Induced Sputum in Systemic Sclerosis Interstitial Lung Disease: Comparison to Healthy Controls and Bronchoalveolar Lavage

Respiration ◽  
2009 ◽  
Vol 78 (1) ◽  
pp. 56-62 ◽  
Author(s):  
N. Damjanov ◽  
P. Ostojic ◽  
O. Kaloudi ◽  
S. Alari ◽  
S. Guiducci ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Bronchoalveolar Lavage ◽  
Lung Disease ◽  
Induced Sputum ◽  
Healthy Controls

scholarly journals Induced sputum compared to bronchoalveolar lavage for evaluating patients with sarcoidosis and non-granulomatous interstitial lung disease

1999 ◽  
Vol 93 (11) ◽  
pp. 827-834 ◽  
Author(s):  
E. Fireman ◽  
I. Topilsky ◽  
J. Greif ◽  
Y. Lerman ◽  
Y. Schwarz ◽  
...  
Keyword(s):  
Interstitial Lung Disease ◽  
Bronchoalveolar Lavage ◽  
Lung Disease ◽  
Induced Sputum

scholarly journals Increased levels of HE4 (WFDC2) in systemic sclerosis: a novel biomarker reflecting interstitial lung disease severity?

2020 ◽  
Vol 11 ◽  
pp. 204062232095642
Author(s):  
Mingxia Zhang ◽  
Liyun Zhang ◽  
Linning E ◽  
Ke Xu ◽  
Xu Fei Wang ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Pulmonary Function Tests ◽  
Lavage Fluid ◽  
Ct Scans ◽  
Function Parameter ◽  
Enzyme Linked Immunosorbent Assay ◽  
Healthy Controls ◽  
High Resolution Computed Tomography

Background: Human epididymis protein 4 (HE4, also known as WFDC-2) has been implicated in fibrotic disorders pathobiology. We tested the hypothesis that HE4 may be used as a candidate biomarker for systemic sclerosis (SSc)-related interstitial lung disease (SSc-ILD). Methods: A total of 169 consecutive SSc patients and 169 age-and sex-matched healthy controls were enrolled and blood samples were collected. Pulmonary function tests (PFTs) and paired lavage was performed on 169 patients and 37 healthy controls. All patients were classified as having SSc-no ILD or SSc-ILD, based on high-resolution computed tomography (CT) scans of the chest, and a semiquantitative grade of ILD extent was evaluated through CT scans (grade 1, 0–25%; grade 2, 26–50%; grade 3, 51–75%; grade 4, 76–100%). Serum and bronchoalveolar lavage fluid (BALF) HE4 levels were measured by enzyme-linked immunosorbent assay. Results: Serum HE4 levels were higher in SSc patients [median (interquartile range), 139.4 (85.9–181.8) pmol/l] compared with healthy controls [39.5 (24.3–54.2) pmol/l, p < 0.001] and were higher in patients with SSc-ILD [172.1 (94.8–263.3) pmol/l] than in those with SSc-no ILD [97.4 (85.5–156.5) pmol/l, p < 0.001]. This observation was replicated in the BALF samples. Corresponding values were 510.8 (144.6–1013.8) pmol/l for SSc cohort, 754.4 (299–1060) pmol/l for SSc-ILD, 555.1 (203.7–776.2) pmol/l for SSc-no ILD, and 238.7 (97.7–397.6) pmol/l for controls. The semiquantitative grade of ILD on CT scan was significantly proportional to the HE4 levels and the lung function parameter (i.e., FVC) had a negative correlation with the HE4 levels. Conclusion: This is the first study to demonstrate the potential clinical utility of blood and BALF HE4 as a biomarker for SSc-ILD. Future prospective validation studies are warranted.

scholarly journals Fractional analysis of bronchoalveolar lavage in systemic sclerosis-associated interstitial lung disease

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Kazumasa Kase ◽  
Satoshi Watanabe ◽  
Keigo Saeki ◽  
Yuko Waseda ◽  
Hazuki Takato ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Bronchoalveolar Lavage ◽  
Lung Disease ◽  
Fractional Analysis

