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Introduction Phosphorylated tau (p‐tau) in cerebrospinal fluid (CSF) is an established Alzheimer's disease (AD) biomarker. Novel immunoassays targeting N‐terminal and mid‐region p‐tau181 and p‐tau217 fragments are available, but head‐to‐head comparison in clinical settings is lacking. Methods N‐terminal‐directed p‐tau217 (N‐p‐tau217), N‐terminal‐directed p‐tau181 (N‐p‐tau181), and standard mid‐region p‐tau181 (Mid‐p‐tau181) biomarkers in CSF were evaluated in three cohorts (n = 503) to assess diagnostic performance, concordance, and associations with amyloid beta (Aβ). Results CSF N‐p‐tau217 and N‐p‐tau181 had better concordance (88.2%) than either with Mid‐p‐tau181 (79.7%–82.7%). N‐p‐tau217 and N‐p‐tau181 were significantly increased in early mild cognitive impairment (MCI)‐AD (A+T–N–) without changes in Mid‐p‐tau181 until AD‐dementia. N‐p‐tau217 and N‐p‐tau181 identified Aβ pathophysiology (area under the curve [AUC] = 94.8%–97.1%) and distinguished MCI‐AD from non‐AD MCI (AUC = 82.6%–90.5%) signficantly better than Mid‐p‐tau181 (AUC = 91.2% and 70.6%, respectively). P‐tau biomarkers equally differentiated AD from non‐AD dementia (AUC = 99.1%–99.8%). Discussion N‐p‐tau217 and N‐p‐tau181 could improve diagnostic accuracy in prodromal‐AD and clinical trial recruitment as both identify Aβ pathophysiology and differentiate early MCI‐AD better than Mid‐p‐tau181.

Aim To determine the influence of high-efficacy disease modifying therapy (DMT) on the development of IgG SARS-CoV-2 antibody response in COVID-19 convalescent people with multiple sclerosis (pwMS). Methods Seventy-four pwMS taking high-efficacy DMTs (specifically natalizumab, fingolimod, alemtuzumab, ocrelizumab, cladribine and ublituximab) and diagnosed with COVID-19 and 44 healthy persons (HC) were enrolled. SARS-CoV2 antibodies were tested with Elecsys® Anti-SARSCoV-2 S assay. Results pwMS taking high-efficacy DMTs had a significantly higher chance of having negative titer of SARS-CoV2 antibodies compared to healthy controls (33 negative pwMS [44.6%] compared to one negative HC [2.3%], p, Graphical abstract Unlabelled Image

Background: It is still unknown if serum glial fibrillary acidic protein (GFAP) is a useful marker in frontotemporal lobar degeneration (FTLD). Objective: To assess the diagnostic and prognostic value of serum GFAP in a large cohort of patients with FTLD. Methods: In this retrospective study, performed on 406 participants, we measured serum GFAP concentration with an ultrasensitive Single molecule array (Simoa) method in patients with FTLD, Alzheimer’s disease (AD), and in cognitively unimpaired elderly controls. We assessed the role of GFAP as marker of disease severity by analyzing the correlation with clinical variables, neurophysiological data, and cross-sectional brain imaging. Moreover, we evaluated the role of serum GFAP as a prognostic marker of disease survival. Results: We observed significantly higher levels of serum GFAP in patients with FTLD syndromes, except progressive supranuclear palsy, compared with healthy controls, but not compared with AD patients. In FTLD, serum GFAP levels correlated with measures of cognitive dysfunction and disease severity, and were associated with indirect measures of GABAergic deficit. Serum GFAP concentration was not a significant predictor of survival. Conclusion: Serum GFAP is increased in FTLD, correlates with cognition and GABAergic deficits, and thus shows promise as a biomarker of disease severity in FTLD.

