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BACKGROUND: Severe asthma (SA) encompasses several clinical phenotypes with a heterogeneous airway microbiome. We determined the phenotypes associated with a low α-diversity microbiome. METHODS: Metagenomic sequencing was performed on sputum samples from SA participants. A threshold of 2 standard deviations below the mean of α-diversity of mild-moderate asthma and healthy control subjects was used to define those with an abnormal abundance threshold as relative dominant species (RDS). FINDINGS: Fifty-one out of 97 SA samples were classified as RDSs with Haemophilus influenzae RDS being most common (n = 16), followed by Actinobacillus unclassified (n = 10), Veillonella unclassified (n = 9), Haemophilus aegyptius (n = 9), Streptococcus pseudopneumoniae (n = 7), Propionibacterium acnes (n = 5), Moraxella catarrhalis (n = 5) and Tropheryma whipplei (n = 5). Haemophilus influenzae RDS had the highest duration of disease, more exacerbations in previous year and greatest number on daily oral corticosteroids. Hierarchical clustering of RDSs revealed a C2 cluster (n = 9) of highest relative abundance of exclusively Haemophilus influenzae RDSs with longer duration of disease and higher sputum neutrophil counts associated with enrichment pathways of MAPK, NF-κB, TNF, mTOR and necroptosis, compared to the only other cluster, C1, which consisted of 7 Haemophilus influenzae RDSs out of 42. Sputum transcriptomics of C2 cluster compared to C1 RDSs revealed higher expression of neutrophil extracellular trap pathway (NETosis), IL6-transignalling signature and neutrophil activation. CONCLUSION: We describe a Haemophilus influenzae cluster of the highest relative abundance associated with neutrophilic inflammation and NETosis indicating a host response to the bacteria. This phenotype of severe asthma may respond to specific antibiotics.
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Asma , Haemophilus influenzae , Neutrófilos , Escarro , Humanos , Asma/microbiologia , Haemophilus influenzae/patogenicidade , Haemophilus influenzae/genética , Escarro/microbiologia , Masculino , Feminino , Adulto , Neutrófilos/metabolismo , Pessoa de Meia-Idade , Fenótipo , Infecções por Haemophilus/microbiologiaRESUMO
BACKGROUND: Clustering approaches using single omics platforms are increasingly used to characterise molecular phenotypes of eosinophilic and neutrophilic asthma. Effective integration of multi-omics platforms should lead towards greater refinement of asthma endotypes across molecular dimensions and indicate key targets for intervention or biomarker development. OBJECTIVES: To determine whether multi-omics integration of sputum leads to improved granularity of the molecular classification of severe asthma. METHODS: We analyzed six -omics data blocks-microarray transcriptomics, gene set variation analysis of microarray transcriptomics, SomaSCAN proteomics assay, shotgun proteomics, 16S microbiome sequencing, and shotgun metagenomic sequencing-from induced sputum samples of 57 severe asthma patients, 15 mild-moderate asthma patients, and 13 healthy volunteers in the U-BIOPRED European cohort. We used Monti consensus clustering algorithm for aggregation of clustering results and Similarity Network Fusion to integrate the 6 multi-omics datasets of the 72 asthmatics. RESULTS: Five stable omics-associated clusters were identified (OACs). OAC1 had the best lung function with the least number of severe asthmatics with sputum paucigranulocytic inflammation. OAC5 also had fewer severe asthma patients but the highest incidence of atopy and allergic rhinitis, with paucigranulocytic inflammation. OAC3 comprised only severe asthmatics with the highest sputum eosinophilia. OAC2 had the highest sputum neutrophilia followed by OAC4 with both clusters consisting of mostly severe asthma but with more ex/current smokers in OAC4. Compared to OAC4, there was higher incidence of nasal polyps, allergic rhinitis, and eczema in OAC2. OAC2 had microbial dysbiosis with abundant Moraxella catarrhalis and Haemophilus influenzae. OAC4 was associated with pathways linked to IL-22 cytokine activation, with the prediction of therapeutic response to anti-IL22 antibody therapy. CONCLUSION: Multi-omics analysis of sputum in asthma has defined with greater granularity the asthma endotypes linked to neutrophilic and eosinophilic inflammation. Modelling diverse types of high-dimensional interactions will contribute to a more comprehensive understanding of complex endotypes. KEY POINTS: Unsupervised clustering on sputum multi-omics of asthma subjects identified 3 out of 5 clusters with predominantly severe asthma. One severe asthma cluster was linked to type 2 inflammation and sputum eosinophilia while the other 2 clusters to sputum neutrophilia. One severe neutrophilic asthma cluster was linked to Moraxella catarrhalis and to a lesser extent Haemophilus influenzae while the second cluster to activation of IL-22.
