scholarly journals Genetic interactions affect lung function in patients with systemic sclerosis

2019 ◽  
Author(s):  
Anna L. Tyler ◽  
J. Matthew Mahoney ◽  
Gregory W. Carter
Keyword(s):  
Systemic Sclerosis ◽  
Autoimmune Disease ◽  
Lung Function ◽  
Lung Disease ◽  
Cause Of Death ◽  
Genetic Variants ◽  
Gene Network ◽  
Genetic Interactions ◽  
Internal Organs ◽  
Autoantibody Status

AbstractScleroderma, or systemic sclerosis (SSc), is an autoimmune disease characterized by progressive fibrosis of the skin and internal organs. The most common cause of death in people with SSc is lung disease, but the pathogenesis of lung disease in SSc is insufficiently understood to devise specific treatment strategies. Developing targeted treatments requires not only the identification of molecular processes involved in SSc-associated lung disease, but also understanding of how these processes interact to drive pathology. One potentially powerful approach is to identify alleles that interact genetically to influence lung outcomes in patients with SSc. Analysis of interactions, rather than individual allele effects, has the potential to delineate molecular interactions that are important in SSc-related lung pathology. However, detecting genetic interactions, or epistasis, in human cohorts is challenging. Large numbers of variants with low minor allele frequencies, paired with heterogeneous disease presentation, reduce power to detect epistasis. Here we present an analysis that increases power to detect epistasis in human genome-wide association studies (GWAS). We tested for genetic interactions influencing lung function and autoantibody status in a cohort of 416 SSc patients. Using Matrix Epistasis to filter SNPs followed by the Combined Analysis of Pleiotropy and Epistasis (CAPE), we identified a network of interacting alleles influencing lung function in patients with SSc. In particular, we identified a three-gene network comprisingWNT5A, RBMS3, andMSI2, which in combination influenced multiple pulmonary pathology measures. The associations of these genes with lung outcomes in SSc are novel and high-confidence. Furthermore, gene coexpression analysis suggested that the interactions we identified are tissue-specific, thus differentiating SSc-related pathogenic processes in lung from those in skin.Author summarySystemic sclerosis (SSc), or scleroderma, is a devastating autoimmune disease. Patients experience progressive fibrosis of their skin and internal organs, reduced quality of life, and increased risk of death. Lung disease associated with SSc is particularly dangerous and is currently the leading cause of death in SSc patients. There are no specific treatments for SSc or SSc-related lung disease, but promising work in the genetics of this disease has identified more than 200 genetic variants that influence SSc [1]. Piecing together how genetic variants interact with each other to influence disease may provide clues for targeted therapies. Here we present a novel analytical approach for identifying genetic interactions in a human disease cohort. In this approach we first filtered SNPs to those that are most likely to interact to influence the disease traits. We then applied the Combined Analysis of Pleiotropy and Epistasis (CAPE), which combines information across multiple traits to increase power to detect genetic interactions. Using this approach, we identified a three-gene network amongMSI2, WNT5A, andRBMS3that influenced autoantibody status and lung function in a cohort of 416 SSc patients. Gene expression data suggest that this interaction network is tissue- and disease-specific, and may thus provide a specific target for SSc therapy.

scholarly journals Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis

2019 ◽  
Vol 10 (1) ◽  
pp. 151-163 ◽  
Author(s):  
Anna Tyler ◽  
J. Matthew Mahoney ◽  
Gregory W. Carter
Keyword(s):  
Systemic Sclerosis ◽  
Lung Function ◽  
Lung Disease ◽  
Association Studies ◽  
Treatment Strategies ◽  
Specific Treatment ◽  
Genetic Interactions ◽  
Genome Wide Association Studies ◽  
Lung Pathology ◽  
Large Numbers

