Asthma is a complex disease well-suited to metabolomic profiling, both for the development of novel biomarkers and for the improved understanding of pathophysiology. In this review, we summarize the ...21 existing metabolomic studies of asthma in humans, all of which reported significant findings and concluded that individual metabolites and metabolomic profiles measured in exhaled breath condensate, urine, plasma, and serum could identify people with asthma and asthma phenotypes with high discriminatory ability. There was considerable consistency across the studies in terms of the reported biomarkers, regardless of biospecimen, profiling technology, and population age. In particular, acetate, adenosine, alanine, hippurate, succinate, threonine, and trans-aconitate, and pathways relating to hypoxia response, oxidative stress, immunity, inflammation, lipid metabolism and the tricarboxylic acid cycle were all identified as significant in at least two studies. There were also a number of nonreplicated results; however, the literature is not yet sufficiently developed to determine whether these represent spurious findings or reflect the substantial heterogeneity and limited statistical power in the studies and their methods to date. This review highlights the need for additional asthma metabolomic studies to explore these issues, and, further, the need for standardized methods in the way these studies are conducted. We conclude by discussing the potential of translation of these metabolomic findings into clinically useful biomarkers and the crucial role that integrated omics is likely to play in this endeavor.
Recent miRNA Research in Asthma Sharma, Rinku; Tiwari, Anshul; McGeachie, Michael J.
Current allergy and asthma reports,
12/2022, Letnik:
22, Številka:
12
Journal Article
Recenzirano
Odprti dostop
Purpose of Review
The study of microRNA in asthma has revealed a vibrant new level of gene regulation underlying asthma pathology. Several miRNAs have been shown to be important in asthma, ...influencing various biological mechanisms which lead to asthma pathology and symptoms. In addition, miRNAs have been proposed as biomarkers of asthma affection status, asthma severity, and asthma treatment response. We review all recent asthma-miRNA work, while also presenting comprehensive tables of all miRNA results related to asthma.
Recent Findings
We here reviewed 63 recent studies published reporting asthma and miRNA research, and an additional 14 reviews of the same. We summarized the information for both adult and childhood asthma, as well as research on miRNAs in asthma–COPD overlap syndrome (ACOs), and virus-induced asthma exacerbations.
Summary
We attempted to present a comprehensive collection of recently published asthma-associated miRNAs as well as tables of all published asthma-related miRNA results.
Background The gut microbiome in infancy influences immune system maturation, and may have an important impact on allergic disease risk. Objective We sought to determine how prenatal and early life ...factors impact the gut microbiome in a relatively large, ethnically diverse study population of infants at age 3 to 6 months, who were enrolled in Vitamin D Antenatal Asthma Reduction Trial, a clinical trial of vitamin D supplementation in pregnancy to prevent asthma and allergies in offspring. Methods We performed 16S rRNA gene sequencing on 333 infants' stool samples. Microbial diversity was computed using the Shannon index. Factor analysis applied to the top 25 most abundant taxa revealed 4 underlying bacterial coabundance groups; the first dominated by Firmicutes ( Lachnospiraceae / Clostridiales ), the second by Proteobacteria ( Klebsiella / Enterobacter ), the third by Bacteriodetes , and the fourth by Veillonella . Scores for coabundance groups were used as outcomes in regression models, with prenatal/birth and demographic characteristics as independent predictors. Multivariate analysis, using all microbial community members, was also conducted. Results White race/ethnicity was associated with lower diversity but higher Bacteroidetes coabundance scores. C-section birth was associated with higher diversity, but decreased Bacteroidetes coabundance scores. Firmicutes scores were higher for infants born by C-section. Breast-fed infants had lower proportions of Clostridiales . Cord blood vitamin D was linked to increased Lachnobacterium , but decreased Lactococcus. Conclusions The findings presented here suggest that race, mode of delivery, breast-feeding, and cord blood vitamin D levels are associated with infant gut microbiome composition, with possible long-term implications for immune system modulation and asthma/allergic disease incidence.
COPD is a leading cause of mortality.
We hypothesized that applying machine learning to clinical and quantitative CT imaging features would improve mortality prediction in COPD.
We selected 30 ...clinical, spirometric, and imaging features as inputs for a random survival forest. We used top features in a Cox regression to create a machine learning mortality prediction (MLMP) in COPD model and also assessed the performance of other statistical and machine learning models. We trained the models in subjects with moderate to severe COPD from a subset of subjects in Genetic Epidemiology of COPD (COPDGene) and tested prediction performance in the remainder of individuals with moderate to severe COPD in COPDGene and Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). We compared our model with the BMI, airflow obstruction, dyspnea, exercise capacity (BODE) index; BODE modifications; and the age, dyspnea, and airflow obstruction index.