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Asma , Escarro , Humanos , Escarro/microbiologia , Escarro/metabolismo , Asma/microbiologia , Asma/imunologia , Asma/genética , Masculino , Feminino , Adulto , Pessoa de Meia-Idade , Neutrófilos/metabolismo , Neutrófilos/imunologia , Eosinófilos/metabolismo , MultiômicaRESUMO
BACKGROUND: Months after infection with severe acute respiratory syndrome coronavirus 2, at least 10% of patients still experience complaints. Long-COVID (coronavirus disease 2019) is a heterogeneous disease, and clustering efforts revealed multiple phenotypes on a clinical level. However, the molecular pathways underlying long-COVID phenotypes are still poorly understood. OBJECTIVES: We sought to cluster patients according to their blood transcriptomes and uncover the pathways underlying their disease. METHODS: Blood was collected from 77 patients with long-COVID from the Precision Medicine for more Oxygen (P4O2) COVID-19 study. Unsupervised hierarchical clustering was performed on the whole blood transcriptome. These clusters were analyzed for differences in clinical features, pulmonary function tests, and gene ontology term enrichment. RESULTS: Clustering revealed 2 distinct clusters on a transcriptome level. Compared with cluster 2 (n = 65), patients in cluster 1 (n = 12) showed a higher rate of preexisting cardiovascular disease (58% vs 22%), higher prevalence of gastrointestinal symptoms (58% vs 29%), shorter hospital duration during severe acute respiratory syndrome coronavirus 2 infection (median, 3 vs 8 days), lower FEV1/forced vital capacity (72% vs 81%), and lower diffusion capacity of the lung for carbon monoxide (68% vs 85% predicted). Gene ontology term enrichment analysis revealed upregulation of genes involved in the antiviral innate immune response in cluster 1, whereas genes involved with the adaptive immune response were upregulated in cluster 2. CONCLUSIONS: This study provides a start in uncovering the pathophysiological mechanisms underlying long-COVID. Further research is required to unravel why the immune response is different in these clusters, and to identify potential therapeutic targets to create an optimized treatment or monitoring strategy for the individual long-COVID patient.
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BACKGROUND: Microbiota alterations are common in patients hospitalised for severe infections, and preclinical models have shown that anaerobic butyrate-producing gut bacteria protect against systemic infections. However, the relationship between microbiota disruptions and increased susceptibility to severe infections in humans remains unclear. We investigated the relationship between gut microbiota and the risk of future infection-related hospitalisation in two large population-based cohorts. METHODS: In this observational microbiome study, gut microbiota were characterised using 16S rRNA gene sequencing in independent population-based cohorts from the Netherlands (HELIUS study; derivation cohort) and Finland (FINRISK 2002 study; validation cohort). HELIUS was conducted in Amsterdam, Netherlands, and included adults (aged 18-70 years at inclusion) who were randomly sampled from the municipality register of Amsterdam. FINRISK 2002 was conducted in six regions in Finland and is a population survey that included a random sample of adults (aged 25-74 years). In both cohorts, participants completed questionnaires, underwent a physical examination, and provided a faecal sample at inclusion (Jan 3, 2013, to Nov 27, 2015, for HELIUS participants and Jan 21 to April 19, 2002, for FINRISK participants. For inclusion in our study, a faecal sample needed to be provided and successfully sequenced, and national registry data needed to be available. Primary predictor variables were microbiota composition, diversity, and relative abundance of butyrate-producing bacteria. Our primary outcome was hospitalisation or mortality due to any infectious disease during 5-7-year follow-up after faecal sample collection, based on national registry data. We examined associations between microbiota and infection risk using microbial ecology and Cox proportional hazards. FINDINGS: We profiled gut microbiota from 10 699 participants (4248 [39·7%] from the derivation cohort and 6451 [60·3%] from the validation cohort). 602 (5·6%) participants (152 [3·6%] from the derivation cohort; 450 [7·0%] from the validation cohort) were hospitalised or died due to infections during follow-up. Gut microbiota composition of these participants differed from those without hospitalisation for infections (derivation p=0·041; validation p=0·0002). Specifically, higher relative abundance of butyrate-producing bacteria was associated with a reduced risk of hospitalisation for infections (derivation cohort cause-specific hazard ratio 0·75 [95% CI 0·60-0·94] per 10% increase in butyrate producers, p=0·013; validation cohort 0·86 [0·77-0·96] per 10% increase, p=0·0077). These associations remained unchanged following adjustment for demographics, lifestyle, antibiotic exposure, and comorbidities. INTERPRETATION: Gut microbiota composition, specifically colonisation with butyrate-producing bacteria, was associated with protection against hospitalisation for infectious diseases in the general population across two independent European cohorts. Further studies should investigate whether modulation of the microbiome can reduce the risk of severe infections. FUNDING: Amsterdam UMC, Porticus, National Institutes of Health, Netherlands Organisation for Health Research and Development (ZonMw), and Leducq Foundation.
