Publications of Julien GUIOT
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See detailAge-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality.
Nakanishi, Tomoko; Pigazzini, Sara; Degenhardt, Frauke et al

in Journal of Clinical Investigation (2021), Online ahead of print.

BACKGROUND: There is considerable variability in COVID-19 outcomes amongst younger adults-and some of this variation may be due to genetic predisposition. We characterized the clinical implications of the ... [more ▼]

BACKGROUND: There is considerable variability in COVID-19 outcomes amongst younger adults-and some of this variation may be due to genetic predisposition. We characterized the clinical implications of the major genetic risk factor for COVID-19 severity, and its age-dependent effect, using individual-level data in a large international multi-centre consortium. METHOD: The major common COVID-19 genetic risk factor is a chromosome 3 locus, tagged by the marker rs10490770. We combined individual level data for 13,424 COVID-19 positive patients (N=6,689 hospitalized) from 17 cohorts in nine countries to assess the association of this genetic marker with mortality, COVID-19-related complications and laboratory values. We next examined if the magnitude of these associations varied by age and were independent from known clinical COVID-19 risk factors. FINDINGS: We found that rs10490770 risk allele carriers experienced an increased risk of all-cause mortality (hazard ratio [HR] 1·4, 95% confidence interval [CI] 1·2-1·6) and COVID-19 related mortality (HR 1·5, 95%CI 1·3-1·8). Risk allele carriers had increased odds of several COVID-19 complications: severe respiratory failure (odds ratio [OR] 2·0, 95%CI 1·6-2·6), venous thromboembolism (OR 1·7, 95%CI 1·2-2·4), and hepatic injury (OR 1·6, 95%CI 1·2-2·0). Risk allele carriers ≤ 60 years had higher odds of death or severe respiratory failure (OR 2·6, 95%CI 1·8-3·9) compared to those > 60 years OR 1·5 (95%CI 1·3-1·9, interaction p-value=0·04). Amongst individuals ≤ 60 years who died or experienced severe respiratory COVID-19 outcome, we found that 31·8% (95%CI 27·6-36·2) were risk variant carriers, compared to 13·9% (95%CI 12·6-15·2%) of those not experiencing these outcomes. Prediction of death or severe respiratory failure among those ≤ 60 years improved when including the risk allele (AUC 0·82 vs 0·84, p=0·016) and the prediction ability of rs10490770 risk allele was similar to, or better than, most established clinical risk factors. INTERPRETATION: The major common COVID-19 risk locus on chromosome 3 is associated with increased risks of morbidity and mortality-and these are more pronounced amongst individuals ≤ 60 years. The effect on COVID-19 severity was similar to, or larger than most established risk factors, suggesting potential implications for clinical risk management. FUNDING: Funding was obtained by each of the participating cohorts individually. [less ▲]

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See detailSputum IL-25, IL-33 and TSLP, IL-23 and IL-36 in airway obstructive diseases. Reduced levels of IL-36 in eosinophilic phenotype.
Moermans, Catherine ULiege; Damas, K.; Guiot, Julien ULiege et al

in Cytokine (2021), 140

INTRODUCTION: Alarmins ((IL-25, IL-33 and thymic stromal lymphopoietin (TSLP)) are known to promote Th2 inflammation and could be associated with eosinophilic airway infiltration. They may also play a ... [more ▼]

