Update on the biomarker core of the Alzheimer's Disease Neuroimaging Initiative subjects

作者
John Q. Trojanowski,Hugo Vandeerstichele,Magdalena Korecka,Christopher M. Clark,Paul Aisen,Ronald C. Petersen,Kaj Blennow,Holly Soares,Adam J. Simon,Piotr Lewczuk,Robert A. Dean,Eric Siemers,William Z. Potter,Michael W. Weiner,Clifford R. Jack,William J. Jagust,Arthur W. Toga,Virginia M.‐Y. Lee,Leslie M. Shaw,Alzheimer's Disease Neuroimaging Initiative
出处
期刊:Alzheimers & Dementia [Wiley]
卷期号:6 (3): 230-238 被引量:314
标识
DOI:10.1016/j.jalz.2010.03.008
摘要

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 Abeta1-42 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 Abeta 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.

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