Einar August Høgestøl

• Korbmacher, Max; Lie, Ingrid Anne; Wesnes, Kristin; Westman, Eric; Espeseth, Thomas & Andreassen, Ole [Show all 13 contributors for this article] (2026). Regional patterns of grey matter volume decline in relapsing-remitting multiple sclerosis relative to healthy ageing. NeuroImage. ISSN 1053-8119. 338, p. 1–9. doi: 10.1016/j.neuroimage.2026.122118. Full text in Research Archive Show summary

  Background: Grey matter volume loss (GM-VL) is an accurate marker of multiple sclerosis (MS)-related progression. However, long-term comparisons of GM-VL between MS and healthy controls (HC) are rare, and the brain regions with most significant GM-VL and their clinical importance still need robust and longitudinal validation. Methods: This multi-cohort longitudinal observational study used two relapsing remitting MS (RRMS) cohorts (N = 386, T1w-scans=940) sampled for up-to-12 years to localise grey matter volume loss (GM-VL) and disease progression (Expanded Disability Status Scale (EDSS), Paced Auditory Serial Addition Test (PASAT), Fatigue Severity Scale (FSS)). The identified region-specific significant GM-VL was compared with 2163 HCs (T1w-scans=4326). Results: The strongest, replicable, significant patterns of brain GM-VL in RRMS were found in the frontal lobes, specifically, in the superior frontal cortex (SFC, βage≤-0.27), pars orbitalis (βage≤-0.25), and thalami (βage≤-0.20). Compared with healthy controls (HCs) >20 years older, MS showed greater GM-VL in the right SFC, caudal-middle frontal cortex, caudate, and left frontal pole (all Z > 2.08, p < 0.019). The overlap of associations between volumetric and clinical outcome changes was limited to EDSS, which was significantly related to left hippocampal volumes βEDSS≤-0.19 in both cohorts. Conclusions: Our findings indicate GM-VL in people with RRMS comparable to 20-year older HC, and stronger in the SFC and thalamus, and cohort-specific relationships with disability-progression.

• Torkildsen, Øivind; Brustad, Hilde Kjelgaard; Høgestøl, Einar August; Alstadhaug, Karl Bjørnar; Bhan, Alok & Flemmen, Heidi Øyen [Show all 22 contributors for this article] (2026). Rituximab versus Ocrelizumab in Newly Diagnosed Relapsing Multiple Sclerosis. New England Journal of Medicine. ISSN 0028-4793. 395(1), p. 44–53. doi: 10.1056/nejmoa2600993. Full text in Research Archive Show summary

  BACKGROUND Anti-CD20 monoclonal antibodies are effective for relapsing multiple sclerosis. However, data from head-to-head trials are lacking. METHODS In this phase 3, multicenter, double-blind, noninferiority trial, we randomly assigned adults with newly diagnosed relapsing multiple sclerosis and recent disease activity in a 3:2 ratio to receive rituximab or ocrelizumab every 6 months for 24 months. The primary end point was the absence of new or enlarging lesions on T2-weighted magnetic resonance imaging (MRI) from month 6 to month 24. Noninferiority was defined as a lower limit of the 95% confidence interval for the risk difference (ritux- imab minus ocrelizumab) of greater than or equal to −10 percentage points. Secondary end points included efficacy and safety. RESULTS A total of 218 participants underwent randomization; 216 received treatment (132 assigned to the rituximab group and 84 assigned to the ocrelizumab group). Between months 6 and 24, the estimated probability of having no new or enlarging lesions detected on T2-weighted MRI was 92.2% with rituximab and 94.8% with ocrelizumab, corresponding to a risk difference of –2.6 percentage points (95% confidence interval, –9.4 to 4.3), which met the prespecified noninferiority criterion. Relapse rates, dis- ability outcomes, and cognitive-performance profiles appeared to be similar in the two groups. Infections were more common in the rituximab group than in the ocreliz- umab group (in 82% vs. 69% of participants), although the percentage of participants with serious adverse events was similar in the two groups (8% and 7%, respectively). CONCLUSIONS In participants with newly diagnosed relapsing multiple sclerosis and recent disease activity, rituximab was noninferior to ocrelizumab in suppressing disease activity as detected by MRI from 6 to 24 months, with a similar incidence of serious adverse events.

• Colman, Jordan; Pontillo, Giuseppe; Goodkin, Olivia; Foster, Michael A.; Mahmoudi, Nima & Wattjes, Mike P. [Show all 47 contributors for this article] (2026). Brain Age Estimation on T2-FLAIR Scans for Application to Multiple Sclerosis. Human Brain Mapping. ISSN 1065-9471. 47(5). doi: 10.1002/hbm.70425. Full text in Research Archive
• Rasmussen, Tilde Harridsleff; Schikora-Rustad, Stine; Lorentzen, Åslaug Rudjord; Tran, Trung; Øverås, Mathias Herstad & Myhr, Kjell-Morten [Show all 22 contributors for this article] (2026). Low risk of severe COVID-19 in vaccinated people with multiple sclerosis: a nationwide Norwegian study. BMJ Neurology Open. 8(1). doi: 10.1136/bmjno-2026-001556. Full text in Research Archive Show summary

  Background: We aimed to assess antibody responses and COVID-19 outcomes after vaccination in people with multiple sclerosis (pwMS) receiving disease-modifying therapies. Methods: NevroVAX is a Norwegian multicentre cohort study including 3559 pwMS and 449 healthy controls (HCs) who received at least one dose of BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna) or ChAdOx1 (AstraZeneca/Oxford) between January 2021 and December 2022. Data from records, registries, questionnaires and blood samples collected June 2021–November 2023 were analysed. Primary outcomes were humoral immune responses assessed by seroconversion (anti-spike and anti-receptor-binding domain (RBD) IgG ≥5 binding antibody units/mL). Secondary outcomes included quantitative anti-RBD IgG levels, breakthrough SARS-CoV-2 infection, COVID-19-related hospitalisation and death. Associations with breakthrough infection were evaluated using multivariable logistic regression. Results: Among 3559 pwMS, 1201 received anti-CD20 monoclonal antibodies and 324 sphingosine-1-phosphate receptor (S1PR) modulators. After three vaccine doses, seroconversion was observed in 43.0% of anti-CD20-treated patients and 48.4% of S1PR-treated patients. In multivariable analysis, seroconversion was associated with lower risk of breakthrough infection (OR 0.67, 95% CI 0.58 to 0.78). During follow-up, 58 pwMS (1.6%) were hospitalised for COVID-19; 4 (0.1%) required non-invasive ventilatory support, no patients required invasive ventilation and no deaths occurred. Conclusions: Humoral vaccine responses were impaired in pwMS receiving anti-CD20 or S1PR therapies, but severe COVID-19 was rare. These findings support continued vaccination programmes and tailored protective measures for immunomodulated populations.

• Breedt, Lucas C.; Pontillo, Giuseppe; Santos, Fernando A.N.; Vriend, Chris; Prados, Ferran & Wink, Alle Meije [Show all 38 contributors for this article] (2026). Structure–function multilayer network integration and cognition in multiple sclerosis. Network Neuroscience. doi: 10.1162/NETN.a.545. Full text in Research Archive
• Høgestøl, Einar August; Brustad, Åge Winje; Celius, Elisabeth Gulowsen; Meling, Martine; Berg-Hansen, Pål & Kro, Grete Anette Birkeland [Show all 13 contributors for this article] (2026). Serum drug levels and JCV assay discrepancies after switching from originator to biosimilar natalizumab. BMJ Neurology Open. 8(1). doi: 10.1136/bmjno-2025-001477. Full text in Research Archive
• Helland, Gisle Berg; Ihle-Hansen, Håkon; Aamodt, Anne Hege; Leonardsen, Esten Høyland; Kaufmann, Tobias Herbert & Enriquez, Brian Anthony [Show all 13 contributors for this article] (2026). Brain age trajectories and cognition after stroke in two longitudinal cohorts. Brain Communications. 8(1). doi: 10.1093/braincomms/fcaf509. Full text in Research Archive Show summary

  Brain age is a promising neuroimaging biomarker, reflecting biological aging, but long-term trajectories and predictive value for cognitive outcomes post-stroke remains unclear. This study aimed to characterize brain aging trajectories over 8 years following a first-ever stroke and to evaluate the predictive value of brain age estimates for long-term cognitive outcomes. We analysed data from working-age (&lt;65 years) ischaemic stroke patients with small- and medium-sized strokes (lesion volumes &lt;70 ml), using two longitudinal stroke cohorts. T1-weighted MRI was acquired in the acute phase and at multiple time points up to 8 years post-stroke. Montreal cognitive assessment (MoCA) was assessed at follow-up sessions. Brain age was estimated using a state-of-the-art deep learning model. Brain-predicted age difference (Brain-PAD) was calculated as estimated brain age minus chronological age and corrected by regressing on age, age² and sex. Linear mixed-effects models examined Brain-PAD over multiple time points (whole-brain, ipsilesional and contralesional). Normalized brain volume was derived from FreeSurfer and included in the whole-brain analysis. Linear regression models evaluated whether brain age was associated with cognitive performance (MoCA) at long-term follow-up. We included 120 patients [n = 50 (42%) female, mean ± SD age at discharge was 54.9 ± 9 and National Institutes of Health Stroke Scale was 3.7 ± 6.4], with a mean follow-up of 3.4 ± 2.5 years. The mean MoCA score at follow-up was 24.7 ± 3.7. Brain-PAD increased significantly over time in the whole-brain analysis (β = 0.6/year, P &lt; 0.01), indicating 60% acceleration in brain aging after stroke, with the association remaining significant after adjusting for normalized brain volume (β = 0.5/year, P &lt; 0.01). Accelerated brain aging was observed in the ipsilesional hemisphere (β = 0.7/year, P &lt; 0.01), but not the contralesional hemisphere (β = 0.3/year, P = 0.12). Higher brain age in the acute phase of stroke predicted lower MoCA scores at follow-up (β = −0.12, P &lt; 0.05), whereas chronological age was not a significant predictor (P = 0.12). The association between brain age estimations and cognitive performance remained significant after adjusting for age, sex and education (β = −0.42, P &lt; 0.01). In this longitudinal study, we found accelerated brain aging following stroke. Furthermore, brain age was associated with cognitive outcomes several years later, highlighting its potential as an early biomarker for long-term cognitive prognosis.