INTRODUCTION: Alarmins ((IL-25, IL-33 and thymic stromal lymphopoietin (TSLP)) are known to promote Th2 inflammation and could be associated with eosinophilic airway infiltration. They may also play a role in airway remodeling in chronic airway obstructive diseases such as asthma and chronic obstructive pulmonary disease (COPD). IL-23 and IL-36 were shown to mediate the neutrophilic airway inflammation as seen in chronic airway obstructive diseases. OBJECTIVES: The purpose of this project was to determine the expression and the production of these cytokines from induced sputum (IS) in patients with chronic airway obstructive diseases including asthmatics and COPD. The relationship of the mediators with sputum inflammatory cellular profile and the severity of airway obstruction was assessed. METHODS: The alarmins (IL-25, IL-33 and TSLP) as well as IL-23 and IL-36 concentrations were measured in IS from 24 asthmatics and 20 COPD patients compared to 25 healthy volunteers. The cytokines were assessed by ELISA in the IS supernatant and by RT-qPCR in the IS cells. RESULTS: At protein level, no difference was observed between controls and patients suffering from airway obstructive diseases regarding the different mediators. IL-36 protein level was negatively correlated with sputum eosinophil and appeared significantly decreased in patients with an eosinophilic airway inflammation compared to those with a neutrophilic profile and controls. At gene level, only IL-36, IL-23 and TSLP were measurable but none differed between controls and patients with airway obstructive diseases. IL-36 and IL-23 were significantly increased in patients with an neutrophilic inflammatory profile compared to those with an eosinophilic inflammation and were correlated with sputum neutrophil proportions. None of the mediators were linked to airway obstruction. CONCLUSIONS: The main finding of our study is that patients with eosinophilic airway inflammation exhibited a reduced IL-36 level which could make them more susceptible to airway infections as IL-36 is implicated in antimicrobial defense. This study showed also an implication of IL-36 and IL-23 in airway neutrophilic inflammation in chronic airway obstructive diseases. [less ▲]

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See detailDoes Facemask Impact Diagnostic During Pulmonary Auscultation?
Uyttendaele, Vincent ULiege; GUIOT, Julien ULiege; Chase, J. Geoffrey et al

in IFAC-PapersOnLine (2021), 54(15), 1-580

Facemasks have been widely used in hospitals, especially since the emergence of the coronavirus 2019 (COVID-19) pandemic, often severely affecting respiratory functions. Masks protect patients from ... [more ▼]

Facemasks have been widely used in hospitals, especially since the emergence of the coronavirus 2019 (COVID-19) pandemic, often severely affecting respiratory functions. Masks protect patients from contagious airborne transmission, and are thus more specifically important for chronic respiratory disease (CRD) patients. However, masks also increase air resistance and thus work of breathing, which may impact pulmonary auscultation and diagnostic acuity, the primary respiratory examination. This study is the first to assess the impact of facemasks on clinical auscultation diagnostic. Lung sounds from 29 patients were digitally recorded using an electronic stethoscope. For each patient, one recording was taken wearing a surgical mask and one without. Recorded signals were segmented in breath cycles using an autocorrelation algorithm. In total, 87 breath cycles were identified from sounds with mask, and 82 without mask. Time-frequency analysis of the signals was used to extract comparison features such as peak frequency, median frequency, band power, or spectral integration. All the features extracted in frequency content, its evolution, or power did not significantly differ between respiratory cycles with or without mask. This early stage study thus suggests minor impact on clinical diagnostic outcomes in pulmonary auscultation. However, further analysis is necessary such as on adventitious sounds characteristics differences with or without mask, to determine if facemask could lead to no discernible diagnostic outcome in clinical practice. [less ▲]

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See detailA review in radiomics: Making personalized medicine a reality via routine imaging.
Guiot, Julien ULiege; Vaidyanathan, Akshayaa; DEPREZ, Louis ULiege et al

in Medicinal Research Reviews (2021)

Radiomics is the quantitative analysis of standard-of-care medical imaging; the information obtained can be applied within clinical decision support systems to create diagnostic, prognostic, and/or ... [more ▼]

Radiomics is the quantitative analysis of standard-of-care medical imaging; the information obtained can be applied within clinical decision support systems to create diagnostic, prognostic, and/or predictive models. Radiomics analysis can be performed by extracting hand-crafted radiomics features or via deep learning algorithms. Radiomics has evolved tremendously in the last decade, becoming a bridge between imaging and precision medicine. Radiomics exploits sophisticated image analysis tools coupled with statistical elaboration to extract the wealth of information hidden inside medical images, such as computed tomography (CT), magnetic resonance (MR), and/or Positron emission tomography (PET) scans, routinely performed in the everyday clinical practice. Many efforts have been devoted in recent years to the standardization and validation of radiomics approaches, to demonstrate their usefulness and robustness beyond any reasonable doubts. However, the booming of publications and commercial applications of radiomics approaches warrant caution and proper understanding of all the factors involved to avoid "scientific pollution" and overly enthusiastic claims by researchers and clinicians alike. For these reasons the present review aims to be a guidebook of sorts, describing the process of radiomics, its pitfalls, challenges, and opportunities, along with its ability to improve clinical decision-making, from oncology and respiratory medicine to pharmacological and genotyping studies. [less ▲]

