Clinical course of suspected familial and sporadic idiopathic pulmonary fibrosis: Data from the PROOF-Next registry.

BACKGROUND AND OBJECTIVE: Real-life data on suspected familial fibrosis, defined as the occurrence of the disease in a patient younger than 50 and/or having at least one relative affected by pulmonary fibrosis remain scarce. METHODS: The Belgian and Luxembourg IPF registry (PROOF-Next) is a multicentric prospective longitudinal and observational study set in Belgium and Luxembourg. We compared characteristics and clinical course of patients with suspected familial pulmonary fibrosis (FPF) and sporadic IPF. RESULTS: We included 618 patients in the analysis, of whom 76 (12%) fulfilled criteria for FPF. They were significantly younger than sIPF (median age (range) 65 (43-87), vs. 72 (51-98), p = 0.0001). Male gender proportion and smoking status did not differ between groups, but the number of pack-year among current and former smokers was lower in FPF (20 vs. 25, p = 0.02). Besides, 87% of FPF and 76% of sIPF were treated with antifibrotic (p = 0.047). Baseline pulmonary function tests were similar in both groups, as well as median time before progression and transplant-free survival. Finally, genetic testing, performed in a minority, led to the identification of 10 telomerase-related gene variants. CONCLUSION: Although younger and exposed to less tobacco, patients with FPF show an equally aggressive progression as observed in sporadic IPF patients. These results warrant early referral of FPF patients to expert centres for optimal management.

Systematic review of overlapping microRNA patterns in COVID-19 and idiopathic pulmonary fibrosis.

BACKGROUND: Pulmonary fibrosis is an emerging complication of SARS-CoV-2 infection. In this study, we speculate that patients with COVID-19 and idiopathic pulmonary fibrosis (IPF) may share aberrant expressed microRNAs (miRNAs) associated to the progression of lung fibrosis. OBJECTIVE: To identify miRNAs presenting similar alteration in COVID-19 and IPF, and describe their impact on fibrogenesis. METHODS: A systematic review of the literature published between 2010 and January 2022 (PROSPERO, CRD42022341016) was conducted using the key words (COVID-19 OR SARS-CoV-2) AND (microRNA OR miRNA) or (idiopathic pulmonary fibrosis OR IPF) AND (microRNA OR miRNA) in Title/Abstract. RESULTS: Of the 1988 references considered, 70 original articles were appropriate for data extraction: 27 studies focused on miRNAs in COVID-19, and 43 on miRNAs in IPF. 34 miRNAs were overlapping in COVID-19 and IPF, 7 miRNAs presenting an upregulation (miR-19a-3p, miR-200c-3p, miR-21-5p, miR-145-5p, miR-199a-5p, miR-23b and miR-424) and 9 miRNAs a downregulation (miR-17-5p, miR-20a-5p, miR-92a-3p, miR-141-3p, miR-16-5p, miR-142-5p, miR-486-5p, miR-708-3p and miR-150-5p). CONCLUSION: Several studies reported elevated levels of profibrotic miRNAs in COVID-19 context. In addition, the balance of antifibrotic miRNAs responsible of the modulation of fibrotic processes is impaired in COVID-19. This evidence suggests that the deregulation of fibrotic-related miRNAs participates in the development of fibrotic lesions in the lung of post-COVID-19 patients.

[An emerging cause of chronic fatigue and pain : post-COVID-19 condition or long COVID]. / Une cause émergente de fatigue et de douleurs chroniques : l'affection post-COVID-19 ou COVID long.

Some individuals who have been infected with SARS-CoV-2 can experience long-term effects from their infection, known as post-COVID conditions, post-acute sequelae of COVID-19 or long COVID. Different underlying mechanisms can lead to long COVID, none of which are mutually exclusive. Lingering symptoms can persist years after SARS-CoV-2 infection, including fatigue, muscle weakness, tachycardia, dyspnea and various neurological symptoms. The symptomatology is partly similar to that reported by people with chronic fatigue syndrome and other unwell studied long-lasting diseases that may occur after other infections. People who have experienced more severe COVID-19 illness are at higher risk of developing long COVID, although anyone who was infected can experience post-COVID conditions. Importantly, unvaccinated individuals are more likely to develop long COVID. Here we review the current knowledge and discuss key findings regarding the epidemiology and physiopathology of long COVID. We briefly review current diagnostic and treatment options that remain so far largely insufficient.

