Machine learning identifies a common signature for anti-SSA/Ro60 antibody expression across autoimmune diseases
Anti-Ro autoantibodies are among the most frequently detected extractable nuclear antigen autoantibodies, mainly associated with primary Sjögren's syndrome (pSS), systemic lupus erythematosus (SLE) and undifferentiated connective tissue disease (UCTD). Is there a common signature to all patient...
Elmentve itt :
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| Dokumentumtípus: | Cikk |
| Megjelent: |
2022
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| Sorozat: | ARTHRITIS & RHEUMATOLOGY
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| Tárgyszavak: | |
| doi: | 10.1002/art.42243 |
| mtmt: | 32869486 |
| Online Access: | http://publicatio.bibl.u-szeged.hu/24510 |
| LEADER | 03286nab a2200373 i 4500 | ||
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| 005 | 20220610120657.0 | ||
| 008 | 220610s2022 hu o 0|| Angol d | ||
| 022 | |a 2326-5191 | ||
| 024 | 7 | |a 10.1002/art.42243 |2 doi | |
| 024 | 7 | |a 32869486 |2 mtmt | |
| 040 | |a SZTE Publicatio Repozitórium |b hun | ||
| 041 | |a Angol | ||
| 100 | 1 | |a Foulquier Nathan | |
| 245 | 1 | 0 | |a Machine learning identifies a common signature for anti-SSA/Ro60 antibody expression across autoimmune diseases |h [elektronikus dokumentum] / |c Foulquier Nathan |
| 260 | |c 2022 | ||
| 300 | |a Terjedelem: 31 p.-Azonosító: 42243 | ||
| 490 | 0 | |a ARTHRITIS & RHEUMATOLOGY | |
| 520 | 3 | |a Anti-Ro autoantibodies are among the most frequently detected extractable nuclear antigen autoantibodies, mainly associated with primary Sjögren's syndrome (pSS), systemic lupus erythematosus (SLE) and undifferentiated connective tissue disease (UCTD). Is there a common signature to all patients expressing anti-Ro60 autoantibodies regardless of their disease phenotype?Using high-throughput multi-omics data collected within the cross-sectional cohort from the PRECISESADS IMI project (genetic, epigenomic, transcriptomic, combined with flow cytometric data, multiplexed cytokines, classical serology and clinical data), we assessed by machine learning the integrated molecular profiling of 520 anti-Ro60-positive (anti-Ro60+ ) compared to 511 anti-Ro60-negative (anti-Ro60- ) patients with pSS, SLE and UCTD, and 279 healthy controls (HCs).The selected features for RNA-Seq, DNA methylation and GWAS data allowed a clear separation between anti-Ro60+ and anti-Ro60- patients. The different features selected by machine learning from the anti-Ro60+ patients constitute specific signatures when compared to anti-Ro60- patients and HCs. Remarkably, the transcript z-score of three genes (ATP10A, MX1 and PARP14), presenting an overexpression associated with a hypomethylation and genetic variation, and independently identified by the Boruta algorithm, was clearly higher in anti-Ro60+ patients compared to anti-Ro60- patients in all the diseases. We demonstrate that these signatures, enriched in interferon stimulated genes, were also found in anti-Ro60+ patients with rheumatoid arthritis and systemic sclerosis and remained stable over time and not influenced by treatment.Anti-Ro60+ patients present a specific inflammatory signature regardless of their disease suggesting that a dual therapeutic approach targeting both Ro-associated RNAs and anti-Ro60 autoantibodies should be considered. | |
| 650 | 4 | |a Immunológia | |
| 700 | 0 | 2 | |a Le Dantec Christelle |e aut |
| 700 | 0 | 2 | |a Bettacchioli Eleonore |e aut |
| 700 | 0 | 2 | |a Jamin Christophe |e aut |
| 700 | 0 | 2 | |a Alarcón-Riquelme Marta Eugenia |e aut |
| 700 | 0 | 2 | |a Pers Jacques-Olivier |e aut |
| 700 | 0 | 2 | |a Kollaborációs szervezet: PRECISESADS Clinical Consortium |e aut |
| 700 | 0 | 2 | |a Kollaborációs szervezet PRECISESADS Flow Cytometry Consortium |e aut |
| 700 | 0 | 2 | |a Kovács László |e aut |
| 700 | 0 | 2 | |a Balog Attila |e aut |
| 700 | 0 | 2 | |a Deák Magdolna |e aut |
| 700 | 0 | 2 | |a Bocskai Márta |e aut |
| 700 | 0 | 2 | |a Dulic Sonja |e aut |
| 700 | 0 | 2 | |a Kádár Gabriella |e aut |
| 856 | 4 | 0 | |u http://publicatio.bibl.u-szeged.hu/24510/1/FoulquierArthritisRheumatology2022.pdf |z Dokumentum-elérés |