• Skattebøl, Lars; Nygaard, Gro Owren; Leonardsen, Esten Høyland; Kaufmann, Tobias Herbert; Moridi, Thomas & Stawiarz, Leszek [Show all 23 contributors for this article] (2025). Brain age in multiple sclerosis: a study with deep learning and traditional machine learning. Brain Communications. 7(3). doi: 10.1093/braincomms/fcaf152. Full text in Research Archive Show summary

  ‘Brain age’ is a numerical estimate of the biological age of the brain and an overall effort to measure neurodegeneration, regardless of disease type. In multiple sclerosis, accelerated brain ageing has been linked to disability accrual. Artificial intelligence has emerged as a promising tool for the assessment and quantification of the impact of neurodegenerative diseases. Despite the existence of numerous AI models, there is a noticeable lack of comparative imaging data for traditional machine learning versus deep learning in conditions such as multiple sclerosis. A retrospective observational study was initiated to analyse clinical and MRI data (4584 MRIs) from various scanners in a large longitudinal cohort (n = 1516) of people with multiple sclerosis collected from two institutions (Karolinska Institute and Oslo University Hospital) using a uniform data post-processing pipeline. We conducted a comparative assessment of brain age using a deep learning simple fully convolutional network and a well-established traditional machine learning model. This study was primarily aimed to validate the deep learning brain age model in multiple sclerosis. The correlation between estimated brain age and chronological age was stronger for the deep learning estimates (r = 0.90, P &lt; 0.001) than the traditional machine learning estimates (r = 0.75, P &lt; 0.001). An increase in brain age was significantly associated with higher expanded disability status scale scores (traditional machine learning: t = 5.3, P &lt; 0.001; deep learning: t = 3.7, P &lt; 0.001) and longer disease duration (traditional machine learning: t = 6.5, P &lt; 0.001; deep learning: t = 5.8, P &lt; 0.001). No significant inter-model difference in clinical correlation or effect measure was found, but significant differences for traditional machine learning-derived brain age estimates were found between several scanners. Our study suggests that the deep learning-derived brain age is significantly associated with clinical disability, performed equally well to the traditional machine learning-derived brain age measures, and may counteract scanner variability.

• Skattebøl, Lars; Lundby, Rigmor; Øverås, Mathias H.; Sowa, Piotr; Celius, Elisabeth G. & Harbo, Hanne-Cathrin Flinstad [Show all 9 contributors for this article] (2025). Quantitative susceptibility mapping of paramagnetic rim lesions in early multiple sclerosis: A cross-sectional study of brain age and disability. Neuroimage: Reports. 5(3). doi: 10.1016/j.ynirp.2025.100277. Full text in Research Archive Show summary

  Objective Chronic inflammation in multiple sclerosis is associated with neurodegeneration and progressive functional decline. Quantitative susceptibility mapping (QSM) is an MRI technique that visualizes paramagnetic rim lesions (PRLs), which are indicative of chronic inflammation. In this cross-sectional study, we explored the prevalence of PRLs in multiple sclerosis and assessed their associations with clinical disability, tissue magnetic susceptibility, and brain age predictions. Methods All participants from the NOR-MS study with a 3T MRI T1-weighted magnetization-prepared rapid gradient echo and QSM were included (n = 42, mean age = 39.4 years, 59.5 % females, median disease duration = 0.1 years [IQR: 0.02–5.42]). The presence and characteristics of PRLs were evaluated by an experienced neuroradiologist. PRL and non-PRL susceptibility were categorized into separate groups through manual segmentation and voxel-wise analysis. We utilized a validated simple fully convolutional network and T1-weighted images to estimate brain age, and its derivative – brain age gap (BAG). Clinical disability was assessed using the Expanded Disability Status Scale (EDSS). Results PRLs were identified in 14.3 % (n = 6) of study participants, and correlated with EDSS (rho = 0.86, p = 0.03). The mean paramagnetic rim susceptibility was 25.6 ± 14.1 parts per billion and correlated with EDSS (rho = 0.93, p = 0.008). EDSS was significantly higher in the PRL-positive group (median EDSS 2.25 vs 1.5, p = 0.02). The PRL-positive group exhibited a mean 5.6-year higher BAG (p = 0.01) than the PRL-negative group. Conclusion PRLs were present in a significant subset of study participants with MS and were associated with greater disability and higher BAG.

• Aamodt, Anne Hege; Ueland, Thor; Boldingh, Marion Ingeborg; Bezgal, Burcu; Argren, Maria Bengtson Argren & Dunne, Cecilia Adele [Show all 29 contributors for this article] (2025). Altered amyloid plasma profile in patients with disabling headaches after SARS-CoV-2 infection and vaccination. BMJ Neurology Open. 7(2). doi: 10.1136/bmjno-2024-001013. Full text in Research Archive Show summary

  Background and objectives Persistent headache has emerged as a symptom following acute COVID-19 and, to a lesser extent, after SARS-CoV-2 vaccination. However, the underlying mechanisms remain poorly understood. This study aimed to evaluate plasma levels of amyloid-related biomarkers in patients experiencing persistent headaches after COVID-19 or SARS-CoV-2 vaccination. Methods In this prospective observational cohort, patients presenting with severe headache as the dominating symptom after COVID-19 (n=29) or SARS-CoV-2 vaccination (n=31) had neurological assessments with reassessments after 6 months. Plasma levels of amyloid precursor protein (APP), pregnancy zone protein (PZP), cathepsin L1 (CTSL) and serum Amyloid A (SAA1) were measured using ELISA and compared with levels in healthy controls (n=16). Results We found a strong and persistent upregulation of APP in patients with headache after COVID-19 as compared with the two other groups. Notably, APP levels remained elevated at both inclusion and after 6 months in individuals with accompanying cognitive symptoms. In contrast, PZP levels were increased in patients with headache after SARS-CoV-2 vaccination at both time points relative to healthy controls. CTSL was only elevated in the post-COVID-19 at baseline, whereas SAA1 showed levels comparable across all groups. Conclusion Altered plasma levels of soluble markers, potentially reflecting changes in amyloid processing, were found in patients with persistent headache following SARS-CoV-2 vaccine, particularly in those with persistent headache after COVID-19. In the latter group, we also found some association with cognitive symptoms. Trial registration numbers NCT04576351 and NCT05235776 .

• Korbmacher, Max; Lie, Ingrid Anne; Wesnes, Kristin; Westman, Eric; Espeseth, Thomas & Specht, Karsten [Show all 12 contributors for this article] (2025). Multimodal predictors of disability progression and processing speed decline in relapsing–remitting multiple sclerosis. Scientific Reports. 15(1), p. 1–13. doi: 10.1038/s41598-025-17894-2. Full text in Research Archive Show summary

  The underlying mechanisms for neurodegeneration in multiple sclerosis are complex and incompletely understood. Multivariate and multimodal investigations integrating demographic, clinical, multi-omics, and neuroimaging data provide opportunities for nuanced analyses, aimed to define disease progression markers. We used data from a 12-year longitudinal multicenter cohort of 88 people with multiple sclerosis, to test the predictive value of multi-omics, T 1 -weighted MRI (lesion count and volume, lesion-filled brain-predicted age), clinical examinations, self-reports on quality of life, demographics, and general health-related variables for future functional and cognitive disability. Systematic increases in Expanded Disability Status Scale (EDSS) scores were used to stratify a progressive disability group (PDG) from relatively stabile disability. A processing speed decline group (PSDG) was defined by a ≥ 20% decrease of Paced Auditory Serial Addition Test score from previous timepoints. We used a multiverse approach to identify which baseline variables were most predictive for PDG and PSDG memberships, considering multiple analysis paths. Future disability (median area under the curve: mAUC = 0.83 ± 0.04, median Brier score: mBS = 0.16 ± 0.02) and the loss of processing speed (mAUC = 0.89 ± 0.05, mBS = 0.10 ± 0.03) could be successfully classified across models. Varibles significantly (median p-values < 0.05) predicting stable disability included receiving disease modifying treatment at 12-year follow-up (median Odds Ratio: mOR PDG = 7.44 ± 4.07, p median = 0.013, proportion of the OR’s directionality: PORSD = 100%), lower baseline EDSS for each 1-unit (mOR PDG = 0.25 ± 0.11, p median = 0.013, PORSD = 100%), and counter-intuitively every year increase in baseline age (mOR PDG = 1.12 ± 0.04, p median = 0.020, PORSD = 100%), and lower vitamin A per 1 umol/L (mOR PDG = 0.10 ± 0.05, p median = 0.016, PORSD = 99.7%) and D levels per 1 nmol/L (mOR PDG = 0.95 ± 0.02, p median = 0.025, PORSD = 100%). Variables significantly predicting stable processing speed were receiving disease modifying treatment at 12-year follow-up (mOR PSDG = 0.10 ± 0.08, p median = 0.013, PORSD = 100%) and baseline PASAT score (mOR PSDG = 0.86 ± 0.03, p median = 0.005, PORSD = 99.73%). These findings were supported by an additional simulation study. Concordant with the literature, disease modifying treatments influence disability progression, as well as a higher EDSS and PASAT scores at measurement start. Experimental and counterintuitive findings on vitamin A and D levels require further validation. The large variability across models suggests a strong influence of analytic flexibility, such as the selection of covariates.

