Dataset Information

Gut microbiota of adults with asthma is broadly similar to non-asthmatics in a large population with varied ethnic origins.

ABSTRACT: Bacterial gut communities might predispose children to develop asthma. Yet, little is known about the role of these micro-organisms in adult asthmatics. We aimed to profile the relationship between fecal microbiota and asthma in a large-scale, ethnically diverse, observational cohort of adults. Fecal microbiota composition of 1632 adults (172 asthmatics and 1460 non-asthmatics) was analyzed using 16S ribosomal RNA gene sequencing. Using extremely randomized trees machine learning models, we assessed the discriminatory ability of gut bacterial features to identify asthmatics from non-asthmatics. Asthma contributed 0.019% to interindividual dissimilarities in intestinal microbiota composition, which was not significant (P = .97). Asthmatics could not be distinguished from non-asthmatics based on individual microbiota composition by an extremely randomized trees classifier model (area under the receiver operating characteristic curve = 0.54). In conclusion, there were no prominent differences in fecal microbiota composition in adult asthmatics when compared to non-asthmatics in an urban, large-sized and ethnically diverse cohort.

SUBMITTER: Kullberg RFJ

PROVIDER: S-EPMC8583066 | biostudies-literature | 2021 Jan-Dec

REPOSITORIES: biostudies-literature

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Gut microbiota of adults with asthma is broadly similar to non-asthmatics in a large population with varied ethnic origins.

Kullberg Robert F J RFJ Haak Bastiaan W BW Abdel-Aziz Mahmoud I MI Davids Mark M Hugenholtz Floor F Nieuwdorp Max M Galenkamp Henrike H Prins Maria M Maitland-van der Zee Anke H AH Wiersinga W Joost WJ

Gut microbes 20210101 1

Bacterial gut communities might predispose children to develop asthma. Yet, little is known about the role of these micro-organisms in adult asthmatics. We aimed to profile the relationship between fecal microbiota and asthma in a large-scale, ethnically diverse, observational cohort of adults. Fecal microbiota composition of 1632 adults (172 asthmatics and 1460 non-asthmatics) was analyzed using 16S ribosomal RNA gene sequencing. Using extremely randomized trees machine learning models, we asse ...[more]

PMID: 34743654

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Project description:BackgroundEmpirical research and health policies on asthma have focused on children and young adults, even though asthma morbidity and mortality are higher among older asthmatics.ObjectiveTo explore the relationship of asthma-related beliefs and self-reported controller medication adherence in older asthmatics.DesignAn observational study of asthma beliefs and self-management among older adults.ParticipantsAsthmatics ages ? 60 years (N?=?324, mean age 67.4 ± 6.8, 28 % white, 32 % black, 30 % Hispanic) were recruited from primary care practices in New York City and Chicago.Main measuresSelf-reported controller medication adherence was assessed using the Medication Adherence Report Scale. Based on the Common Sense Model of Self-Regulation, patients were asked if they believe they only have asthma with symptoms, their physician can cure their asthma, and if their asthma will persist. Beliefs on the benefit, necessity and concerns of treatment use were also assessed. Multivariate logistic regression was used to examine the association of beliefs with self-reported medication adherence.Key resultsThe majority (57.0 %) of patients reported poor adherence. Poor self-reported adherence was more common among those with erroneous beliefs about asthma illness and treatments, including the "no symptoms, no asthma" belief (58.7 % vs. 31.7 %, respectively, p?<?0.001), "will not always have asthma" belief (34.8 % vs. 12.5 %, p?<?0.001), and the "MD can cure asthma" belief (21.7 % vs. 9.6 %, p?=?0.01). Adjusting for illness beliefs, treatment beliefs and demographics, patients with a "no symptoms, no asthma" belief had lower odds of having good self-reported adherence (odds ratio [OR] 0.45, 95 % confidence interval [CI] 0.23-0.86), as did those with negative beliefs about the benefits (OR 0.73, 95 % CI 0.57-0.94) and necessity (OR 0.89, 95 % CI 0.83-0.96) of treatment.ConclusionsIllness and treatment beliefs have a strong influence on self-reported medication adherence in older asthmatics. Interventions to improve medication adherence in older asthmatics by modifying illness and treatment beliefs warrant study.

Project description:BackgroundMultiple studies suggest a potential connection between the gut microbiome and asthma. Our objective is to use advanced genetic and metagenomic techniques to elucidate the causal relationships and underlying mechanisms between gut microbiota and asthma.MethodsThe study utilized comprehensive Linkage Disequilibrium Score Regression (LDSC) and Mendelian randomization (MR) analyses to examine the relationship between 119 gut microbiota genera and asthma, using publicly accessible genome-wide association studies (GWAS). The meta-analysis synthesized summary effect estimates obtained from LDSC, forward MR, and reverse MR. The MiBioGen collaboration, involving 18,340 individuals, identified genetic variations associated with gut bacteria. Asthma data were collected from the UK Biobank, FinnGen, and GERA, encompassing a total of 82,060 cases and 641,049 controls.ResultsLDSC analysis revealed significant negative genetic correlations between asthma and RuminococcaceaeUCG004 (Rg = -0.55, p = 7.66 × 10-5) and Subdoligranulum (Rg = -0.35, p = 3.61 × 10-4). Forward MR analysis suggested associations between Butyricicoccus (OR = 0.92, p = 0.01), Turicibacter (OR = 0.95, p = 0.025), Butyrivibrio (OR = 0.98, p = 0.047), and reduced asthma risk. Conversely, Coprococcus2 (OR = 1.10, p = 0.035) and Roseburia (OR = 1.07, p = 0.039) were associated with increased risk. Reverse MR analysis indicated significant associations between genetically predicted asthma and Eubacteriumxylanophilumgroup (Beta = -0.08, p = 9.25 × 10-7), LachnospiraceaeNK4A136group (Beta = -0.05, p = 1.26 × 10-4), and Eisenbergiella (Beta = 0.06, p = 0.015, Rg_P = 0.043).ConclusionThe findings underscore significant genetic correlations and causal relationships between specific gut microbiota and asthma. These insights highlight the potential of gut microbiota as both markers and modulators of asthma risk, offering new avenues for targeted therapeutic strategies.

