Acute respiratory failure due to pulmonary exacerbation in children with cystic fibrosis admitted in a pediatric intensive care unit: outcomes and factors associated with mortality.

BACKGROUND: Children with advanced pulmonary disease due to cystic fibrosis (CF) are at risk of acute respiratory failure due to pulmonary exacerbations leading to their admission to pediatric intensive care units (PICU). The objectives of this study were to determine short and medium-term outcomes of children with CF admitted to PICU for acute respiratory failure due to pulmonary exacerbation and to identify prognosis factors. METHODS: This retrospective monocentric study included patients less than 18 years old admitted to the PICU of a French university hospital between 2000 and 2020. Cox proportional hazard regression methods were used to determine prognosis factors of mortality or lung transplant. RESULTS: Prior to PICU admission, the 29 patients included (median age 13.5 years) had a severe lung disease (median Forced Expiratory Volume in 1 s percentage predicted at 29%). Mortality rates were respectively 17%, 31%, 34%, 41% at discharge and at 3, 12 and 36 months post-discharge. Survival rates free of lung transplant were 34%, 32%, 24% and 17% respectively. Risk factors associated with mortality or lung transplant using the univariate analysis were female sex and higher pCO2 and chloride levels at PICU admission, and following pre admission characteristics: home respiratory and nutritional support, registration on lung transplant list and Stenotrophomonas Maltophilia bronchial colonization. CONCLUSION: Children with CF admitted to PICU for acute respiratory failure secondary to pulmonary exacerbations are at high risk of death, both in the short and medium terms. Lung transplant is their main chance of survival and should be considered early.

Representation and quantification of module activity from omics data with rROMA.

The efficiency of analyzing high-throughput data in systems biology has been demonstrated in numerous studies, where molecular data, such as transcriptomics and proteomics, offers great opportunities for understanding the complexity of biological processes. One important aspect of data analysis in systems biology is the shift from a reductionist approach that focuses on individual components to a more integrative perspective that considers the system as a whole, where the emphasis shifted from differential expression of individual genes to determining the activity of gene sets. Here, we present the rROMA software package for fast and accurate computation of the activity of gene sets with coordinated expression. The rROMA package incorporates significant improvements in the calculation algorithm, along with the implementation of several functions for statistical analysis and visualizing results. These additions greatly expand the package's capabilities and offer valuable tools for data analysis and interpretation. It is an open-source package available on github at: www.github.com/sysbio-curie/rROMA . Based on publicly available transcriptomic datasets, we applied rROMA to cystic fibrosis, highlighting biological mechanisms potentially involved in the establishment and progression of the disease and the associated genes. Results indicate that rROMA can detect disease-related active signaling pathways using transcriptomic and proteomic data. The results notably identified a significant mechanism relevant to cystic fibrosis, raised awareness of a possible bias related to cell culture, and uncovered an intriguing gene that warrants further investigation.

Proteomic profiling of sweat in patients with cystic fibrosis provides new insights into epidermal homoeostasis.

Background: A high proportion of patients with Cystic Fibrosis (CF) also present the rare skin disease aquagenic palmoplantar keratoderma. A possible link between this condition and absence of a functional CF Transmembrane conductance Regulator protein in the sweat acinus and collecting duct remains unknown. Methods: In-depth characterization of sweat proteome profiles was performed in 25 CF patients compared to 12 healthy controls. A 20 µL sweat sample was collected after pilocarpine iontophoresis and liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomic analysis was performed. Results: Sweat proteome profile of CF patients was significantly different from that of healthy subjects with 57 differentially expressed proteins. Cystic Fibrosis sweat proteome was characterized by an increase in 25 proteins including proteases (Kallikrein 7 and 13, Phospholipase B domain containing 1, Cathepsin A L2 and B, Lysosomal Pro-X carboxypeptidase); proinflammatory proteins (Annexin A2, Chitinase-3-like protein 1); cytochrome c and transglutaminases. Thirty-two proteins were downregulated in CF sweat including proteases (Elastase 2), antioxidative protein FAM129 B; membrane-bound transporter SLC6A14 and regulator protein Sodium-hydrogen antiporter 3 regulator 1. Conclusion: This study is the first to report in-depth characterization of endogenous peptides in CF sweat and could help understand the complex physiology of the sweat gland. The proteome profile highlights the unbalanced proteolytic and proinflammatory activity of sweat in CF. These results also suggest a defect in pathways involved in skin barrier integrity in CF patients. Sweat proteome profile could prove to be a useful tool in the context of personalized medicine in CF.

Profiling the response to lumacaftor-ivacaftor in children with cystic between fibrosis and new insight from a French-Italian real-life cohort.

INTRODUCTION: Clinical trials for CFTR modulators consider mean changes of clinical status at the cohort level, and thus fail to assess the heterogeneity of the response. We aimed to study the different response profiles to lumacaftor-ivacaftor according to age in children with cystic fibrosis (CF). METHODS: A mathematical framework, including principal component analysis, data clustering, and data completion, was applied to a multicenter cohort of 112 children aged 6-18 years, treated with lumacaftor-ivacaftor. Studied parameters at baseline and 6 months included body mass index (BMI), number of days of antibiotics (ATB), Sweat test (ST), forced expiratory volume in 1 s expressed in percentage predicted (ppFEV1 ), forced vital capacity (ppFVC), and forced expiratory flow at 25%-75% of FVC (ppFEF25-75 ). RESULTS: Change in ppFEV1 was the most significant parameter in characterizing response heterogeneity among the 12-18-year-old patients. Patients with minimal changes in ppFEV1 were further separated by change in BMI and ATB course. In the 6-12-year-old children both BMI and ppFEV1 evolution were the most relevant. ST change was not associated with a clinical response. CONCLUSIONS: Change in ppFEV1 , BMI, and ATB course are the most relevant outcomes to discriminate clinical response profiles in children treated with lumacaftor-ivacaftor. Prepubertal and pubertal children display different response profiles.