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BACKGROUND: Pediatric post coronavirus disease 2019 (COVID-19) condition (PPCC) is a heterogeneous syndrome, which can significantly affect the daily lives of children. This study aimed to identify clinically meaningful phenotypes in children with PPCC, to better characterize and treat this condition. METHODS: Participants were children with physician-diagnosed PPCC, referred to the academic hospital Amsterdam UMC in the Netherlands between November 2021 and March 2023. Demographic factors and information on post-COVID symptoms, comorbidities, and impact on daily life were collected. Clinical clusters were identified using an unsupervised and unbiased approach for mixed data types. RESULTS: Analysis of 111 patients (aged 3-18 years) revealed three distinct clusters within PPCC. Cluster 1 (n = 62, median age = 15 years) predominantly consisted of girls (74.2%). These patients suffered relatively more from exercise intolerance, dyspnea, and smell disorders. Cluster 2 (n = 33, median age = 13 years) contained patients with an even gender distribution (51.5% girls). They suffered from relatively more sleep problems, memory loss, gastrointestinal symptoms, and arthralgia. Cluster 3 (n = 16, median age = 11 years) had a higher proportion of boys (75.0%), suffered relatively more from fever, had significantly fewer symptoms (median of 5 symptoms compared to 8 and 10 for clusters 1 and 2 respectively), and experienced a lower impact on daily life. CONCLUSIONS: This study identified three distinct clinical PPCC phenotypes, with variations in sex, age, symptom patterns, and impact on daily life. These findings highlight the need for further research to understand the potentially diverse underlying mechanisms contributing to post-COVID symptoms in children.
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COVID-19 , Fenótipo , Humanos , Criança , Feminino , COVID-19/epidemiologia , Masculino , Adolescente , Pré-Escolar , Países Baixos/epidemiologia , SARS-CoV-2 , Síndrome de COVID-19 Pós-AgudaRESUMO
RATIONALE: Early identification of children with poorly controlled asthma is imperative for optimizing treatment strategies. The analysis of exhaled volatile organic compounds (VOCs) is an emerging approach to identify prognostic and diagnostic biomarkers in pediatric asthma. OBJECTIVES: To assess the accuracy of gas chromatography-mass spectrometry based exhaled metabolite analysis to differentiate between controlled and uncontrolled pediatric asthma. METHODS: This study encompassed a discovery (SysPharmPediA) and validation phase (U-BIOPRED, PANDA). Firstly, exhaled VOCs that discriminated asthma control levels were identified. Subsequently, outcomes were validated in two independent cohorts. Patients were classified as controlled or uncontrolled, based on asthma control test scores and number of severe attacks in the past year. Additionally, potential of VOCs in predicting two or more future severe asthma attacks in SysPharmPediA was evaluated. MEASUREMENTS AND MAIN RESULTS: Complete data were available for 196 children (SysPharmPediA=100, U-BIOPRED=49, PANDA=47). In SysPharmPediA, after randomly splitting the population into training (n=51) and test sets (n=49), three compounds (acetophenone, ethylbenzene, and styrene) distinguished between uncontrolled and controlled asthmatics. The area under the receiver operating characteristic curve (AUROCC) for training and test sets were respectively: 0.83 (95% CI: 0.65-1.00) and 0.77 (95% CI: 0.58-0.96). Combinations of these VOCs resulted in AUROCCs of 0.74 ±0.06 (UBIOPRED) and 0.68 ±0.05 (PANDA). Attacks prediction tests, resulted in AUROCCs of 0.71 (95% CI 0.51-0.91) and 0.71 (95% CI 0.52-0.90) for training and test sets. CONCLUSIONS: Exhaled metabolites analysis might enable asthma control classification in children. This should stimulate further development of exhaled metabolites-based point-of-care tests in asthma.