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See detailAsthma and COPD Are Not Risk Factors for ICU Stay and Death in Case of SARS-CoV2 Infection
CALMES, Doriane ULiege; Graff, Sophie ULiege; MAES, Nathalie ULiege et al

in Journal of Allergy and Clinical Immunology: In Practice (2021), 9(1), 160-169

BACKGROUND: Asthmatics and patients with chronic obstructive pulmonary disease (COPD) have more severe outcomes with viral infections than people without obstructive disease. OBJECTIVE: To evaluate if ... [more ▼]

BACKGROUND: Asthmatics and patients with chronic obstructive pulmonary disease (COPD) have more severe outcomes with viral infections than people without obstructive disease. OBJECTIVE: To evaluate if obstructive diseases are risk factors for intensive care unit (ICU) stay and death due to coronavirus disease 2019 (COVID19). METHODS: We collected data from the electronic medical record from 596 adult patients hospitalized in University Hospital of Liege between March 18 and April 17, 2020, for severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection. We classified patients into 3 groups according to the underlying respiratory disease, present before the COVID19 pandemic. RESULTS: Among patients requiring hospitalization for COVID19, asthma and COPD accounted for 9.6% and 7.7%, respectively. The proportions of asthmatics, patients with COPD, and patients without obstructive airway disease hospitalized in the ICU were 17.5%, 19.6%, and 14%, respectively. One-third of patients with COPD died during hospitalization, whereas only 7.0% of asthmatics and 13.6% of patients without airway obstruction died due to SARS-CoV2. The multivariate analysis showed that asthma, COPD, inhaled corticosteroid treatment, and oral corticosteroid treatment were not independent risk factors for ICU admission or death. Male gender (odds ratio [OR]: 1.9; 95% confidence interval [CI]: 1.1-3.2) and obesity (OR: 8.5; 95% CI: 5.1-14.1) were predictors of ICU admission, whereas male gender (OR 1.9; 95% CI: 1.1-3.2), older age (OR: 1.9; 95% CI: 1.6-2.3), cardiopathy (OR: 1.8; 95% CI: 1.1-3.1), and immunosuppressive diseases (OR: 3.6; 95% CI: 1.5-8.4) were independent predictors of death. CONCLUSION: Asthma and COPD are not risk factors for ICU admission and death related to SARS-CoV2 infection. [less ▲]

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See detailCan predicting COVID-19 mortality in a European cohort using only demographic and comorbidity data surpass age-based prediction: An externally validated study.
Chatterjee, Avishek; Wu, Guangyao; Primakov, Sergey et al

in PLoS ONE (2021), 16(4), 0249920

OBJECTIVE: To establish whether one can build a mortality prediction model for COVID-19 patients based solely on demographics and comorbidity data that outperforms age alone. Such a model could be a ... [more ▼]

OBJECTIVE: To establish whether one can build a mortality prediction model for COVID-19 patients based solely on demographics and comorbidity data that outperforms age alone. Such a model could be a precursor to implementing smart lockdowns and vaccine distribution strategies. METHODS: The training cohort comprised 2337 COVID-19 inpatients from nine hospitals in The Netherlands. The clinical outcome was death within 21 days of being discharged. The features were derived from electronic health records collected during admission. Three feature selection methods were used: LASSO, univariate using a novel metric, and pairwise (age being half of each pair). 478 patients from Belgium were used to test the model. All modeling attempts were compared against an age-only model. RESULTS: In the training cohort, the mortality group's median age was 77 years (interquartile range = 70-83), higher than the non-mortality group (median = 65, IQR = 55-75). The incidence of former/active smokers, male gender, hypertension, diabetes, dementia, cancer, chronic obstructive pulmonary disease, chronic cardiac disease, chronic neurological disease, and chronic kidney disease was higher in the mortality group. All stated differences were statistically significant after Bonferroni correction. LASSO selected eight features, novel univariate chose five, and pairwise chose none. No model was able to surpass an age-only model in the external validation set, where age had an AUC of 0.85 and a balanced accuracy of 0.77. CONCLUSION: When applied to an external validation set, we found that an age-only mortality model outperformed all modeling attempts (curated on www.covid19risk.ai) using three feature selection methods on 22 demographic and comorbid features. [less ▲]