Project description:BackgroundType 2 diabetes (T2D), a multifactorial disease influenced by host genetics and environmental factors, is the most common endocrine disease. Several studies have shown that the gut microbiota as a close-up environmental mediator influences host physiology including metabolism. The aim of the present study is to examine the compositional and functional potential of the gut microbiota across individuals from Denmark and South India with a focus on T2D. Many earlier studies have investigated the microbiome aspects of T2D, and it has also been anticipated that such microbial associations would be dependent on diet and ethnic origin. However, there has been no large scale trans-ethnic microbiome study earlier in this direction aimed at evaluating any "universal" microbiome signature of T2D.Methods16S ribosomal RNA gene amplicon sequencing was performed on stool samples from 279 Danish and 294 Indian study participants. Any differences between the gut microbiota of both populations were explored using diversity measures and negative binomial Wald tests. Study samples were stratified to discover global and country-specific microbial signatures for T2D and treatment with the anti-hyperglycemic drug, metformin. To identify taxonomical and functional signatures of the gut microbiota for T2D and metformin treatment, we used alpha and beta diversity measures and differential abundances analysis, comparing metformin-naive T2D patients, metformin-treated T2D patients, and normoglycemic individuals.ResultsOverall, the gut microbial communities of Danes and Indians are compositionally very different. By analyzing the combined study materials, we identify microbial taxonomic and functional signatures for T2D and metformin treatment. T2D patients have an increased relative abundance of two operational taxonomic units (OTUs) from the Lachnospiraceae family, and a decreased abundance of Subdoligranulum and Butyricicoccus. Studying each population per se, we identified T2D-related microbial changes at the taxonomic level within the Danish population only. Alpha diversity indices show that there is no significant difference between normoglycemic individuals and metformin-naive T2D patients, whereas microbial richness is significantly decreased in metformin-treated T2D patients compared to metformin-naive T2D patients and normoglycemic individuals. Enrichment of two OTUs from Bacteroides and depletion of Faecalibacterium constitute a trans-ethnic signature of metformin treatment.ConclusionsWe demonstrate major compositional differences of the gut microbiota between Danish and South Indian individuals, some of which may relate to differences in ethnicity, lifestyle, and demography. By comparing metformin-naive T2D patients and normoglycemic individuals, we identify T2D-related microbiota changes in the Danish and Indian study samples. In the present trans-ethnic study, we confirm that metformin changes the taxonomic profile and functional potential of the gut microbiota.

Project description:BackgroundColorectal cancer (CRC) is a multifactorial disease with genetic and environmental factors. Regional differences in risk factors are an important reason for the different incidences of CRC in different regions.ObjectiveThe goal was to clarify the intestinal microbial composition and structure of CRC patients in different regions and construct CRC risk prediction models based on regional differences.MethodsA metagenomic dataset of 601 samples from 6 countries in the GMrepo and NCBI databases was collected. All whole-genome sequencing (WGS) data were annotated for species by MetaPhlAn2. We obtained the relative abundance of species composition at the species level and genus level. The MicrobiotaProcess package was used to visualize species composition and PCA. LEfSe analysis was used to analyze the differences in the datasets in each region. Spearman correlation analysis was performed for CRC differential species. Finally, the CRC risk prediction model was constructed and verified in each regional dataset.ResultsThe composition of the intestinal bacterial community varied in different regions. Differential intestinal bacteria of CRC in different regions are inconsistent. There was a common diversity of bacteria in all six countries, such as Peptostreptococcus stomatis and Fusobacterium nucleatum at the species level. Peptostreptococcus stomatis (species level) and Peptostreptococcus (genus level) are important CRC-related bacteria that are related to other bacteria in different regions. Region has little influence on the accuracy of the CRC risk prediction model. Peptostreptococcus stomatis is an important variable in CRC risk prediction models in all regions.ConclusionPeptostreptococcus stomatis is a common high-risk pathogen of CRC worldwide, and it is an important variable in CRC risk prediction models in all regions. However, regional differences in intestinal bacteria had no significant impact on the accuracy of the CRC risk prediction model.

Dataset Information

Gut microbiota of adults with asthma is broadly similar to non-asthmatics in a large population with varied ethnic origins.

Publications

Gut microbiota of adults with asthma is broadly similar to non-asthmatics in a large population with varied ethnic origins.

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