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BACKGROUND: Four months after SARS-CoV-2 infection, 22%-50% of COVID-19 patients still experience complaints. Long COVID is a heterogeneous disease and finding subtypes could aid in optimising and developing treatment for the individual patient. METHODS: Data were collected from 95 patients in the P4O2 COVID-19 cohort at 3-6 months after infection. Unsupervised hierarchical clustering was performed on patient characteristics, characteristics from acute SARS-CoV-2 infection, long COVID symptom data, lung function and questionnaires describing the impact and severity of long COVID. To assess robustness, partitioning around medoids was used as alternative clustering. RESULTS: Three distinct clusters of patients with long COVID were revealed. Cluster 1 (44%) represented predominantly female patients (93%) with pre-existing asthma and suffered from a median of four symptom categories, including fatigue and respiratory and neurological symptoms. They showed a milder SARS-CoV-2 infection. Cluster 2 (38%) consisted of predominantly male patients (83%) with cardiovascular disease (CVD) and suffered from a median of three symptom categories, most commonly respiratory and neurological symptoms. This cluster also showed a significantly lower forced expiratory volume within 1 s and diffusion capacity of the lung for carbon monoxide. Cluster 3 (18%) was predominantly male (88%) with pre-existing CVD and diabetes. This cluster showed the mildest long COVID, and suffered from symptoms in a median of one symptom category. CONCLUSIONS: Long COVID patients can be clustered into three distinct phenotypes based on their clinical presentation and easily obtainable information. These clusters show distinction in patient characteristics, lung function, long COVID severity and acute SARS-CoV-2 infection severity. This clustering can help in selecting the most beneficial monitoring and/or treatment strategies for patients suffering from long COVID. Follow-up research is needed to reveal the underlying molecular mechanisms implicated in the different phenotypes and determine the efficacy of treatment.
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COVID-19 , Fenótipo , Síndrome de COVID-19 Pós-Aguda , SARS-CoV-2 , Humanos , COVID-19/complicações , COVID-19/epidemiologia , COVID-19/fisiopatologia , Feminino , Masculino , Pessoa de Meia-Idade , Idoso , Índice de Gravidade de Doença , Adulto , Estudos de Coortes , Testes de Função Respiratória , Análise por Conglomerados , Volume Expiratório Forçado , Fatores de TempoRESUMO
Introduction. Perforated peptic ulcer remains one of the critical abdominal conditions that requires early surgical intervention. Leakage after omental patch repair represents one of the devastating complications that increase morbidity and mortality. Our study aimed to assess risk factors and early predictors for incidence of leakage. Methods. Retrospective analysis of data of the patients who underwent omental patch repair for perforated peptic ulcer in the period between January 2019 and January 2022 in Mansoura University Hospital, Egypt. Pre, intra and postoperative variables were collected and statistically analyzed. Incriminated risk factors for leakage incidence were analyzed using univariate and multivariate analysis. Results. This study included 123 patients who met inclusion criteria. Leakage was detected in seven (5.7%) patients. Although associated comorbidities (p=0.01), postoperative intensive care unit admission (p=0.03), and postoperative hypotension (p=0.02) were significant risk factors in univariate analysis, septic shock (p=0.001), delayed intervention (p=0.04), preoperative hypoalbuminemia (p=0.017), and perforation size >5mm (p= 0.04) were found as independent risk factors for leakage upon multivariate analysis. Conclusion. Delayed presentation in septic shock, preoperative hypoalbuminemia, prolonged perforation, operation interval, and large perforation size > 5mm were detected as independent risk factors for leakage. Postoperative tachypnea and tachycardia with increased levels of C-reactive protein and total leucocytic count are alarming signs for incidence of leakage
Introducción. La úlcera péptica perforada es una de las afecciones abdominales críticas que requiere una intervención quirúrgica temprana. La fuga después de la reparación con parche de epiplón representa una de las complicaciones más devastadoras, que aumentan la morbilidad y la mortalidad. Nuestro estudio tuvo como objetivo evaluar los factores de riesgo y los predictores tempranos de fugas. Métodos. Análisis retrospectivo de los datos de los pacientes sometidos a reparación con parche de epiplón por úlcera péptica perforada, en el período comprendido entre enero de 2019 y enero de 2022, en el Hospital Universitario de Mansoura, Egipto. Se recogieron y analizaron estadísticamente variables pre, intra y postoperatorias. Los factores de riesgo asociados a la incidencia de fugas se analizaron mediante análisis univariado y multivariado. Resultados. Este estudio incluyó 123 pacientes que cumplieron con los criterios de inclusión. Se detectó fuga en siete (5,7 %) pacientes. Aunque las comorbilidades asociadas (p=0,01), el ingreso postoperatorio a la unidad de cuidados intensivos (p=0,03) y la hipotensión postoperatoria (p=0,02) fueron factores de riesgo en el análisis univariado, el shock séptico (p=0,001), el retraso en la intervención (p=0,04), la hipoalbuminemia preoperatoria (p=0,017) y el tamaño de la perforación mayor de 5 mm (p=0,04) se encontraron como factores de riesgo de fuga independientes en el análisis multivariado. Conclusión. Se detectaron como factores de riesgo independientes de fuga la presentación tardía en shock séptico, la hipoalbuminemia preoperatoria, la perforación prolongada, el intervalo operatorio y el tamaño de la perforación mayor de 5 mm. La taquipnea posoperatoria y la taquicardia con niveles elevados de proteína C reactiva y recuento leucocitario total son signos de alarma sobre la presencia de fuga.