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See detailMapping the human genetic architecture of COVID-19 by worldwide meta-analysis
The COVID-19 Host Genetics Initiative; Gazon, Hélène; JUSZCZAK, Danusia ULiege et al

in Nature (2021)

The genetic makeup of an individual contributes to susceptibility and response to viral infection. While environmental, clinical and social factors play a role in exposure to SARS-CoV-2 and COVID-19 ... [more ▼]

The genetic makeup of an individual contributes to susceptibility and response to viral infection. While environmental, clinical and social factors play a role in exposure to SARS-CoV-2 and COVID-19 disease severity, host genetics may also be important. Identifying host-specific genetic factors indicate biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-COV-2 infection and COVID-19 severity. We describe the results of three genome-wide association meta-analyses comprising 49,562 COVID-19 patients from 46 studies across 19 countries worldwide. We reported 15 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases. They also represent potentially actionable mechanisms in response to infection. We further identified smoking and body mass index as causal risk factors for severe COVID-19. The identification of novel host genetic factors associated with COVID-19, with unprecedented speed, was enabled by prioritization of shared resources and analytical frameworks. This working model of international collaboration a blue-print for future genetic discoveries in the event of pandemics or for any complex human disease. [less ▲]

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See detailMacrophage-derived exosomes attenuate fibrosis in airway epithelial cells through delivery of antifibrotic miR-142-3p
GUIOT, Julien ULiege; Cambier, Maureen ULiege; Boeckx, Amandine ULiege et al

in Thorax (2020), 75(10), 870-881

Introduction: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrosing interstitial lung disease of unknown aetiology and cure. Recent studies have reported a dysregulation of exosomal microRNAs ... [more ▼]

Introduction: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrosing interstitial lung disease of unknown aetiology and cure. Recent studies have reported a dysregulation of exosomal microRNAs (miRs) in the IPF context. However, the impact of IPF-related exosomal miRs on the progression of pulmonary fibrosis is unknown. Methods: Two independent cohorts were enrolled at the ambulatory care polyclinic of Liège University. Exosomes from sputum were obtained from 19 patients with IPF and 23 healthy subjects (HSs) (cohort 1), and the ones from plasma derived from 14 patients with IPF and 14 HSs (cohort 2). Exosomal miR expression was performed by quantitative reverse transcription–PCR. The functional role of exosomal miRs was assessed in vitro by transfecting miR mimics in human alveolar epithelial cells and lung fibroblasts. Results: Exosomal miR analysis showed that miR-142-3p was significantly upregulated in sputum and plasma of patients with IPF (8.06-fold, p<0.0001; 1.64 fold, p=0.008, respectively). Correlation analysis revealed a positive association between exosomal miR-142-3p and the percentage of macrophages from sputum of patients with IPF (r=0.576, p=0.012), suggesting macrophage origin of exosomal miR-142-3p upregulation. The overexpression of miR-142-3p in alveolar epithelial cells and lung fibroblasts was able to reduce the expression of transforming growth factor β receptor 1 (TGFβ-R1) and profibrotic genes. Furthermore, exosomes isolated from macrophages present antifibrotic properties due in part to the repression of TGFβ-R1 by miR-142-3p transfer in target cells. Discussion: Our results suggest that macrophage-derived exosomes may fight against pulmonary fibrosis progression via the delivery of antifibrotic miR-142–3 p to alveolar epithelial cells and lung fibroblasts. [less ▲]

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See detailDiagnostic and Prognostic Biomarkers for Chronic Fibrosing Interstitial Lung Diseases With a Progressive Phenotype
Inoue, Y.; Kaner, R. J.; Guiot, Julien ULiege et al

in CHEST (2020), 158(2), 646-659

Biomarkers have the potential to become central to the clinical evaluation and monitoring of patients with chronic fibrosing interstitial lung diseases (ILDs) with a progressive phenotype. Here we ... [more ▼]