We included 2,632 participants from COPDGene and 1,268 participants from ECLIPSE. The top predictors of mortality were 6-min walk distance, FEV1 % predicted, and age. The top imaging predictor was pulmonary artery-to-aorta ratio. The MLMP-COPD model resulted in a C index ≥ 0.7 in both COPDGene and ECLIPSE (6.4- and 7.2-year median follow-ups, respectively), significantly better than all tested mortality indexes (P < .05). The MLMP-COPD model had fewer predictors but similar performance to that of other models. The group with the highest BODE scores (7-10) had 56% mortality, whereas the highest mortality group defined by the MLMP-COPD model had 62% mortality (P = .046).
An MLMP-COPD model outperformed four existing models for predicting all-cause mortality across two COPD cohorts. Performance of machine learning was similar to that of traditional statistical methods. The model is available online at: https://cdnm.shinyapps.io/cgmortalityapp/.
Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with ...mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.
Circulating microRNAs have shown promise as non-invasive biomarkers and predictors of disease activity. Prior asthma studies using clinical, biochemical and genomic data have not shown excellent ...prediction of exacerbation. We hypothesized that a panel of circulating microRNAs in a pediatric asthma cohort combined with an exacerbation clinical score might predict exacerbation better than the latter alone.
Serum samples from 153 children at randomization in the Childhood Asthma Management Program were profiled for 754 microRNAs. Data dichotomized for asthma exacerbation one year after randomization to inhaled corticosteroid treatment were used for binary logistic regression with miRNA expressions and exacerbation clinical score.
12 of 125 well-detected circulating microRNAs had significant odd ratios for exacerbation with miR-206 being most significant. Each doubling of expression of the 12 microRNA corresponded to a 25-67% increase in exacerbation risk. Stepwise logistic regression yielded a 3-microRNA model (miR-146b, miR-206 and miR-720) that, combined with the exacerbation clinical score, had excellent predictive power with a 0.81 AUROC. These 3 microRNAs were involved in NF-kβ and GSK3/AKT pathways.
This combined circulating microRNA-clinical score model predicted exacerbation in asthmatic subjects on inhaled corticosteroids better than each constituent feature alone.
ClinicalTrials.gov Identifier: NCT00000575 .
Intrauterine smoke (IUS) exposure during early childhood has been associated with a number of negative health consequences, including reduced lung function and asthma susceptibility. The biological ...mechanisms underlying these associations have not been established. MicroRNAs regulate the expression of numerous genes involved in lung development. Thus, investigation of the impact of IUS on miRNA expression during human lung development may elucidate the impact of IUS on post-natal respiratory outcomes. We sought to investigate the effect of IUS exposure on miRNA expression during early lung development. We hypothesized that miRNA-mRNA networks are dysregulated by IUS during human lung development and that these miRNAs may be associated with future risk of asthma and allergy. Human fetal lung samples from a prenatal tissue retrieval program were tested for differential miRNA expression with IUS exposure (measured using placental cotinine concentration). RNA was extracted and miRNA-sequencing was performed. We performed differential expression using IUS exposure, with covariate adjustment. We also considered the above model with an additional sex-by-IUS interaction term, allowing IUS effects to differ by male and female samples. Using paired gene expression profiles, we created sex-stratified miRNA-mRNA correlation networks predictive of IUS using DIABLO. We additionally evaluated whether miRNAs were associated with asthma and allergy outcomes in a cohort of childhood asthma. We profiled pseudoglandular lung miRNA in
= 298 samples, 139 (47%) of which had evidence of IUS exposure. Of 515 miRNAs, 25 were significantly associated with intrauterine smoke exposure (q-value < 0.10). The IUS associated miRNAs were correlated with well-known asthma genes (e.g., ORM1-Like Protein 3,
) and enriched in disease-relevant pathways (oxidative stress). Eleven IUS-miRNAs were also correlated with clinical measures (e.g., Immunoglobulin E andlungfunction) in children with asthma, further supporting their likely disease relevance. Lastly, we found substantial differences in IUS effects by sex, finding 95 significant IUS-miRNAs in male samples, but only four miRNAs in female samples. The miRNA-mRNA correlation networks were predictive of IUS (AUC = 0.78 in males and 0.86 in females) and suggested that IUS-miRNAs are involved in regulation of disease-relevant genes (e.g., A disintegrin and metalloproteinase domain 19 (
, LBH regulator of WNT signaling (
) and sex hormone signaling (Coactivator associated methyltransferase 1(
). Our study demonstrated differential expression of miRNAs by IUS during early prenatal human lung development, which may be modified by sex. Based on their gene targets and correlation to clinical asthma and atopy outcomes, these IUS-miRNAs may be relevant for subsequent allergy and asthma risk. Our study provides insight into the impact of IUS in human fetal lung transcriptional networks and on the developmental origins of asthma and allergic disorders.