Bronchoalveolar lavage cellular profiles in patients with systemic sclerosis–associated interstitial lung disease are not predictive of disease progression

2007 ◽  
Vol 56 (6) ◽  
pp. 2005-2012 ◽  
Author(s):  
Nicole S. L. Goh ◽  
Srihari Veeraraghavan ◽  
Sujal R. Desai ◽  
Derek Cramer ◽  
David M. Hansell ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Bronchoalveolar Lavage ◽  
Lung Disease ◽  
Disease Progression

scholarly journals OP0249 SERUM PROTEOMIC BIOMARKERS DEFINE PATIENTS WITH SYSTEMIC SCLEROSIS WITH INTERSTITIAL LUNG DISEASE

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 152.2-152
Author(s):  
M. De Santis ◽  
N. Isailovic ◽  
A. Ceribelli ◽  
F. Motta ◽  
M. Vecellio ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Proteomic Analysis ◽  
Organ Involvement ◽  
High Morbidity ◽  
Healthy Controls ◽  
Altered Expression ◽  
Calgranulin B ◽  
Angiopoietin 2

Background:Systemic sclerosis (SSc) is a systemic condition affecting multiple organs and thus being burdened by high morbidity and mortality; disease management is based largely on the early detection of organ involvement, particularly in the case of interstitial lung disease (ILD), ideally through noninvasive biomarkers. Beside serum autoantibodies associated with diffuse SSc, there is currently no reliable serum marker to predict the onset of SSc organ involvement, monitor its progression, and foresee the response to treatments. Proteomic analysis based on aptamer technology is a powerful method with the potential to address this unmet need in SSc.Objectives:To identify serum biomarkers associated with ILD in SSc.Methods:Serum samples from 6 women with SSc (3 with ILD at high-resolution pulmonary CT scan) and 7 age-matched female healthy controls (HC) were analyzed using the SOMAscan platform (SomaLogic, Inc., Boulder, CO, USA) to test more than 1300 proteins even at femtomolar concentration. Subsequent validation of candidate proteins was performed using ELISA in an independent cohort of 88 patients with SSc and 48 HC. Statistical analysis included Student’s t-test and was assessed using the SomaSuite software (SomaLogic, Boulder, CO, USA).Results:The proteomic analysis identified 33 proteins with significantly different serum levels in SSc cases compared to HC and 9 proteins differentiating SSc patients according to ILD (Table 1). Compared to HC, SSc sera manifested an altered expression of proteins involved in extracellular matrix formation and cell-cell adhesion (with higher Calpain, EphA5, IDS, MATN2, MMP-12, TNR4, and lower desmoglein-1, SNP25), angiogenesis (with higher anti-angiogenetic factors as angiopoietin-2 and kininogen high molecular weight) lymphocyte recruitment, activation, and signaling (with higher CXCL-1, LAG3 and lower SH21A) with an overall inhibition of neutrophil function (with lower G-CSF-R, CD177, calgranulin B).Table 1.Significantly altered proteins at serum proteomic analysis of systemic sclerosis (SSc) with or without interstitial lung disease (ILD) and healthy controls (HC)SSc versus healthy controlsSSc with ILD versus SSc without ILD and healthy controlsIncreasedReducedIncreasedReducedAldolase AAngiopoietin-2*C1QR1CalpainCOLEC12 EotaxinEphA5Fractalkine/CXCL-1GranulinsIDS Kininogen, HMVLAG-3Lamin-B1LRP1bMATN2MMP-12STAT1 TMR4AdrenomedullinASGR1C1sC5Calgranulin BCD177Desmoglein-1Flt-3 ligandG-CFS-RIL-1RaLeptinLypd3SH21ASNP25TPBS2FCRL3IL-22BP**MCP-3PDE11PGP9.5sICAM-5StratifinBAFFDERM*significantly increased also at ELISA** significantly increased at ELISA only in SSc with ILD versus HCThe majority of proteins with higher levels in SSc with ILD compared to SSc without ILD were involved in intracellular signaling and cell cycle (FCRL3, PDE11, Stratifin), along with higher MCP-3, a monocyte chemoattractant, and sICAM-5, ligand for the leukocyte adhesion protein LFA-1. Of note, we found that increased IL-22BP, antagonist of IL-22, and decreased BAFF levels characterized SSc with ILD.Conclusion:Aptamer proteomic analysis allowed to define serum profiles differentiating SSc patients from healthy controls and SSc with ILD from SSc without ILD; the proteins identified are involved in SSc pathogenic pathways and after further investigation on larger cohorts they can be used as reliable biomarkers.Characters from table content including title and footnotes: 631Disclosure of Interests:None declared

