Publications by authors named "Mahmoud Abdel-Aziz"

An estimated 10% of COVID-19 survivors have been reported to suffer from complaints after at least three months. The intestinal microbiome has been shown to impact long COVID through the gut-lung axis and impact the severity. We aimed to investigate the relationship between the gut microbiome and clinical characteristics, exploring microbiome heterogeneity through clustering.

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Background: Asthma exacerbations (AEs) represent the major contributor to the global asthma burden. Although genetic and environmental factors have been associated with AEs, the role of epigenetics remains uncovered.

Objective: This study aimed to identify whole blood DNA methylation (DNAm) markers associated with AEs in Europeans.

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: Metered-dose inhalers (MDIs) and dry powder inhalers (DPIs) are common inhaled corticosteroid (ICS) inhaler devices. The difference in formulation and administration technique of these devices may influence oral cavity microbiota composition. We aimed to compare the saliva microbiome in children with moderate-to-severe asthma using ICS via MDIs versus DPIs.

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Background: Underlying immunological mechanisms in children with moderate-to-severe asthma are complex and unclear. We aimed to investigate the association between blood inflammatory parameters and asthma burden in children with moderate-to-severe asthma.

Methods: Blood inflammatory parameters (eosinophil and neutrophil counts and inflammatory mediators using multiplex immunoassay technology) were measured in children (6-17 years) with moderate-to-severe asthma from the SysPharmPediA cohort across four European countries.

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Background: Lung quantitative computed tomography (qCT) severe asthma clusters have been reported, but their replication and underlying disease mechanisms are unknown. We identified and replicated qCT clusters of severe asthma in two independent asthma cohorts and determined their association with molecular pathways, using radiomultiomics, integrating qCT, multiomics and machine learning/artificial intelligence.

Methods: We used consensus clustering on qCT measurements of airway and lung CT scans, performed in 105 severe asthmatic adults from the U-BIOPRED cohort.

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Article Synopsis
  • Severe asthma (SA) has various clinical phenotypes linked to a diverse airway microbiome, and a study focused on identifying phenotypes with low microbial diversity.
  • Metagenomic sequencing of sputum samples from SA participants identified 51 out of 97 samples with relative dominant species (RDS), with Haemophilus influenzae being the most prevalent.
  • The research found that a specific cluster of RDSs associated with Haemophilus influenzae had more severe disease characteristics and indicated a host response linked to neutrophilic inflammation, suggesting potential for antibiotic treatment in this group.
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Introduction: Early dental implant failure (EDIF) can occur even when optimal materials are used, surgical protocols are strictly followed and the quantity and quality of bone at the recipient site are sufficient. The existence of specific patient-related risk factors require an investigation into the regulatory mechanisms controlling bone metabolism, bone remodelling and bone turnover as well as serum Vitamin D. The implant stability quotient is used as a prognostic indicator for possible implant failure.

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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.

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Article Synopsis
  • - The study investigated how changes in gut microbiota might influence the risk of future hospitalization due to infections in two large groups from the Netherlands and Finland, focusing on individuals aged 18-74.
  • - Researchers used 16S rRNA gene sequencing to analyze gut microbiota from participants' fecal samples and looked for links between microbiota characteristics (like diversity and butyrate-producing bacteria) and infection-related health outcomes over a follow-up period of 5-7 years.
  • - The results included data from 10,699 participants, revealing potential relationships between certain microbiota profiles and increased susceptibility to severe infections, although further clarification on these interactions in humans is needed.
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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.

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  • Pediatric post coronavirus disease 2019 (COVID-19) condition (PPCC) is a complex syndrome affecting children's daily lives, and this study aimed to uncover specific phenotypes to improve understanding and treatment.
  • Researchers analyzed data from 111 children aged 3-18 with diagnosed PPCC, identifying three distinct clusters based on symptoms and demographics.
  • The study found variations in age, sex, symptom patterns, and daily life impact among the clusters, emphasizing the need for further research into the diverse causes of post-COVID symptoms in children.
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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.

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  • Early identification of poorly controlled asthma in children is crucial for improving treatment methods, and analyzing exhaled volatile organic compounds (VOCs) shows promise for this task.
  • A study evaluated the effectiveness of gas chromatography-mass spectrometry to distinguish between controlled and uncontrolled pediatric asthma, using data from multiple research phases.
  • Key findings revealed that specific VOCs, such as acetophenone and ethylbenzene, could differentiate asthma control levels, achieving strong accuracy in predicting outcomes based on the collected data from 196 children.
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: 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.

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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).

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Article Synopsis
  • Children with preschool wheezing or school-age asthma have different microbial profiles in their airways, which can affect their condition and treatment outcomes.
  • A study of oropharyngeal samples from 241 children identified four distinct clusters based on microbial composition, with significant differences in associated allergies and asthma severity.
  • The findings suggest that understanding these microbial clusters could offer new insights into asthma management and lead to innovative treatment strategies.
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  • * Researchers analyzed blood samples from 121 children with moderate-to-severe asthma to find DNAm markers linked to BDR and FeNO, using regression models to ensure accuracy while controlling for variables like age and sex.
  • * They identified specific DNA markers and differential regions related to FeNO and BDR, with findings indicating associations with allergic reactions and inflammation, potentially opening avenues for better understanding and management of asthma in pediatric patients.
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  • Uncontrolled asthma in children can significantly affect their quality of life, and the study explores the link between the gastrointestinal microbiome and asthma control.
  • Researchers analyzed fecal samples from 143 children with asthma using various methods, including machine learning, to compare the microbiomes of those with controlled versus uncontrolled asthma.
  • Findings revealed specific bacteria, like Haemophilus and Veillonella, that could distinguish between the two groups, suggesting the microbiome could serve as a potential biomarker for improving asthma treatment in children.
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  • Uncontrolled pediatric asthma significantly affects children and their caregivers, highlighting the need for deeper understanding of its determinants through the SysPharmPediA study.
  • The study enrolled 145 children (ages 6-17) with moderate to severe asthma from multiple countries and analyzed factors like treatment regimens, medication adherence, and lung function to assess uncontrolled vs. controlled asthma.
  • Results showed children on higher treatment steps had more uncontrolled asthma, and while they had a greater lung function response to salbutamol, medication adherence and inhaler technique did not differ significantly between the two groups—suggesting other factors might contribute to uncontrolled asthma risk.
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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.

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Article Synopsis
  • * The study analyzed oropharyngeal swab samples from children in a multicenter study, comparing microbiota between those with severe and mild/moderate asthma/wheeze using advanced gene sequencing techniques.
  • * Although initial analyses showed no major differences in microbiota between severe and mild cases, a multivariable analysis revealed significant variations when considering factors like previous exacerbations and age-related microbial development.
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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.

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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.

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