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Humanos , Úlcera Péptica Perfurada , Complicações Pós-Operatórias , Omento , Fatores de RiscoRESUMO
Introduction: The coronavirus disease 2019 (COVID-19) pandemic has led to the death of almost 7 million people, however, with a cumulative incidence of 0.76 billion, most people survive COVID-19. Several studies indicate that the acute phase of COVID-19 may be followed by persistent symptoms including fatigue, dyspnea, headache, musculoskeletal symptoms, and pulmonary functional-and radiological abnormalities. However, the impact of COVID-19 on long-term health outcomes remains to be elucidated. Aims: The Precision Medicine for more Oxygen (P4O2) consortium COVID-19 extension aims to identify long COVID patients that are at risk for developing chronic lung disease and furthermore, to identify treatable traits and innovative personalized therapeutic strategies for prevention and treatment. This study aims to describe the study design and first results of the P4O2 COVID-19 cohort. Methods: The P4O2 COVID-19 study is a prospective multicenter cohort study that includes nested personalized counseling intervention trial. Patients, aged 40-65 years, were recruited from outpatient post-COVID clinics from five hospitals in The Netherlands. During study visits at 3-6 and 12-18 months post-COVID-19, data from medical records, pulmonary function tests, chest computed tomography scans and biological samples were collected and questionnaires were administered. Furthermore, exposome data was collected at the patient's home and state-of-the-art imaging techniques as well as multi-omics analyses will be performed on collected data. Results: 95 long COVID patients were enrolled between May 2021 and September 2022. The current study showed persistence of clinical symptoms and signs of pulmonary function test/radiological abnormalities in post-COVID patients at 3-6 months post-COVID. The most commonly reported symptoms included respiratory symptoms (78.9%), neurological symptoms (68.4%) and fatigue (67.4%). Female sex and infection with the Delta, compared with the Beta, SARS-CoV-2 variant were significantly associated with more persisting symptom categories. Conclusions: The P4O2 COVID-19 study contributes to our understanding of the long-term health impacts of COVID-19. Furthermore, P4O2 COVID-19 can lead to the identification of different phenotypes of long COVID patients, for example those that are at risk for developing chronic lung disease. Understanding the mechanisms behind the different phenotypes and identifying these patients at an early stage can help to develop and optimize prevention and treatment strategies.
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BACKGROUND: Because of altered airway microbiome in asthma, we analysed the bacterial species in sputum of patients with severe asthma. METHODS: Whole genome sequencing was performed on induced sputum from non-smoking (SAn) and current or ex-smoker (SAs/ex) severe asthma patients, mild/moderate asthma (MMA) and healthy controls (HC). Data were analysed by asthma severity, inflammatory status and transcriptome-associated clusters (TACs). RESULTS: α-diversity at the species level was lower in SAn and SAs/ex, with an increase in Haemophilus influenzae and Moraxella catarrhalis, and Haemophilus influenzae and Tropheryma whipplei, respectively, compared to HC. In neutrophilic asthma, there was greater abundance of Haemophilus influenzae and Moraxella catarrhalis and in eosinophilic asthma, Tropheryma whipplei was increased. There was a reduction in α-diversity in TAC1 and TAC2 that expressed high levels of Haemophilus influenzae and Tropheryma whipplei, and Haemophilus influenzae and Moraxella catarrhalis, respectively, compared to HC. Sputum neutrophils correlated positively with Moraxella catarrhalis and negatively with Prevotella, Neisseria and Veillonella species and Haemophilus parainfluenzae. Sputum eosinophils correlated positively with Tropheryma whipplei which correlated with pack-years of smoking. α- and ß-diversities were stable at one year. CONCLUSIONS: Haemophilus influenzae and Moraxella catarrhalis were more abundant in severe neutrophilic asthma and TAC2 linked to inflammasome and neutrophil activation, while Haemophilus influenzae and Tropheryma whipplei were highest in SAs/ex and in TAC1 associated with highest expression of IL-13 type 2 and ILC2 signatures with the abundance of Tropheryma whipplei correlating positively with sputum eosinophils. Whether these bacterial species drive the inflammatory response in asthma needs evaluation.
