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Title:Deregulation in adult IgA vasculitis skin as the basis for the discovery of novel serum biomarkers
Authors:ID Bajželj, Matija (Author)
ID Hladnik, Matjaž (Author)
ID Blagus, Rok (Author)
ID Jurčić, Vesna (Author)
ID Markež, Ana (Author)
ID Toluay, Tanya Deniz (Author)
ID Sodin-Šemrl, Snežna (Author)
ID Hočevar, Alojzija (Author)
ID Lakota, Katja (Author)
Files:.pdf PDF - Presentation file, download (1,70 MB)
MD5: 7810033380A278D8DE4DA30D2142CDAB
 
URL URL - Source URL, visit https://arthritis-research.biomedcentral.com/articles/10.1186/s13075-024-03317-6
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo UKC LJ - Ljubljana University Medical Centre
Abstract:Introduction: Immunoglobulin A vasculitis (IgAV) in adults has a variable disease course, with patients often developing gastrointestinal and renal involvement and thus contributing to higher mortality. Due to understudied molecular mechanisms in IgAV currently used biomarkers for IgAV visceral involvement are largely lacking. Our aim was to search for potential serum biomarkers based on the skin transcriptomic signature. Methods: RNA sequencing analysis was conducted on skin biopsies collected from 6 treatment-naïve patients (3 skin only and 3 renal involvement) and 3 healthy controls (HC) to get insight into deregulated processes at the transcriptomic level. 15 analytes were selected and measured based on the transcriptome analysis (adiponectin, lipopolysaccharide binding protein (LBP), matrix metalloproteinase-1 (MMP1), C-C motif chemokine ligand (CCL) 19, kallikrein-5, CCL3, leptin, C-X-C motif chemokine ligand (CXCL) 5, osteopontin, interleukin (IL)-15, CXCL10, angiopoietin-like 4 (ANGPTL4), SERPIN A12/vaspin, IL-18 and fatty acid-binding protein 4 (FABP4)) in sera of 59 IgAV and 22 HC. Machine learning was used to assess the ability of the analytes to predict IgAV and its organ involvement. Results: Based on the gene expression levels in the skin, we were able to differentiate between IgAV patients and HC using principal component analysis (PCA) and a sample-to-sample distance matrix. Differential expression analysis revealed 49 differentially expressed genes (DEGs) in all IgAV patient's vs. HC. Patients with renal involvement had more DEGs than patients with skin involvement only (507 vs. 46 DEGs) as compared to HC, suggesting different skin signatures. Major dysregulated processes in patients with renal involvement were lipid metabolism, acute inflammatory response, and extracellular matrix (ECM)-related processes. 11 of 15 analytes selected based on affected processes in IgAV skin (osteopontin, LBP, ANGPTL4, IL-15, FABP4, CCL19, kallikrein-5, CCL3, leptin, IL-18 and MMP1) were significantly higher (p-adj < 0.05) in IgAV serum as compared to HC. Prediction models utilizing measured analytes showed high potential for predicting adult IgAV. Conclusion: Skin transcriptomic data revealed deregulations in lipid metabolism and acute inflammatory response, reflected also in serum analyte measurements. LBP, among others, could serve as a potential biomarker of renal complications, while adiponectin and CXCL10 could indicate gastrointestinal involvement.
Keywords:acute inflammatory response, adults, IgA vasculitis, lipid metabolism, machine learning, RNA sequencing, serum biomarkers
Publication status:Published
Publication version:Version of Record
Year of publishing:2024
Number of pages:str. 1-12
Numbering:Vol. 26, iss. 1, [article no.] 85
PID:20.500.12556/DiRROS-29731 New window
UDC:616-002
ISSN on article:1478-6362
DOI:10.1186/s13075-024-03317-6 New window
COBISS.SI-ID:199720707 New window
Note: Nasl z nasl. zaslona; Opis vira z dne 18. 6. 2024;
Publication date in DiRROS:04.06.2026
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Downloads:79
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Record is a part of a journal

Title:Arthritis research & therapy
Shortened title:Arthritis Res Ther
Publisher:BioMed Central.
ISSN:1478-6362
COBISS.SI-ID:3271700 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P3-0314-2022
Name:Sistemske avtoimunske bolezni

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P3-0154-2022
Name:Metodologija za analizo podatkov v medicini

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:akutni vnetni odziv, odrasli, IgA vaskulitis, metabolizem lipidov, strojno učenje, sekvenciranje RNA, serumski biološki označevalci


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