Multiscale networks in multiple sclerosis.

Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. In fact, any phenotype for an organism is dictated by the interplay among these scales. We conducted a multilayer network analysis and deep phenotyping with multi-omics data (genomics, phosphoproteomics and cytomics), brain and retinal imaging, and clinical data, obtained from a multicenter prospective cohort of 328 patients and 90 healthy controls. Multilayer networks were constructed using mutual information for topological analysis, and Boolean simulations were constructed using Pearson correlation to identified paths within and among all layers. The path more commonly found from the Boolean simulations connects protein MK03, with total T cells, the thickness of the retinal nerve fiber layer (RNFL), and the walking speed. This path contains nodes involved in protein phosphorylation, glial cell differentiation, and regulation of stress-activated MAPK cascade, among others. Specific paths identified were subsequently analyzed by flow cytometry at the single-cell level. Combinations of several proteins (GSK3AB, HSBP1 or RS6) and immune cells (Th17, Th1 non-classic, CD8, CD8 Treg, CD56 neg, and B memory) were part of the paths explaining the clinical phenotype. The advantage of the path identified from the Boolean simulations is that it connects information about these known biological pathways with the layers at higher scales (retina damage and disability). Overall, the identified paths provide a means to connect the molecular aspects of MS with the overall phenotype.

Interactions of optic radiation lesions with retinal and brain atrophy in early multiple sclerosis.

OBJECTIVE: Retrograde trans-synaptic neuroaxonal degeneration is considered a key pathological factor of subclinical retinal neuroaxonal damage in multiple sclerosis (MS). We aim to evaluate the longitudinal association of optic radiation (OR) lesion activity with retinal neuroaxonal damage and its role in correlations between retinal and brain atrophy in people with clinically isolated syndrome and early MS (pweMS). METHODS: Eighty-five pweMS were retrospectively screened from a prospective cohort (Berlin CIS cohort). Participants underwent 3T magnetic resonance imaging (MRI) for OR lesion volume and brain atrophy measurements and optical coherence tomography (OCT) for retinal layer thickness measurements. All pweMS were followed with serial OCT and MRI over a median follow-up of 2.9 (interquartile range: 2.6-3.4) years. Eyes with a history of optic neuritis prior to study enrollment were excluded. Linear mixed models were used to analyze the association of retinal layer thinning with changes in OR lesion volume and brain atrophy. RESULTS: Macular ganglion cell-inner plexiform layer (GCIPL) thinning was more pronounced in pweMS with OR lesion volume increase during follow-up compared to those without (Difference: -0.82 µm [95% CI:-1.49 to -0.15], p = 0.018). Furthermore, GCIPL thinning correlated with both OR lesion volume increase (ß [95% CI] = -0.27 [-0.50 to -0.03], p = 0.028) and brain atrophy (ß [95% CI] = 0.47 [0.25 to 0.70], p < 0.001). Correlations of GCIPL changes with brain atrophy did not differ between pweMS with or without OR lesion increase ( η p 2 = 5.92e-7 , p = 0.762). INTERPRETATION: Faster GCIPL thinning rate is associated with increased OR lesion load. Our results support the value of GCIPL as a sensitive biomarker reflecting both posterior visual pathway pathology and global brain neurodegeneration.

N-acetylglucosamine inhibits inflammation and neurodegeneration markers in multiple sclerosis: a mechanistic trial.