Scleroderma, or systemic sclerosis (SSc), is an autoimmune disease characterized by progressive fibrosis of the skin and internal organs. The most common cause of death in people with SSc is lung disease, but the pathogenesis of lung disease in SSc is insufficiently understood to devise specific treatment strategies. Developing targeted treatments requires not only the identification of molecular processes involved in SSc-associated lung disease, but also understanding of how these processes interact to drive pathology. One potentially powerful approach is to identify alleles that interact genetically to influence lung outcomes in patients with SSc. Analysis of interactions, rather than individual allele effects, has the potential to delineate molecular interactions that are important in SSc-related lung pathology. However, detecting genetic interactions, or epistasis, in human cohorts is challenging. Large numbers of variants with low minor allele frequencies, paired with heterogeneous disease presentation, reduce power to detect epistasis. Here we present an analysis that increases power to detect epistasis in human genome-wide association studies (GWAS). We tested for genetic interactions influencing lung function and autoantibody status in a cohort of 416 SSc patients. Using Matrix Epistasis to filter SNPs followed by the Combined Analysis of Pleiotropy and Epistasis (CAPE), we identified a network of interacting alleles influencing lung function in patients with SSc. In particular, we identified a three-gene network comprising WNT5A, RBMS3, and MSI2, which in combination influenced multiple pulmonary pathology measures. The associations of these genes with lung outcomes in SSc are novel and high-confidence. Furthermore, gene coexpression analysis suggested that the interactions we identified are tissue-specific, thus differentiating SSc-related pathogenic processes in lung from those in skin.

scholarly journals Impact of Lung Function Decline on Time to Hospitalisation Events in Systemic Sclerosis-associated Interstitial Lung Disease (SSc-ILD): a Joint Model Analysis

2021 ◽  
Author(s):  
Michael Kreuter ◽  
Francesco Del Galdo ◽  
Corinna Miede ◽  
Dinesh Khanna ◽  
Wim A. Wuyts ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Function ◽  
Lung Disease ◽  
Fold Increase ◽  
Phase Iii ◽  
Lung Function Decline ◽  
Related Hospitalisation ◽  
The Relationship ◽  
Increase In Risk

Abstract Background: Interstitial lung disease (ILD) is a common organ manifestation in systemic sclerosis (SSc) and is the leading cause of death in patients with SSc. A decline in forced vital capacity (FVC) is an indicator of ILD progression and is associated with mortality in patients with SSc-associated ILD (SSc-ILD). However, the relationship between FVC decline and hospitalisation events in patients with SSc-ILD is largely unknown. The objective of this post-hoc analysis was to investigate the relationship between FVC decline and clinically important hospitalisation endpoints.Methods: We used data from SENSCIS®, a Phase III trial investigating the efficacy and safety of nintedanib in patients with SSc-ILD. Joint models for longitudinal and time-to-event data were used to assess the association between rate of decline in FVC% predicted and hospitalisation-related endpoints (including time to first all-cause hospitalisation or death; time to first SSc-related hospitalisation or death; and time to first admission to an emergency room [ER] or admission to hospital followed by admission to intensive care unit [ICU] or death) during the treatment period, over 52 weeks in patients with SSc-ILD.Results: There was a statistically significant association between FVC decline and the risk of all-cause (n=78) and SSc-related (n=42) hospitalisations or death (both P<0.0001). A decrease of 3% in FVC corresponded to a 1.43-fold increase in risk of all-cause hospitalisation or death (95% confidence interval [CI] 1.24, 1.65) and a 1.48-fold increase in risk of SSc-related hospitalisation or death (95% CI 1.23, 1.77). No statistically significant association was observed between FVC decline and admission to ER or to hospital followed by admission to ICU or death (n=75; P=0.15). The estimated slope difference for nintedanib versus placebo in the longitudinal sub-model was consistent with the primary analysis in SENSCIS®.Conclusions: The association of lung function decline with an increased risk of hospitalisation suggests that slowing FVC decline in patients with SSc-ILD may prevent hospitalisations. Our findings also provide evidence that FVC decline may serve as a surrogate endpoint for clinically relevant hospitalisation-associated endpoints.Trial registration: Clinialtrials.gov, NCT02597933. Registered 8 October 2015, https://clinicaltrials.gov/ct2/show/study/NCT02597933.

