AbstractObjectiveThe first international consensus criteria for optic neuritis (ICON) were published in 2022. We applied these criteria to a prospective, global observational study of acute optic neuritis (ON).MethodsWe included 160 patients with a first‐ever acute ON suggestive of a demyelinating CNS disease from the Acute Optic Neuritis Network (ACON). We applied the 2022 ICON to all participants and subsequently adjusted the ICON by replacing a missing relative afferent pupillary defect (RAPD) or dyschromatopsia if magnetic resonance imaging pathology of the optical nerve plus optical coherence tomography abnormalities or certain biomarkers are present.ResultsAccording to the 2022 ICON, 80 (50%) patients were classified as definite ON, 12 (7%) patients were classified as possible ON, and 68 (43%) as not ON (NON). The main reasons for classification as NON were absent RAPD (52 patients, 76%) or dyschromatopsia (49 patients, 72%). Distribution of underlying ON etiologies was as follows: 78 (49%) patients had a single isolated ON, 41 (26%) patients were diagnosed with multiple sclerosis, 25 (16%) patients with myelin oligodendrocyte glycoprotein antibody‐associated disease, and 15 (9%) with neuromyelitis optica spectrum disorder. The application of the adjusted ON criteria yielded a higher proportion of patients classified as ON (126 patients, 79%).InterpretationAccording to the 2022 ICON, almost half of the included patients in ACON did not fulfill the requirements for classification of definite or possible ON, particularly due to missing RAPD and dyschromatopsia. Thorough RAPD examination and formal color vision testing are critical to the application of the 2022 ICON.
Abstract Background: Optic neuritis (ON) is a frequent presentation of multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocyte glycoprotein-antibody disease (MOGAD) at onset. The pathophysiology underlying these diseases, especially MOGAD, is still being elucidated. While obesity has been reported to potentially be a risk factor for MS, this has not been explored in NMOSD or MOGAD. We aimed to investigate a possible association between obesity (body mass index [BMI] >30 kg/m²) and patients with MOGAD, NMOSD or MS. Methods: Multicenter non-interventional retrospective data collection from a first ever demyelinating attack of ON in patients subsequently diagnosed with MOGAD, NMOSD or MS between 2005-2020. The following data was collected: age, gender, ethnicity, BMI at disease onset and the etiology of ON after diagnostic work-up. A mixed model analysis was performed to assess the ability of obesity or BMI to predict MOGAD-ON and distinguish MOGAD-ON from NMOSD- and MS-ON. Main outcome measures included BMI in patients with acute ON and subsequent diagnosis of MOGAD, NMOSD or MS. Results: One-hundred and eighty-three patients were included: 44 with MOGAD, 49 with NMOSD, and 90 with MS. A higher BMI was significantly associated with a diagnosis of MOGAD-ON (p<0.001); in MOGAD patients the mean BMI was 31.6 kg/m² (standard deviation (SD) 7.2), while the mean BMI was 24.7 kg/m² (SD 5.3) in NMOSD patients and 26.9 kg/m² (SD 6.2) in MS patients. Mixed effects multionimal logistic regression, adjusted for age and gender with obesity as a binary variable revealed that obesity was associated with a higher odds ratio (OR) of a subsequent MOGAD diagnosis (OR 5.466, 95% CI: [2.039, 14.650], p = 0.001) in contradistinction with NMOSD. Conclusion: This study suggests an association between obesity and MOGAD. Our finding requires further exploration, but could have significant pathophysiologic implications if confirmed in larger prospective studies.
Obesity is Associated With Myelin Oligodendrocyte Glycoprotein Antibody Associated Disease in Acute Optic Neuritis
Abstract Background: Optic neuritis (ON) is a frequent presentation of multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocyte glycoprotein-antibody disease (MOGAD) at onset. The pathophysiology underlying these diseases, especially MOGAD, is still being elucidated. While obesity has been reported to potentially be a risk factor for MS, this has not been explored in NMOSD or MOGAD. We aimed to investigate a possible association between obesity (body mass index [BMI] >30 kg/m²) and patients with MOGAD, NMOSD or MS. Methods: Multicenter non-interventional retrospective data collection from a first ever demyelinating attack of ON in patients subsequently diagnosed with MOGAD, NMOSD or MS between 2005-2020. The following data was collected: age, gender, ethnicity, BMI at disease onset and the etiology of ON after diagnostic work-up. A mixed model analysis was performed to assess the ability of obesity or BMI to predict MOGAD-ON and distinguish MOGAD-ON from NMOSD- and MS-ON. Main outcome measures included BMI in patients with acute ON and subsequent diagnosis of MOGAD, NMOSD or MS. Results: One-hundred and eighty-three patients were included: 44 with MOGAD, 49 with NMOSD, and 90 with MS. A higher BMI was significantly associated with a diagnosis of MOGAD-ON (p<0.001); in MOGAD patients the mean BMI was 31.6 kg/m² (standard deviation (SD) 7.2), while the mean BMI was 24.7 kg/m² (SD 5.3) in NMOSD patients and 26.9 kg/m² (SD 6.2) in MS patients. Mixed effects multionimal logistic regression, adjusted for age and gender with obesity as a binary variable revealed that obesity was associated with a higher odds ratio (OR) of a subsequent MOGAD diagnosis (OR 5.466, 95% CI: [2.039, 14.650], p = 0.001) in contradistinction with NMOSD. Conclusion: This study suggests an association between obesity and MOGAD. Our finding requires further exploration, but could have significant pathophysiologic implications if confirmed in larger prospective studies.