Chen, John J.

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.

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.

AbstractBackgroundAs the only optically accessible part of the central nervous system, the retina represents an intriguing opportunity for the detection of biomarkers for Alzheimer’s disease (AD). This study evaluated the performance of the Retinal Deep PhenotypingTM platform, a digital biomarker platform comprising a hyperspectral retinal camera and image analysis algorithms, for the detection of likely positron‐emission tomography (PET) amyloid status (negative or positive) in older adults. A set of phenotypic features that correlates with the cerebral amyloid status as determined by amyloid PET scan were identified and used to train a classifying algorithm.MethodHyperspectral retinal images acquired with a Mydriatic Hyperspectral Retinal Camera from 194 participants (age ≥ 50 years), including cognitively normal and cognitively impaired (mild cognitive impairment and dementia) across 5 imaging sites were processed in order to train the model. Of these 194 participants, 73 individuals (38%) were amyloid‐positive, as confirmed by unanimous readings of PET scans by a panel of 3 expert reviewers. The pre‐processed hyperspectral images were segmented into various anatomical sites, and a texture‐based approach was used to extract several thousands of spatial‐spectral features. The most relevant features for the classification task were selected using a minimum redundancy maximum relevance (MRMR) algorithm and used to train a linear support vector machine (SVM) classifier. A nested, cross‐validation technique was used to evaluate the performance of the classifier.ResultThe resulting model based on the 17 most significant features showed high performance to discriminate between amyloid positive and negative subjects with an area under the receiver operating curve (AUCROC) of 0.87 (95% CI: 0.83 – 0.92).ConclusionThe Retinal Deep PhenotypingTM platform shows promise for detecting the likely cerebral amyloid PET status in adults 50 years and older from a simple, non‐invasive retinal scan and could provide an accessible means to identify individuals with abnormal cerebral amyloid in a clinical or drug development context. This phenotyping platform provides a flexible approach that could also be used for the detection of multiple biomarkers involved in cognitive decline from the same hyperspectral images of the retina.

Objective Determine the utility of aquaporin 4 IgG (AQP4-IgG) testing (live cell-based assay) for Neuromyelitis Optica Spectrum Disorders (NMOSD). Methods We included Mayo Clinic patients (1/1/2018-12/31/2019) tested for serum AQP4-IgG by live cell-based flow-cytometric assay. Medical records were reviewed to assess if patients fulfilled 2015 NMOSD criteria. Results Of 1371 patients tested, 41 were positive (3%) and all fulfilled NMOSD criteria with AQP4-IgG (specificity = 100%). Only 10/1330 testing negative met NMOSD criteria without AQP4-IgG (sensitivity = 80%) and seven of these 10 were MOG-IgG positive. Conclusions AQP4-IgG by live cell-based assay was highly specific and without false positives in a high throughput setting.

Papilledema is optic nerve swelling caused by increased intracranial hypertension, which has the potential to cause significant vision loss. Papilledema from idiopathic intracranial hypertension (IIH) is typically bilateral and symmetric, but can sometimes be asymmetric and even unilateral. The cause for this asymmetry is unknown. The purpose of this study was to develop ultrasound vibro-elastography (UVE) for assessing patients with papilledema to evaluate for biomechanical differences in these eyes. Nine patients with papilledema from IIH and 9 age-matched healthy control subjects were enrolled. A local harmonic vibration was used to generate wave propagation through the eyelid. Three excitation frequencies of 100, 150, and 200 Hz were used. A 6.4 MHz ultrasound probe was used to measure wave propagation in the eye structures. Wave speeds were measured in the posterior sclera of the maculae. The magnitudes of the wave speed of the IIH patients’ posterior sclera were significantly higher than those of healthy subjects. In patients with unilateral papilledema, the wave speed of the posterior sclera were higher in the eyes with papilledema than in the contralateral eyes without papilledema. UVE provides a noninvasive technique to measure the wave speed of posterior sclera, which is stiffer in eyes with papilledema.