Perspectives for multimodal neurochemical and imaging biomarkers in Alzheimer's disease.

Abstract

The diagnosis of Alzheimer's disease (AD) is presently going through a paradigm shift from disease categories to dimensions and toward the implementation of biomarkers to support identification of predementia and even preclinical asymptomatic stages of the disease. We outline the methodological basis of presently available biomarkers and technological methodologies in AD, including exploratory and hypothesis-based plasma and blood candidates, cerebrospinal fluid markers of amyloid load and axonal destruction, and imaging markers of amyloid deposition, synaptic dysfunction, cortical functional and structural disconnection, and regional atrophy. We integrate biomarker findings into a comprehensive model of AD pathogenesis from healthy aging to cognitive decline, the resilience to cerebral amyloid load (RECAL) matrix. The RECAL framework integrates factors of risk and resilience to cerebral amyloid load for individual risk prediction. We show the clinical consequences when the RECAL matrix is operationalized into a diagnostic algorithm both for individual counseling of subjects and for the identification of at risk samples for primary and secondary preventive trials. We discuss the implication of biomarkers for the identification of prodromal AD for the primary care system that seems presently not even prepared to cope with the increasing number of subjects afflicted with late stage AD dementia, let alone future cohorts of subjects searching counseling or treatment of predementia and asymptomatic stages of AD. The paradigm shift in AD diagnosis and its operationalization into a diagnostic framework will have major implications for our understanding of disease pathogenesis. Now, for the first time, we have access to in vivo markers of key events in AD pathogenesis integrated into a heuristic framework that makes strong predictions on pattern of multimodal biomarkers in different stages of AD. Critical testing of these predictions will help us to modify or even falsify the currently hold assumptions on the pathogenesis of AD based on in vivo evidence in humans.