Lewczuk, Piotr

Abstract Background The quantification of Neurofilament Light chain (NfL) in blood and cerebrospinal fluid (CSF) has proven valuable for diagnosing and prognosing various neurological disorders, including Alzheimer's disease, frontotemporal dementia, amyotrophic lateral sclerosis, parkinsonism, multiple sclerosis, and ischemic damage. However, there is considerable variability in clinical and laboratory practices between centers, primarily due to different contexts of use (COU), analytical methods, and the application of cutoffs or scales. Additionally, for the same biochemical profile, the interpretation and reporting of results may vary from one center to another, raising concerns about the commutability of the tests. To date, no consensus has been reached among laboratories to define the most appropriate use of cutoffs or conclusions/comments based on NfL profiles. Method This international project involves 38 laboratories across 18 countries, all specialized in the biochemical diagnosis of neurological disorders. Using a questionnaire, we obtained descriptions from each center regarding their COU, pre‐analytical and analytical protocols (including the biological fluid and methods used to quantify NfL). Through a consensus approach, we developed a harmonized strategy for the use and reporting of NfL results across different centres according to their respective COU. Results Among the centers, 63% quantified NfL in the CSF, 87% in blood and 53% in both fluids. COU were as follow: frontotemporal dementia (71%), Alzheimer disease (71%), multiple sclerosis (61%), amyotrophic lateral sclerosis (61%), psychiatric syndrome (45%), Creutzfeldt‐Jakob disease (32%), Parkinson disease (39%), peripheral neuropathy (29%), traumatic brain injury (21%), Huntington's disease (13%), amyloid transthyretin related (11%) and cardiac arrest (8%). Most of the centers define pathological cutoffs based on publications (50%) and take age into account for this purpose (42%). Reporting is mostly transmitted through numeric results (95%). Conclusion Harmonizing cutoffs, reporting, and interpretation across various clinical contexts will facilitate the incorporation of this biomarker into routine clinical practice.

Abstract INTRODUCTION Neurofilament light chain (NfL) quantification aids in diagnosing and predicting neurological disorders, but clinical and laboratory practices vary across centers. Differences in result interpretation and reporting further challenge test commutability. This study aimed to review the global analytical and post‐analytical methods used for NfL measurement in routine clinical practice across different contexts. METHODS We established an international working group (WG) and distributed a survey to its members to gather information on context of use (COU), (pre) analytical methods, cutoff usage, as well as the interpretation and reporting of NfL measurements. RESULTS Among the centers, 63% measured NfL in cerebrospinal fluid (CSF), 87% in blood, and 53% in both. COU was widespread, with 50% defining pathological cutoffs based on publications and 42% considering age. Reporting was primarily done through numeric results (95%). DISCUSSION Harmonizing cutoffs, reporting, and interpretation across various clinical contexts will facilitate the incorporation of this biomarker into routine clinical practice. Highlights Unique international overview of current analytical and post‐analytical methods for neurofilament light chain (NfL) measurement in routine clinical practice. Tailored sheets for each neurological application. Strategies to harmonize cutoffs, reporting, and interpretation of NfL's measurement.

AbstractBackgroundThe quantification of neurofilament light chain (NfL) in blood and cerebrospinal fluid (CSF) has proved useful in many contexts, for the diagnosis and prognosis of various neurological disorders. There is, however, a diversity of practices between centers, essentially linked to the context of use (COU), analytical methods, consideration of comorbidities, determination of cut‐points or use of interpretation scales. Finally, for the same biochemical profile, the interpretation and reporting of results may differ from one center to another, raising the question of test commutability. To date, no consensus has been reached between the different laboratories involved to define the most appropriate conclusions/comments based on COU and cut‐points. This work is an essential step towards consensual harmonization of the clinical use of NfL after CSF and/or blood analysis in various neurological contexts, as advocated by the Alzheimer's Association "Biofluid Based Biomarkers PIA" working group.MethodThis international project involves 58 clinical laboratories in 16 countries, specializing in the biochemical diagnosis of neurological disorders. By means of a questionnaire, we obtained a description of the COU, pre‐analytical and analytical (biological fluid and method used to quantify NfL) protocols of all the centers involved.ResultsOf the centers, 42% quantified NfL in CSF, 29% in serum and 28% in plasma, and 1% in dried blood spot. The COUs were as follows: Frontotemporal dementia (FTD, 17%), Alzheimer's disease (AD, 16%), multiple sclerosis (MS, 16%), amyotrophic lateral sclerosis (ALS, 11%), psychiatric syndrome (PS, 10%), Creutzfeldt‐Jakob disease (CJD, 8%), Parkinson's disease (PD, 8%), peripheral neuropathy (PN, 7%) and traumatic brain injury (TBI, 7%). Most centers define pathological cut‐points based on published literature and take age into account (50%).ConclusionOur initial results highlight the state of the art in terms of the clinical use of NfL analysis in CSF and blood in the context of different neurological diseases. We have now defined a coordinator for each COU subgroup and are organizing consensus meetings to harmonize the use and reporting of NfL measurements for the identified clinical applications. The results of these next steps will be presented.