Biomarkers have the potential to become central to the clinical evaluation and monitoring of patients with chronic fibrosing interstitial lung diseases (ILDs) with a progressive phenotype. Here we summarize the current understanding of putative serum, BAL fluid, and genetic biomarkers in this setting, according to their hypothesized pathobiologic mechanisms: evidence of epithelial cell dysfunction (eg, Krebs von den Lungen-6 antigen), fibroblast proliferation and extracellular matrix production or turnover (eg, matrix metalloproteinase-1), or immune dysregulation (eg, CC chemokine ligand 18). While most of the available data come from idiopathic pulmonary fibrosis (IPF), the prototypic progressive fibrosing ILD, data are available in the broader patient population of chronic fibrosing ILDs. A number of these biomarkers show promise, however, none have been validated. In this review article, we assess both the status of proposed biomarkers for chronic fibrosing lung diseases with a progressive phenotype in predicting disease risk or predisposition, diagnosis, prognosis, and treatment response and provide a direct comparison between IPF and other chronic fibrotic ILDs. We also reflect on the current clinical usefulness and future direction of research for biomarkers in the setting of chronic fibrosing ILDs with a progressive phenotype. © 2020 The Authors [less ▲]

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See detailExosomal Long Non-Coding RNAs in Lung Diseases
Poulet, Christophe ULiege; NJOCK, Makon-Sébastien ULiege; MOERMANS, Catherine ULiege et al

in International Journal of Molecular Sciences (2020), 21(10), 3580

Within the non-coding genome landscape, long non-coding RNAs (lncRNAs) and their secretion within exosomes are a window that could further explain the regulation, the sustaining, and the spread of lung ... [more ▼]

Within the non-coding genome landscape, long non-coding RNAs (lncRNAs) and their secretion within exosomes are a window that could further explain the regulation, the sustaining, and the spread of lung diseases. We present here a compilation of the current knowledge on lncRNAs commonly found in Chronic Obstructive Pulmonary Disease (COPD), asthma, Idiopathic Pulmonary Fibrosis (IPF), or lung cancers. We built interaction networks describing the mechanisms of action for COPD, asthma, and IPF, as well as private networks for H19, MALAT1, MEG3, FENDRR, CDKN2B-AS1, TUG1, HOTAIR, and GAS5 lncRNAs in lung cancers. We identified five signaling pathways targeted by these eight lncRNAs over the lung diseases mentioned above. These lncRNAs were involved in ten treatment resistances in lung cancers, with HOTAIR being itself described in seven resistances. Besides, five of them were previously described as promising biomarkers for the diagnosis and prognosis of asthma, COPD, and lung cancers. Additionally, we describe the exosomal-based studies on H19, MALAT1, HOTAIR, GAS5, UCA1, lnc-MMP2-2, GAPLINC, TBILA, AGAP2-AS1, and SOX2-OT. This review concludes on the need for additional studies describing the lncRNA mechanisms of action and confirming their potential as biomarkers, as well as their involvement in resistance to treatment, especially in non-cancerous lung diseases. [less ▲]

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See detailL’hypertension (artérielle) pulmonaire : l’apport des nouveaux vasodilatateurs artériels pulmonaires
Guiot, Julien ULiege; CORNIA, Olivia ULiege; Louis, Renaud ULiege

in Revue medicale de Liege (2020), 75(5-6), 344-349

Pulmonary arterial hypertension (PAH) is a rare disease, characterized by a progressive increase in pulmonary arterial pressure. The therapeutic management of PAH patients has evolved significantly over ... [more ▼]

Pulmonary arterial hypertension (PAH) is a rare disease, characterized by a progressive increase in pulmonary arterial pressure. The therapeutic management of PAH patients has evolved significantly over the past decades following the appearance of new specific therapies, but also the performance of multiple clinical studies in an otherwise rare pathology. As a result, the care is very well codified and makes it possible to treat all patients at best. To date, we can cite four therapeutic families: endothelin receptor antagonists (ERA), drugs that interfere with the cyclic guanosine monophosphate (cGMP) pathway such as phosphodiesterase type 5 inhibitors (PDE5i) or the stimulator of soluble guanylate cyclase, prostacyclin analogues, and, finally, calcium antagonists. The therapeutic approach, formerly sequential, has proven to be insufficient in favor of an aggressive and rapidly progressive upfront therapeutic approach, making it possible to greatly improve the morbidity and mortality of patients. In this context, early management remains the most appropriate attitude and justifies recourse, from the first symptoms, to a competence center. [less ▲]