• Furevik, Liv; Lapina, Oksana; Lindland, Elisabeth Margrete Stokke; Høgestøl, Einar August; Geier, Oliver Marcel & Devik, Kristina [Show all 22 contributors for this article] (2025). Brain MRI findings in patients with post COVID-19 condition: frequency and longitudinal changes in a nationwide cohort study. Frontiers in Neurology. 16, p. 1–9. doi: 10.3389/fneur.2025.1662263. Full text in Research Archive Show summary

  Background Prolonged neurological symptoms following COVID-19 are common, yet few longitudinal studies describe brain MRI findings in this patient group. The use of contrast enhanced sequences is particularly lacking. We address this knowledge gap by reporting the frequency and longitudinal changes in brain MRI findings among patients with post COVID-19 condition exhibiting neurological symptoms. Methods This prospective multicenter study included 140 adult patients referred for persistent neurological symptoms following COVID-19. Brain MRI was performed at both 6 and 12 months after infection onset, reporting white matter hyperintensities, cerebral microbleeds, and additional pathological findings including contrast enhancement. White matter hyperintensities were compared with a healthy control group. Results The prevalence of white matter hyperintensities was comparable to healthy controls, and microbleeds were found at rates comparable to population studies, with longitudinal changes being infrequent. Lesions consistent with inflammation or demyelination were present in 4% (5/120) of patients at 6 months. Cranial nerve enhancement was found in 7% (7/94) of patients, persisting up to 12 months, predominantly affecting the oculomotor nerve. However, enhancement occurred without clinically detected ocular muscle paresis. Conclusion Our findings indicate that brain MRI primarily serves to exclude differential diagnoses in post COVID-19 condition, with limited clinical benefit of repeated imaging in the absence of new symptoms. However, signs of long-term inflammatory processes can be observed, and detection is improved by contrast enhanced sequences.

• Høgestøl, Einar August; Rinker, Daniel Allen; Maximov, Ivan; Sowa, Piotr; Celius, Elisabeth Gulowsen & Hope, Tuva Roaldsdatter [Show all 26 contributors for this article] (2025). A cross-sectional multicentre study of multishell diffusion MRI in multiple sclerosis. Multiple Sclerosis and Related Disorders. ISSN 2211-0348. 98. doi: 10.1016/j.msard.2025.106435. Full text in Research Archive Show summary

  Background and objectives White matter (WM) microstructural properties from advanced multishell diffusion MRI (dMRI) have been linked to clinical disability in multiple sclerosis (MS). This multicentre study used multishell dMRI to compute WM metrics and test for differences between people with MS (pwMS) and healthy controls (HCs). Methods We included multishell dMRI data from 251 pwMS or clinically isolated syndrome (CIS) (mean age 40.7 years, 72.4 % women, 88.8 % relapsing remitting MS) at six MAGNIMS centres and 543 HCs. Eleven scalar metric maps were estimated from multishell dMRI sequences, based on diffusion tensor imaging (DTI) and restriction spectrum imaging (RSI). The maps were analysed using tract-based spatial statistics (TBSS). The diffusion output was submitted to paired sampled t-tests to test for case-control differences and linear regression models to test for associations with Expanded Disability Status Scale (EDSS) scores, while accounting for confounders. In a sub-sample from Oslo, we tested for correlations between EDSS and dMRI metrics within WM lesions. Results Significant group differences were found in nine out of eleven dMRI metrics. Linear regression models revealed significant correlations between EDSS and fractional anisotropy (FA) fast (β=-4.54, p = 0.01) and apparent diffusion coefficient (ADC) fast (β=10.92, p = 8.7 × 10−3). Conclusions Diffusion MRI based on clinically feasible multishell sequences uncovers WM group differences between pwMS and HCs, but only a selection of the advanced multishell parameters were sensitive to disability, and no statistically significant correlations with disability remained after Bonferroni correction.

• Rød, Brit Ellen; Høgestøl, Einar August; Torkildsen, Øivind; Bjørnevik, Kjetil; Gran, Jon Michael & Øverås, Mathias Herstad [Show all 10 contributors for this article] (2025). Comparative effectiveness of rituximab and cladribine in relapsing–remitting multiple sclerosis: A target trial emulation. Multiple Sclerosis. ISSN 1352-4585. 31(8), p. 975–984. doi: 10.1177/13524585251342727. Full text in Research Archive Show summary

  Background: Head-to-head comparisons of high-efficacy therapies for relapsing–remitting multiple sclerosis (RRMS) are lacking. We conducted a target trial emulation to compare the long-term effectiveness of rituximab and cladribine. Methods: We estimated the effect of initiating treatment with rituximab versus cladribine using observational data from the Norwegian MS Registry and Biobank at two university hospitals with different treatment strategies. Cumulative incidence and risk differences (RDs) were estimated using weighted Kaplan-Meier estimators, adjusting for baseline covariates. The primary outcome was magnetic resonance imaging (MRI) disease activity, with secondary outcomes including relapses and safety. Results: The study included 285 patients, 159 receiving rituximab and 126 cladribine, with a median follow-up of 4.5 years (interquartile range (IQR): 4.2–4.7). The 4-year risk of new MRI disease activity was 17% (95% confidence interval (CI): 11–23) for rituximab-treated patients and 57% (95% CI: 44–66) for cladribine-treated patients, yielding an RD of 40 percentage-points (95% CI: 28–50). The 4-year RD for relapse was 12 percentage-points (95% CI: 4–19). The incidence of hospitalizations related to potential adverse events was 6.0 per 100 person-years for rituximab and 4 per 100 person-years for cladribine. Conclusion: These findings suggest that rituximab has superior effectiveness compared to cladribine during a median follow-up of 4.5 years.

• Pontillo, Giuseppe; Prados, Ferran; Wink, Alle Meije; Kanber, Baris; Bisecco, Alvino & Broeders, Tommy A. A. [Show all 43 contributors for this article] (2025). More Than the Sum of Its Parts: Disrupted Core Periphery of Multiplex Brain Networks in Multiple Sclerosis. Human Brain Mapping. ISSN 1065-9471. 46(1). doi: 10.1002/hbm.70107. Full text in Research Archive
• Fleischer, Vinzenz; Gonzalez-Escamilla, Gabriel; Pareto, Deborah; Rovira, Alex; Sastre-Garriga, Jaume & Sowa, Piotr [Show all 23 contributors for this article] (2024). Prognostic value of single-subject grey matter networks in early multiple sclerosis. Brain. ISSN 0006-8950. 147(1), p. 135–146. doi: 10.1093/brain/awad288. Full text in Research Archive Show summary

  The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict 5-year Expanded Disability Status Scale (EDSS) progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from MRI, outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for 5 years (mean follow-up = 5.0 ± 0.6 years). EDSS was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again 1 year after baseline. Grey matter atrophy over 1 year and white matter lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on grey matter atrophy measures derived from a statistical parameter mapping-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for grey matter atrophy and white matter lesion load, and the network measures and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over 5 years through lower values for network degree [H(2) = 30.0, P < 0.001] and global efficiency [H(2) = 31.3, P < 0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups [H(2) = 1.5, P = 0.474]. Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of grey matter atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over grey matter atrophy and white matter lesion load in predicting EDSS worsening (all P-values < 0.05). Our findings provide evidence that grey matter network reorganization over 1 year discloses relevant information about subsequent clinical worsening in RRMS. Early grey matter restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors.

