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...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Foulquier Nathan
Le Dantec Christelle
Bettacchioli Eleonore
Jamin Christophe
Alarcón-Riquelme Marta Eugenia
Pers Jacques-Olivier
Kollaborációs szervezet: PRECISESADS Clinical Consortium
Kollaborációs szervezet PRECISESADS Flow Cytometry Consortium
Kovács László
Balog Attila
Deák Magdolna
Bocskai Márta
Dulic Sonja
Kádár Gabriella
Dokumentumtípus: Cikk
Megjelent: 2022
Sorozat:ARTHRITIS & RHEUMATOLOGY
Tárgyszavak:
doi:10.1002/art.42243

mtmt:32869486
Online Access:http://publicatio.bibl.u-szeged.hu/24510
Leíró adatok
Tartalmi kivonat: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.
Terjedelem/Fizikai jellemzők:Terjedelem: 31 p.-Azonosító: 42243
ISSN:2326-5191