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Asma , Haemophilus influenzae , Humanos , Moraxella catarrhalis , Escarro/microbiologia , Inflamassomos , Imunidade Inata , Ativação de Neutrófilo , Linfócitos , Asma/diagnóstico , Asma/microbiologia , BactériasRESUMO
Rationale: Children with preschool wheezing or school-age asthma are reported to have airway microbial imbalances. Objectives: To identify clusters in children with asthma or wheezing using oropharyngeal microbiota profiles. Methods: Oropharyngeal swabs from the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) pediatric asthma or wheezing cohort were characterized using 16S ribosomal RNA gene sequencing, and unsupervised hierarchical clustering was performed on the Bray-Curtis ß-diversity. Enrichment scores of the Molecular Signatures Database hallmark gene sets were computed from the blood transcriptome using gene set variation analysis. Children with severe asthma or severe wheezing were followed up for 12-18 months, with assessment of the frequency of exacerbations. Measurements and Main Results: Oropharyngeal samples from 241 children (age range, 1-17 years; 40% female) revealed four taxa-driven clusters dominated by Streptococcus, Veillonella, Rothia, and Haemophilus. The clusters showed significant differences in atopic dermatitis, grass pollen sensitization, FEV1% predicted after salbutamol, and annual asthma exacerbation frequency during follow-up. The Veillonella cluster was the most allergic and included the highest percentage of children with two or more exacerbations per year during follow-up. The oropharyngeal clusters were different in the enrichment scores of TGF-ß (transforming growth factor-ß) (highest in the Veillonella cluster) and Wnt/ß-catenin signaling (highest in the Haemophilus cluster) transcriptomic pathways in blood (all q values <0.05). Conclusions: Analysis of the oropharyngeal microbiota of children with asthma or wheezing identified four clusters with distinct clinical characteristics (phenotypes) that associate with risk for exacerbation and transcriptomic pathways involved in airway remodeling. This suggests that further exploration of the oropharyngeal microbiota may lead to novel pathophysiologic insights and potentially new treatment approaches.
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Asma , Hipersensibilidade , Microbiota , Feminino , Masculino , Humanos , Transcriptoma , Sons Respiratórios/genética , Asma/genética , Microbiota/genéticaRESUMO
Asthma is the most prevalent pediatric chronic disease. Bronchodilator drug response (BDR) and fractional exhaled nitric oxide (FeNO) are clinical biomarkers of asthma. Although DNA methylation (DNAm) contributes to asthma pathogenesis, the influence of DNAm on BDR and FeNO is scarcely investigated. This study aims to identify DNAm markers in whole blood associated either with BDR or FeNO in pediatric asthma. We analyzed 121 samples from children with moderate-to-severe asthma. The association of genome-wide DNAm with BDR and FeNO has been assessed using regression models, adjusting for age, sex, ancestry, and tissue heterogeneity. Cross-tissue validation was assessed in 50 nasal samples. Differentially methylated regions (DMRs) and enrichment in traits and biological pathways were assessed. A false discovery rate (FDR) < 0.1 and a genome-wide significance threshold of p < 9 × 10-8 were used to control for false-positive results. The CpG cg12835256 (PLA2G12A) was genome-wide associated with FeNO in blood samples (coefficient= -0.015, p = 2.53 × 10-9) and nominally associated in nasal samples (coefficient = -0.015, p = 0.045). Additionally, three CpGs were suggestively associated with BDR (FDR < 0.1). We identified 12 and four DMRs associated with FeNO and BDR (FDR < 0.05), respectively. An enrichment in allergic and inflammatory processes, smoking, and aging was observed. We reported novel associations of DNAm markers associated with BDR and FeNO enriched in asthma-related processes.
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BACKGROUND: Uncontrolled asthma can lead to severe exacerbations and reduced quality of life. Research has shown that the microbiome may be linked with asthma characteristics; however, its association with asthma control has not been explored. We aimed to investigate whether the gastrointestinal microbiome can be used to discriminate between uncontrolled and controlled asthma in children. METHODS: 143 and 103 feces samples were obtained from 143 children with moderate-to-severe asthma aged 6 to 17 years from the SysPharmPediA study. Patients were classified as controlled or uncontrolled asthmatics, and their microbiome at species level was compared using global (alpha/beta) diversity, conventional differential abundance analysis (DAA, analysis of compositions of microbiomes with bias correction), and machine learning [Recursive Ensemble Feature Selection (REFS)]. RESULTS: Global diversity and DAA did not find significant differences between controlled and uncontrolled pediatric asthmatics. REFS detected a set of taxa, including Haemophilus and Veillonella, differentiating uncontrolled and controlled asthma with an average classification accuracy of 81% (saliva) and 86% (feces). These taxa showed enrichment in taxa previously associated with inflammatory diseases for both sampling compartments, and with COPD for the saliva samples. CONCLUSION: Controlled and uncontrolled children with asthma can be differentiated based on their gastrointestinal microbiome using machine learning, specifically REFS. Our results show an association between asthma control and the gastrointestinal microbiome. This suggests that the gastrointestinal microbiome may be a potential biomarker for treatment responsiveness and thereby help to improve asthma control in children.