scholarly journals Eosinophilic Globules in Bronchoalveolar Lavage Fluid of Patients With Systemic Sclerosis–Related Interstitial Lung Disease

2008 ◽  
Vol 130 (6) ◽  
pp. 927-933
Author(s):  
Giulio Rossi ◽  
Alessandro Andreani ◽  
Paola Morandi ◽  
Alessandro Marchioni ◽  
Paolo Corradini ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Bronchoalveolar Lavage ◽  
Lung Disease ◽  
Bronchoalveolar Lavage Fluid ◽  
Lavage Fluid

scholarly journals OP0269 A COMBINED CLINICAL AND BIOMARKER ALGORITHM TO PREDICT FVC DECLINE IN SYSTEMIC SCLEROSIS ASSOCIATED INTERSTITIAL LUNG DISEASE: RESULTS FROM AN INTERNATIONAL MULTICENTRE OBSERVATIONAL COHORT

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 163.2-164
Author(s):  
M. Hutchinson ◽  
G. Abignano ◽  
J. Blagojevic ◽  
S. L. Bosello ◽  
Y. Allanore ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Predictive Value ◽  
Large Population ◽  
Healthy Controls ◽  
Research Support ◽  
Clinical Value ◽  
Linear Predictor ◽  
Risk Of Progression