BACKGROUND: In the demyelinating disease multiple sclerosis (MS), chronic-active brain inflammation, remyelination failure and neurodegeneration remain major issues despite immunotherapy. While B cell depletion and blockade/sequestration of T and B cells potently reduces episodic relapses, they act peripherally to allow persistence of chronic-active brain inflammation and progressive neurological dysfunction. N-acetyglucosamine (GlcNAc) is a triple modulator of inflammation, myelination and neurodegeneration. GlcNAc promotes biosynthesis of Asn (N)-linked-glycans, which interact with galectins to co-regulate the clustering/signaling/endocytosis of multiple glycoproteins simultaneously. In mice, GlcNAc crosses the blood brain barrier to raise N-glycan branching, suppress inflammatory demyelination by T and B cells and trigger stem/progenitor cell mediated myelin repair. MS clinical severity, demyelination lesion size and neurodegeneration inversely associate with a marker of endogenous GlcNAc, while in healthy humans, age-associated increases in endogenous GlcNAc promote T cell senescence. OBJECTIVES AND METHODS: An open label dose-escalation mechanistic trial of oral GlcNAc at 6 g (n = 18) and 12 g (n = 16) for 4 weeks was performed in MS patients on glatiramer acetate and not in relapse from March 2016 to December 2019 to assess changes in serum GlcNAc, lymphocyte N-glycosylation and inflammatory markers. Post-hoc analysis examined changes in serum neurofilament light chain (sNfL) as well as neurological disability via the Expanded Disability Status Scale (EDSS). RESULTS: Prior to GlcNAc therapy, high serum levels of the inflammatory cytokines IFNγ, IL-17 and IL-6 associated with reduced baseline levels of a marker of endogenous serum GlcNAc. Oral GlcNAc therapy was safe, raised serum levels and modulated N-glycan branching in lymphocytes. Glatiramer acetate reduces TH1, TH17 and B cell activity as well as sNfL, yet the addition of oral GlcNAc dose-dependently lowered serum IFNγ, IL-17, IL-6 and NfL. Oral GlcANc also dose-dependently reduced serum levels of the anti-inflammatory cytokine IL-10, which is increased in the brain of MS patients. 30% of treated patients displayed confirmed improvement in neurological disability, with an average EDSS score decrease of 0.52 points. CONCLUSIONS: Oral GlcNAc inhibits inflammation and neurodegeneration markers in MS patients despite concurrent immunomodulation by glatiramer acetate. Blinded studies are required to investigate GlcNAc's potential to control residual brain inflammation, myelin repair and neurodegeneration in MS.

Digital Motor Biomarkers of Cerebellar Ataxia Using an RGB-Depth Camera-Based Motion Analysis System.

This study aimed to identify quantitative biomarkers of motor function for cerebellar ataxia by evaluating gait and postural control using an RGB-depth camera-based motion analysis system. In 28 patients with degenerative cerebellar ataxia and 33 age- and sex-matched healthy controls, motor tasks (short-distance walk, closed feet stance, and stepping in place) were selected from a previously reported protocol, and scanned using Kinect V2 and customized software. The Clinical Assessment Scale for the Assessment and Rating of Ataxia (SARA) was also evaluated. Compared with the normal control group, the cerebellar ataxia group had slower gait speed and shorter step lengths, increased step width, and mediolateral trunk sway in the walk test (all P < 0.001). Lateral sway increased in the stance test in the ataxia group (P < 0.001). When stepping in place, the ataxia group showed higher arrhythmicity of stepping and increased stance time (P < 0.001). In the correlation analyses, the ataxia group showed a positive correlation between the total SARA score and arrhythmicity of stepping in place (r = 0.587, P = 0.001). SARA total score (r = 0.561, P = 0.002) and gait subscore (ρ = 0.556, P = 0.002) correlated with mediolateral truncal sway during walking. These results suggest that the RGB-depth camera-based motion analyses on mediolateral truncal sway during walking and arrhythmicity of stepping in place are useful digital motor biomarkers for the assessment of cerebellar ataxia, and could be utilized in future clinical trials.

Functional connectome fingerprinting and stability in multiple sclerosis.

Background: Functional connectome fingerprinting can identify individuals based on their functional connectome. Previous studies relied mostly on short intervals between fMRI acquisitions. Objective: This cohort study aimed to determine the stability of connectome-based identification and their underlying signatures in patients with multiple sclerosis and healthy individuals with long follow-up intervals. Methods: We acquired resting-state fMRI in 70 patients with multiple sclerosis and 273 healthy individuals with long follow-up times (up to 4 and 9 years, respectively). Using functional connectome fingerprinting, we examined the stability of the connectome and additionally investigated which regions, connections and networks supported individual identification. Finally, we predicted cognitive and behavioural outcome based on functional connectivity. Results: Multiple sclerosis patients showed connectome stability and identification accuracies similar to healthy individuals, with longer time delays between imaging sessions being associated with accuracies dropping from 89% to 76%. Lesion load, brain atrophy or cognitive impairment did not affect identification accuracies within the range of disease severity studied. Connections from the fronto-parietal and default mode network were consistently most distinctive, i.e., informative of identity. The functional connectivity also allowed the prediction of individual cognitive performances. Conclusion: Our results demonstrate that discriminatory signatures in the functional connectome are stable over extended periods of time in multiple sclerosis, resulting in similar identification accuracies and distinctive long-lasting functional connectome fingerprinting signatures in patients and healthy individuals.