• Nersesjan, Vardan; Boldingh, Marion Ingeborg; Paulsen, Else Quist; Argren, Maria Bengtson Argren; Høgestøl, Einar August & Aamodt, Anne Hege [Show all 11 contributors for this article] (2024). Antibodies against SARS-CoV-2 spike protein in the cerebrospinal fluid of COVID-19 patients and vaccinated controls: a multicentre study. Journal of Neurology. ISSN 0340-5354. 272, p. 1–14. doi: 10.1007/s00415-024-12769-4. Full text in Research Archive Show summary

  Introduction SARS-CoV-2 antibodies in the cerebrospinal fluid (CSF) of COVID-19 patients possibly reflect blood-cerebrospinal fluid barrier (BCB) disruption due to systemic inflammation. However, some studies indicate that CSF antibodies signal a neurotropic infection. Currently, larger studies are needed to clarify this, and it is unknown if CSF antibodies appear solely after infection or also after COVID-19 vaccination. Therefore, we aimed to investigate the CSF dynamics of SARS-CoV-2 antibodies in a multicenter study of COVID-19 patients and vaccinated controls. Methods A cohort study of Danish and Norwegian COVID-19 patients and controls investigated with a lumbar puncture (April 2020–December 2022). Serum and CSF were analysed locally for routine investigations, and centrally at Statens Serum Institut (Danish governmental public health institute) for SARS-CoV-2 IgG antibodies against the spike protein using the Euroimmun (quantitative) and Wantai (qualitative) assays. Primary outcome was the quantity of CSF SARS-CoV-2 antibodies post-COVID versus post-vaccination. Secondary outcomes included regression models examining the relationship between CSF antibodies and serum levels, albumin ratio, CSF pleocytosis, COVID-19 severity, and temporal antibody dynamics. Results We included 124 individuals (Mean [SD] age 47.2 [16.6]; 59.7% males surviving COVID-19 and controls. Of these, 86 had paired CSF-serum testing. Antibody-index calculations did not support a SARS-CoV-2 brain infection. Multi-variate regression revealed that CSF SARS-CoV-2 antibodies were most strongly influenced by serum antibody levels and BCB permeability, as measured by increasing albumin ratio. CSF antibody levels displayed a dose–response relationship (p < 0.0001) influenced by preceding vaccinations or infections. CSF antibody levels (median [IQR]) were highest among those both previously infected and vaccinated, 100.0 [25.0–174.0], and those vaccinated without prior infection, 85.0 [12.0–142.0], and lowest among previously infected individuals without preceding vaccination, 5.9 [2.7–55.1], (p = 0.003). SARS-CoV-2 antibodies in CSF were also detected via qualitative assays in the COVID-19 (46.8%) and vaccinated (78.6%) groups, p = 0.03. Conclusion SARS-CoV-2 antibodies detected in CSF can be derived following both infection and vaccination for COVID-19. CSF antibody levels increase in a dose–response relationship with the number of prior infections and vaccinations and are most strongly influenced by serum antibody levels and BCB permeability. These findings stress the importance of carefully interpreting CSF antibody results when assessing neurological complications following infections not categorized as neurotropic.

• Helland, Gisle Berg; Beyer, Mona K.; Enriquez, Brian Anthony; Ihle-Hansen, Hege Beate; Ihle-Hansen, Håkon & Andersson, Stein [Show all 13 contributors for this article] (2024). Lesion Volume as a Predictor for Return to Work After Endovascular Treatment: A 4‐Year Prospective Cohort Study. Stroke: Vascular and Interventional Neurology. 4(6). doi: 10.1161/SVIN.124.001494. Full text in Research Archive Show summary

  Background There are no known objective biomarkers for predicting return to work (RTW) in ischemic stroke survivors. This study aims to explore the predictive utility and defines a cutoff value of lesion volume on RTW after endovascular treatment. Methods We included patients aged <65 years undergoing endovascular treatment at Oslo University Hospital between January 2017 and May 2019. Employment status was obtained at both baseline and a 4‐year follow‐up. Stroke lesion volumes were segmented using magnetic resonance imaging scans 24 hours after endovascular treatment. Logistic regression models were conducted to assess the impact of lesion volume on RTW status at follow‐up, adjusted for patients’ characteristics, stroke‐related factors, and treatment. We calculated the receiver operating characteristic curve to determine the optimal lesion volume cutoff. Machine learning regression models were used to assess the predictive abilities of baseline clinical and imaging variables for RTW. Results Of the 109 individuals treated, 81 (74%) were employed at baseline. Among these, 60 completed 4‐year follow‐up with magnetic resonance imaging available for stroke lesion segmentation and were included in the analyses. Mean age at stroke onset was 51.8 years (range, 23.5–64.9 years), and 50% were female. Median lesion volume was 18 mL (interquartile ranges, 45—47 mL). After 4 years, 34 (57%) had successfully RTW. The odds for not RTW increased by 5% for every 1 mL increase in lesion volume (adjusted odds ratio, 1.05 [95% CI, 1.02–1.11]; P = 0.02). A lesion volume cutoff value of 29 cm3 yielded a sensitivity of 0.91 and specificity of 0.65 for predicting RTW. Notably, the most influential feature in the machine learning model for predicting RTW was lesion volume. Conclusion Lesion volume was the most robust predictor of RTW 4 years after endovascular treatment. Our findings suggest that a cutoff of 29 cm3 is suitable to distinguish between those with high and low chance of RTW.

• Pontillo, Giuseppe; Prados, Ferran; Colman, Jordan; Kanber, Baris; Abdel-Mannan, Omar & Al-Araji, Sarmad [Show all 62 contributors for this article] (2024). Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap. Neurology. ISSN 0028-3878. 103(10). doi: 10.1212/WNL.0000000000209976. Full text in Research Archive Show summary

  Background and Objectives Disentangling brain aging from disease-related neurodegeneration in patients with multiple sclerosis (PwMS) is increasingly topical. The brain-age paradigm offers a window into this problem but may miss disease-specific effects. In this study, we investigated whether a disease-specific model might complement the brain-age gap (BAG) by capturing aspects unique to MS. Methods In this retrospective study, we collected 3D T1-weighted brain MRI scans of PwMS to build (1) a cross-sectional multicentric cohort for age and disease duration (DD) modeling and (2) a longitudinal single-center cohort of patients with early MS as a clinical use case. We trained and evaluated a 3D DenseNet architecture to predict DD from minimally preprocessed images while age predictions were obtained with the DeepBrainNet model. The brain-predicted DD gap (the difference between predicted and actual duration) was proposed as a DD-adjusted global measure of MS-specific brain damage. Model predictions were scrutinized to assess the influence of lesions and brain volumes while the DD gap was biologically and clinically validated within a linear model framework assessing its relationship with BAG and physical disability measured with the Expanded Disability Status Scale (EDSS). Results We gathered MRI scans of 4,392 PwMS (69.7% female, age: 42.8 ± 10.6 years, DD: 11.4 ± 9.3 years) from 15 centers while the early MS cohort included 749 sessions from 252 patients (64.7% female, age: 34.5 ± 8.3 years, DD: 0.7 ± 1.2 years). Our model predicted DD better than chance (mean absolute error = 5.63 years, R2 = 0.34) and was nearly orthogonal to the brain-age model (correlation between DD and BAGs: r = 0.06 [0.00–0.13], p = 0.07). Predictions were influenced by distributed variations in brain volume and, unlike brain-predicted age, were sensitive to MS lesions (difference between unfilled and filled scans: 0.55 years [0.51–0.59], p < 0.001). DD gap significantly explained EDSS changes (B = 0.060 [0.038–0.082], p < 0.001), adding to BAG (ΔR2 = 0.012, p < 0.001). Longitudinally, increasing DD gap was associated with greater annualized EDSS change (r = 0.50 [0.39–0.60], p < 0.001), with an incremental contribution in explaining disability worsening compared with changes in BAG alone (ΔR2 = 0.064, p < 0.001). Discussion The brain-predicted DD gap is sensitive to MS-related lesions and brain atrophy, adds to the brain-age paradigm in explaining physical disability both cross-sectionally and longitudinally, and may be used as an MS-specific biomarker of disease severity and progression.

• Kennedy, Keith E.; Rosbo, Nicole Kerlero de; Uccelli, Antonio; Cellerino, Maria; Ivaldi, Federico & Contini, Paola [Show all 37 contributors for this article] (2024). Multiscale networks in multiple sclerosis. PLoS Computational Biology. ISSN 1553-734X. 20(2). doi: 10.1371/journal.pcbi.1010980. Full text in Research Archive Show summary

  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.

• Martí-Juan, Gerard; Sastre-Garriga, Jaume; Vidal-Jordana, Angela; Martinez-Heras, Eloy; Llufriu, Sara & Groppa, Sergiu [Show all 21 contributors for this article] (2024). Conservation of structural brain connectivity in people with multiple sclerosis. Network Neuroscience. 8(4), p. 1545–1562. doi: 10.1162/netn_a_00404. Full text in Research Archive
• Martí-Juan, Gerard; Sastre-Garriga, Jaume; Martinez-Heras, Eloy; Vidal-Jordana, Angela; Llufriu, Sara & Groppa, Sergiu [Show all 20 contributors for this article] (2023). Using The Virtual Brain to study the relationship between structural and functional connectivity in patients with multiple sclerosis: a multicenter study. Cerebral Cortex. ISSN 1047-3211. 33(12), p. 7322–7334. doi: 10.1093/cercor/bhad041. Full text in Research Archive
• Wolf, Asia-Sophia Fumika Michaela; Ravussin, Anthony; König, Marton; Øverås, Mathias Herstad; Solum, Guri & Kjønstad, Ingrid Fadum [Show all 18 contributors for this article] (2023). T cell responses to SARS-CoV-2 vaccination differ by disease-modifying therapy for multiple sclerosis. JCI Insight. 8(12), p. 1–14. doi: 10.1172/jci.insight.165111. Full text in Research Archive Show summary

  Immune responses in people with multiple sclerosis (pwMS) receiving disease-modifying therapies (DMTs) have been of significant interest throughout the COVID-19 pandemic. Lymphocyte-targeting immunotherapies, including anti-CD20 treatments and sphingosine-1-phosphate receptor (S1PR) modulators, attenuate Ab responses after vaccination. Evaluation of cellular responses after vaccination, therefore, is of particular importance in these populations. In this study, we used flow cytometry to analyze CD4 and CD8 T cell functional responses to SARS-CoV-2 spike peptides in healthy control study participants and pwMS receiving 5 different DMTs. Although pwMS receiving rituximab and fingolimod therapies had low Ab responses after both 2 and 3 vaccine doses, T cell responses in pwMS taking rituximab were preserved after a third vaccination, even when an additional dose of rituximab was administered between vaccine doses 2 and 3. PwMS taking fingolimod had low detectable T cell responses in peripheral blood. CD4 and CD8 T cell responses to SARS-CoV-2 variants of concern Delta and Omicron were lower than to the ancestral Wuhan-Hu-1 variant. Our results indicate the importance of assessing both cellular and humoral responses after vaccination and suggest that, even in the absence of robust Ab responses, vaccination can generate immune responses in pwMS.

