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A new nucleosomic-based model to identify and diagnose SSc-ILD

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 pred...

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Published in:Clinical epigenetics 2020-08, Vol.12 (1), p.124-124, Article 124
Main Authors: Guiot, Julien, Henket, Monique, Andre, Béatrice, Herzog, Marielle, Hardat, Nathalie, Njock, Makon-Sebastien, Moermans, Catherine, Malaise, Michel, Louis, Renaud
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container_title Clinical epigenetics
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creator Guiot, Julien
Henket, Monique
Andre, Béatrice
Herzog, Marielle
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Moermans, Catherine
Malaise, Michel
Louis, Renaud
description 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. 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. 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 R = 19% (p = 0.013). We identified in the sole group of SSc-ILD patients a significant linear regression with a R = 54.4% with the variation of DLCO between T1 and T2 (p < 0.05). 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.
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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. 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. We found that H3.1 nucleosome levels were significantly higher in patients with SSc-ILD compared SSc patients without ILD (p &lt; 0.05) and levels of MMP-9 were significantly increased in patients with SSc-ILD compared to SSc patients without ILD (p &lt; 0.05). Conversely, IGFBP-1 was significantly reduced in patients with SSc-ILD compared to SSc without ILD (p &lt; 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 R = 19% (p = 0.013). We identified in the sole group of SSc-ILD patients a significant linear regression with a R = 54.4% with the variation of DLCO between T1 and T2 (p &lt; 0.05). 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. 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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. 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. We found that H3.1 nucleosome levels were significantly higher in patients with SSc-ILD compared SSc patients without ILD (p &lt; 0.05) and levels of MMP-9 were significantly increased in patients with SSc-ILD compared to SSc patients without ILD (p &lt; 0.05). Conversely, IGFBP-1 was significantly reduced in patients with SSc-ILD compared to SSc without ILD (p &lt; 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 R = 19% (p = 0.013). We identified in the sole group of SSc-ILD patients a significant linear regression with a R = 54.4% with the variation of DLCO between T1 and T2 (p &lt; 0.05). 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.</abstract><cop>Germany</cop><pub>BioMed Central Ltd</pub><pmid>32807242</pmid><doi>10.1186/s13148-020-00915-4</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0001-7800-1730</orcidid><oa>free_for_read</oa></addata></record>
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subjects Ambulatory care
Analysis
Biomarkers
Cardiovascular & respiratory systems
Connective tissue diseases
Diagnosis
Enzymes
Evolution
Fibrosis
Gelatinase B
Gender
Growth factors
Health aspects
Human health sciences
Insulin-like growth factor-binding protein 1
Lung diseases
Medical research
Mortality
Nucleosomes
Patients
Plasma levels
Prediction models
Prognosis
Sciences de la santé humaine
Scleroderma
Scleroderma (Disease)
Skin
Systemic sclerosis
Systèmes cardiovasculaire & respiratoire
title A new nucleosomic-based model to identify and diagnose SSc-ILD
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