Visual function resists early neurodegeneration in the visual system in primary progressive multiple sclerosis.

BACKGROUND: Neurodegeneration in multiple sclerosis (MS) affects the visual system but dynamics and pathomechanisms over several years especially in primary progressive MS (PPMS) are not fully understood. METHODS: We assessed longitudinal changes in visual function, retinal neurodegeneration using optical coherence tomography, MRI and serum NfL (sNfL) levels in a prospective PPMS cohort and matched healthy controls. We investigated the changes over time, correlations between outcomes and with loss of visual function. RESULTS: We followed 81 patients with PPMS (mean disease duration 5.9 years) over 2.7 years on average. Retinal nerve fibre layer thickness (RNFL) was reduced in comparison with controls (90.1 vs 97.8 µm; p<0.001). Visual function quantified by the area under the log contrast sensitivity function (AULCSF) remained stable over a continuous loss of RNFL (0.46 µm/year, 95% CI 0.10 to 0.82; p=0.015) up until a mean turning point of 91 µm from which the AULCSF deteriorated. Intereye RNFL asymmetry above 6 µm, suggestive of subclinical optic neuritis, occurred in 15 patients and was related to lower AULCSF but occurred also in 5 out of 44 controls. Patients with an AULCSF progression had a faster increase in Expanded Disability Status Scale (beta=0.17/year, p=0.043). sNfL levels were elevated in patients (12.2 pg/mL vs 8.0 pg/mL, p<0.001), but remained stable during follow-up (beta=-0.14 pg/mL/year, p=0.291) and were not associated with other outcomes. CONCLUSION: Whereas neurodegeneration in the anterior visual system is already present at onset, visual function is not impaired until a certain turning point. sNfL is not correlated with structural or functional impairment in the visual system.

Topological reorganization of brain network might contribute to the resilience of cognitive functioning in mildly disabled relapsing remitting multiple sclerosis.

Multiple sclerosis (MS) is an inflammatory and demyelinating disease which leads to impairment in several functional systems including cognition. Alteration of brain networks is linked to disability and its progression. However, results are mostly cross-sectional and yet contradictory as putative adaptive and maladaptive mechanisms were found. Here, we aimed to explore longitudinal reorganization of brain networks over 2-years by combining diffusion tensor imaging (DTI), resting-state functional MRI (fMRI), magnetoencephalography (MEG), and a comprehensive neuropsychological-battery. In 37 relapsing-remitting MS (RRMS) and 39 healthy-controls, cognition remained stable over-time. We reconstructed network models based on the three modalities and analyzed connectivity in relation to the hierarchical topology and functional subnetworks. Network models were compared across modalities and in their association with cognition using linear-mixed-effect-regression models. Loss of hub connectivity and global reduction was observed on a structural level over-years (p < .010), which was similar for functional MEG-networks but not for fMRI-networks. Structural hub connectivity increased in controls (p = .044), suggesting a physiological mechanism of healthy aging. Despite a general loss in structural connectivity in RRMS, hub connectivity was preserved (p = .002) over-time in default-mode-network (DMN). MEG-networks were similar to DTI and weakly correlated with fMRI in MS (p < .050). Lower structural (ß between .23-.33) and both lower (ß between .40-.59) and higher functional connectivity (ß = -.54) in DMN was associated with poorer performance in attention and memory in RRMS (p < .001). MEG-networks involved no association with cognition. Here, cognitive stability despite ongoing neurodegeneration might indicate a resilience mechanism of DMN hubs mimicking a physiological reorganization observed in healthy aging.

Brain grey matter perfusion in primary progressive multiple sclerosis: Mild decrease over years and regional associations with cognition and hand function.