• Brune-Ingebretsen, Synne; Høgestøl, Einar August; Rosbo, Nicole Kerlero de; Berg-Hansen, Pål; Brunborg, Cathrine & Blennow, Kaj [Show all 12 contributors for this article] (2023). Immune cell subpopulations and serum neurofilament light chain are associated with increased risk of disease worsening in multiple sclerosis. Journal of Neuroimmunology. ISSN 0165-5728. 382. doi: 10.1016/j.jneuroim.2023.578175. Full text in Research Archive Show summary

  Changes is lymphocyte subpopulations in peripheral blood have been proposed as biomarkers for evaluation of disease activity in multiple sclerosis (MS). Serum neurofilament light chain (sNfL) is a biomarker reflecting neuro-axonal injury in MS that could be used to monitor disease activity, response to drugs and to prognosticate disease course. Here we show a moderate correlation between sNfL and lymphocyte cell subpopulations, and our data furthermore suggest that sNfL and specific immune cell subpopulations together could predict future disease worsening in MS.

• Andorra, Magi; Freire, Ana; Zubizarreta, Irati; Rosbo, Nicole Kerlero de; Bos, Steffan Daniel & Rinas, Melanie [Show all 40 contributors for this article] (2023). Predicting disease severity in multiple sclerosis using multimodal data and machine learning. Journal of Neurology. ISSN 0340-5354. doi: 10.1007/s00415-023-12132-z. Full text in Research Archive Show summary

  Background Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity. Methods We have analysed a prospective multi-centric cohort of 322 MS patients and 98 healthy controls from four MS centres, collecting disability scales at baseline and 2 years later. Imaging data included brain MRI and optical coherence tomography, and omics included genotyping, cytomics and phosphoproteomic data from peripheral blood mononuclear cells. Predictors of clinical outcomes were searched using Random Forest algorithms. Assessment of the algorithm performance was conducted in an independent prospective cohort of 271 MS patients from a single centre. Results We found algorithms for predicting confirmed disability accumulation for the different scales, no evidence of disease activity (NEDA), onset of immunotherapy and the escalation from low- to high-efficacy therapy with intermediate to high- accuracy. This accuracy was achieved for most of the predictors using clinical data alone or in combination with imaging data. Still, in some cases, the addition of omics data slightly increased algorithm performance. Accuracies were comparable in both cohorts. Conclusion Combining clinical, imaging and omics data with machine learning helps identify MS patients at risk of dis- ability worsening.

• Brorson, Ina Skaara; Eriksson, Anna Maria; Høgestøl, Einar August; Leikfoss, Ingvild Sørum; Harbo, Hanne-Cathrin Flinstad & Berge, Tone [Show all 8 contributors for this article] (2022). Global DNA methylation changes in treated and untreated MS patients measured over time. Journal of Neuroimmunology. ISSN 0165-5728. 364. doi: 10.1016/j.jneuroim.2022.577808. Full text in Research Archive Show summary

  Multiple sclerosis (MS) is an autoimmune, neurological disease. We investigated genome-wide DNA methylation profiles of CD4+ and CD8+ T cells from MS patients and healthy controls at baseline and a follow-up visit. Patients were all treatment-naïve at baseline, and either on treatment or remained untreated at the follow-up visit. MS patients show more changes in their T cell DNA methylation profiles as compared to healthy controls over time, with the most pronounced differences observed in the untreated MS patients. These findings underline the potential of DNA methylation as biomarkers in MS.

• Rise, Henning Hoel; Brune, Synne; Chien, Claudia; Berge, Tone; Bos, Steffan Daniel & Andorrà, Magí [Show all 23 contributors for this article] (2022). Brain disconnectome mapping derived from white matter lesions and serum neurofilament light levels in multiple sclerosis: A longitudinal multicenter study. NeuroImage: Clinical. 35, p. 1–11. doi: 10.1016/j.nicl.2022.103099. Full text in Research Archive Show summary

  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.

• Brune, Synne; Høgestøl, Einar August; Benavent, Sigrid Aune de Rodez; Berg-Hansen, Pål; Beyer, Mona K. & Leikfoss, Ingvild Sørum [Show all 23 contributors for this article] (2022). Serum neurofilament light chain concentration predicts disease worsening in multiple sclerosis. Multiple Sclerosis. ISSN 1352-4585. 28(12), p. 1859–1870. doi: 10.1177/13524585221097296. Full text in Research Archive Show summary

  Background: Serum neurofilament light (sNfL) chain is a promising biomarker reflecting neuro-axonal injury in multiple sclerosis (MS). However, the ability of sNfL to predict outcomes in real-world MS cohorts requires further validation. Objective: The aim of the study is to investigate the associations of sNfL concentration, magnetic resonance imaging (MRI) and retinal optical coherence tomography (OCT) markers with disease worsening in a longitudinal European multicentre MS cohort. Methods: MS patients ( n = 309) were prospectively enrolled at four centres and re-examined after 2 years ( n = 226). NfL concentration was measured by single molecule array assay in serum. The patients’ phenotypes were thoroughly characterized with clinical examination, retinal OCT and MRI brain scans. The primary outcome was disease worsening at median 2-year follow-up. Results: Patients with high sNfL concentrations (⩾8 pg/mL) at baseline had increased risk of disease worsening at median 2-year follow-up (odds ratio (95% confidence interval) = 2.8 (1.5–5.3), p = 0.001). We found no significant associations of MRI or OCT measures at baseline with risk of disease worsening. Conclusion: Serum NfL concentration was the only factor associated with disease worsening, indicating that sNfL is a useful biomarker in MS that might be relevant in a clinical setting.

• Cappelletti, Chiara; Eriksson, Anna Maria; Brorson, Ina Skaara; Leikfoss, Ingvild Sørum; Kråbøl, Oda Glomstad & Høgestøl, Einar August [Show all 12 contributors for this article] (2022). Quantitative proteomics reveals protein dysregulation during T cell activation in multiple sclerosis patients compared to healthy controls. Clinical Proteomics. ISSN 1542-6416. 19(1), p. 1–17. doi: 10.1186/s12014-022-09361-1. Full text in Research Archive Show summary

  Background Multiple sclerosis (MS) is an autoimmune, neurodegenerative disorder with a strong genetic component that acts in a complex interaction with environmental factors for disease development. CD4+ T cells are pivotal players in MS pathogenesis, where peripherally activated T cells migrate to the central nervous system leading to demyelination and axonal degeneration. Through a proteomic approach, we aim at identifying dysregulated pathways in activated T cells from MS patients as compared to healthy controls. Methods CD4+ T cells were purified from peripheral blood from MS patients and healthy controls by magnetic separation. Cells were left unstimulated or stimulated in vitro through the TCR and costimulatory CD28 receptor for 24 h prior to sampling. Electrospray liquid chromatography-tandem mass spectrometry was used to measure protein abundances. Results Upon T cell activation the abundance of 1801 proteins was changed. Among these proteins, we observed an enrichment of proteins expressed by MS-susceptibility genes. When comparing protein abundances in T cell samples from healthy controls and MS patients, 18 and 33 proteins were differentially expressed in unstimulated and stimulated CD4+ T cells, respectively. Moreover, 353 and 304 proteins were identified as proteins exclusively induced upon T cell activation in healthy controls and MS patients, respectively and dysregulation of the Nur77 pathway was observed only in samples from MS patients. Conclusions Our study highlights the importance of CD4+ T cell activation for MS, as proteins that change in abundance upon T cell activation are enriched for proteins encoded by MS susceptibility genes. The results provide evidence for proteomic disturbances in T cell activation in MS, and pinpoint to dysregulation of the Nur77 pathway, a biological pathway known to limit aberrant effector T cell responses.

