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Genomic Risk Score impact on susceptibility to systemic sclerosis.

Authors :
Bossini-Castillo L
Villanueva-Martin G
Kerick M
Acosta-Herrera M
López-Isac E
Simeón CP
Ortego-Centeno N
Assassi S
Hunzelmann N
Gabrielli A
de Vries-Bouwstra JK
Allanore Y
Fonseca C
Denton CP
Radstake TR
Alarcón-Riquelme ME
Beretta L
Mayes MD
Martin J
Source :
Annals of the rheumatic diseases [Ann Rheum Dis] 2021 Jan; Vol. 80 (1), pp. 118-127. Date of Electronic Publication: 2020 Oct 01.
Publication Year :
2021

Abstract

Objectives: Genomic Risk Scores (GRS) successfully demonstrated the ability of genetics to identify those individuals at high risk for complex traits including immune-mediated inflammatory diseases (IMIDs). We aimed to test the performance of GRS in the prediction of risk for systemic sclerosis (SSc) for the first time.<br />Methods: Allelic effects were obtained from the largest SSc Genome-Wide Association Study (GWAS) to date (9 095 SSc and 17 584 healthy controls with European ancestry). The best-fitting GRS was identified under the additive model in an independent cohort that comprised 400 patients with SSc and 571 controls. Additionally, GRS for clinical subtypes (limited cutaneous SSc and diffuse cutaneous SSc) and serological subtypes (anti-topoisomerase positive (ATA+) and anti-centromere positive (ACA+)) were generated. We combined the estimated GRS with demographic and immunological parameters in a multivariate generalised linear model.<br />Results: The best-fitting SSc GRS included 33 single nucleotide polymorphisms (SNPs) and discriminated between patients with SSc and controls (area under the receiver operating characteristic (ROC) curve (AUC)=0.673). Moreover, the GRS differentiated between SSc and other IMIDs, such as rheumatoid arthritis and Sjögren's syndrome. Finally, the combination of GRS with age and immune cell counts significantly increased the performance of the model (AUC=0.787). While the SSc GRS was not able to discriminate between ATA+ and ACA+ patients (AUC<0.5), the serological subtype GRS, which was based on the allelic effects observed for the comparison between ACA+ and ATA+ patients, reached an AUC=0.693.<br />Conclusions: GRS was successfully implemented in SSc. The model discriminated between patients with SSc and controls or other IMIDs, confirming the potential of GRS to support early and differential diagnosis for SSc.<br />Competing Interests: Competing interests: LB-C: none; GV-M: none; MK: none; MA-H: none; ELI: none; International SSc Group: none; PRECISESADS Consortium: none; MEAl-R: none; LB: none; JM: none.<br /> (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Details

Language :
English
ISSN :
1468-2060
Volume :
80
Issue :
1
Database :
MEDLINE
Journal :
Annals of the rheumatic diseases
Publication Type :
Academic Journal
Accession number :
33004331
Full Text :
https://doi.org/10.1136/annrheumdis-2020-218558