TY - JOUR
T1 - Applying a genetic risk score model to enhance prediction of future multiple sclerosis diagnosis at first presentation with optic neuritis
AU - Loginovic, Pavel
AU - Wang, Feiyi
AU - Li, Jiang
AU - Ferrat, Lauric
AU - Mirshahi, Uyenlinh L.
AU - Rao, H. Shanker
AU - Petzold, Axel
AU - Tyrrell, Jessica
AU - Green, Harry D.
AU - Weedon, Michael N.
AU - Ganna, Andrea
AU - Tuomi, Tiinamaija
AU - Carey, David J.
AU - Oram, Richard A.
AU - Braithwaite, Tasanee
N1 - Publisher Copyright: © The Author(s) 2024.
PY - 2024/12/1
Y1 - 2024/12/1
N2 - Optic neuritis (ON) is associated with numerous immune-mediated inflammatory diseases, but 50% patients are ultimately diagnosed with multiple sclerosis (MS). Differentiating MS-ON from non-MS-ON acutely is challenging but important; non-MS ON often requires urgent immunosuppression to preserve vision. Using data from the United Kingdom Biobank we showed that combining an MS-genetic risk score (GRS) with demographic risk factors (age, sex) significantly improved MS prediction in undifferentiated ON; one standard deviation of MS-GRS increased the Hazard of MS 1.3-fold (95% confidence interval 1.07–1.55, P < 0.01). Participants stratified into quartiles of predicted risk developed incident MS at rates varying from 4% (95%CI 0.5–7%, lowest risk quartile) to 41% (95%CI 33–49%, highest risk quartile). The model replicated across two cohorts (Geisinger, USA, and FinnGen, Finland). This study indicates that a combined model might enhance individual MS risk stratification, paving the way for precision-based ON treatment and earlier MS disease-modifying therapy.
AB - Optic neuritis (ON) is associated with numerous immune-mediated inflammatory diseases, but 50% patients are ultimately diagnosed with multiple sclerosis (MS). Differentiating MS-ON from non-MS-ON acutely is challenging but important; non-MS ON often requires urgent immunosuppression to preserve vision. Using data from the United Kingdom Biobank we showed that combining an MS-genetic risk score (GRS) with demographic risk factors (age, sex) significantly improved MS prediction in undifferentiated ON; one standard deviation of MS-GRS increased the Hazard of MS 1.3-fold (95% confidence interval 1.07–1.55, P < 0.01). Participants stratified into quartiles of predicted risk developed incident MS at rates varying from 4% (95%CI 0.5–7%, lowest risk quartile) to 41% (95%CI 33–49%, highest risk quartile). The model replicated across two cohorts (Geisinger, USA, and FinnGen, Finland). This study indicates that a combined model might enhance individual MS risk stratification, paving the way for precision-based ON treatment and earlier MS disease-modifying therapy.
UR - http://www.scopus.com/inward/record.url?scp=85186240086&partnerID=8YFLogxK
U2 - 10.1038/s41467-024-44917-9
DO - 10.1038/s41467-024-44917-9
M3 - Article
C2 - 38418465
SN - 2041-1723
VL - 15
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 1415
ER -