• Nes, Dragana; Berg-Hansen, Pål; Benavent, Sigrid Aune de Rodez; Høgestøl, Einar August; Beyer, Mona K. & Rinker, Daniel Allen [Show all 12 contributors for this article] (2022). Exploring Retinal Blood Vessel Diameters as Biomarkers in Multiple Sclerosis. Journal of Clinical Medicine. 11(11). doi: 10.3390/jcm11113109. Full text in Research Archive Show summary

  We aimed to determine whether retinal vessel diameters and retinal oxygen saturation in newly diagnosed patients with multiple sclerosis (pwMS) are different from those of a healthy population. Retinal blood vessel diameters were measured using imaging with a spectrophotometric non-invasive retinal oximeter. Twenty-three newly diagnosed untreated relapsing-remitting MS (RRMS) patients (mean age: 32.2 ± 7.5 years, age range = 18–50 years, 56.5% female) were measured and compared to 23 age- and sex-matched healthy controls (HCs) (mean age: 34.8 ± 8.1 years). Patients with Optic Neuritis were excluded. Retinal venular diameter (143.8 µm versus 157.8 µm: mean; p = 0.0013) and retinal arteriolar diameter (112.6 µm versus 120.6 µm: mean; p = 0.0089) were smaller in pwMS when compared with HCs, respectively. There was no significant difference in the oxygen saturation in retinal venules and arterioles in pwMS (mean: 60.0% and 93.7%; p = 0.5980) compared to HCs (mean: 59.3% and 91.5%; p = 0.8934), respectively. There was a significant difference in the median low contrast visual acuity (2.5% contrast) between the pwMS and the HC groups (p = 0.0143) Retinal arteriolar and venular diameter may have potential as objective biomarkers for MS.

• Leonardsen, Esten Høyland; Peng, Han; Kaufmann, Tobias; Agartz, Ingrid; Andreassen, Ole & Celius, Elisabeth Gulowsen [Show all 19 contributors for this article] (2022). Deep neural networks learn general and clinically relevant representations of the ageing brain. NeuroImage. ISSN 1053-8119. 256. doi: 10.1016/j.neuroimage.2022.119210. Full text in Research Archive Show summary

  The discrepancy between chronological age and the apparent age of the brain based on neuroimaging data — the brain age delta — has emerged as a reliable marker of brain health. With an increasing wealth of data, approaches to tackle heterogeneity in data acquisition are vital. To this end, we compiled raw structural magnetic resonance images into one of the largest and most diverse datasets assembled (n=53542), and trained convolutional neural networks (CNNs) to predict age. We achieved state-of-the-art performance on unseen data from unknown scanners (n=2553), and showed that higher brain age delta is associated with diabetes, alcohol intake and smoking. Using transfer learning, the intermediate representations learned by our model complemented and partly outperformed brain age delta in predicting common brain disorders. Our work shows we can achieve generalizable and biologically plausible brain age predictions using CNNs trained on heterogeneous datasets, and transfer them to clinical use cases.

• Beck, Dani; Lange, Ann-Marie G. de; Pedersen, Mads L.; Alnæs, Dag; Maximov, Ivan & Voldsbekk, Irene [Show all 18 contributors for this article] (2021). Cardiometabolic risk factors associated with brain age and accelerate brain ageing. Human Brain Mapping. ISSN 1065-9471. p. 1–21. doi: 10.1002/hbm.25680. Full text in Research Archive Show summary

  The structure and integrity of the ageing brain is interchangeably linked to physical health, and cardiometabolic risk factors (CMRs) are associated with dementia and other brain disorders. In this mixed cross-sectional and longitudinal study (interval mean = 19.7 months), including 790 healthy individuals (mean age = 46.7 years, 53% women), we investigated CMRs and health indicators including anthropometric measures, lifestyle factors, and blood biomarkers in relation to brain structure using MRI-based morphometry and diffusion tensor imaging (DTI). We performed tissue specific brain age prediction using machine learning and performed Bayesian multilevel modeling to assess changes in each CMR over time, their respective association with brain age gap (BAG), and their interaction effects with time and age on the tissue-specific BAGs. The results showed credible associations between DTI-based BAG and blood levels of phosphate and mean cell volume (MCV), and between T1-based BAG and systolic blood pressure, smoking, pulse, and C-reactive protein (CRP), indicating older-appearing brains in people with higher cardiometabolic risk (smoking, higher blood pressure and pulse, low-grade inflammation). Longitudinal evidence supported interactions between both BAGs and waist-to-hip ratio (WHR), and between DTI-based BAG and systolic blood pressure and smoking, indicating accelerated ageing in people with higher cardiometabolic risk (smoking, higher blood pressure, and WHR). The results demonstrate that cardiometabolic risk factors are associated with brain ageing. While randomized controlled trials are needed to establish causality, our results indicate that public health initiatives and treatment strategies targeting modifiable cardiometabolic risk factors may also improve risk trajectories and delay brain ageing.

• Aamodt, Anne Hege; Høgestøl, Einar August; Popperud, Trine Haug; Holter, Jan Cato; Dyrhol-Riise, Anne Ma & Tonby, Kristian [Show all 15 contributors for this article] (2021). Blood neurofilament light concentration at admittance: a potential prognostic marker in COVID-19. Journal of Neurology. ISSN 0340-5354. doi: 10.1007/s00415-021-10517-6. Full text in Research Archive Show summary

  Objective To test the hypotheses that blood biomarkers for nervous system injury, serum concentrations of neurofilament light chain protein (NfL) and glial fibrillary acidic protein (GFAp) can serve as biomarkers for disease severity in COVID-19 patients. Methods Forty-seven inpatients with confirmed COVID-19 had blood samples drawn on admission for assessing serum biomarkers of CNS injury by Single molecule array (Simoa), NfL and GFAp. Concentrations of NfL and GFAp were analyzed in relation to symptoms, clinical signs, inflammatory biomarkers and clinical outcomes. We used multivariate linear models to test for differences in biomarker concentrations in the subgroups, accounting for confounding effects. Results In total, 21% (n = 10) of the patients were admitted to an intensive care unit, and the overall mortality rate was 13% (n = 6). Non-survivors had higher serum concentrations of NfL (p < 0.001) upon admission than patients who were discharged alive both in adjusted analyses (p = 2.6 × 10–7) and unadjusted analyses (p = 0.001). The concentrations of NfL in non-survivors increased over repeated measurements; whereas, the concentrations in survivors were stable. The GFAp concentration was also significantly higher in non-survivors than survivors (p = 0.02). Conclusion Increased concentrations of NfL and GFAp in COVID-19 patients on admission may indicate increased mortality risk. Measurement of blood biomarkers for nervous system injury can be useful to detect and monitor CNS injury in COVID-19.

• Høgestøl, Einar August; Ghezzo, Samuele; Nygaard, Gro Owren; Espeseth, Thomas; Sowa, Piotr & Beyer, Mona K. [Show all 10 contributors for this article] (2021). Functional connectivity in multiple sclerosis modelled as connectome stability: A 5-year follow-up study. Multiple Sclerosis. ISSN 1352-4585. p. 1–9. doi: 10.1177/13524585211030212. Full text in Research Archive Show summary

  Background: Brain functional connectivity (FC) in multiple sclerosis (MS) is abnormal compared to healthy controls (HCs). More longitudinal studies in MS are needed to evaluate whether FC stability is clinically relevant. Objective: To compare functional magnetic resonance imaging (fMRI)-based FC between MS and HC, and to determine the relationship between longitudinal FC changes and structural brain damage, cognitive performance and physical disability. Methods: T1-weighted MPRAGE and resting-state fMRI (1.5T) were acquired from 70 relapsing-remitting MS patients and 94 matched HC at baseline (mean months since diagnosis 14.0 ± 11) and from 60 MS patients after 5 years. Independent component analysis and network modelling were used to measure longitudinal FC stability and cross-sectional comparisons with HC. Linear mixed models, adjusted for age and sex, were used to calculate correlations. Results: At baseline, patients with MS showed FC abnormalities both within networks and in single connections compared to HC. Longitudinal analyses revealed functional stability and no significant relationships with clinical disability, cognitive performance, lesion or brain volume. Conclusion: FC abnormalities occur already at the first decade of MS, yet we found no relevant clinical correlations for these network deviations. Future large-scale longitudinal fMRI studies across a range of MS subtypes and outcomes are required.

• Brune, Synne; Høgestøl, Einar August; Cengija, Vanja; Berg-Hansen, Pål; Sowa, Piotr & Nygaard, Gro Owren [Show all 8 contributors for this article] (2020). LesionQuant for assessment of MRI in multiple sclerosis—A promising supplement to the visual scan inspection. Frontiers in Neurology. 11:546744, p. 1–10. doi: 10.3389/fneur.2020.546744. Full text in Research Archive Show summary

  Background and Goals: Multiple sclerosis (MS) is a central nervous system inflammatory disease where magnetic resonance imaging (MRI) is an important tool for diagnosis and disease monitoring. Quantitative measurements of lesion volume, lesion count, distribution of lesions, and brain atrophy have a potentially significant value for evaluating disease progression. We hypothesize that utilizing software designed for evaluating MRI data in MS will provide more accurate and detailed analyses compared to the visual neuro-radiological evaluation. Methods: A group of 56 MS patients (mean age 35 years, 70% females and 96% relapsing-remitting MS) was examined with brain MRI one and 5 years after diagnosis. The T1 and FLAIR brain MRI sequences for all patients were analyzed using the LesionQuant (LQ) software. These data were compared with data from structured visual evaluations of the MRI scans performed by neuro-radiologists, including assessments of atrophy, and lesion count. The data from LQ were also compared with data from other validated research methods for brain segmentation, including assessments of whole brain volume and lesion volume. Correlations with clinical tests like the timed 25-foot walk test (T25FT) were performed to explore additional value of LQ analyses. Results: Lesion count assessments by LQ and by the neuro-radiologist were significantly correlated one year (cor = 0.92, p = 2.2 × 10 −16 ) and 5 years (cor = 0.84, p = 2.7 × 10 −16 ) after diagnosis. Analyzes of the intra- and interrater variability also correlated significantly (cor = 0.96, p &amp;lt; 0.001, cor = 0.97, p &amp;lt; 0.001). Significant positive correlation was found between lesion volume measured by LQ and by the software Cascade (cor = 0.7, p &amp;lt; 0.001. LQ detected a reduction in whole brain percentile &amp;gt;10 in 10 patients across the time-points, whereas the neuro-radiologist assessment identified six of these. The neuro-radiologist additionally identified five patients with increased atrophy in the follow-up period, all of them displayed decreasing low whole brain percentiles (median 11, range 8–28) in the LQ analysis. Significant positive correlation was identified between lesion volume measured by LQ and test performance on the T25FT both at 1 and 5 years after diagnosis. Conclusion: For the number of MS lesions at both time-points, we demonstrated strong correlations between the assessments done by LQ and the neuro-radiologist. Lesion volume evaluated with LQ correlated with T25FT performance. LQ-analyses classified more patients to have brain atrophy than the visual neuro-radiological evaluation. In conclusion, LQ seems like a promising supplement to the evaluation performed by neuro-radiologists, providing an automated tool for evaluating lesions in MS patients and also detecting early signs of atrophy in both a longitudinal and cross-sectional setting.