Certains individus infectés par le SARS-CoV-2 peuvent présenter des symptômes à long terme, évoluant parfois durant plusieurs années. Il est alors question d'affection post-COVID-19 ou COVID long. Les symptômes sont très polymorphes, fluctuants, et comprennent, notamment, une fatigue intense, des douleurs articulaires et musculaires, de la dyspnée, de la tachycardie, ainsi qu'une constellation de plaintes neurologiques. Cette symptomatologie est, en partie, similaire à celle du syndrome de fatigue chronique et est retrouvée également après d'autres types d'infections. Les mécanismes à l'origine du COVID long sont probablement multiples et encore mal connus. Si le COVID long peut toucher tout individu infecté par le SARS-CoV-2, certains groupes sont plus à risque, notamment les personnes non vaccinées ou les individus ayant présenté une infection sévère. Dans cet article, nous résumons les connaissances actuelles et mettons en lumière les découvertes clés quant à l'épidémiologie et aux mécanismes physiopathologiques du COVID long. Nous discutons aussi des critères diagnostiques et des options thérapeutiques qui sont, à ce jour, largement insuffisantes.

[Advances in pulmonary hypertension diagnosis and risk stratification]. / Nouveautés dans le diagnostic et la stratification du risque de l'hypertension pulmonaire.

Pulmonary hypertension (PH) is a common clinical condition linked to chronic cardiopulmonary illnesses. It must be distinguished from pulmonary arterial hypertension (PAH), a rare disease characterized by a specific involvement of the pulmonary arterial bed. An early diagnosis and accurate classification by a multidisciplinary team are necessary for a multimodal and individualized therapy approach. This article aims to provide a summary of the most recent ESC/ERS recommendations published in 2022.

L'hypertension pulmonaire (HTP) est une entité clinique fréquemment retrouvée chez les patients atteints d'affections cardio-pulmonaires chroniques. Elle est à différentier de l'hypertension artérielle pulmonaire (HTAP) qui est, quant à elle, une maladie rare caractérisée par une atteinte spécifique du lit artériel pulmonaire. Une identification précoce et une classification correcte, en équipe pluridisciplinaire, sont primordiales pour une prise en charge thérapeutique multimodale et personnalisée. Cet article a pour but de résumer, de façon pratique, les dernières recommandations des sociétés européennes de cardiologie (ESC) et de pneumologie (ERS) publiées en 2022.

[Clinically amyopathic dermatomyositis : a rare entity associated with acute and severe interstitial lung disease]. / La dermatomyosite amyopathique : une entité rare associée à une pneumopathie interstitielle fulminante.

Dermatomyositis is a rare disease of unknown etiology characterized by a severe inflammatory myopathy associated with a cutaneous syndrome. Dermatomyositis is associated with multisystemic disorders mostly represented by cardiac, pulmonary and articular involvements, which are particularly associated with a bad prognosis. We report a case of a 50-year-old patient suffering from dermatomyositis associated with an interstitial lung disease with a particularly fast and pejorative clinical evolution. The anti-Melanoma Differentiation-Associated gene 5 (anti-MDA5) antibodies are frequently associated with a severe and rapidly progressive lung disease without myositis named «amyopathic dermatomyositis¼. High blood levels of anti-MDA5 were found in our patient. Despite maximal immunosuppressive treatment and supportive care, he died 3 months after the diagnosis. Patients may present different antibodies that correspond to distinct clinical phenotypes of dermatomyositis. The anti-MDA5 is known to be a marker of clinically amyopathic dermatomyositis (CADM) associated with a rapidly progressive interstitial lung disease. Moreover, blood level of anti-MDA5 antibody predicts the response to treatment and survival in CADM.