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See detailLes aspects radiologiques de la pneumopathie à COVID-19 : de l’imagerie conventionnelle à l’intelligence artificielle.
Guiot, Julien ULiege; Danthine, Denis ULiege; DEPREZ, Louis ULiege et al

in Revue medicale de Liege (2020), 75(S1), 81-85

In the course of the pandemic induced by the appearance of a new coronavirus (SARS-CoV-2; COVID-19) causing acute respiratory distress syndrome (ARDS), we had to rethink the diagnostic approach for ... [more ▼]

In the course of the pandemic induced by the appearance of a new coronavirus (SARS-CoV-2; COVID-19) causing acute respiratory distress syndrome (ARDS), we had to rethink the diagnostic approach for patients suffering from respiratory symptoms. Indeed, although the use of RT-PCR remains the keystone of the diagnosis, the delay in diagnosis as well as the overload of the microbiological platforms have led us to make almost systematic the use of thoracic imaging for taking in charge of patients. In this context, thoracic imaging has shown a major interest in diagnostic aid in order to better guide the management of patients admitted to hospital. The most common signs encountered are particularly well described in thoracic computed tomography. Typical imaging combines bilateral, predominantly peripheral and posterior, multi-lobar, ground glass opacities. Of note, it is common to identify significant lesions in asymptomatic patients, with imaging sometimes preceding the onset of symptoms. Beyond conventional chest imaging, many teams have developed new artificial intelligence tools to better help clinicians in decision-making. [less ▲]

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See detailA new nucleosomic-based model to identify and diagnose SSc-ILD
Guiot, Julien ULiege; HENKET, Monique ULiege; André, Béatrice ULiege et al

in Clinical Epigenetics (2020), 12(1), 124

BACKGROUND: Systemic sclerosis (SSc) is a rare connective tissue disease associated with rapid evolving interstitial lung disease (SSc-ILD), driving its mortality. Specific biomarkers associated with the ... [more ▼]

BACKGROUND: Systemic sclerosis (SSc) is a rare connective tissue disease associated with rapid evolving interstitial lung disease (SSc-ILD), driving its mortality. Specific biomarkers associated with the evolution of the lung disease are highly needed. We aimed to identify specific biomarkers of SSc-ILD to predict the evolution of the disease. Nucleosomes are stable DNA/protein complexes that are shed into the blood stream making them ideal candidates for biomarkers. METHODS: We studied circulating cell-free nucleosomes (cf-nucleosomes) in SSc patients, 31 with ILD (SSc-ILD) and 67 without ILD. We analyzed plasma levels for cf-nucleosomes and investigated whether global circulating nucleosome levels in association with or without other biomarkers of interest for systemic sclerosis or lung fibrosis (e.g., serum growth factors: IGFBP-1 and the MMP enzyme: MMP-9), could be suitable potential biomarkers for the correct identification of SSc-ILD disease. RESULTS: We found that H3.1 nucleosome levels were significantly higher in patients with SSc-ILD compared SSc patients without ILD (p < 0.05) and levels of MMP-9 were significantly increased in patients with SSc-ILD compared to SSc patients without ILD (p < 0.05). Conversely, IGFBP-1 was significantly reduced in patients with SSc-ILD compared to SSc without ILD (p < 0.001). The combination of cf-nucleosomes H3.1 coupled to MMP-9 and IGFBP-1 increased the sensitivity for the differential detection of SSc-ILD. High levels of accuracy were reached with this combined model: its performances are strong with 68.4% of positive predictive value and 77.2% of negative predictive value for 90% of specificity. With our model, we identified a significant negative correlation with FVC % pred (r = -0.22) and TLC % pred (r = -0.31). The value of our model at T1 (baseline) has a predictive power over the Rodnan score at T2 (after 6-18 months), showed by a significant linear regression with R2 = 19% (p = 0.013). We identified in the sole group of SSc-ILD patients a significant linear regression with a R2 = 54.4% with the variation of DLCO between T1 and T2 (p < 0.05). CONCLUSION: In our study, we identified a new blood-based model with nucleosomic biomarker in order to diagnose SSc-ILD in a SSc cohort. This model is correlated with TLC and FVC at baseline and predictive of the skin evolution and the DLCO. Further longitudinal exploration studies should be performed in order to evaluate the potential of such diagnostic and predictive model. [less ▲]