Current guidelines do not sufficiently capture the heterogeneous nature of asthma; a more detailed molecular classification is needed. Metabolomics represents a novel and compelling approach to ...derive asthma endotypes (i.e., subtypes defined by functional and/or pathobiological mechanisms).
To validate metabolomic-driven endotypes of asthma and explore their underlying biology.
In the Genetics of Asthma in Costa Rica Study (GACRS), untargeted metabolomic profiling, similarity network fusion, and spectral clustering was used to identify metabo-endotypes of asthma, and differences in asthma-relevant phenotypes across these metabo-endotypes were explored. The metabo-endotypes were recapitulated in the Childhood Asthma Management Program (CAMP), and clinical differences were determined. Metabolomic drivers of metabo-endotype membership were investigated by meta-analyzing findings from GACRS and CAMP.
Five metabo-endotypes were identified in GACRS with significant differences in asthma-relevant phenotypes, including prebronchodilator (p-ANOVA = 8.3 × 10
) and postbronchodilator (p-ANOVA = 1.8 × 10
) FEV
/FVC. These differences were validated in the recapitulated metabo-endotypes in CAMP. Cholesterol esters, trigylcerides, and fatty acids were among the most important drivers of metabo-endotype membership. The findings suggest dysregulation of pulmonary surfactant homeostasis may play a role in asthma severity.
Clinically meaningful endotypes may be derived and validated using metabolomic data. Interrogating the drivers of these metabo-endotypes has the potential to help understand their pathophysiology.
Inhaled corticosteroids (ICS) are key treatments for controlling asthma and preventing asthma attacks. However, the responsiveness to ICS varies among individuals. MicroRNAs (miRNAs) have been lauded ...for their prognostic utility.
We hypothesized that circulating miRNAs obtained at baseline/prerandomization in the Childhood Asthma Management Program (CAMP) could serve as biomarkers and biologic mediators of ICS clinical response over the 4-year clinical trial period.
We selected baseline serum samples from 462 CAMP subjects subsequently randomized to either ICS (budesonide) or placebo. Samples underwent small RNA sequencing, and read counts were normalized and filtered by depth and coverage. Linear regression was used to associate miRNAs with change in FEV
% (prebronchodilator FEV
as a percent predicted) over the 4-year treatment period in both main effects and interaction models. We validated the function of the top associated miRNAs by luciferase reporter assays of glucocorticoid-mediated transrepression and predicted response to ICS through logistic regression models.
We identified 7 miRNAs significantly associated with FEV
% change (
≤ 0.05) and 15 miRNAs with significant interaction (
≤ 0.05) to ICS versus placebo treatments. We selected three miRNAs for functional validation, of which hsa-miR-155-5p and hsa-miR-532-5p were significantly associated with changes in dexamethasone-induced transrepression of NF-κB. Combined, these two miRNAs were predictive of ICS response over the course of the clinical trial, with an area under the receiver operating characteristic curve of 0.86.
We identified two functional circulating miRNAs predictive of asthma ICS treatment response over time.
Vitamin D may help to alleviate asthma exacerbation because of its anti-inflammation effect, but the evidence is inconsistent in childhood asthma. MiRNAs are important mediators in asthma ...pathogenesis and also excellent non-invasive biomarkers. We hypothesized that circulating miRNAs are associated with asthma exacerbation and modified by vitamin D levels.
We sequenced baseline serum miRNAs from 461 participants in the Childhood Asthma Management Program (CAMP). Logistic regression was used to associate miRNA expression with asthma exacerbation through interaction analysis first and then stratified by vitamin D insufficient and sufficient groups. Microarray from lymphoblastoid B-cells (LCLs) treated by vitamin D or sham of 43 subjects in CAMP were used for validation in vitro. The function of miRNAs was associated with gene modules by weighted gene co-expression network analysis (WGCNA).
We identified eleven miRNAs associated with asthma exacerbation with vitamin D effect modification. Of which, five were significant in vitamin D insufficient group and nine were significant in vitamin D sufficient group. Six miRNAs, including hsa-miR-143-3p, hsa-miR-192-5p, hsa-miR-151a-5p, hsa-miR-24-3p, hsa-miR-22-3p and hsa-miR-451a were significantly associated with gene modules of immune-related functions, implying miRNAs may mediate vitamin D effect on asthma exacerbation through immune pathways. In addition, hsa-miR-143-3p and hsa-miR-451a are potential predictors of childhood asthma exacerbation at different vitamin D levels.
miRNAs are potential mediators of asthma exacerbation and their effects are directly impacted by vitamin D levels.
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