La dermatomyosite est une maladie rare, d'étiologie inconnue, caractérisée par une myopathie inflammatoire associée à un syndrome cutané typique. Outre l'atteinte musculaire et cutanée, la dermatomyosite peut se manifester par des atteintes organiques, notamment pulmonaires, cardiaques et articulaires qui contribuent à la sévérité de la maladie. Nous rapportons le cas d'un patient âgé de 50 ans atteint d'une dermatomyosite compliquée d'une pneumopathie interstitielle d'évolution clinique particulièrement rapide et péjorative. Le patient présentait des anticorps anti-MDA5 (anti-Melanoma Differentiation-Associated gene 5), anticorps associés assez fréquemment à une atteinte pulmonaire sévère et rapidement progressive, ainsi qu'à une présentation particulière de la maladie appelée «dermatomyosite amyopathique¼. Malgré un traitement immunosuppresseur intensif, l'état pulmonaire du patient s'est rapidement aggravé, entraînant son décès par insuffisance respiratoire trois mois après le diagnostic. Cette histoire clinique illustre le fait que les patients atteints de dermatomyosite peuvent présenter différents anticorps qui correspondent à des phénotypes cliniques distincts. L'association entre anticorps anti-MDA5 et la pathologie pulmonaire interstitielle justifie qu'un screening des anticorps anti-MDA5 soit réalisé chez les patients porteurs d'une dermatomyosite. De plus, le titrage sanguin des anti-MDA5 est un facteur pronostique de la réponse au traitement et de la survie.

[Lung disease associated with rheumatoid arthritis]. / La pathologie pulmonaire associée à la polyarthrite rhumatoïde.

Rheumatoid arthritis is a chronic inflammatory systemic disease. Pulmonary manifestations are the most common extra-articular involvements and can impact all components of the respiratory system: parenchyma, pleura, vessels and airways, all complications that are briefly described in this article. Interstitial lung disease is the most common of these and is associated with significant morbidity and mortality. Its detection and monitoring are based on spirometry and thoracic imaging. Specific treatments are initiated in order to reduce the risk of disease flare up but may themselves in case of toxicity be associated with respiratory manifestations, either directly or by promoting infectious complications.

La polyarthrite rhumatoïde est une pathologie systémique inflammatoire chronique. Les manifestations pulmonaires représentent l'atteinte extra-articulaire la plus fréquente et peuvent affecter tous les composants du système respiratoire : le parenchyme, la plèvre, les vaisseaux et les voies aériennes, complications décrites brièvement dans cet article. La pneumopathie interstitielle diffuse en est la plus commune et associée à une morbi-mortalité importante. Son dépistage et son suivi reposent sur les épreuves fonctionnelles et l'imagerie thoracique. Des traitements spécifiques sont initiés afin de limiter au mieux l'évolution pulmonaire, mais peuvent eux-mêmes être associés à des manifestations respiratoires, soit directement, soit en favorisant des complications infectieuses.

A review in radiomics: Making personalized medicine a reality via routine imaging.

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.

Airway Macrophages Encompass Transcriptionally and Functionally Distinct Subsets Altered by Smoking.

Alveolar macrophages (AMs) are functionally important innate cells involved in lung homeostasis and immunity and whose diversity in health and disease is a subject of intense investigations. Yet, it remains unclear to what extent conditions like smoking or chronic obstructive pulmonary disease (COPD) trigger changes in the AM compartment. Here, we aimed to explore heterogeneity of human AMs isolated from healthy nonsmokers, smokers without COPD, and smokers with COPD by analyzing BAL fluid cells by flow cytometry and bulk and single-cell RNA sequencing. We found that subpopulations of BAL fluid CD206+ macrophages could be distinguished based on their degree of autofluorescence in each subject analyzed. CD206+ autofluorescenthigh AMs were identified as classical, self-proliferative AM, whereas autofluorescentlow AMs were expressing both monocyte and classical AM-related genes, supportive of a monocytic origin. Of note, monocyte-derived autofluorescentlow AMs exhibited a functionally distinct immunoregulatory profile, including the ability to secrete the immunosuppressive cytokine IL-10. Interestingly, single-cell RNA-sequencing analyses showed that transcriptionally distinct clusters of classical and monocyte-derived AM were uniquely enriched in smokers with and without COPD as compared with healthy nonsmokers. Of note, such smoking-associated clusters exhibited gene signatures enriched in detoxification, oxidative stress, and proinflammatory responses. Our study independently confirms previous reports supporting that monocyte-derived macrophages coexist with classical AM in the airways of healthy subjects and patients with COPD and identifies smoking-associated changes in the AM compartment that may favor COPD initiation or progression.

Combined obstructive airflow limitation associated with interstitial lung diseases (O-ILD): the bad phenotype ?