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Asma , Microbiota , Humanos , Criança , Qualidade de Vida , Asma/tratamento farmacológico , Bactérias , Fezes/microbiologiaRESUMO
Asthma is a complex, heterogeneous disease that necessitates a proper patient evaluation to decide the correct treatment and optimize disease control. The recent introduction of new target therapies for the most severe form of the disease has heralded a new era of treatment options, intending to treat and control specific molecular pathways in asthma pathophysiology. Precision medicine, using omics sciences, investigates biological and molecular mechanisms to find novel biomarkers that can be used to guide treatment selection and predict response. The identification of reliable biomarkers indicative of the pathological mechanisms in asthma is essential to unravel new potential treatment targets. In this chapter, we provide a general description of the currently available -omics techniques, focusing on their implications in asthma therapy.
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Asma , Medicina de Precisão , Humanos , Medicina de Precisão/métodos , Asma/tratamento farmacológico , BiomarcadoresRESUMO
BACKGROUND: Uncontrolled pediatric asthma has a large impact on patients and their caregivers. More insight into determinants of uncontrolled asthma is needed. We aim to compare treatment regimens, inhaler techniques, medication adherence and other characteristics of children with controlled and uncontrolled asthma in the: Systems Pharmacology approach to uncontrolled Paediatric Asthma (SysPharmPediA) study. MATERIAL AND METHODS: 145 children with moderate to severe doctor-diagnosed asthma (91 uncontrolled and 54 controlled) aged 6-17 years were enrolled in this multicountry, (Germany, Slovenia, Spain, and the Netherlands) observational, case-control study. The definition of uncontrolled asthma was based on asthma symptoms and/or exacerbations in the past year. Patient-reported adherence and clinician-reported medication use were assessed, as well as lung function and inhalation technique. A logistic regression model was fitted to assess determinants of uncontrolled pediatric asthma. RESULTS: Children in higher asthma treatment steps had a higher risk of uncontrolled asthma (OR (95%CI): 3.30 (1.56-7.19)). The risk of uncontrolled asthma was associated with a larger change in FEV1% predicted post and pre-salbutamol (OR (95%CI): 1.08 (1.02-1.15)). Adherence and inhaler techniques were not associated with risk of uncontrolled asthma in this population. CONCLUSION: This study showed that children with uncontrolled moderate-to-severe asthma were treated in higher treatment steps compared to their controlled peers, but still showed a higher reversibility response to salbutamol. Self-reported adherence and inhaler technique scores did not differ between controlled and uncontrolled asthmatic children. Other determinants, such as environmental factors and differences in biological profiles, may influence the risk of uncontrolled asthma in this moderate to severe asthmatic population.
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Antiasmáticos , Asma , Criança , Humanos , Antiasmáticos/uso terapêutico , Estudos de Casos e Controles , Administração por Inalação , Asma/tratamento farmacológico , Albuterol/uso terapêuticoRESUMO
INTRODUCTION: Childhood asthma is a complex heterogenous inflammatory disease that can pose a large burden on patients and their caregivers. There is a strong need to adapt asthma treatment to the individual patient taking into account underlying inflammatory profiles, moving from a 'one size fits all' approach toward a much-needed personalized approach. AREAS COVERED: This review article aims to provide an overview of recent advances in the management and treatment of pediatric asthma, including novel insights on the molecular heterogeneity of childhood asthma, the emergence of biologicals to treat severe asthma, and innovative e-health and home monitoring techniques to make asthma management more convenient and accessible. EXPERT OPINION: Molecular technologies have provided new treatment leads. E-health and home monitoring technologies have helped to gain more insights into disease dynamics and improve adherence to treatment while bringing health care to the patient. However, uncontrolled childhood asthma is still a major unmet clinical need and precision-medicine approaches are still scarce in clinical practice. Advanced omics methods may help researchers or clinicians to more accurately phenotype and treat subtypes of childhood asthma and gain more insight into the complexity of the disease.
