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Györfi AH, Filla T, Dickel N, Möller F, Li YN, Bergmann C, Matei AE, Harrer T, Kunz M, Schett G, Distler JHW. Performance of serum biomarkers reflective of different pathogenic processes in systemic sclerosis-associated interstitial lung disease. Rheumatology (Oxford) 2024; 63:962-969. [PMID: 37421394 DOI: 10.1093/rheumatology/kead332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 05/12/2023] [Accepted: 06/06/2023] [Indexed: 07/10/2023] Open
Abstract
OBJECTIVE Interstitial lung disease (ILD) is the leading cause of mortality in SSc. Novel biomarkers are crucial to improve outcomes in SSc-ILD. We aimed to compare the performance of potential serum biomarkers of SSc-ILD that reflect different pathogenic processes: KL-6 and SP-D (epithelial injury), CCL18 (type 2 immune response), YKL-40 (endothelial injury and matrix remodelling) and MMP-7 (ECM remodelling). METHODS Baseline and follow-up serum samples from 225 SSc patients were analysed by ELISA. Progressive ILD was defined according to the 2022-ATS/ERS/JRS/ALAT guidelines. Linear mixed models and random forest models were used for statistical analyses. RESULTS Serum levels of KL-6 [MD 35.67 (95% CI 22.44-48.89, P < 0.01)], SP-D [81.13 (28.46-133.79, P < 0.01)], CCL18 [17.07 (6.36-27.77, P < 0.01)], YKL-40 [22.81 (7.19-38.44, P < 0.01)] and MMP-7 [2.84 (0.88-4.80, P < 0.01)] were independently associated with the presence of SSc-ILD. A machine-learning model including all candidates classified patients with or without ILD with an accuracy of 85%. The combination of KL-6 and SP-D was associated with the presence [0.77 (0.53-1.00, P' <0.01)] and previous progression of SSc-ILD [OR 1.28 (1.01-1.61, P' =0.047)]. Higher baseline levels of KL-6 [OR 3.70 (1.52-9.03, P < 0.01)] or SP-D [OR 2.00 (1.06-3.78, P = 0.03)] increased the odds of future SSc-ILD progression, independent of other conventional risk factors, and the combination of KL-6 and SP-D [1.109 (0.665-1.554, P < 0.01)] showed improved performance compared with KL-6 and SP-D alone. CONCLUSION All candidates performed well as diagnostic biomarkers for SSc-ILD. The combination of KL-6 and SP-D might serve as biomarker for the identification of SSc patients at risk of ILD progression.
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Affiliation(s)
- Andrea-Hermina Györfi
- Clinic for Rheumatology, University Hospital Düsseldorf, Medical Faculty of Heinrich-Heine University, Düsseldorf, Germany
- Hiller Research Unit, University Hospital Düsseldorf, Medical Faculty of Heinrich-Heine University, Düsseldorf, Germany
| | - Tim Filla
- Clinic for Rheumatology, University Hospital Düsseldorf, Medical Faculty of Heinrich-Heine University, Düsseldorf, Germany
- Hiller Research Unit, University Hospital Düsseldorf, Medical Faculty of Heinrich-Heine University, Düsseldorf, Germany
| | - Nicholas Dickel
- Chair of Medical Informatics, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany
| | - Florian Möller
- Department of Internal Medicine 3, Rheumatology and Clinical Immunology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
- Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander University (FAU) Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Yi-Nan Li
- Clinic for Rheumatology, University Hospital Düsseldorf, Medical Faculty of Heinrich-Heine University, Düsseldorf, Germany
- Hiller Research Unit, University Hospital Düsseldorf, Medical Faculty of Heinrich-Heine University, Düsseldorf, Germany
| | - Christina Bergmann
- Department of Internal Medicine 3, Rheumatology and Clinical Immunology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
- Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander University (FAU) Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Alexandru-Emil Matei
- Clinic for Rheumatology, University Hospital Düsseldorf, Medical Faculty of Heinrich-Heine University, Düsseldorf, Germany
- Hiller Research Unit, University Hospital Düsseldorf, Medical Faculty of Heinrich-Heine University, Düsseldorf, Germany
| | - Thomas Harrer
- Department of Internal Medicine 3, Rheumatology and Clinical Immunology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
- Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander University (FAU) Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Meik Kunz
- Chair of Medical Informatics, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany
- Fraunhofer Institute for Toxicology and Experimental Medicine (ITEM), Hanover, Germany
- Fraunhofer Cluster of Excellence Immune-Mediated Diseases (CIMD), Hannover, Germany
| | - Georg Schett
- Department of Internal Medicine 3, Rheumatology and Clinical Immunology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
- Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander University (FAU) Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Jörg H W Distler
- Clinic for Rheumatology, University Hospital Düsseldorf, Medical Faculty of Heinrich-Heine University, Düsseldorf, Germany
- Hiller Research Unit, University Hospital Düsseldorf, Medical Faculty of Heinrich-Heine University, Düsseldorf, Germany
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