The MOG antibody non-P42 epitope is predictive of a relapsing course in MOG antibody-associated disease

JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY(2024)

引用 0|浏览6
暂无评分
摘要
Background Myelin oligodendrocyte glycoprotein (MOG) IgG seropositivity is a prerequisite for MOG antibody-associated disease (MOGAD) diagnosis. While a significant proportion of patients experience a relapsing disease, there is currently no biomarker predictive of disease course. We aim to determine whether MOG-IgG epitopes can predict a relapsing course in MOGAD patients.Methods MOG-IgG-seropositive confirmed adult MOGAD patients were included (n=202). Serum MOG-IgG and epitope binding were determined by validated flow cytometry live cell-based assays. Associations between epitopes, disease course, clinical phenotype, Expanded Disability Status Scale and Visual Functional System Score at onset and last review were evaluated.Results Of 202 MOGAD patients, 150 (74%) patients had MOG-IgG that recognised the immunodominant proline42 (P42) epitope and 115 (57%) recognised histidine103/serine104 (H103/S104). Fifty-two (26%) patients had non-P42 MOG-IgG and showed an increased risk of a relapsing course (HR 1.7; 95% CI 1.15 to 2.60, p=0.009). Relapse-freedom was shorter in patients with non-P42 MOG-IgG (p=0.0079). Non-P42 MOG-IgG epitope status remained unchanged from onset throughout the disease course and was a strong predictor of a relapsing course in patients with unilateral optic neuritis (HR 2.7, 95% CI 1.06 to 6.98, p=0.038), with high specificity (95%, 95% CI 77% to 100%) and positive predictive value (85%, 95% CI 45% to 98%).Conclusions Non-P42 MOG-IgG predicts a relapsing course in a significant subgroup of MOGAD patients. Patients with unilateral optic neuritis, the most frequent MOGAD phenotype, can reliably be tested at onset, regardless of age and sex. Early detection and specialised management in these patients could minimise disability and improve long-term outcomes.
更多
查看译文
关键词
NEUROIMMUNOLOGY,IMMUNOLOGY,MULTIPLE SCLEROSIS
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要