scholarly journals Apoptosis Modulation as a Promising Target for Treatment of Systemic Sclerosis

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Stéphane Chabaud ◽  
Véronique J. Moulin
Keyword(s):  
Systemic Sclerosis ◽  
Autoimmune Disease ◽  
Therapeutic Targets ◽  
Immune Dysfunction ◽  
Vascular Damage ◽  
Loss Of Function ◽  
Internal Organs ◽  
Promising Target ◽  
New Findings ◽  
Diffuse Systemic Sclerosis

Diffuse systemic sclerosis (SSc) is a fatal autoimmune disease characterized by an excessive ECM deposition inducing a loss of function of skin and internal organs. Apoptosis is a key mechanism involved in all the stages of the disease: vascular damage, immune dysfunction, and fibrosis. The purpose of this paper is to gather new findings in apoptosis related to SSc, to highlight relations between apoptosis and fibrosis, and to identify new therapeutic targets.

scholarly journals Lung Function and Survival in Systemic Sclerosis Interstitial Lung Disease

2014 ◽  
Vol 41 (11) ◽  
pp. 2326-2328 ◽  
Author(s):  
SAMAR SHADLY AHMED ◽  
SINDHU R. JOHNSON ◽  
CHRISTOPHER MEANEY ◽  
CATHY CHAU ◽  
THEODORE K. MARRAS
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Function ◽  
Lung Disease

FRI0254 The Effect of Cyclophosphamide on Lung Function in Different Stages of Interstitial Lung Disease Associated To Systemic Sclerosis: Table 1.

2016 ◽  
Vol 75 (Suppl 2) ◽  
pp. 526.1-526
Author(s):  
W.M.T. Van Den Hombergh ◽  
E. Teesselink ◽  
H.K.A. Knaapen-Hans ◽  
S.O. Simons ◽  
F.H.J. van den Hoogen ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Function ◽  
Lung Disease

scholarly journals Predictors of lung function test severity and outcome in systemic sclerosis-associated interstitial lung disease

PLoS ONE ◽  
2017 ◽  
Vol 12 (8) ◽  
pp. e0181692 ◽  
Author(s):  
Noémie Le Gouellec ◽  
Alain Duhamel ◽  
Thierry Perez ◽  
Anne-Lise Hachulla ◽  
Vincent Sobanski ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Function ◽  
Lung Disease ◽  
Lung Function Test ◽  
Function Test

scholarly journals AB0425 CLINICAL AND PATHOLOGICAL FEATURES OF BREAST CANCER IN PATIENTS WITH SYSTEMIC SCLEROSIS: PRELIMINARY DATA FROM THE SCLERO-BREAST STUDY

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1241.1-1241
Author(s):  
A. Spinella ◽  
A. Toss ◽  
C. Isca ◽  
C. Vacchi ◽  
A. Iannone ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Cause Of Death ◽  
Preliminary Data ◽  
Pulmonary Function Tests ◽  
Endocrine Treatment ◽  
Pathological Characteristics ◽  
Kidney Involvement