Discrimination of multiple sclerosis using OCT images from two different centers.

BACKGROUND: Multiple sclerosis (MS) is one of the most prevalent chronic inflammatory diseases caused by demyelination and axonal damage in the central nervous system. Structural retinal imaging via optical coherence tomography (OCT) shows promise as a noninvasive biomarker for monitoring of MS. There are successful reports regarding the application of Artificial Intelligence (AI) in the analysis of cross-sectional OCTs in ophthalmologic diseases. However, the alteration of thicknesses of various retinal layers in MS is noticeably subtle compared to other ophthalmologic diseases. Therefore, raw cross-sectional OCTs are replaced with multilayer segmented OCTs for discrimination of MS and healthy controls (HCs). METHODS: To conform to the principles of trustworthy AI, interpretability is provided by visualizing the regional layer contribution to classification performance with the proposed occlusion sensitivity approach. The robustness of the classification is also guaranteed by showing the effectiveness of the algorithm while being tested on the new independent dataset. The most discriminative features from different topologies of the multilayer segmented OCTs are selected by the dimension reduction method. Support vector machine (SVM), random forest (RF), and artificial neural network (ANN) are used for classification. Patient-wise cross-validation (CV) is utilized to evaluate the performance of the algorithm, where the training and test folds contain records from different subjects. RESULTS: The most discriminative topology is determined to square with a size of 40 pixels and the most influential layers are the ganglion cell and inner plexiform layer (GCIPL) and inner nuclear layer (INL). Linear SVM resulted in 88% Accuracy (with standard deviation (std) = 0.49 in 10 times of execution to indicate the repeatability), 78% precision (std=1.48), and 63% recall (std=1.35) in the discrimination of MS and HCs using macular multilayer segmented OCTs. CONCLUSION: The proposed classification algorithm is expected to help neurologists in the early diagnosis of MS. This paper distinguishes itself from other studies by employing two distinct datasets, which enhances the robustness of its findings in comparison with previous studies with lack of external validation. This study aims to circumvent the utilization of deep learning methods due to the limited quantity of the available data and convincingly demonstrates that favorable outcomes can be achieved without relying on deep learning techniques.

Visually Evoked Potential as Prognostic Biomarker for Neuroaxonal Damage in Multiple Sclerosis From a Multicenter Longitudinal Cohort.

BACKGROUND AND OBJECTIVES: With the increasing use of visually evoked potentials (VEPs) as quantitative outcome parameters for myelin in clinical trials, an in-depth understanding of longitudinal VEP latency changes and their prognostic potential for subsequent neuronal loss will be required. In this longitudinal multicenter study, we evaluated the association and prognostic potential of VEP latency for retinal neurodegeneration, measured by optical coherence tomography (OCT), in relapsing-remitting MS (RRMS). METHODS: We included 293 eyes of 147 patients with RRMS (age [years, median ± SD] 36 ± 10, male sex 35%, F/U [years, median {IQR} 2.1 {1.5-3.9}]): 41 eyes had a history of optic neuritis (ON) ≥6 months before baseline (CHRONIC-ON), and 252 eyes had no history of ON (CHRONIC-NON). P100 latency (VEP), macular combined ganglion cell and inner plexiform layer volume (GCIPL), and peripapillary retinal nerve fiber layer thickness (pRNFL) (OCT) were quantified. RESULTS: P100 latency change over the first year predicted subsequent GCIPL loss (36 months) across the entire chronic cohort (p = 0.001) and in (and driven by) the CHRONIC-NON subset (p = 0.019) but not in the CHRONIC-ON subset (p = 0.680). P100 latency and pRNFL were correlated at baseline (CHRONIC-NON p = 0.004, CHRONIC-ON p < 0.001), but change in P100 latency and pRNFL were not correlated. P100 latency did not differ longitudinally between protocols or centers. DISCUSSION: VEP in non-ON eyes seems to be a promising marker of demyelination in RRMS and of potential prognostic value for subsequent retinal ganglion cell loss. This study also provides evidence that VEP may be a useful and reliable biomarker for multicenter studies.

Diagnostic value of intereye difference metrics for optic neuritis in aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders.

