Blennow, Kaj

Abstract During the past decade, a conceptual shift occurred in the field of Alzheimer's disease (AD) considering the disease as a continuum. Thanks to evolving biomarker research and substantial discoveries, it is now possible to identify the disease even at the preclinical stage before the occurrence of the first clinical symptoms. This preclinical stage of AD has become a major research focus as the field postulates that early intervention may offer the best chance of therapeutic success. To date, very little evidence is established on this “silent” stage of the disease. A clarification is needed about the definitions and lexicon, the limits, the natural history, the markers of progression, and the ethical consequence of detecting the disease at this asymptomatic stage. This article is aimed at addressing all the different issues by providing for each of them an updated review of the literature and evidence, with practical recommendations.

AbstractIntroductionWe describe Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1–42), t‐tau, and p‐tau181 analytical performance, definition of Alzheimer's disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids.MethodsReview publications authored or coauthored by ADNI Biomarker core faculty and selected non‐ADNI studies to deepen the understanding and interpretation of CSF Aβ1–42, t‐tau, and p‐tau181 data.ResultsCSF AD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non‐ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies.DiscussionFurther studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease‐modifying therapeutic trials.

Abstract The lack of readily available biomarkers is a significant hindrance toward progressing to effective therapeutic and preventative strategies for Alzheimer's disease (AD). Blood‐based biomarkers have potential to overcome access and cost barriers and greatly facilitate advanced neuroimaging and cerebrospinal fluid biomarker approaches. Despite the fact that preanalytical processing is the largest source of variability in laboratory testing, there are no currently available standardized preanalytical guidelines. The current international working group provides the initial starting point for such guidelines for standardized operating procedures (SOPs). It is anticipated that these guidelines will be updated as additional research findings become available. The statement provides (1) a synopsis of selected preanalytical methods utilized in many international AD cohort studies, (2) initial draft guidelines/SOPs for preanalytical methods, and (3) a list of required methodological information and protocols to be made available for publications in the field to foster cross‐validation across cohorts and laboratories.

AbstractTo address the pending public health crisis due to Alzheimer's disease (AD) and related neurodegenerative disorders, the Marian S. Ware Alzheimer Program at the University of Pennsylvania held a meeting entitled “State of the Science Conference on the Advancement of Alzheimer's Diagnosis, Treatment and Care,” on June 21‐22, 2012. The meeting comprised four workgroups focusing on Biomarkers; Clinical Care and Health Services Research; Drug Development; and Health Economics, Policy, and Ethics. The workgroups shared, discussed, and compiled an integrated set of priorities, recommendations, and action plans, which are presented in this article.

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.

Background Different cerebrospinal fluid (CSF) amyloid-beta 1–42 (A β 1–42 ), total Tau (Tau) and Tau phosphorylated at threonine 181 (P-Tau) levels are reported, but currently there is a lack of quality control programmes. The aim of this study was to compare the measurements of these CSF biomarkers, between and within centres. Methods Three CSF-pool samples were distributed to 13 laboratories in 2004 and the same samples were again distributed to 18 laboratories in 2008. In 2004 six laboratories measured A β 1–42 , Tau and P-Tau and seven laboratories measured one or two of these marker(s) by enzyme-linked immunosorbent assays (ELISAs). In 2008, 12 laboratories measured all three markers, three laboratories measured one or two marker(s) by ELISAs and three laboratories measured the markers by Luminex. Results In 2004, the ELISA intercentre coefficients of variance (interCV) were 31%, 21% and 13% for A β 1–42 , Tau and P-Tau, respectively. These were 37%, 16% and 15%, respectively, in 2008. When we restricted the analysis to the Innotest ® ( N = 13) for A β 1–42 , lower interCV were calculated (22%). The centres that participated in both years ( N = 9) showed interCVs of 21%, 15% and 9% and intra-centre coefficients (intraCV) of variance of 25%,18% and 7% in 2008. Conclusions The highest variability was found for A β 1–42 . The variabilities for Tau and P-Tau were lower in both years. The centres that participated in both years showed a high intraCV comparable to their interCV, indicating that there is not only a high variation between but also within centres. Besides a uniform standardization of (pre)analytical procedures, the same assay should be used to decrease the inter/intracentre variation.