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See detailSingle-center experience of patients with interstitial lung diseases during the early days of te COVID-19 pandemic.
GUIOT, Julien ULiege; HENKET, Monique ULiege; Frix, Anne-Noëlle ULiege et al

in Respiratory Investigation (2020), 58(6), 437-9

Introduction: Patients with interstitial lung diseases (ILD) can be suspected to be at risk of experiencing a rapid flare-up due to COVID-19. However, no specific data are currently available for these ... [more ▼]

Introduction: Patients with interstitial lung diseases (ILD) can be suspected to be at risk of experiencing a rapid flare-up due to COVID-19. However, no specific data are currently available for these patients. <br /> <br />Methods: We retrospectively analyzed a cohort of 401 patients with ILD and determined the proportion of patients hospitalized for proven severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and specific symptoms of COVID-19. <br /> <br />Results: We found that 1% of patients (n = 4) were hospitalized (1 in ICU) for COVID-19. In total, 310 of the 401 patients answered the phone call. Only 33 patients (0.08%) experienced specific symptoms of SARS-CoV-2 infection. <br /> <br />Conclusion: Our study did not demonstrate any increased occurrence of severe COVID-19 in ILD patients compared to the global population. Based on our findings, we could not make any conclusion on the incidence rate of SARS-CoV-2 infection in patients with ILDs, or on the overall outcome of immunocompromised patients affected by COVID-19. [less ▲]

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See detailDevelopment and Validation of an Automated Radiomic CT Signature for Detecting COVID-19.
GUIOT, Julien ULiege; Vaidyanathan, Akshayaa; DEPREZ, Louis ULiege et al

in Diagnostics (Basel, Switzerland) (2020), 11(1),

The coronavirus disease 2019 (COVID-19) outbreak has reached pandemic status. Drastic measures of social distancing are enforced in society and healthcare systems are being pushed to and beyond their ... [more ▼]

The coronavirus disease 2019 (COVID-19) outbreak has reached pandemic status. Drastic measures of social distancing are enforced in society and healthcare systems are being pushed to and beyond their limits. To help in the fight against this threat on human health, a fully automated AI framework was developed to extract radiomics features from volumetric chest computed tomography (CT) exams. The detection model was developed on a dataset of 1381 patients (181 COVID-19 patients plus 1200 non COVID control patients). A second, independent dataset of 197 RT-PCR confirmed COVID-19 patients and 500 control patients was used to assess the performance of the model. Diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC). The model had an AUC of 0.882 (95% CI: 0.851-0.913) in the independent test dataset (641 patients). The optimal decision threshold, considering the cost of false negatives twice as high as the cost of false positives, resulted in an accuracy of 85.18%, a sensitivity of 69.52%, a specificity of 91.63%, a negative predictive value (NPV) of 94.46% and a positive predictive value (PPV) of 59.44%. Benchmarked against RT-PCR confirmed cases of COVID-19, our AI framework can accurately differentiate COVID-19 from routine clinical conditions in a fully automated fashion. Thus, providing rapid accurate diagnosis in patients suspected of COVID-19 infection, facilitating the timely implementation of isolation procedures and early intervention. [less ▲]

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See detailDevelopment of a Clinical Decision Support System for Severity Risk Prediction and Triage of COVID-19 Patients at Hospital Admission: an International Multicenter Study.
Wu, Guangyao; Yang, Pei; Xie, Yuanliang et al

in European Respiratory Journal (2020)

BACKGROUND: The outbreak of the coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality. OBJECTIVE: To develop and validate machine-learning model ... [more ▼]

BACKGROUND: The outbreak of the coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality. OBJECTIVE: To develop and validate machine-learning model based on clinical features for severity risk assessment and triage for COVID-19 patients at hospital admission. METHOD: 725 patients were used to train and validate the model including a retrospective cohort of 299 hospitalised COVID-19 patients at Wuhan, China, from December 23, 2019, to February 13, 2020, and five cohorts with 426 patients from eight centers in China, Italy, and Belgium, from February 20, 2020, to March 21, 2020. The main outcome was the onset of severe or critical illness during hospitalisation. Model performances were quantified using the area under the receiver operating characteristic curve (AUC) and metrics derived from the confusion-matrix. RESULTS: The median age was 50.0 years and 137 (45.8%) were men in the retrospective cohort. The median age was 62.0 years and 236 (55.4%) were men in five cohorts. The model was prospectively validated on five cohorts yielding AUCs ranging from 0.84 to 0.89, with accuracies ranging from 74.4% to 87.5%, sensitivities ranging from 75.0% to 96.9%, and specificities ranging from 57.5% to 88.0%, all of which performed better than the pneumonia severity index. The cut-off values of the low, medium, and high-risk probabilities were 0.21 and 0.80. The online-calculators can be found at www.covid19risk.ai. CONCLUSION: The machine-learning model, nomogram, and online-calculator might be useful to access the onset of severe and critical illness among COVID-19 patients and triage at hospital admission. [less ▲]