BACKGROUND: The novel optic neuritis (ON) diagnostic criteria include intereye differences (IED) of optical coherence tomography (OCT) parameters. IED has proven valuable for ON diagnosis in multiple sclerosis but has not been evaluated in aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders (AQP4+NMOSD). We evaluated the diagnostic accuracy of intereye absolute (IEAD) and percentage difference (IEPD) in AQP4+NMOSD after unilateral ON >6 months before OCT as compared with healthy controls (HC). METHODS: Twenty-eight AQP4+NMOSD after unilateral ON (NMOSD-ON), 62 HC and 45 AQP4+NMOSD without ON history (NMOSD-NON) were recruited by 13 centres as part of the international Collaborative Retrospective Study on retinal OCT in Neuromyelitis Optica study. Mean thickness of peripapillary retinal nerve fibre layer (pRNFL) and macular ganglion cell and inner plexiform layer (GCIPL) were quantified by Spectralis spectral domain OCT. Threshold values of the ON diagnostic criteria (pRNFL: IEAD 5 µm, IEPD 5%; GCIPL: IEAD: 4 µm, IEPD: 4%) were evaluated using receiver operating characteristics and area under the curve (AUC) metrics. RESULTS: The discriminative power was high for NMOSD-ON versus HC for IEAD (pRNFL: AUC 0.95, specificity 82%, sensitivity 86%; GCIPL: AUC 0.93, specificity 98%, sensitivity 75%) and IEPD (pRNFL: AUC 0.96, specificity 87%, sensitivity 89%; GCIPL: AUC 0.94, specificity 96%, sensitivity 82%). The discriminative power was high/moderate for NMOSD-ON versus NMOSD-NON for IEAD (pRNFL: AUC 0.92, specificity 77%, sensitivity 86%; GCIP: AUC 0.87, specificity 85%, sensitivity 75%) and for IEPD (pRNFL: AUC 0.94, specificity 82%, sensitivity 89%; GCIP: AUC 0.88, specificity 82%, sensitivity 82%). CONCLUSIONS: Results support the validation of the IED metrics as OCT parameters of the novel diagnostic ON criteria in AQP4+NMOSD.

Optical coherence tomography reflects clinically relevant gray matter damage in patients with multiple sclerosis.

BACKGROUND: Retinal degeneration leading to optical coherence tomography (OCT) changes is frequent in patients with multiple sclerosis (PwMS). OBJECTIVE: To investigate associations among OCT changes, MRI measurements of global and regional brain volume loss, and physical and cognitive impairment in PwMS. METHODS: 95 PwMS and 52 healthy controls underwent OCT and MRI examinations. Mean peripapillary retinal nerve fiber layer (pRNFL) thickness and ganglion cell/inner plexiform layer (GCIPL) volume were measured. In PwMS disability was quantified with the Expanded Disability Status Scale (EDSS) and Symbol Digit Modalities Test (SDMT). Associations between OCT, MRI, and clinical measures were investigated with multivariable regression models. RESULTS: In PwMS, pRNFL and GCIPL were associated with the volume of whole brain (p < 0.04), total gray matter (p < 0.002), thalamus (p ≤ 0.04), and cerebral cortex (p ≤ 0.003) -both globally and regionally-, but not white matter. pRNFL and GCIPL were also inversely associated with T2-lesion volume (T2LV), especially in the optic radiations (p < 0.0001). The brain volumes associated with EDSS and SDMT significantly overlapped with those correlating with pRNFL and GCIPL. CONCLUSIONS: In PwMS, pRNFL and GCIPL reflect the integrity of clinically-relevant gray matter structures, underling the value of OCT measures as markers of neurodegeneration and disability in multiple sclerosis.

Retinal ganglion cell loss is associated with future disability worsening in early relapsing-remitting multiple sclerosis.

BACKGROUND AND PURPOSE: Thinning of the retinal combined ganglion cell and inner plexiform layer (GCIP) as measured by optical coherence tomography (OCT) is a common finding in patients with multiple sclerosis. This study aimed to investigate whether a single retinal OCT analysis allows prediction of future disease activity after a first demyelinating event. METHODS: This observational cohort study included 201 patients with recently diagnosed clinically isolated syndrome or relapsing-remitting multiple sclerosis from two German tertiary referral centers. Individuals underwent neurological examination, magnetic resonance imaging, and OCT at baseline and at yearly follow-up visits. RESULTS: Patients were included at a median disease duration of 2.0 months. During a median follow-up of 59 (interquartile range = 43-71) months, 82% of patients had ongoing disease activity as demonstrated by failing the no evidence of disease activity 3 (NEDA-3) criteria, and 19% presented with confirmed disability worsening. A GCIP threshold of ≤77 µm at baseline identified patients with a high risk for NEDA-3 failure (hazard ratio [HR] = 1.7, 95% confidence interval [CI] = 1.1-2.8, p = 0.04), and GCIP measures of ≤69 µm predicted disability worsening (HR = 2.2, 95% CI = 1.2-4.3, p = 0.01). Higher rates of annualized GCIP loss increased the risk for disability worsening (HR = 2.5 per 1 µm/year increase of GCIP loss, p = 0.03). CONCLUSIONS: Ganglion cell thickness as measured by OCT after the initial manifestation of multiple sclerosis may allow early risk stratification as to future disease activity and progression.