• Cellerino, Maria; Ivaldi, Frederico; Pardini, Matteo; Rotta, Gianluca; Vila, Gemma & Bäcker-Koduah, Priscilla [Show all 23 contributors for this article] (2020). Impact of treatment on cellular immunophenotype in MS: A cross-sectional study. Neurology: Neuroimmunology and neuroinflammation. 7(3), p. 1–13. doi: 10.1212/NXI.0000000000000693. Full text in Research Archive Show summary

  Objective: To establish cytometry profiles associated with disease stages and immunotherapy in MS. Methods: Demographic/clinical data and peripheral blood samples were collected from 227 patients with MS and 82 sex- and age-matched healthy controls (HCs) enrolled in a cross-sectional study at 4 European MS centers (Spain, Italy, Germany, and Norway). Flow cytometry of isolated peripheral blood mononuclear cells was performed in each center using specifically prepared antibody-cocktail Lyotubes; data analysis was centralized at the Genoa center. Differences in immune cell subsets were assessed between groups of untreated patients with relapsing-remitting or progressive MS (RRMS or PMS) and HCs and between groups of patients with RRMS taking 6 commonly used disease-modifying drugs. Results: In untreated patients with MS, significantly higher frequencies of Th17 cells in the RRMS population compared with HC and lower frequencies of B-memory/B-regulatory cells as well as higher percentages of B-mature cells in patients with PMS compared with HCs emerged. Overall, the greatest deviation in immunophenotype in MS was observed by treatment rather than disease course, with the strongest impact found in fingolimod-treated patients. Fingolimod induced a decrease in total CD4+ T cells and in B-mature and B-memory cells and increases in CD4+ and CD8+ T-regulatory and B-regulatory cells. Conclusions: Our highly standardized, multisite cytomics data provide further understanding of treatment impact on MS immunophenotype and could pave the way toward monitoring immune cells to help clinical management of MS individuals.

• Elvsåshagen, Torbjørn; Bahrami, Shahram; Meer, Dennis van der; Agartz, Ingrid; Alnæs, Dag & Barch, Deanna M. [Show all 76 contributors for this article] (2020). The genetic architecture of human brainstem structures and their involvement in common brain disorders. Nature Communications. 11. doi: 10.1038/s41467-020-17376-1. Full text in Research Archive Show summary

  Brainstem regions support vital bodily functions, yet their genetic architectures and involvement in common brain disorders remain understudied. Here, using imaging-genetics data from a discovery sample of 27,034 individuals, we identify 45 brainstem-associated genetic loci, including the first linked to midbrain, pons, and medulla oblongata volumes, and map them to 305 genes. In a replication sample of 7432 participants most of the loci show the same effect direction and are significant at a nominal threshold. We detect genetic overlap between brainstem volumes and eight psychiatric and neurological disorders. In additional clinical data from 5062 individuals with common brain disorders and 11,257 healthy controls, we observe differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson’s disease, supporting the relevance of brainstem regions and their genetic architectures in common brain disorders.

• Berge, Tone; Eriksson, Anna; Brorson, Ina Skaara; Høgestøl, Einar August; Berg-Hansen, Pål & Døskeland, Anne Marie Simonne [Show all 10 contributors for this article] (2019). Quantitative proteomic analyses of CD4+ and CD8+ T cells reveal differentially expressed proteins in multiple sclerosis patients and healthy controls. Clinical Proteomics. ISSN 1542-6416. 16:19, p. 1–18. doi: 10.1186/s12014-019-9241-5. Full text in Research Archive Show summary

  Background Multiple sclerosis (MS) is an autoimmune, neuroinflammatory disease, with an unclear etiology. However, T cells play a central role in the pathogenesis by crossing the blood–brain-barrier, leading to inflammation of the central nervous system and demyelination of the protective sheath surrounding the nerve fibers. MS has a complex inheritance pattern, and several studies indicate that gene interactions with environmental factors contribute to disease onset. Methods In the current study, we evaluated T cell dysregulation at the protein level using electrospray liquid chromatography–tandem mass spectrometry to get novel insights into immune-cell processes in MS. We have analyzed the proteomic profiles of CD4+ and CD8+ T cells purified from whole blood from 13 newly diagnosed, treatment-naive female patients with relapsing–remitting MS and 14 age- and sex-matched healthy controls. Results An overall higher protein abundance was observed in both CD4+ and CD8+ T cells from MS patients when compared to healthy controls. The differentially expressed proteins were enriched for T-cell specific activation pathways, especially CTLA4 and CD28 signaling in CD4+ T cells. When selectively analyzing proteins expressed from the genes most proximal to > 200 non-HLA MS susceptibility polymorphisms, we observed differential expression of eight proteins in T cells between MS patients and healthy controls, and there was a correlation between the genotype at three MS genetic risk loci and protein expressed from proximal genes. Conclusion Our study provides evidence for proteomic differences in T cells from relapsing–remitting MS patients compared to healthy controls and also identifies dysregulation of proteins encoded from MS susceptibility genes.

• Høgestøl, Einar August; Kaufmann, Tobias; Nygaard, Gro Owren; Beyer, Mona K.; Sowa, Piotr & Nordvik, Jan Egil [Show all 11 contributors for this article] (2019). Cross-sectional and longitudinal MRI brain scans reveal accelerated brain aging in multiple sclerosis. Frontiers in Neurology. 10:450, p. 1–9. doi: 10.3389/fneur.2019.00450. Full text in Research Archive Show summary

  Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. By combining longitudinal MRI-based brain morphometry and brain age estimation using machine learning, we tested the hypothesis that MS patients have higher brain age relative to chronological age than healthy controls (HC) and that longitudinal rate of brain aging in MS patients is associated with clinical course and severity. Seventy-six MS patients [71% females, mean age 34.8 years (range 21–49) at inclusion] were examined with brain MRI at three time points with a mean total follow up period of 4.4 years (±0.4 years). We used additional cross-sectional MRI data from 235 HC for case-control comparison. We applied a machine learning model trained on an independent set of 3,208 HC to estimate individual brain age and to calculate the difference between estimated and chronological age, termed brain age gap (BAG). We also assessed the longitudinal change rate in BAG in individuals with MS. MS patients showed significantly higher BAG (4.4 ± 6.6 years) compared to HC (Cohen's D = 0.69, p = 4.0 × 10−6). Longitudinal estimates of BAG in MS patients showed high reliability and suggested an accelerated rate of brain aging corresponding to an annual increase of 0.41 (SE = 0.15) years compared to chronological aging (p = 0.008). Multiple regression analyses revealed higher rate of brain aging in patients with more brain atrophy (Cohen's D = 0.86, p = 4.3 × 10−15) and increased white matter lesion load (WMLL) (Cohen's D = 0.55, p = 0.015). On average, patients with MS had significantly higher BAG compared to HC. Progressive brain aging in patients with MS was related to brain atrophy and increased WMLL. No significant clinical associations were found in our sample, future studies are warranted on this matter. Brain age estimation is a promising method for evaluation of subtle brain changes in MS, which is important for predicting clinical outcome and guide choice of intervention.

• Kaufmann, Tobias; Meer, Dennis van der; Doan, Nhat Trung; Schwarz, Emanuel; Lund, Martina Jonette & Agartz, Ingrid [Show all 84 contributors for this article] (2019). Common brain disorders are associated with heritable patterns of apparent aging of the brain. Nature Neuroscience. ISSN 1097-6256. 22(10), p. 1617–1623. doi: 10.1038/s41593-019-0471-7. Full text in Research Archive Show summary

  Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3–96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.