Background:Systemic Sclerosis (SSc) is a rare and life-threatening connective tissue disease characterized by vascular dysfunction, specific autoimmune abnormalities and fibrosis of the skin and internal organs. Previous studies have shown a 1.5-fold increase in cancer risk in SSc patients compared with the general population, including breast cancer (BC). The relationship between BC and SSc has long been discussed but past research has been contradictory and inconclusive on this topic.Objectives:The aim of our project was to analyze clinical and pathological characteristics of BC developed by SSc subjects and possible correlations with scleroderma features. Here we present the preliminary data from the Sclero-Breast study.Methods:Our observational retrospective multicenter study enrolled 33 SSc women with a personal history of BC identified at two Rheumatology/SSc Units in the north of Italy between January 2017 and December 2019 (lc/dcSSc 23/9, 1 unknown; mean age at SSc onset 57 years, range 32-73). All patients underwent general and instrumental assessment: smoking habits; presence of skin ulcers, calcinosis, teleangectasia; presence of gastro-intestinal and kidney involvement; interstitial lung disease (at HR-CT); pulmonary function tests; ECG abnormalities; echocardiographic assessment of pulmonary arterial hypertension (PAH); videocapillaroscopic pattern; autoantibody profile; exposure to immunosuppressive and vasoactive therapies; status at last follow-up evaluation and cause of death. Clinical and pathological characteristics of BC were also evaluated: age at diagnosis; menopausal status; histotype; hormone receptor status; MIB1, HER2 expression; clinical and pathological stage at diagnosis; metastatic sites; type of loco-regional treatment (surgery and radiotherapy); type of systemic treatment (neoadjuvant/adjuvant chemotherapy and endocrine treatment); other cancers and time from diagnosis of the first disorder to the second one.Results:A total of 54.5% of subjects developed BC before SSc (median interval of 5 years), whereas 45.5% of patients developed BC after SSc (median delay of 8 years). 54.5% of patients showed interstitial lung disease and the cause of death of the 6 deceased subjects was PAH. A significant association (p<0.05) was observed between the use of immunosuppressive therapy and diffuse skin extension, negative ACA, positive Anti-Scl-70 and interstitial lung disease, but not with BC status. 93.1% of patients were diagnosed with an early-stage tumor, 70.8% of invasive carcinomas with a low MIB-1, 8.3% with a tubular histotype, while 42.8% presented with a Luminal A-like tumor. 66.6% underwent breast conserving surgery and 55.5% RT after surgery. 40% of patients developed interstitial lung disease after RT and 20% dcSSc.Conclusion:According to our preliminary data, SSc patients developed BC at good prognosis, suggesting a de-escalation strategy of cancer therapies. On these grounds, a proper screening is mandatory in order to allow for early cancer detection in SSc patients. Further investigations on larger numbers of patients are needed. First of all, they would further clarify the intriguing relationship between BC and SSc. Secondly, they would help to explore the common biological and molecular pathways at the basis of these two disorders, with the aim to improve BC diagnosis and prognosis and to personalize oncological targeted treatments in this subset of fragile patients.Disclosure of Interests:None declared

scholarly journals SAT0569 “IMAGES ARE MORE THAN PICTURES, THEY ARE DATA” [1] – EXPLORATION OF RADIOMICS ANALYSIS FOR SYSTEMIC SCLEROSIS-ASSOCIATED INTERSTITIAL LUNG DISEASE

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1242.2-1243
Author(s):  
J. Schniering ◽  
M. Maciukiewicz ◽  
H. Gabrys ◽  
M. Brunner ◽  
C. Blüthgen ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Function ◽  
Correlation Analysis ◽  
Lung Disease ◽  
Roc Curve ◽  
Wilcoxon Test ◽  
Grey Level ◽  
Research Support ◽  
Long Run

