conclusions The gut microbiome and function signatures based on machine learning analysis are novel potential biomarkers for predicting resistance/relapse after corticosteroid treatment and response to TPO-RAs, which may have important manifestations in the clinical. Disclosures No relevant conflicts of interest to declare.

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