Diagnosis of myelin oligodendrocyte glycoprotein antibody-associated disease: International MOGAD Panel proposed criteria.

Serum antibodies directed against myelin oligodendrocyte glycoprotein (MOG) are found in patients with acquired CNS demyelinating syndromes that are distinct from multiple sclerosis and aquaporin-4-seropositive neuromyelitis optica spectrum disorder. Based on an extensive literature review and a structured consensus process, we propose diagnostic criteria for MOG antibody-associated disease (MOGAD) in which the presence of MOG-IgG is a core criterion. According to our proposed criteria, MOGAD is typically associated with acute disseminated encephalomyelitis, optic neuritis, or transverse myelitis, and is less commonly associated with cerebral cortical encephalitis, brainstem presentations, or cerebellar presentations. MOGAD can present as either a monophasic or relapsing disease course, and MOG-IgG cell-based assays are important for diagnostic accuracy. Diagnoses such as multiple sclerosis need to be excluded, but not all patients with multiple sclerosis should undergo screening for MOG-IgG. These proposed diagnostic criteria require validation but have the potential to improve identification of individuals with MOGAD, which is essential to define long-term clinical outcomes, refine inclusion criteria for clinical trials, and identify predictors of a relapsing versus a monophasic disease course.

Berlin Registry of Neuroimmunological entities (BERLimmun): protocol of a prospective observational study.

BACKGROUND: Large-scale disease overarching longitudinal data are rare in the field of neuroimmunology. However, such data could aid early disease stratification, understanding disease etiology and ultimately improve treatment decisions. The Berlin Registry of Neuroimmunological Entities (BERLimmun) is a longitudinal prospective observational study, which aims to identify diagnostic, disease activity and prognostic markers and to elucidate the underlying pathobiology of neuroimmunological diseases. METHODS: BERLimmun is a single-center prospective observational study of planned 650 patients with neuroimmunological disease entity (e.g. but not confined to: multiple sclerosis, isolated syndromes, neuromyelitis optica spectrum disorders) and 85 healthy participants with 15 years of follow-up. The protocol comprises annual in-person visits with multimodal standardized assessments of medical history, rater-based disability staging, patient-report of lifestyle, diet, general health and disease specific symptoms, tests of motor, cognitive and visual functions, structural imaging of the neuroaxis and retina and extensive sampling of biological specimen. DISCUSSION: The BERLimmun database allows to investigate multiple key aspects of neuroimmunological diseases, such as immunological differences between diagnoses or compared to healthy participants, interrelations between findings of functional impairment and structural change, trajectories of change for different biomarkers over time and, importantly, to study determinants of the long-term disease course. BERLimmun opens an opportunity to a better understanding and distinction of neuroimmunological diseases.

Prior optic neuritis detection on peripapillary ring scans using deep learning.

BACKGROUND: The diagnosis of multiple sclerosis (MS) requires demyelinating events that are disseminated in time and space. Peripapillary retinal nerve fiber layer (pRNFL) thickness as measured by optical coherence tomography (OCT) distinguishes eyes with a prior history of acute optic neuritis (ON) and may provide evidence to support a demyelinating attack. OBJECTIVE: To investigate whether a deep learning (DL)-based network can distinguish between eyes with prior ON and healthy control (HC) eyes using peripapillary ring scans. METHODS: We included 1033 OCT scans from 415 healthy eyes (213 HC subjects) and 510 peripapillary ring scans from 164 eyes with prior acute ON (140 patients with MS). Data were split into 70% training, 15% validation, and 15% test data. We included 102 OCT scans from 80 healthy eyes (40 HC) and 61 scans from 40 ON eyes (31 MS patients) from an independent second center. Receiver operating characteristic curve analyses with area under the curve (AUC) were used to investigate performance. RESULTS: We used a dilated residual convolutional neural network for the classification. The final network had an accuracy of 0.85 and an AUC of 0.86, whereas pRNFL only had an AUC of 0.77 in recognizing ON eyes. Using data from a second center, the network achieved an accuracy of 0.77 and an AUC of 0.90 compared to pRNFL, which had an AUC of 0.84. INTERPRETATION: DL-based disease classification of prior ON is feasible and has the potential to outperform thickness-based classification of eyes with and without history of prior ON.