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See detailIgG4-related pleural disease in a patient with a history of unknown origin acute pancreatitis: a case report and review of the literature.
Damas, François ULiege; Ghysen, K.; GESTER, Fanny ULiege et al

in Acta Clinica Belgica (2019), 8

Immunoglobulin G4-related disease is a rare autoimmune systemic disease with the capability of involving every organ. The disease is microscopically defined by a diffuse tissular inflammation with an ... [more ▼]

Immunoglobulin G4-related disease is a rare autoimmune systemic disease with the capability of involving every organ. The disease is microscopically defined by a diffuse tissular inflammation with an infiltration of IgG4 positive plasma cells in the affected organs. IgG4 disease has an increasing incidence in the last few years with a growing interest in its pathophysiology still misunderstood to date. Despite the growing recognition of this pathology, the literature still does not allow to propose a simple diagnostic algorithm. In this article, we present a case of a 56-year-old man with a history of unknown etiology acute pancreatitis and a unilateral pleural effusion. [less ▲]

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See detailExosomal miRNAs in Lung Diseases: From Biologic Function to Therapeutic Targets.
GUIOT, Julien ULiege; Struman, Ingrid ULiege; Louis, Edouard ULiege et al

in Journal of clinical medicine (2019), 8(9),

Increasing evidence suggests the potential role of extracellular vesicles (EVs) in many lung diseases. According to their subcellular origin, secretion mechanism, and size, EVs are currently classified ... [more ▼]

Increasing evidence suggests the potential role of extracellular vesicles (EVs) in many lung diseases. According to their subcellular origin, secretion mechanism, and size, EVs are currently classified into three subpopulations: exosomes, microvesicles, and apoptotic bodies. Exosomes are released in most biofluids, including airway fluids, and play a key role in intercellular communication via the delivery of their cargo (e.g., microRNAs (miRNAs)) to target cell. In a physiological context, lung exosomes present protective effects against stress signals which allow them to participate in the maintenance of lung homeostasis. The presence of air pollution alters the composition of lung exosomes (dysregulation of exosomal miRNAs) and their homeostatic property. Indeed, besides their potential as diagnostic biomarkers for lung diseases, lung exosomes are functional units capable of dysregulating numerous pathophysiological processes (including inflammation or fibrosis), resulting in the promotion of lung disease progression. Here, we review recent studies on the known and potential role of lung exosomes/exosomal miRNAs, in the maintaining of lung homeostasis on one hand, and in promoting lung disease progression on the other. We will also discuss using exosomes as prognostic/diagnostic biomarkers as well as therapeutic tools for lung diseases. [less ▲]

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See detailBiomarkers in systemic sclerosis-associated interstitial lung disease: review of the literature.
BONHOMME, Olivier ULiege; ANDRE, Béatrice ULiege; GESTER, Fanny ULiege et al

in Rheumatology (Oxford, England) (2019)

SSc is a rare disease of unknown origin associated with multiple organ involvement. One of the major complications that drives the mortality of SSc patients is interstitial lung disease. The course of SSc ... [more ▼]

SSc is a rare disease of unknown origin associated with multiple organ involvement. One of the major complications that drives the mortality of SSc patients is interstitial lung disease. The course of SSc-interstitial lung disease progression has a wide spectrum. Since the treatment is based on aggressive immunosuppression it should not be given to stable or non-progressing disease. The correct identification of disease with high risk of progression remains a challenge for early therapeutic intervention, and biomarkers remain urgently needed. In fact, eight categories of biomarkers have been identified and classified according to the different biological pathways involved. The purpose of this article is to describe the main biomarkers thought to be of interest with clinical value in the diagnosis and prognosis of SSc-interstitial lung disease. [less ▲]

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