The neuropathological confirmation of amyloid-β (Aβ) plaques and tau neurofibrillary tangles (NFT) remains the gold standard for a definitive diagnosis of Alzheimer's disease (AD). Nowadays, the in vivo diagnosis of AD is greatly aided by both cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers. Although highly accurate, their broad implementation is restricted by high cost, limited accessibility and invasiveness. We recently developed a high-performance, ultrasensitive immunoassay for the quantification of tau phosphorylated at threonine-181 (p-tau181) in plasma, which identifies AD pathophysiology with high accuracy. However, it remains unclear whether plasma p-tau181, measured years before the death, can predict the eventual neuropathological confirmation of AD, and successfully discriminates AD from non-AD dementia pathologies. We studied a unique cohort of 115 individuals with longitudinal blood collections with clinical evaluation at 8, 4 and 2 years prior to neuropathological assessment at death. The results demonstrate that plasma p-tau181 associates better with AD neuropathology and Braak staging than a clinical diagnosis 8 years before post-mortem. Moreover, while all patients had a diagnosis of AD dementia during life, plasma p-tau181 proved to discriminate AD from non-AD pathologies with high accuracy (AUC = 97.4%, 95% CI = 94.1-100%) even 8 years before death. Additionally, the longitudinal trajectory of plasma p-tau181 was assessed in all patients. We found that the main increases in plasma p-tau181 occurred between 8 and 4 years prior to death in patients with AD neuropathology and later plateauing. In contrast, non-AD pathologies and controls exhibited minor, albeit significant, increases in p-tau181 up until death. Overall, our study demonstrates that plasma p-tau181 is highly predictive and specific of AD neuropathology years before post-mortem examination. These data add further support for the use of plasma p-tau181 to aid clinical management in primary care and recruitment for clinical trials. Open access funding provided by University of Gothenburg. This study represents independent research partly funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. Tissue samples were supplied by The London Neurodegenerative Diseases Brain Bank, which receives funding from the UK Medical Research Council and as part of the Brains for Dementia Research programme, jointly funded by Alzheimer’s Research UK and the Alzheimer’s Society. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. TKK holds a postdoctoral fellowship from the BrightFocus Foundation (#A2020812F), and was further supported by the Swedish Alzheimer Foundation (Alzheimerfonden; #AF-930627), the Swedish Brain Foundation (Hjärnfonden; #FO2020-0240), the Swedish Dementia Foundation (Demensförbundet), the Agneta Prytz-Folkes and Gösta Folkes Foundation, Gamla Tjänarinnor, the Aina (Ann) Wallströms and Mary-Ann Sjöbloms Foundation, the Gun and Bertil Stohnes Foundation, and the Anna Lisa and Brother Björnsson’s Foundation. MSC received funding from the European Union’s Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie action grant agreement no. 752310, and currently receives funding from Instituto de Salud Carlos III (PI19/00155) and from the Spanish Ministry of Science, Innovation and Universities (Juan de la Cierva Programme grant IJC2018-037478-I). AH is funded by Research Centre for Mental Health and Biomedical Research Unit for Dementia. KB holds the Torsten Söderberg Professorship in Medicine and is supported by grants from the Swedish Research Council, the Swedish Alzheimer Foundation, and the Swedish Brain Foundation. AH is funded by Research Centre for Mental Health and Biomedical Research Unit for Dementia. KB holds the Torsten Söderberg Professorship in Medicine and is supported by grants from the Swedish Research Council, the Swedish Alzheimer Foundation, and the Swedish Brain Foundation. KB holds the Torsten Söderberg Professorship in Medicine at the Royal Swedish Academy of Sciences, and is supported by the Swedish Research Council (#2017-00915), the Swedish Alzheimer Foundation (#AF-742881), Hjärnfonden, Sweden (#FO2017-0243), and a grant (#ALFGBG-715986) from the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement. NJA is supported by the Wallenberg Centre for Molecular and Translational Medicine, the Swedish Alzheimer Foundation (Alzheimerfonden), the Swedish Dementia Foundation (Demensförbundet), and Hjärnfonden, Sweden.

ObjectiveTo assess the diagnostic and prognostic value of serum neurofilament light (NfL) and serum phospho-Tau181(p-Tau181) in a large cohort of patients with frontotemporal lobar degeneration (FTLD).MethodsIn this retrospective study, performed on 417 participants, we analysed serum NfL and p-Tau181concentrations with an ultrasensitive single molecule array (Simoa) approach. We assessed the diagnostic values of serum biomarkers in the differential diagnosis between FTLD, Alzheimer’s disease (AD) and healthy ageing; their role as markers of disease severity assessing the correlation with clinical variables, cross-sectional brain imaging and neurophysiological data; their role as prognostic markers, considering their ability to predict survival probability in FTLD.ResultsWe observed significantly higher levels of serum NfL in patients with FTLD syndromes, compared with healthy controls, and lower levels of p-Tau181compared with patients with AD. Serum NfL concentrations showed a high accuracy in discriminating between FTLD and healthy controls (area under the curve (AUC): 0.86, p181showed high accuracy in differentiating FTLD from patients with AD (AUC: 0.93, pConclusionsThe assessment of serum NfL and p-Tau181may provide a comprehensive view of FTLD, aiding in the differential diagnosis, in staging disease severity and in defining survival probability.

Background/Objective Novel biomarkers identifying and predicting disease activity in multiple sclerosis (MS) would be valuable for primary diagnosis and as outcome measures for monitoring therapeutic effects in clinical trials. Axonal loss is present from the earliest stages of MS and correlates with disability measures. Growth-associated protein 43 (GAP-43) is a presynaptic protein with induced expression during axonal growth. We hypothesized this protein could serve as a biomarker of axonal regeneration capacity in MS. Methods We developed a novel GAP-43 enzyme-linked immunosorbent assay for quantification in cerebrospinal fluid (CSF) and measured GAP-43 levels in 71 patients with clinically isolated syndrome, 139 MS patients and 51 controls. Results GAP-43 concentrations were similar in patients and controls. Nevertheless, GAP-43 levels were higher in patients with >10 T2-magnetic resonance imaging (MRI) lesions ( p = 0.005). CSF GAP-43 concentrations correlated with CSF mononuclear cell counts ( p = 0.031) and were inversely correlated with patient age ( p = 0.038) with a trend for higher CSF GAP-43 concentrations in patients with gadolinium-enhancing MRI lesions and positive CSF oligoclonal immunoglobulin G status. Conclusion Our results suggest that axonal regeneration capacity is relatively preserved in early MS. CSF GAP-43 concentration is positively associated with markers of inflammation, suggesting possible inflammatory-driven expression of this growth-associated protein in early MS.