BACKGROUND: Patients suffering from combined obstructive and interstitial lung disease (O-ILD) represent a pathological entity which still has to be well clinically described. The aim of this descriptive and explorative study was to describe the phenotype and functional characteristics of a cohort of patients suffering from functional obstruction in a population of ILD patients in order to raise the need of dedicated prospective observational studies and the evaluation of the impact of anti-fibrotic therapies. METHODS: The current authors conducted a retrospective study including 557 ILD patients, with either obstructive (O-ILD, n = 82) or non-obstructive (non O-ILD, n = 475) pattern. Patients included were mainly males (54%) with a mean age of 62 years. RESULTS: Patients with O-ILD exhibited a characteristic functional profile with reduced percent predicted forced expired volume in 1 s (FEV1) [65% (53-77) vs 83% (71-96), p < 0.00001], small airway involvement assessed by maximum expiratory flow (MEF) 25/75 [29% (20-41) vs 81% (64-108), p < 0.00001], reduced sGaw [60% (42-75) vs 87% (59-119), p < 0.01] and sub-normal functional residual capacity (FRC) [113% (93-134) vs 92% (75-109), p < 0.00001] with no impaired of carbon monoxide diffusing capacity of the lung (DLCO) compared to those without obstruction. Total lung capacity (TLC) was increased in O-ILD patients [93% (82-107) vs 79% (69-91), p < 0.00001]. Of interest, DLCO sharply dropped in O-ILD patients over a 5-year follow-up. We did not identify a significant increase in mortality in patients with O-ILD. Interestingly, the global mortality was increased in the specific sub-group of patients with O-ILD and no progressive fibrosing ILD phenotype and in those with connective tissue disease associated ILD especially in case of rheumatoid arthritis. CONCLUSIONS: The authors individualized a specific functional-based pattern of ILD patients with obstructive lung disease, who are at risk of increased mortality and rapid DLCO decline over time. As classically those patients are excluded from clinical trials, a dedicated prospective study would be of interest in order to define more precisely treatment response of those patients.

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions.

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research.

Breathomics to diagnose systemic sclerosis using thermal desorption and comprehensive two-dimensional gas chromatography high-resolution time-of-flight mass spectrometry.

Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance t-test, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease.

Vital Signs Prediction for COVID-19 Patients in ICU.

This study introduces machine learning predictive models to predict the future values of the monitored vital signs of COVID-19 ICU patients. The main vital sign predictors include heart rate, respiration rate, and oxygen saturation. We investigated the performances of the developed predictive models by considering different approaches. The first predictive model was developed by considering the following vital signs: heart rate, blood pressure (systolic, diastolic and mean arterial, pulse pressure), respiration rate, and oxygen saturation. Similar to the first approach, the second model was developed using the same vital signs, but it was trained and tested based on a leave-one-subject-out approach. The third predictive model was developed by considering three vital signs: heart rate (HR), respiration rate (RR), and oxygen saturation (SpO2). The fourth model was a leave-one-subject-out model for the three vital signs. Finally, the fifth predictive model was developed based on the same three vital signs, but with a five-minute observation rate, in contrast with the aforementioned four models, where the observation rate was hourly to bi-hourly. For the five models, the predicted measurements were those of the three upcoming observations (on average, three hours ahead). Based on the obtained results, we observed that by limiting the number of vital sign predictors (i.e., three vital signs), the prediction performance was still acceptable, with the average mean absolute percentage error (MAPE) being 12%,5%, and 21.4% for heart rate, oxygen saturation, and respiration rate, respectively. Moreover, increasing the observation rate could enhance the prediction performance to be, on average, 8%,4.8%, and 17.8% for heart rate, oxygen saturation, and respiration rate, respectively. It is envisioned that such models could be integrated with monitoring systems that could, using a limited number of vital signs, predict the health conditions of COVID-19 ICU patients in real-time.

Macrophage-derived exosomes attenuate fibrosis in airway epithelial cells through delivery of antifibrotic miR-142-3p.

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 ß receptor 1 (TGFß-R1) and profibrotic genes. Furthermore, exosomes isolated from macrophages present antifibrotic properties due in part to the repression of TGFß-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.

Development of a clinical decision support system for severity risk prediction and triage of COVID-19 patients at hospital admission: an international multicentre study.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality. OBJECTIVE: To develop and validate a 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. This included a retrospective cohort from Wuhan, China of 299 hospitalised COVID-19 patients from 23 December 2019 to 13 February 2020, and five cohorts with 426 patients from eight centres in China, Italy and Belgium from 20 February 2020 to 21 March 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: In the retrospective cohort, the median age was 50 years and 137 (45.8%) were male. In the five test cohorts, the median age was 62 years and 236 (55.4%) were male. The model was prospectively validated on five cohorts yielding AUCs ranging from 0.84 to 0.93, with accuracies ranging from 74.4% to 87.5%, sensitivities ranging from 75.0% to 96.9%, and specificities ranging from 55.0% to 88.0%, most 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.

