Altered IgA Response to Gut Bacteria Is Associated with Childhood Asthma in Peru

Methodology for biomarker discovery with reproducibility in microbiome data using machine learning

BACKGROUND

In recent years, human microbiome studies have received increasing attention as this field is considered a potential source for clinical applications. With the advancements in omics technologies and AI, research focused on the discovery for potential biomarkers in the human microbiome using machine learning tools has produced positive outcomes. Despite the promising results, several issues can still be found in these studies such as datasets with small number of samples, inconsistent results, lack of uniform processing and methodologies, and other additional factors lead to lack of reproducibility in biomedical research. In this work, we propose a methodology that combines the DADA2 pipeline for 16s rRNA sequences processing and the Recursive Ensemble Feature Selection (REFS) in multiple datasets to increase reproducibility and obtain robust and reliable results in biomedical research.

RESULTS

Three experiments were performed analyzing microbiome data from patients/cases in Inflammatory Bowel Disease (IBD), Autism Spectrum Disorder (ASD), and Type 2 Diabetes (T2D). In each experiment, we found a biomarker signature in one dataset and applied to 2 other as further validation. The effectiveness of the proposed methodology was compared with other feature selection methods such as K-Best with F-score and random selection as a base line. The Area Under the Curve (AUC) was employed as a measure of diagnostic accuracy and used as a metric for comparing the results of the proposed methodology with other feature selection methods. Additionally, we use the Matthews Correlation Coefficient (MCC) as a metric to evaluate the performance of the methodology as well as for comparison with other feature selection methods.

CONCLUSIONS

We developed a methodology for reproducible biomarker discovery for 16s rRNA microbiome sequence analysis, addressing the issues related with data dimensionality, inconsistent results and validation across independent datasets. The findings from the three experiments, across 9 different datasets, show that the proposed methodology achieved higher accuracy compared to other feature selection methods. This methodology is a first approach to increase reproducibility, to provide robust and reliable results.

Dysbiosis of the gut microbiota as a susceptibility factor for Kawasaki disease

Introduction

Gut microbial imbalance (dysbiosis) has been reported in patients with acute Kawasaki disease (KD). However, no studies have analyzed the gut microbiota while focusing on susceptibility to KD. This study aimed to evaluate whether dysbiosis elevates susceptibility to KD by assessing children with a history of KD.

Methods

Fecal DNA was extracted from 26 children with a history of KD approximately 1 year prior (KD group, 12 boys; median age, 32.5 months; median time from onset, 11.5 months) and 57 age-matched healthy controls (HC group, 35 boys; median age, 36.0 months). 16S rRNA gene analysis was conducted with the Illumina Miseq instrument. Sequence reads were analyzed using QIIME2.

Results

For alpha diversity, Faith's phylogenetic diversity was significantly higher in the KD group. Regarding beta diversity, the two groups formed significantly different clusters based on Bray-Curtis dissimilarity. Comparing microbial composition at the genus level, the KD and HC groups were significantly different in the abundance of two genera with abundance over 1% after Benjamini-Hochberg false discovery rate correction for multiple comparisons. Compared with the HC group, the KD group had higher relative abundance of Ruminococcus gnavus group and lower relative abundance of Blautia.

Discussion and conclusion

Ruminococcus gnavus group reportedly includes pro-inflammatory bacteria. In contrast, Blautia suppresses inflammation via butyrate production. In the predictive functional analysis, the proportion of gut microbiota involved in several pathways was lower in the KD group. Therefore, dysbiosis characterized by distinct microbial diversity and decreased abundance of Blautia in parallel with increased abundance of Ruminococcus gnavus group might be a susceptibility factor for KD.

Paediatric Asthma and the Microbiome: A Systematic Review

Evidence from the literature suggests an association between the microbiome and asthma development. Here, we aimed to identify the current evidence for the association between asthma and the upper airway, lower airway and/or the gut microbiome. An electronic systemic search of PubMed, EBSCO, Science Direct and Web of Science was conducted until February 2022 to identify the eligible studies. The Newcastle–Ottawa Scale and the Systematic Review Centre for Laboratory Animal Experimentation risk of the bias tools were used to assess quality of included studies. Twenty-five studies met the inclusion criteria. Proteobacteria and Firmicutes were identified as being significantly higher in the asthmatic children compared with the healthy controls. The high relative abundance of Veillonella, Prevotella and Haemophilus in the microbiome of the upper airway in early infancy was associated with a higher risk of asthma development later in life. The gut microbiome analyses indicated that a high relative abundance of Clostridium in early childhood might be associated with asthma development later in life. The findings reported here serve as potential microbiome signatures associated with the increased risk of asthma development. There is a need for large longitudinal studies to further identify high-risk infants, which will help in design strategies and prevention mechanisms to avoid asthma early in life.

Intestinal IgA-Coated Bacteria in Healthy- and Altered-Microbiomes (Dysbiosis) and Predictive Value in Successful Fecal Microbiota Transplantation

IgA-coated bacteria in the gut (IgA-biome) provide a homeostatic function in healthy people through inhibition of microbial invaders and by protecting the epithelial monolayer of the gut. The laboratory methods used to detect this group of bacteria require flow cytometry and DNA sequencing (IgA-Seq). With dysbiosis (reduced diversity of the microbiome), the IgA-biome also is impaired. In the presence of enteric infection, oral vaccines, or an intestinal inflammatory disorder, the IgA-biome focuses on the pathogenic bacteria or foreign antigens, while in other chronic diseases associated with dysbiosis, the IgA-biome is reduced in capacity. Fecal microbiota transplantation (FMT), the use of fecal product from well-screened, healthy donors administered to patients with dysbiosis, has been successful in engrafting the intestine with healthy microbiota and metabolites leading to improve health. Through FMT, IgA-coated bacteria have been transferred to recipients retaining their immune coating. The IgA-biome should be evaluated in FMT studies as these mucosal-associated bacteria are more likely to be associated with successful transplantation than free luminal organisms. Studies of the microbiome pre- and post-FMT should employ metagenomic methods that identify bacteria at least at the species level to better identify organisms of interest while allowing comparisons of microbiota data between studies.

Asthma in the Americas: An Update: A Joint Perspective from the Brazilian Thoracic Society, Canadian Thoracic Society, Latin American Thoracic Society, and American Thoracic Society

Asthma affects a large number of people living in the Americas, a vast and diverse geographic region comprising 35 nations in the Caribbean and North, Central, and South America. The marked variability in the prevalence, morbidity, and mortality from asthma across and within nations in the Americas offers a unique opportunity to improve our understanding of the risk factors and management of asthma phenotypes and endotypes in children and adults. Moreover, a better assessment of the causes and treatment of asthma in less economically developed regions in the Americas would help diagnose and treat individuals migrating from those areas to Canada and the United States. In this focused review, we first assess the epidemiology of asthma, review known and potential risk factors, and examine commonalities and differences in asthma management across the Americas. We then discuss future directions in research and health policies to improve the prevention, diagnosis, and management of pediatric and adult asthma in the Americas, including standardized and periodic assessment of asthma burden across the region; large-scale longitudinal studies including omics and comprehensive environmental data on racially and ethnically diverse populations; and dissemination and implementation of guidelines for asthma management across the spectrum of disease severity. New initiatives should recognize differences in socioeconomic development and health care systems across the region while paying particular attention to novel or more impactful risk factors for asthma in the Americas, including indoor pollutants such as biomass fuel, tobacco use, infectious agents and the microbiome, and psychosocial stressor and chronic stress.