Background:Interstitial lung disease (ILD) is the leading cause of mortality in patients with Systemic Sclerosis (SSc). Forced Vital Capacity (FVC) is a major indicator of severity in SSc ILD. The ELF serum test and its constituent biomarkers (HA, PIIINP and TIMP-1) have shown to correlate with FVC in two large, independent multicentre cohorts of 457 patients, but also showed a correlation with age.Objectives:Here we aimed to investigate the relationship of the ELF biomarkers and age in a large population of healthy controls and to identify a combined clinical and biomarkers model to stratify for risk of ILD progression in a multicentre longitudinal cohort of patients with SSc.Methods:ELF score was measured in sera from 925 healthy controls in one centre and 869 longitudinal samples from 254 SSc patients from 6 centres across 4 European countries. Clinical data were recorded according to EUSTAR Minimal Essential dataset. FVC% change over time was estimated by Mixed-effects modelling. Patients were then divided in two groups: progressors, with a %FVC drop > 3%/year (according to published MCID) and a group of patients with stable or improving FVC. Lasso penalised regression was carried out with biomarkers and the available clinical and demographic variables at patient’s first visit as potential predictors. The resulting linear predictor was used to derive two thresholds, one for optimal sensitivity (rule-out) and one for optimal specificity (rule-in). Patients within thresholds were further selected according to the ratio of TIMP-1: PIIINP (Figure 1).Results:HA was the only ELF biomarker that correlated significantly with age in the healthy control cohort. Therefore, we defined by linear regression a “residual HA” which accounted for age. TIMP1, PIIINP and residual HA were then considered as distinct biomarkers in the analysis of the SSc cohort. 189 SSc patients with 785 time-points had complete datasets and were included in the analysis. Median follow up was 33 months (IQR 18-48). One-hundred and forty patients (74%) were classified as non progressors, 94 (50%) with no change or improving FVC and 46 (24%) with FVC drop <3% year. 49 patients (26%) were classed as progressors (drop of 3%/year or more in FVC, median slope -4.7%/year). Variable selection via Lasso penalised logistic regression resulted in a model with a c-index of 0.69 (95% CI: 0.60-0.78)) and contained age, disease duration (from first non-Raynaud’s symptom), residual HA, anti-centromere antibodies (ACA) status, previous diagnosis of ILD, joint synovitis and history of protein pump inhibitor use. A two-step process was developed using the linear predictor from the model and the ratio of TIMP-1 and PIIINP (Figure 1). The stratification tool increased by nearly two-fold the ability to predict progressors in any 12 months interval (46 to 49% predictive value vs 26% probability) identifying an 82 to 91% negative predictive value for progression.Conclusion:Building on the face and content validity of the biomarkers included in the ELF score, here we identify an easy to assess combined clinical and biomarker model to stratify patients for their risk of ILD progression. Despite its derivation from a large multicentre cohort, independent validation will determine the clinical value of Scleroscore as a stratification tool for risk of progression of SSc ILD.Disclosure of Interests:Michelle Hutchinson: None declared, Giuseppina Abignano: None declared, Jelena Blagojevic: None declared, Silvia Laura Bosello: None declared, Yannick Allanore Grant/research support from: Alpine, Boehringer Ingelheim, Genentech/Roche, Medsenic, and Sanofi, Christopher Denton Consultant of: Corbus, Actelion, GlaxoSmithKline, Bayer, Sanofi, Galapagos, Inventiva, Boehringer Ingelheim, Roche, CSL Behring, Acceleron, Horizon, Arxx Therapeutics, Grant/research support from: Corbus, Actelion, GlaxoSmithKline, Bayer, Sanofi, Galapagos, Inventiva, Boehringer Ingelheim, Roche, CSL Behring, Acceleron, Horizon, Arxx Therapeutics, Oliver Distler Consultant of: Abbvie, Acceleron Pharma, Amgen, AnaMar, Arxx Therapeutics, Baecon Discovery, Blade Therapeutics, Bayer, Boehringer Ingelheim, ChemomAb, Corbus Pharmaceuticals, CSL Behring, Galapagos NV, Glenmark Pharmaceuticals, GSK, Horizon (Curzion) Pharmaceuticals, Inventiva, iQvia, Italfarmaco, iQone, Kymera Therapeutics, Lilly, Medac, Medscape, Mitsubishi Tanabe Pharma, MSD, Novartis, Pfizer, Roche, Sanofi, Serodapharm, Topadur, Target Bioscience and UCB, Grant/research support from: Abbvie, Acceleron Pharma, Amgen, AnaMar, Arxx Therapeutics, Baecon Discovery, Blade Therapeutics, Bayer, Boehringer Ingelheim, ChemomAb, Corbus Pharmaceuticals, CSL Behring, Galapagos NV, Glenmark Pharmaceuticals, GSK, Horizon (Curzion) Pharmaceuticals, Inventiva, iQvia, Italfarmaco, iQone, Kymera Therapeutics, Lilly, Medac, Medscape, Mitsubishi Tanabe Pharma, MSD, Novartis, Pfizer, Roche, Sanofi, Serodapharm, Topadur, Target Bioscience and UCB, Paul Emery Consultant of: Lilly, Abbvie, Roche, Grant/research support from: Lilly, Marco Matucci-Cerinic Consultant of: Chemomab, Lilly, Abbvie, Actelion, Francesco Del Galdo Speakers bureau: Astra-Zeneca, Boehringer Ingelheim, Actelion, Consultant of: Astra-Zeneca, Mitsubishi-Tanabe, Capella Biosciences, Chemomab, Actelion, Boehringer-Ingelheim, Grant/research support from: Capella Biosciences, Chemomab, Kymab, Mitsubishi-Tanabe

Sign in / Sign up

Export Citation Format

Share Document