Structure-function correlates of vision loss in neuromyelitis optica spectrum disorders.

Optic neuritis (ON) in neuromyelitis optica spectrum disorders (NMOSD) regularly leads to more profound vision loss compared to multiple sclerosis (MS) and myelin-oligodendrocyte-glycoprotein-antibody associated disease (MOGAD). Here we investigate ON-related vision loss in NMOSD compared to MS and MOGAD in order to identify neuroaxonal and retinal contributors to visual dysfunction. In this retrospective study we included patients with aquaporin-4-antibody seropositive NMOSD (n = 28), MOGAD (n = 14), MS (n = 29) and controls (n = 14). We assessed optic nerve damage and fovea morphometry by optical coherence tomography. Visual function was assessed as high (HCVA) and low contrast visual acuity (LCVA), and visual fields' mean deviation (MD). In all diseases, lower visual function was associated with peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell and inner plexiform layer (GCIP) thinning following a broken stick model, with pRNFL and GCIP cutoff point at ca. 60 µm. HCVA loss per µm pRNFL and GCIP thinning was stronger in NMOSD compared with MOGAD. Foveal inner rim volume contributed to MD and LCVA in NMOSD eyes, only. Together these data supports that visual dysfunction in NMOSD is associated with neuroaxonal damage beyond the effect seen in MS and MOGAD. A primary retinopathy, respectively Müller cell pathology, may contribute to this effect.

Normative Data and Conversion Equation for Spectral-Domain Optical Coherence Tomography in an International Healthy Control Cohort.

BACKGROUND: Spectral-domain (SD-) optical coherence tomography (OCT) can reliably measure axonal (peripapillary retinal nerve fiber layer [pRNFL]) and neuronal (macular ganglion cell + inner plexiform layer [GCIPL]) thinning in the retina. Measurements from 2 commonly used SD-OCT devices are often pooled together in multiple sclerosis (MS) studies and clinical trials despite software and segmentation algorithm differences; however, individual pRNFL and GCIPL thickness measurements are not interchangeable between devices. In some circumstances, such as in the absence of a consistent OCT segmentation algorithm across platforms, a conversion equation to transform measurements between devices may be useful to facilitate pooling of data. The availability of normative data for SD-OCT measurements is limited by the lack of a large representative world-wide sample across various ages and ethnicities. Larger international studies that evaluate the effects of age, sex, and race/ethnicity on SD-OCT measurements in healthy control participants are needed to provide normative values that reflect these demographic subgroups to provide comparisons to MS retinal degeneration. METHODS: Participants were part of an 11-site collaboration within the International Multiple Sclerosis Visual System (IMSVISUAL) consortium. SD-OCT was performed by a trained technician for healthy control subjects using Spectralis or Cirrus SD-OCT devices. Peripapillary pRNFL and GCIPL thicknesses were measured on one or both devices. Automated segmentation protocols, in conjunction with manual inspection and correction of lines delineating retinal layers, were used. A conversion equation was developed using structural equation modeling, accounting for clustering, with healthy control data from one site where participants were scanned on both devices on the same day. Normative values were evaluated, with the entire cohort, for pRNFL and GCIPL thicknesses for each decade of age, by sex, and across racial groups using generalized estimating equation (GEE) models, accounting for clustering and adjusting for within-patient, intereye correlations. Change-point analyses were performed to determine at what age pRNFL and GCIPL thicknesses exhibit accelerated rates of decline. RESULTS: The healthy control cohort (n = 546) was 54% male and had a wide distribution of ages, ranging from 18 to 87 years, with a mean (SD) age of 39.3 (14.6) years. Based on 346 control participants at a single site, the conversion equation for pRNFL was Cirrus = -5.0 + (1.0 × Spectralis global value). Based on 228 controls, the equation for GCIPL was Cirrus = -4.5 + (0.9 × Spectralis global value). Standard error was 0.02 for both equations. After the age of 40 years, there was a decline of -2.4 µm per decade in pRNFL thickness ( P < 0.001, GEE models adjusting for sex, race, and country) and -1.4 µm per decade in GCIPL thickness ( P < 0.001). There was a small difference in pRNFL thickness based on sex, with female participants having slightly higher thickness (2.6 µm, P = 0.003). There was no association between GCIPL thickness and sex. Likewise, there was no association between race/ethnicity and pRNFL or GCIPL thicknesses. CONCLUSIONS: A conversion factor may be required when using data that are derived between different SD-OCT platforms in clinical trials and observational studies; this is particularly true for smaller cross-sectional studies or when a consistent segmentation algorithm is not available. The above conversion equations can be used when pooling data from Spectralis and Cirrus SD-OCT devices for pRNFL and GCIPL thicknesses. A faster decline in retinal thickness may occur after the age of 40 years, even in the absence of significant differences across racial groups.