BACKGROUND AND PURPOSE: Extent and dynamic of neurodegeneration in progressive multiple sclerosis (MS) might be reflected by global and regional brain perfusion, an outcome at the intercept between structure and function. Here, we provide a first insight into the evolution of brain perfusion and its association with disability in primary progressive MS (PPMS) over several years. METHODS: Seventy-seven persons with PPMS were followed over up to 5 years. Visits included a 3-T magnetic resonance imaging with pulsed arterial spin labelling perfusion, the Timed 25-Foot Walk, 9-Hole Peg Test (NHPT), Symbol Digit Modalities Test (SDMT), and Expanded Disability Status Scale (EDSS). We extracted regional cerebral blood flow surrogates and compared them to 11 controls. Analyses focused on cortical and deep grey matter, the change over time, and associations with disability on the regional and global levels. RESULTS: Baseline brain perfusion of patients and controls was comparable for the cortex (p = 0.716) and deep grey matter (p = 0.095). EDSS disability increased mildly (p = 0.023), whereas brain perfusion decreased during follow-up (p < 0.001) and with disease duration (p = 0.009). Lower global perfusion correlated with higher disability as indicated by EDSS, NHPT, and Timed 25-Foot Walk (p < 0.001). The motor task NHPT showed associations with 20 grey matter regions. In contrast, better SDMT performance correlated with lower perfusion (p < 0.001) in seven predominantly frontal regions, indicating a functional maladaptation. CONCLUSIONS: Decreasing perfusion indicates a putative association with MS disease mechanisms such as neurodegeneration, reduced metabolism, and loss of resilience. A low alteration rate limits its use in clinical practice, but regional association patterns might provide a snapshot of adaptive and maladaptive functional reorganization.

Functional and structural connectivity substrates of cognitive performance in relapsing remitting multiple sclerosis with mild disability.

Multiple Sclerosis (MS) is the most common chronic inflammatory and neurodegenerative disease of the central nervous system (CNS), which can lead to severe cognitive impairment over time. Magnetic resonance imaging (MRI) is currently the best available biomarker to track MS pathophysiology in vivo and examine the link to clinical disability. However, conventional MRI metrics have limited sensitivity and specificity to detect direct associations between symptoms and their underlying CNS substrates. In this study, we aimed to investigate structural and resting state functional connectomes and subnetworks associated with neuropsychological (NP) performance using a graph theoretical approach. A comprehensive NP test battery was administered in a sample of patients with relapsing remitting MS (RRMS) and mild disability [n = 33, F/M = 20/13, age = 40.9 ± 9.7, median [Expanded Disability Status Scale] (EDSS) = 2, range =0-4] and compared to healthy controls (HC) [n = 29, F/M = 19/10, age = 41.0 ± 8.5] closely matched for age, sex, and level of education. The NP battery comprised the most relevant domains of cognitive dysfunction in MS including attention, processing speed, verbal and spatial learning and memory, and executive function. While standard MRI metrics showed good correlations with TAP Alertness test, disease duration and neurological exams, structural networks showed closer associations with 9-hole peg test and cognitive performances. Decreased graph strength was associated with two out of the 5 NP tests in the spatial learning and memory domain specified by BVMT [Sum 1-3] and BVMT [Recall], and with also SDMT which is one out of the 9 NP tests in the attention/processing speed domain, while no correlation was found between these scores and functional connectivity. Nodal strength was decreased in all subnetworks based on Yeo atlas in patients compared to HC; however, no difference was observed in nodal level of functional connectivity between the groups. The difference in structural and functional nodal connectivity between the groups was also observed in the relationship between structural and functional connectivity within the groups; the relationship between nodal degree and nodal strength was reversed in patients but positive in controls. On a nodal level, structural and functional networks (mainly the default mode network) were correlated with more than one cognitive domain rather than one specific network for each domain within patients. Interestingly, poorer cognitive performance was mostly correlated with increased functional connectivity but decreased structural connectivity in patients. Increased functional connectivity in the default mode network had both positive as well as negative associations with verbal and spatial learning and memory, possibly indicating adaptive and maladaptive mechanisms. In conclusion, our results suggest that cognitive performance, even in patients with RRMS and very mild disability, may reflect a loss of structural connectivity. In contrast, widespread increases in functional connectivity may be the result of maladaptive processes.