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Neuronal damage is the morphological substrate of persisting neurological disability. Neurofilaments (Nf) are cytoskeletal proteins of neurons and their release into cerebrospinal fluid has shown encouraging results as a biomarker for neurodegeneration. This study aimed to validate the quantification of the Nf light chain (NfL) in blood samples, as a biofluid source easily accessible for longitudinal studies. We developed and applied a highly sensitive electrochemiluminescence (ECL) based immunoassay for quantification of NfL in blood and CSF. Patients with Alzheimer's disease (AD) (30.8 pg/ml, n=20), Guillain-Barré-syndrome (GBS) (79.4 pg/ml, n=19) or amyotrophic lateral sclerosis (ALS) (95.4 pg/ml, n=46) had higher serum NfL values than a control group of neurological patients without evidence of structural CNS damage (control patients, CP) (4.4 pg/ml, n=68, p<0.0001 for each comparison, p=0.002 for AD patients) and healthy controls (HC) (3.3 pg/ml, n=67, p<0.0001). Similar differences were seen in corresponding CSF samples. CSF and serum levels correlated in AD (r=0.48, p=0.033), GBS (r=0.79, p<0.0001) and ALS (r=0.70, p<0.0001), but not in CP (r=0.11, p=0.3739). The sensitivity and specificity of serum NfL for separating ALS from healthy controls was 91.3% and 91.0%. We developed and validated a novel ECL based sandwich immunoassay for the NfL protein in serum (NfL(Umea47:3)); levels in ALS were more than 20-fold higher than in controls. Our data supports further longitudinal studies of serum NfL in neurodegenerative diseases as a potential biomarker of on-going disease progression, and as a potential surrogate to quantify effects of neuroprotective drugs in clinical trials.

The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.

Background The Montreal Cognitive Assessment (MoCA) has good sensitivity for mild cognitive impairment, but specificity is low when the original cut-off (25/26) is used. We aim to revise the cut-off on the German MoCA for its use in clinical routine. Methods Data were analyzed from 496 Memory Clinic outpatients (447 individuals with a neurocognitive disorder; 49 with cognitive normal findings) and from 283 normal controls. Cut-offs were identified based on (a) Youden’s index and (b) the 10th percentile of the control group. Results A cut-off of 23/24 on the MoCA had better correct classification rates than the MMSE and the original MoCA cut-off. Compared to the original MoCA cut-off, the cut-off of 23/24 points had higher specificity (92% vs 63%), but lower sensitivity (65% vs 86%). Introducing two separate cut-offs increased diagnostic accuracies with 92% specificity (23/24 points) and 91% sensitivity (26/27 points). Scores between these two cut-offs require further examinations. Conclusions Using two separate cut-offs for the MoCA combined with scores in an indecisive area enhances the accuracy of cognitive screening.

Significance Many evolutionary–developmental models have attempted to relate development and aging, with one popular hypothesis proposing that healthy age-related brain decline mirrors developmental maturation. But this elegant hypothesis has so far lacked clear and direct data to support it. Here, we describe intrinsic, entirely data-driven evidence that healthy brain degeneration and developmental process mirror one another in certain brain regions. Specifically, a data-driven decomposition of structural brain images in 484 healthy participants reveals a network of mainly higher-order regions that develop relatively late during adolescence, demonstrate accelerated degeneration in old age, and show heightened vulnerability to disorders that impact on brain structure during adolescence and aging. These results provide a fundamental link between development, aging, and disease processes in the brain. Several theories link processes of development and aging in humans. In neuroscience, one model posits for instance that healthy age-related brain degeneration mirrors development, with the areas of the brain thought to develop later also degenerating earlier. However, intrinsic evidence for such a link between healthy aging and development in brain structure remains elusive. Here, we show that a data-driven analysis of brain structural variation across 484 healthy participants (8–85 y) reveals a largely—but not only—transmodal network whose lifespan pattern of age-related change intrinsically supports this model of mirroring development and aging. We further demonstrate that this network of brain regions, which develops relatively late during adolescence and shows accelerated degeneration in old age compared with the rest of the brain, characterizes areas of heightened vulnerability to unhealthy developmental and aging processes, as exemplified by schizophrenia and Alzheimer’s disease, respectively. Specifically, this network, while derived solely from healthy subjects, spatially recapitulates the pattern of brain abnormalities observed in both schizophrenia and Alzheimer’s disease. This network is further associated in our large-scale healthy population with intellectual ability and episodic memory, whose impairment contributes to key symptoms of schizophrenia and Alzheimer’s disease. Taken together, our results suggest that the common spatial pattern of abnormalities observed in these two disorders, which emerge at opposite ends of the life spectrum, might be influenced by the timing of their separate and distinct pathological processes in disrupting healthy cerebral development and aging, respectively.