Serum glial fibrillary acidic protein correlates with retinal structural damage in aquaporin-4 antibody positive neuromyelitis optica spectrum disorder.

BACKGROUND: Aquaporin-4 immunoglobulin-G positive (AQP4-IgG+) neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune astrocytopathy associated with optic neuritis (ON). Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is an oligodendrocytopathy with a similar phenotype. Serum glial fibrillary acidic protein (sGFAP), an astrocyte-derived protein, is associated with disease severity in AQP4-IgG+ NMOSD. Serum neurofilament light (sNfL) indicates neuroaxonal damage. The objective was to investigate the association of sGFAP and sNfL with subclinical afferent visual system damage in clinically stable AQP4-IgG+ NMOSD and MOGAD patients. METHODS: In this cross-sectional study, clinically stable patients with AQP4-IgG+ NMOSD (N = 33) and MOGAD (N = 16), as diseased controls, underwent sGFAP and sNfL measurements by single molecule array, retinal optical coherence tomography and visually evoked potentials. RESULTS: Higher sGFAP concentrations were associated with thinner ganglion cell-inner plexiform layer (ß (95% confidence interval (CI)) = -0.75 (-1.23 to -0.27), p = 0.007) and shallower fovea (average pit depth: ß (95%CI) = -0.59 (-0.63 to -0.55), p = 0.020) in NMOSD non-ON eyes. Participants with pathological P100 latency had higher sGFAP (median [interquartile range]: 131.32 [81.10-179.34] vs. 89.50 [53.46-121.91] pg/ml, p = 0.024). In MOGAD, sGFAP was not associated with retinal structural or visual functional measures. CONCLUSIONS: The association of sGFAP with structural and functional markers of afferent visual system damage in absence of ON suggests that sGFAP may be a sensitive biomarker for chronic disease severity in clinically stable AQP4-IgG+ NMOSD.

Central Macular Topographic and Volumetric Measures: New Biomarkers for Detection of Glaucoma.

Purpose: To test the hypothesis that newly developed shape measures using optical coherence tomography (OCT) macular volume scans can discriminate patients with perimetric glaucoma from healthy subjects. Methods: OCT structural measures defining macular topography and volume were recently developed based on cubic Bézier curves. We exported macular volume scans from 135 eyes with glaucoma (133 patients) and 155 healthy eyes (85 subjects) and estimated global and quadrant-based measures. The best subset of measures to predict glaucoma was explored with a gradient boost model (GBM) with subsequent logistic regression. Accuracy and area under receiver operating curves (AUC) were the primary metrics. In addition, we separately investigated model performance in 66 eyes with mild glaucoma (mean deviation ≥ -6 dB). Results: Average (±SD) 24-2 mean deviation was -8.2 (±6.1) dB in eyes with glaucoma. The main predictive measures for glaucoma were temporal inferior rim height, nasal inferior pit volume, and temporal inferior pit depth. Lower values for these measures predicted higher risk of glaucoma. Sensitivity, specificity, and AUC for discriminating between healthy and glaucoma eyes were 81.5% (95% CI = 76.6-91.9%), 89.7% (95% CI = 78.7-94.2%), and 0.915 (95% CI = 0.882-0.948), respectively. Corresponding metrics for mild glaucoma were 84.8% (95% CI = 72.1%-95.5%), 85.8% (95% CI = 87.1%-97.4%), and 0.913 (95% CI = 0.867-0.958), respectively. Conclusions: Novel macular shape biomarkers detect early glaucoma with clinically relevant performance. Such biomarkers do not depend on intraretinal segmentation accuracy and may be helpful in eyes with suboptimal macular segmentation. Translational Relevance: Macular shape biomarkers provide valuable information for detection of early glaucoma and may provide additional information beyond thickness measurements.