Exosomal Long Non-Coding RNAs in Lung Diseases.

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.

Sputum exosomes: promising biomarkers for idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive fibrosing interstitial lung disease of unknown aetiology which leads rapidly to death. As diagnosis of IPF is complex, we aimed to characterise microRNA (miRNA) content of exosomes from sputum of patients with IPF. Using miRNA quantitative PCR array, we found a substantial dysregulation of sputum exosomal miRNA levels between patients with IPF and healthy subjects and identified a unique signature of three miRNAs. Interestingly, we found a negative correlation between miR-142-3p and diffusing capacity of the lungs for carbon monoxide/alveolar volume. This is the first characterisation of miRNA content of sputum-derived exosomes in IPF that identified promising biomarkers for diagnosis and disease severity.

Suitable reference genes determination for real-time PCR using induced sputum samples.

Induced sputum is a non-invasive method of collecting cells from airways. Gene expression analysis from sputum cells has been used to understand the underlying mechanisms of airway diseases such as asthma or chronic obstructive pulmonary disease (COPD). Suitable reference genes for normalisation of target mRNA levels between sputum samples have not been defined so far.The current study assessed the expression stability of nine common reference genes in sputum samples from 14 healthy volunteers, 12 asthmatics and 12 COPD patients.Using three different algorithms (geNorm, NormFinder and BestKeeper), we identified HPRT1 and GNB2L1 as the most optimal reference genes to use for normalisation of quantitative reverse transcriptase (RT) PCR data from sputum cells. The higher expression stability of HPRT1 and GNB2L1 were confirmed in a validation set of patients including nine healthy controls, five COPD patients and five asthmatic patients. In this group, the RNA extraction and RT-PCR methods differed, which attested that these genes remained the most reliable whatever the method used to extract the RNA, generate complementary DNA or amplify it.Finally, an example of relative quantification of gene expression linked to eosinophils or neutrophils provided more accurate results after normalisation with the reference genes identified as the most stable compared to the least stable and confirmed our findings.

Biomarkers in systemic sclerosis-associated interstitial lung disease: review of the literature.

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.

Increased production of TGF-ß1 from sputum cells of COPD: Relationship with airway obstruction.

Chronic obstructive pulmonary disease (COPD) is a chronic airway disease characterized by a profound airway remodelling that leads to airway obstruction. A role for transforming growth factor-ß1 (TGF-ß1) has been proposed in airway remodelling of COPD. Regarding the TGF-ß1 production at local level, the results seemed to be controversial. In this study, an original model of sputum cell culture thought to maintain important cells interactions, was used. We investigated the production of TGF-ß1 from sputum cell culture in 33 COPD encompassing the whole severity spectrum and compared the results with those found in 39 healthy controls. Sputum was induced by inhalation of saline, the cellular fraction cultured for 24 h and the spontaneous production of total TGF-ß1 was assessed by ELISA. Using, a TGF-ß1 reporter cell assay, we also compared the levels of active and total TGF-ß1 in the sputum cell culture supernatants of COPD and controls. Moreover, as a combination of tumor necrosis factor-α (TNF-α) and TGF-ß1 have been shown to have a cumulative impact on the severity of airflow limitation in COPD, the TNF-α release was also measured in a representative subgroup of patients. Our results indicated that the use of sputum cell culture was a reliable and reproducible method to assess TGF-ß1 production at airway level. Sputum cells from COPD produced greater amount of total TGF-ß1 than those of healthy controls (p<0.001). This result was confirmed using the cell reporter assay which also showed a higher level of active TGF-ß1 in the COPD group compared to controls. In addition, total TGF-ß1 production was increased according to GOLD stage and was inversely related to FEV1/FVC ratio (p<0.05). By contrast, the production of this growth factor was not correlated with the functional markers of emphysema nor with demographic characteristics such as age, BMI or smoking status. Interestingly, the production of total TGF-ß1 was inversely related to that of TNF-α (r=-0.53, p<0.05) which was decreased in COPD. In summary, COPD patients displayed a raised production of total and active TGF-ß1 from their airway cells. Total TGF-ß1 correlates with the severity of airway obstruction without evidence of a link with emphysema. .