Background:Interstitial lung disease (ILD) affects 60% of patients with systemic sclerosis (SSc) and is the primary cause of death. Medical imaging is an integral part of the routine work-up for diagnosis and monitoring of SSc-ILD and includes high-resolution computed tomography (HRCT). Radiomics is a novel research area that describes the in-depth analysis of tissue phenotypes in medical images with computational retrieval of quantitative, mineable metadata appropriate for statistical analyses.Objectives:To explore the performance of HRCT-derived radiomic features for the assessment of SSc-associated ILD (i.e. diagnosis, staging, and lung function).Methods:Radiomics analysis was performed on HRCT scans from 98 SSc patients, including n=33 SSc patients without ILD, n=33 with limited and n=32 with extensive ILD as defined by 0%, <20% and ≥20% visual extent of fibrosis on HRCT, respectively. Following semi-automated segmentation of lung tissue on 3D reconstructed HRCT scans, 1386 radiomic features, including 17 intensity, 137 texture, and 1232 wavelet features were extracted using the in-house developed software Z-Rad (Python 2.7). In order to identify robust features, we conducted intra- and inter-reader correlation analysis (ICC) in a subgroup of patients. Only features with good reproducibility (ICC ≥ 0.75) entered subsequent analyses. We applied the Wilcoxon test, followed by Receiver Operating Characteristic ROC) curve analyses, to identify features significantly different between a) ILD and non-ILD and b) limited vs. extensive ILD patients. Spearman rank correlation was performed to reveal significant associations of radiomic features from a) and b) with lung function as measured by percentage of predicted forced vital capacity (FVC% predicted).Results:In total, 1355/1386 radiomic features passed the test of robustness and were eligible for further, exploratory analyses. Radiomic features with good performance (area under the ROC curve (AUC) ≥ 0.7 and p-value ≤ 0.05) were considered as potential candidate discriminators. Under this criterion, we identified 288/1355 (21.3%) radiomic features that were significantly different between ILD and non-ILD patients and 409/1355 (30.2%) features that significantly discriminated between limited and extensive ILD (Fig. 1). For diagnosis, the texture featuredependence count entropywas the top parameter to distinguish ILD patients from healthy controls (AUC = 0.89, p = 1.83x10-10), whereas for staging the wavelet featureHHH long run high grey level emphasisproved to be best suited to separate limited from extensive ILD (AUC = 0.88, p = 7.76x10-9).Fig 1.Correlation analysis of the most significant (best performing) discriminative radiomic features with lung function revealed a significant negative correlation ofdependence count entropy(rho = -0.51, p = 9.89x10-8) andHHH long run high grey level emphasis(rho = -0.51, p = 1.73x10-5) with FVC% predicted.Conclusion:Our study adds novelty to the field of SSc-ILD showing that radiomic features have great potential as quantitative imaging biomarkers for diagnosis and staging of SSc-ILD and that they may reflect lung function. As the next step, we are planning to build predictive models, using machine learning, for diagnosis, staging, and lung function and validate them in external patient cohorts. If validated such models will pave the way for computer-aided management in SSc-ILD and thus improve patients’ outcome.References:[1]Gillies, R. J., Kinahan, P. E. & Hricak, H. Radiomics: Images Are More than Pictures, They Are Data. Radiology 278, 563-577, doi:10.1148/radiol.2015151169 (2016).Disclosure of Interests:Janine Schniering: None declared, Malgorzata Maciukiewicz: None declared, Hubert Gabrys: None declared, Matthias Brunner: None declared, Christian Blüthgen: None declared, Oliver Distler Grant/research support from: Grants/Research support from Actelion, Bayer, Boehringer Ingelheim, Competitive Drug Development International Ltd. and Mitsubishi Tanabe; he also holds the issued Patent on mir-29 for the treatment of systemic sclerosis (US8247389, EP2331143)., Consultant of: Consultancy fees from Actelion, Acceleron Pharma, AnaMar, Bayer, Baecon Discovery, Blade Therapeutics, Boehringer, CSL Behring, Catenion, ChemomAb, Curzion Pharmaceuticals, Ergonex, Galapagos NV, GSK, Glenmark Pharmaceuticals, Inventiva, Italfarmaco, iQvia, medac, Medscape, Mitsubishi Tanabe Pharma, MSD, Roche, Sanofi and UCB, Speakers bureau: Speaker fees from Actelion, Bayer, Boehringer Ingelheim, Medscape, Pfizer and Roche, Matthias Guckenberger: None declared, Thomas Frauenfelder: None declared, Stephanie Tanadini-Lang: None declared, Britta Maurer Grant/research support from: AbbVie, Protagen, Novartis, congress support from Pfizer, Roche, Actelion, and MSD, Speakers bureau: Novartis

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