Brain disconnectome mapping derived from white matter lesions and serum neurofilament light levels in multiple sclerosis: A longitudinal multicenter study.

BACKGROUND AND OBJECTIVES: Connectivity-based approaches incorporating the distribution and magnitude of the extended brain network aberrations caused by lesions may offer higher sensitivity for axonal damage in patients with multiple sclerosis (MS) than conventional lesion characteristics. Using individual brain disconnectome mapping, we tested the longitudinal associations between putative imaging-based brain network aberrations and levels of serum neurofilament light chain (NfL) as a neuroaxonal injury biomarker. METHODS: MS patients (n = 312, mean age 42.9 years, 71 % female) and healthy controls (HC) (n = 59, mean age 39.9 years, 78 % female) were prospectively enrolled at four European MS centres, and reassessed after two years (MS, n = 242; HC, n = 30). Post-processing of 3 Tesla (3 T) MRI data was performed at one centre using a harmonized pipeline, and disconnectome maps were calculated using BCBtoolkit based on individual lesion maps. Global disconnectivity (GD) was defined as the average disconnectome probability in each patient's white matter. Serum NfL concentrations were measured by single molecule array (Simoa). Robust linear mixed models (rLMM) with GD or T2-lesion volume (T2LV) as dependent variables, patient as a random factor, serum NfL, age, sex, timepoint for visit, diagnosis, treatment, and center as fixed factors were run. RESULTS: rLMM revealed significant associations between GD and serum NfL (t = 2.94, p = 0.003), age (t = 4.21, p = 2.5 × 10-5), and longitudinal changes in NfL (t = -2.29, p = 0.02), but not for sex (t = 0.63, p = 0.53) or treatments (t = 0.80-0.83, p = 0.41-0.42). Voxel-wise analyses revealed significant associations between dysconnectivity in cerebellar and brainstem regions and serum NfL (t = 7.03, p < 0.001). DISCUSSION: In our prospective multi-site MS cohort, rLMMs demonstrated that the extent of global and regional brain disconnectivity is sensitive to a systemic biomarker of axonal damage, serum NfL, in patients with MS. These findings provide a neuroaxonal correlate of advanced disconnectome mapping and provide a platform for further investigations of the functional and potential clinical relevance of brain disconnectome mapping in patients with brain disorders.

Longitudinal Retinal Changes in MOGAD.

OBJECTIVE: Patients with myelin oligodendrocyte glycoprotein antibody (MOG-IgG)-associated disease (MOGAD) suffer from severe optic neuritis (ON) leading to retinal neuro-axonal loss, which can be quantified by optical coherence tomography (OCT). We assessed whether ON-independent retinal atrophy can be detected in MOGAD. METHODS: Eighty patients with MOGAD and 139 healthy controls (HCs) were included. OCT data was acquired with (1) Spectralis spectral domain OCT (MOGAD: N = 66 and HCs: N = 103) and (2) Cirrus high-definition OCT (MOGAD: N = 14 and HCs: N = 36). Macular combined ganglion cell and inner plexiform layer (GCIPL) and peripapillary retinal nerve fiber layer (pRNFL) were quantified. RESULTS: At baseline, GCIPL and pRNFL were lower in MOGAD eyes with a history of ON (MOGAD-ON) compared with MOGAD eyes without a history of ON (MOGAD-NON) and HCs (p < 0.001). MOGAD-NON eyes had lower GCIPL volume compared to HCs (p < 0.001) in the Spectralis, but not in the Cirrus cohort. Longitudinally (follow-up up to 3 years), MOGAD-ON with ON within the last 6-12 months before baseline exhibited greater pRNFL thinning than MOGAD-ON with an ON greater than 12 months ago (p < 0.001). The overall MOGAD cohort did not exhibit faster GCIPL thinning compared with the HC cohort. INTERPRETATION: Our study suggests the absence of attack-independent retinal damage in patients with MOGAD. Yet, ongoing neuroaxonal damage or edema resolution seems to occur for up to 12 months after ON, which is longer than what has been reported with other ON forms. These findings support that the pathomechanisms underlying optic nerve involvement and the evolution of OCT retinal changes after ON is distinct in patients with MOGAD. ANN NEUROL 2022;92:476-485.