Background Detection of cerebrospinal fluid (CSF) specific oligoclonal bands (OCB) supports the diagnosis of multiple sclerosis (MS), but the method is technically demanding and gives only qualitative information. Kappa free light chains (KFLC) quantification could represent a convenient alternative. We evaluated the diagnostic accuracy of OCB and KFLC in our cohort to further estimate the gain in diagnostic performance when combining both of them. Methods KFLC were measured in paired serum and CSF samples of 80 patients with MS and 50 patients with non-inflammatory neurological disorders. OCB were detected using an in-house alkaline phosphatase assay. Likelihood ratio (LR) was used to explore the benefit of the combined KFLC and OCB test. Results Sensitivity of KFLC index (≥5.3) and intrathecal KFLC fraction (≥10%) was 96% and 95% respectively, compared to 91% sensitivity of OCB assay. Specificity was 96% for intrathecal KFLC synthesis and 98% for OCB. Probability of MS in the absence of OCB was further reduced with concurrently normal KFLC index. Conclusions Normal KFLC parameters allow confident exclusion of intrathecal inflammation, but probability of MS is greater with positive OCB. Use of KFLC as an adjunct test might be beneficial in specialized MS centers with larger pretest probability.

© 2015 Elsevier Inc. All rights reserved., Decreased levels of alpha-synuclein (aSyn) in cerebrospinal fluid (CSF) in Parkinson's disease and related synucleinopathies have been reported, however, not consistently in all cross-sectional studies. To test the performance of one recently released human-specific enzyme-linked immunosorbent assay (ELISA) for the quantification of aSyn in CSF, we carried out a round robin trial with 18 participating laboratories trained in CSF ELISA analyses within the BIOMARKAPD project in the EU Joint Program - Neurodegenerative Disease Research. CSF samples (homogeneous aliquots from pools) and ELISA kits (one lot) were provided centrally and data reported back to one laboratory for data analysis. Our study showed that although factors such as preanalytical sample handling and lot-to-lot variability were minimized by our study design, we identified high variation in absolute values of CSF aSyn even when the same samples and same lots of assays were applied. We further demonstrate that although absolute concentrations differ between laboratories the quantitative results are comparable. With further standardization this assay may become an attractive tool for comparing aSyn measurements in diverse settings. Recommendations for further validation experiments and improvement of the interlaboratory results obtained are given., This is an EU Joint Program – Neurodegenerative Disease Research (JPND) project. The project is supported through the following funding organizations under the aegis of JPND–www.jpnd.eu: The Alzheimer Research Foundation (SAO-FRA), Belgium (grant number S#12018); Danish Council for Strategic Research, Denmark (grant number 0603-00511B); Bundesministerium für Bildung und Forschung (BMBF), Germany (grant number OIED1203C); General Secretary of Research and Technology, Greece; Italian Ministry of Health (Ricerca Corrente), Italy; The Fundação para a Ciência e a Tecnologia, Portugal (grant numbers JPND/0004/2011, IMM/BPD/51-2013, IMM/BI/7-2013, JPND/0005/2011); Fondo de Investigaciones Sanitarias, Instituto de Salud Carlos III, Spain (grant numbers PI11/03026, PI11/03035; cofinanced by the Fondo Europeo de Desarrollo Regional); The Ministry of Education, Research and Sport of the Slovak Republic, Slovakia; The Slovenian Research Agency, Slovenia (grant number A3-0001); The Swedish Research Council, Sweden; Ministry of Education for Netherlands: ZonMw (The Netherlands Organisation for Health Research and Development), The Netherlands (grant number 629000002); The Scientific and Technological Research Council of Turkey (grant number 112S335).

Altogether 875 subjects were included in the analysis. Each cohort and the combination of all cohorts were analyzed separately using leave-one-out cross-validation to identify the most important features in each cohort. The cohorts were then tested using the other cohorts as a training group to see if cross cohort comparison is feasible. Results: MRI features alone give good classification accuracies (0.68-0.81) to the four cohorts studied, which can be slightly improved by adding MMSE, APOE, CSF and neuropsychological test data. Among the imaging methods, multi template tensor-based morphometry was the most accurate in all cohorts except for AddNeuroMed, where voxel-based morphometry had the best accuracy. CSF was one of the most accurate features in both the Kuopio MCI and DESCRIPA cohorts. Using the other cohorts as a training group, the combination ofMRI, APOE and MMSE reached good classification accuracies in all the cohorts (0.66-0.78). Conclusions: Results show that the prediction accuracy of the combined cohort (0.70) is close to the average of the individual cohort accuracies (0.68-0.83). Using different cohorts as training sets for the DSI is feasible, as long as they share parameters investigated.