AbstractThe last decade has seen a substantial increase in research focused on the identification of blood‐based biomarkers that have utility in Alzheimer's disease (AD). Blood‐based biomarkers have significant advantages of being time‐ and cost‐efficient as well as reduced invasiveness and increased patient acceptance. Despite these advantages and increased research efforts, the field has been hampered by lack of reproducibility and an unclear path for moving basic discovery toward clinical utilization. Here we reviewed the recent literature on blood‐based biomarkers in AD to provide a current state of the art. In addition, a collaborative model is proposed that leverages academic and industry strengths to facilitate the field in moving past discovery only work and toward clinical use. Key resources are provided. This new public‐private partnership model is intended to circumvent the traditional handoff model and provide a clear and useful paradigm for the advancement of biomarker science in AD and other neurodegenerative diseases.

BackgroundThe cerebrospinal fluid (CSF) biomarkers amyloid β (Aβ)‐42, total‐tau (T‐tau), and phosphorylated‐tau (P‐tau) demonstrate good diagnostic accuracy for Alzheimer's disease (AD). However, there are large variations in biomarker measurements between studies, and between and within laboratories. The Alzheimer's Association has initiated a global quality control program to estimate and monitor variability of measurements, quantify batch‐to‐batch assay variations, and identify sources of variability. In this article, we present the results from the first two rounds of the program.MethodsThe program is open for laboratories using commercially available kits for Aβ, T‐tau, or P‐tau. CSF samples (aliquots of pooled CSF) are sent for analysis several times a year from the Clinical Neurochemistry Laboratory at the Mölndal campus of the University of Gothenburg, Sweden. Each round consists of three quality control samples.ResultsForty laboratories participated. Twenty‐six used INNOTEST enzyme‐linked immunosorbent assay kits, 14 used Luminex xMAP with the INNO‐BIA AlzBio3 kit (both measure Aβ‐(1‐42), P‐tau(181P), and T‐tau), and 5 used Meso Scale Discovery with the Aβ triplex (AβN‐42, AβN‐40, and AβN‐38) or T‐tau kits. The total coefficients of variation between the laboratories were 13% to 36%. Five laboratories analyzed the samples six times on different occasions. Within‐laboratory precisions differed considerably between biomarkers within individual laboratories.ConclusionsMeasurements of CSF AD biomarkers show large between‐laboratory variability, likely caused by factors related to analytical procedures and the analytical kits. Standardization of laboratory procedures and efforts by kit vendors to increase kit performance might lower variability, and will likely increase the usefulness of CSF AD biomarkers.

Here, we review progress by the Penn Biomarker Core in the Alzheimer's Disease Neuroimaging Initiative (ADNI) toward developing a pathological cerebrospinal fluid (CSF) and plasma biomarker signature for mild Alzheimer's disease (AD) as well as a biomarker profile that predicts conversion of mild cognitive impairment (MCI) and/or normal control subjects to AD. The Penn Biomarker Core also collaborated with other ADNI Cores to integrate data across ADNI to temporally order changes in clinical measures, imaging data, and chemical biomarkers that serve as mileposts and predictors of the conversion of normal control to MCI as well as MCI to AD, and the progression of AD. Initial CSF studies by the ADNI Biomarker Core revealed a pathological CSF biomarker signature of AD defined by the combination of Aβ1‐42 and total tau (T‐tau) that effectively delineates mild AD in the large multisite prospective clinical investigation conducted in ADNI. This signature appears to predict conversion from MCI to AD. Data fusion efforts across ADNI Cores generated a model for the temporal ordering of AD biomarkers which suggests that Aβ amyloid biomarkers become abnormal first, followed by changes in neurodegenerative biomarkers (CSF tau, F‐18 fluorodeoxyglucose‐positron emission tomography, magnetic resonance imaging) with the onset of clinical symptoms. The timing of these changes varies in individual patients due to genetic and environmental factors that increase or decrease an individual's resilience in response to progressive accumulations of AD pathologies. Further studies in ADNI will refine this model and render the biomarkers studied in ADNI more applicable to routine diagnosis and to clinical trials of disease modifying therapies.