Given advantages in reperfusion therapy leading to mild stroke, less apparent cognitive deficits can be overseen in a routine neurological examination. Despite the widespread use of the Montreal Cognitive Assessment (MoCA), age- and education-specific cutoffs for the detection of post-stroke cognitive impairment (PSCI) are not established, hampering its valid application in stroke. We aimed to establish age- and education-specific MoCA cutoffs to better discriminate patients with and without acute PSCI. Patients with acute ischemic stroke underwent the MoCA and a detailed neuropsychological assessment. PSCI was defined as a performance < − 1.5 SD in ≥ 2 cognitive domains. As secondary data analysis, the discriminant abilities of the MoCA raw -score (not adding + 1 as correction for ≤ 12 years of education, YoE) cutoffs were automatically derived based on Youden Index and evaluated by receiver operating characteristic analyses across age- (< 55, 55–70, > 70 years old) and education-specific (≤ 12 and > 12 YoE) groups. 351 stroke patients (67.4 ± 14.1 years old; 13.1 ± 2.8 YoE) underwent the neuropsychological assessment 2.7 ± 2.0 days post-stroke. The original MoCA cutoff < 26 falsely classified 26.2% of examined patients, with poor sensitivity in younger adults (34.8% in patients < 55 years > 12 YoE) and poor specificity in older adults (55.0%, in > 70 years ≤ 12 YoE). By maximizing both sensitivity and specificity, the optimal MoCA raw cutoffs were: (i) < 28 in patients aged < 55 with > 12 YoE (sensitivity = 69.6%, specificity = 77.8%); (ii) < 22 and < 25 in patients > 70 years with ≤ 12 and > 12 YoE (sensitivity = 61.6%, specificity = 90.0%; sensitivity = 63.3%, specificity = 84.0%, respectively). In other groups the optimal MoCA raw cutoff was < 26. Age and education level should be considered when interpreting MoCA-scores. Though new age- and education-specific cutoffs demonstrated higher discriminant ability for PSCI, their performance in young stroke and adults with higher education level was low due to ceiling effects and MoCA subtests structure, and cautious interpretation in these patients is warranted. Trial registration : ClinicalTrials.gov Identifier: NCT05653141.

Introduction: Harmonized neuropsychological assessment for neurocognitive disorders, an international priority for valid and reliable diagnostic procedures, has been achieved only in specific countries or research contexts.Methods: To harmonize the assessment of mild cognitive impairment in Europe, a workshop (Geneva, May 2018) convened stakeholders, methodologists, academic, and non-academic clinicians and experts from European, US, and Australian harmonization initiatives.Results: With formal presentations and thematic working-groups we defined a standard battery consistent with the U.S. Uniform DataSet, version 3, and homogeneous methodology to obtain consistent normative data across tests and languages. Adaptations consist of including two tests specific to typical Alzheimer's disease and behavioral variant frontotemporal dementia. The methodology for harmonized normative data includes consensus definition of cognitively normal controls, classification of confounding factors (age, sex, and education), and calculation of minimum sample sizes.Discussion: This expert consensus allows harmonizing the diagnosis of neurocognitive disorders across European countries and possibly beyond.

Introduction: Cognition often remains unassessed in primary care. To improve early diagnosis of neurocognitive disorder (NCD) in Switzerland, the tablet‐based UCSF brain health assessment (BHA) and brain health survey (BHS) were validated. Methods: The German BHA, BHS, and Montreal Cognitive Assessment (MoCA) were administered to 67 patients with mild/major NCD and 50 controls. BHA includes subtests of memory, executive, visuospatial, and language functioning, and informant‐based BHS asks about behavior and motor functioning. Results: The complete instrument (BHA + BHS) was most accurate at detecting mild NCD (AUC = 0.95) and NCD without amyloid pathology (AUC = 0.96), followed by the BHA. All measures were accurate (all AUCs > 0.95) at distinguishing major NCD and NCD with amyloid pathology (Alzheimer's disease [AD]) from controls. Discussion: The German BHA and BHS are more sensitive to mild NCD and non‐AD presentations than the MoCA and thus have a high potential to identify patients with NCD in primary care earlier than currently used screens. We show that a novel, tablet‐based assessement is sensitive to detect patients with neurodegenerative diseases as early as in the mild cognitive impairment stage. Our results show that the novel tool is superior to existing paper‐and‐pencil‐based instruments like the Montreal Cognitive Assessment (MoCA).