• Høgestøl, Einar August; Nygaard, Gro Owren; Alnæs, Dag; Beyer, Mona K.; Westlye, Lars Tjelta & Harbo, Hanne Flinstad (2019). Symptoms of fatigue and depression is reflected in altered default mode network connectivity in multiple sclerosis. PLOS ONE. 14(4). doi: 10.1371/journal.pone.0210375. Full text in Research Archive Show summary

  Background Fatigue and depression are frequent and often co-occurring symptoms in multiple sclerosis (MS). Resting-state functional magnetic resonance imaging (rs-fMRI) represents a promising tool for disentangling differential associations between depression and fatigue and brain network function and connectivity. In this study we tested for associations between symptoms of fatigue and depression and DMN connectivity in patients with MS. Materials and methods Seventy-four MS patients were included on average 14 months after diagnosis. They underwent MRI scanning of the brain including rs-fMRI, and symptoms of fatigue and depression were assessed with Fatigue Severity Scale (FSS) and Beck Depression Inventory II (BDI). A principal component analysis (PCA) on FSS and BDI scores was performed, and the component scores were analysed using linear regression models to test for associations with default mode network (DMN) connectivity. Results We observed higher DMN connectivity with higher scores on the primary principal component reflecting common symptom burden for fatigue and depression (Cohen’s f2 = 0.075, t = 2.17, p = 0.03). The secondary principal component reflecting a pattern of low fatigue scores with high scores of depression was associated with lower DMN connectivity (Cohen’s f2 = 0.067, t = -2.1, p = 0.04). Using continuous mean scores of FSS we also observed higher DMN connectivity with higher symptom burden (t = 3.1, p = 0.003), but no significant associations between continuous sum scores of BDI and DMN connectivity (t = 0.8, p = 0.4). Conclusion Multivariate decomposition of FSS and BDI data supported both overlapping and unique manifestation of fatigue and depression in MS patients. Rs-fMRI analyses showed that symptoms of fatigue and depression were reflected in altered DMN connectivity, and that higher DMN activity was seen in MS patients with fatigue even with low depression scores.

• Berg-Johnsen, Jon & Høgestøl, Einar August (2018). Supplementary motor area syndrome after surgery for parasagittal meningiomas. Acta Neurochirurgica. ISSN 0001-6268. 160(3), p. 583–587. doi: 10.1007/s00701-018-3474-3. Full text in Research Archive
• Akhmadeev, Konstantin; Houssein, Aya; Moussaoui, Said; Høgestøl, Einar August; Tutturen, Ingerid Maria Voorham & Harbo, Hanne Flinstad [Show all 10 contributors for this article] (2018). SVM-based tool to detect patients with multiple sclerosis using a commercial EMG sensor. Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop. ISSN 1551-2282. 2018-July, p. 376–379. doi: 10.1109/SAM.2018.8448391. Full text in Research Archive Show summary

  Multiple sclerosis (MS) is a major auto-immune disease that is the leading cause of non-traumatic impairment of the central nervous system (CNS) in young adults. Successful treatment of MS patients depends on accurate tools for both the MS diagnosis and the disability progression. In current and upcoming studies the authors aim to explore the capabilities of applying a commercial electromyographic and inertial sensor (MYO Armband by Thalmic Labs Inc.), coupled with a multichannel signal processing tool, to standard neurological examination of MS progression. In this pilot study we formulate a two-class “healthy control” - “having MS” classification problem. A dataset of electromyographic signals and inertial sensor measurements from 71 individuals (31 MS patients and 40 healthy controls) was acquired during standard neurological examination routine. Temporal and spectral features of the signals were extracted in order to train and validate a classification model. Finally, a Support Vector Machine classifier was obtained giving AUROC = 0.94, 95% CI = [0.88, 0.99]. We propose a set of signal descriptors that correlate with objective components of the neurological examination. The proposed signal acquisition and processing technique, being easy to integrate into the traditional neurological exam, may have high potential for aiding in quantifying MS progression.

• Høgestøl, Einar August & Berg-Johnsen, Jon (2016). Regression of Intracranial Meningioma during Treatment with α1-Adrenoceptor Blocker. Journal of Neurological Surgery Reports. ISSN 2193-6358. 77(1), p. e62–e65. doi: 10.1055/s-0035-1571204. Full text in Research Archive

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• Schoof, Lisa G.; Rød, Brit Ellen; Mahdaoui, Sahla El; Michelsen, Josephine S.; Høgestøl, Einar August & Myhr, Kjell-Morten [Show all 27 contributors for this article] (2025). Non-inferiority of Rituximab versus OCrelizumab in Multiple Sclerosis (ROC-MS)—an individual participant data meta-analysis. doi: 10.1016/j.msard.2025.106858. Full text in Research Archive
• Høgestøl, Einar August; Sowa, Piotr; Holmøy, Trygve; Bø, Lars; Nygaard, Gro Owren & Wergeland, Stig (2025). Oppdaterte diagnosekriterier for multippel sklerose. Tidsskrift for Den norske legeforening (Tidsskriftet). ISSN 0029-2001. 145(15). doi: 10.4045/tidsskr.25.0592. Full text in Research Archive
• Dahlén, Sara; Bjørneboe, John Andreas; Sandmo, Stian Bahr; Bache-Mathiesen, Lena Kristin; Filipcik, Peter & Howe, Emilie Isager [Show all 12 contributors for this article] (2025). Brain health in female former top-level football players . Full text in Research Archive
• Dahlén, Sara; Bjørneboe, John Andreas; Sandmo, Stian Bahr; Bache-Mathiesen, Lena Kristin; Filipcik, Peter & Howe, Emilie Isager [Show all 12 contributors for this article] (2025). Brain health in Norwegian female former top-level football players: a protocol for a longitudinal cohort study. doi: 10.1136/bmjopen-2024-092456. Full text in Research Archive
• Cappelletti, Chiara; Berge, Tone; Hammerstad, Sara Salehi; Høgestøl, Einar August; Celius, Elisabeth Gulowsen & Brorson, Ina Skaara [Show all 7 contributors for this article] (2024). Menopause affects DNA methylation and aging in women with multiple sclerosis. Full text in Research Archive
• Skattebøl, Lars; Øverås, Mathias Herstad; Nordhøy, Wibeke; Harbo, Hanne Flinstad; Sowa, Piotr & Lundby, Rigmor [Show all 8 contributors for this article] (2023). Brain Age and Quantitative Susceptibility Mapping of Chronic Active Lesions in Relapsing Multiple Sclerosis. Full text in Research Archive
• Nygaard, Gro Owren; Torgauten, Hilde Marie; Skattebøl, Lars; Høgestøl, Einar August; Sowa, Piotr & Myhr, Kjell-Morten [Show all 8 contributors for this article] (2022). Risk of fingolimod rebound after switching to cladribine or rituximab in multiple sclerosis. Multiple Sclerosis and Related Disorders. ISSN 2211-0348. 62. doi: 10.1016/j.msard.2022.103812. Full text in Research Archive
• König, Marton; Wolf, Asia-Sophia Fumika Michaela; Ravussin, Anthony; Chopra, Adity; Tran, Trung & Torgauten, Hilde Marie [Show all 28 contributors for this article] (2022). Immunogenicity and efficacy of mRNA-COVID-19 vaccines in people with multiple sclerosis. Full text in Research Archive
• Kaufmann, Tobias; Meer, Dennis van der; Doan, Nhat Trung; Schwarz, Emanuel; Lund, Martina Jonette & Agartz, Ingrid [Show all 97 contributors for this article] (2020). Publisher Correction: Common brain disorders are associated with heritable patterns of apparent aging of the brain (Nature Neuroscience, (2019), 22, 10, (1617-1623), 10.1038/s41593-019-0471-7). Nature Neuroscience. ISSN 1097-6256. 23(2), p. 295–295. doi: 10.1038/s41593-019-0553-6. Full text in Research Archive
• Berge, Tone; Eriksson, Anna; Brorson, Ina Skaara; Høgestøl, Einar August; Bos, Steffan Daniel & Harbo, Hanne Flinstad [Show all 7 contributors for this article] (2018). Proteomic profiling of CD4+ and CD8+ T cells from multiple sclerosis patients and healthy controls. Full text in Research Archive
• Berge, Tone; Brorson, Ina Skaara; Høgestøl, Einar August; Bos, Steffan Daniel; Harbo, Hanne Flinstad & Berven, Frode (2018). Proteomic profiling of CD4+ and CD8+ T cells from multiple sclerosis patients and healthy controls. Full text in Research Archive
• Eriksson, Anna; Brorson, Ina Skaara; Høgestøl, Einar August; Bos, Steffan Daniel; Harbo, Hanne Flinstad & Berven, Frode [Show all 7 contributors for this article] (2018). Proteomic profiling of CD4+ T cells from MS patients show increased activity of T cell activation pathways (compared to healthy controls). Full text in Research Archive
• Zubizarreta, Irati; Rosbo, Nicole Kerlero de; Rinas, Melanie; Høgestøl, Einar August; Benavent, Sigrid Aune de Rodez & Bos, Steffan Daniel [Show all 17 contributors for this article] (2018). The Sys4MS project: Personalizing health care in Multiple Sclerosis using systems medicine tools. Full text in Research Archive
• Berge, Tone; Eriksson, Anna; Brorson, Ina Skaara; Høgestøl, Einar August; Harbo, Hanne Flinstad & Bos, Steffan Daniel [Show all 7 contributors for this article] (2018). Proteomic profiling of T cells from multiple sclerosis patients and healthy controls. Full text in Research Archive
• Bos, Steffan Daniel; Brorson, Ina Skaara; Høgestøl, Einar August; Berge, Tone; Saez-Rodriguez, Julio & Uccelli, Antonio [Show all 9 contributors for this article] (2018). Multiple Sclerosis genetic burden score in a systems biology study of MS patients from four countries. Full text in Research Archive

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