Clark, Christopher M.

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.