Assuntos
Asma , Farmacologia Clínica , Humanos , Asma/tratamento farmacológico , Medicina de Precisão/métodos , FenótipoRESUMO
Rationale: There is a major unmet need for improving the care of children and adolescents with severe asthma and wheeze. Identifying factors contributing to disease severity may lead to improved diagnostics, biomarkers, or therapies. The airway microbiota may be such a key factor. Objectives: To compare the oropharyngeal airway microbiota of children and adolescents with severe and mild/moderate asthma/wheeze. Methods: Oropharyngeal swab samples from school-age and preschool children in the European U-BIOPRED (Unbiased BIOmarkers in the PREDiction of respiratory disease outcomes) multicenter study of severe asthma, all receiving severity-appropriate treatment, were examined using 16S ribosomal RNA gene sequencing. Bacterial taxa were defined as amplicon sequence variants. Results: We analyzed 241 samples from four cohorts: A) 86 school-age children with severe asthma; B) 39 school-age children with mild/moderate asthma; C) 65 preschool children with severe wheeze; and D) 51 preschool children with mild/moderate wheeze. The most common bacteria were Streptococcus (mean relative abundance, 33.5%), Veillonella (10.3%), Haemophilus (7.0%), Prevotella (5.9%), and Rothia (5.5%). Age group (school-age vs. preschool) was associated with the microbiota in ß-diversity analysis (F = 3.32, P = 0.011) and in a differential abundance analysis (28 significant amplicon sequence variants). Among all children, we found no significant difference in the microbiota between children with severe and mild/moderate asthma/wheeze in univariable ß-diversity analysis (F = 1.99, P = 0.08, N = 241), but a significant difference in a multivariable model (F = 2.66, P = 0.035), including the number of exacerbations in the previous year. Age was also significant when expressed as a microbial maturity score (Spearman Rho, 0.39; P = 4.6 × 10-10); however, this score was not associated with asthma/wheeze severity. Conclusions: There was a modest difference in the oropharyngeal airway microbiota between children with severe and mild/moderate asthma/wheeze across all children but not in individual age groups, and a strong association between the microbiota and age. This suggests the oropharyngeal airway microbiota as an interesting entity in studying asthma severity, but probably without the strength to serve as a biomarker for targeted intervention.
Assuntos
Asma , Microbiota , Humanos , Adolescente , Pré-Escolar , Sons Respiratórios , Microbiota/genética , Asma/microbiologia , Orofaringe/microbiologia , Bactérias/genéticaRESUMO
BACKGROUND: Ventilator-associated pneumonia (VAP) is associated with high morbidity and health care costs, yet diagnosis remains a challenge. Analysis of airway microbiota by amplicon sequencing provides a possible solution, as pneumonia is characterised by a disruption of the microbiome. However, studies evaluating the diagnostic capabilities of microbiome analysis are limited, with a lack of alignment on possible biomarkers. Using bronchoalveolar lavage fluid (BALF) from ventilated adult patients suspected of VAP, we aimed to explore how key characteristics of the microbiome differ between patients with positive and negative BALF cultures and whether any differences could have a clinically relevant role. METHODS: BALF from patients suspected of VAP was analysed using 16s rRNA sequencing in order to: (1) differentiate between patients with and without a positive culture; (2) determine if there was any association between microbiome diversity and local inflammatory response; and (3) correctly identify pathogens detected by conventional culture. RESULTS: Thirty-seven of 90 ICU patients with suspected VAP had positive cultures. Patients with a positive culture had significant microbiome dysbiosis with reduced alpha diversity. However, gross compositional variance was not strongly associated with culture positivity (AUROCC range 0.66-0.71). Patients with a positive culture had a significantly higher relative abundance of pathogenic bacteria compared to those without [0.45 (IQR 0.10-0.84), 0.02 (IQR 0.004-0.09), respectively], and an increased interleukin (IL)-1ß was associated with reduced species evenness (rs = - 0.33, p < 0.01) and increased pathogenic bacteria presence (rs = 0.28, p = 0.013). Untargeted 16s rRNA pathogen detection was limited by false positives, while the use of pathogen-specific relative abundance thresholds showed better diagnostic accuracy (AUROCC range 0.89-0.998). CONCLUSION: Patients with positive BALF culture had increased dysbiosis and genus dominance. An increased caspase-1-dependent IL-1b expression was associated with a reduced species evenness and increased pathogenic bacterial presence, providing a possible causal link between microbiome dysbiosis and lung injury development in VAP. However, measures of diversity were an unreliable predictor of culture positivity and 16s sequencing used agnostically could not usefully identify pathogens; this could be overcome if pathogen-specific relative abundance thresholds are used.