Background The Placebo Group Simulation Approach (PGSA) aims at partially replacing randomized placebo-controlled trials (RPCTs), making use of data from historical control groups in order to decrease the needed number of study participants exposed to lengthy placebo treatment. PGSA algorithms to create virtual control groups were originally derived from mild cognitive impairment (MCI) data of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. To produce more generalizable algorithms, we aimed to compile five different MCI databases in a heuristic manner to create a “standard control algorithm” for use in future clinical trials. Methods We compared data from two North American cohort studies ( n =395 and 4328, respectively), one company-sponsored international clinical drug trial ( n =831) and two convenience patient samples, one from Germany ( n =726), and one from Switzerland ( n =1558). Results Despite differences between the five MCI samples regarding inclusion and exclusion criteria, their baseline demographic and cognitive performance data varied less than expected. However, the five samples differed markedly with regard to their subsequent cognitive performance and clinical development: (1) MCI patients from the drug trial did not deteriorate on verbal fluency over 3 years, whereas patients in the other samples did; (2) relatively few patients from the drug trial progressed from MCI to dementia (about 10% after 4 years), in contrast to the other four samples with progression rates over 30%. Conclusion Conventional MCI criteria were insufficient to allow for the creation of well-defined and internationally comparable samples of MCI patients. More recently published criteria for MCI or “MCI due to AD” are unlikely to remedy this situation. The Alzheimer scientific community needs to agree on a standard set of neuropsychological tests including appropriate selection criteria to make MCI a scientifically more useful concept. Patient data from different sources would then be comparable, and the scientific merits of algorithm-based study designs such as the PGSA could be properly assessed.

Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is considered as risk factor for the development of mild cognitive impairment (MCI) and dementia. However, dynamics of cognitive functions are subtle, and neurocognitive assessments largely differ in detecting these changes. We aimed to develop and evaluate a score which represents the common aspects of the cognitive functions measured by validated tests (i.e., \"general cognitive construct\"), while reducing overlap between tests and be more sensitive to identify changes in overall cognitive functioning. We developed the CoCo (cognitive construct) score to reflect the cognitive performance obtained by all items of four neurocognitive assessments (Montreal Cognitive Assessment (MoCA); Trail Making Test; Semantic Fluency, animals; Digital Symbol Substitution Test). The sample comprised 2,415 AF patients from the Swiss Atrial Fibrillation Cohort Study (Swiss-AF), 87% aged at least 65 years. Psychometric statistics were calculated for two cognitive measures based on (i) the full set of items from the neurocognitive test battery administered in the Swiss-AF study (i.e., CoCo item set) and (ii) the items from the widely used MoCA test. For the CoCo item set, a factor score was derived based on a principal component analysis, and its measurement properties were analyzed. Both the MoCA item set and the full neurocognitive test battery revealed good psychometric properties, especially the full battery. A one-factor model with good model fit and performance across time and groups was identified and used to generate the CoCo score, reflecting for each patient the common cognitive skill performance measured across the full neurocognitive test battery. The CoCo score showed larger effect sizes compared to the MoCA score in relation to relevant clinical variables. The derived factor score allows summarizing AF patients' cognitive performance as a single score. Using this score in the Swiss-AF project increases measurement sensitivity and decreases the number of statistical tests needed, which will be helpful in future studies addressing how AF affects the risk of developing cognitive impairment.

INTRODUCTION Disease‐modifying therapies (DMTs) for Alzheimer's disease (AD) will increase diagnostic demand. A non‐invasive blood‐based biomarker (BBBM) test for detection of amyloid‐β pathology may reduce diagnostic barriers and facilitate DMT initiation. OBJECTIVE To explore heterogeneity in AD care pathways and potential role of BBBM tests. METHODS Survey of 213 healthcare professionals/payers in US/China/UK/Germany/Spain/France and two advisory boards (US/Europe). RESULTS Current diagnostic pathways are heterogeneous, meaning many AD patients are missed while low‐risk patients undergo unnecessary procedures. Confirmatory amyloid testing (cerebrospinal fluid biomarkers/positron emission tomography) is utilized in few patients, resulting in diagnostic/treatment delays. A high negative‐predictive‐value test could streamline the diagnostic pathway by reducing unnecessary procedures in low‐risk patients; supporting confirmatory testing where needed. Imminent approval of DMTs will increase need for fast and reliable AD diagnostic tests. DISCUSSION An easy‐to‐use, accurate, non‐invasive BBBM test for amyloid pathology could guide diagnostic procedures or referral, streamlining early diagnosis and DMT initiation. Highlights This study explored AD care pathways and how BBBM may meet diagnostic demands Current diagnostic pathways are heterogeneous, with country and setting variations Many AD patients are missed, while low‐risk patients undergo unnecessary procedures An easy‐to‐use, accurate, non‐invasive BBBM test for amyloid pathology is needed This test could streamline early diagnosis of amyloid pathology and DMT initiation