An Algorithm for Preclinical Diagnosis of Alzheimer's Disease

Abstract

Almost all Alzheimer's disease (AD) therapeutic trials have failed in recent years. One of the main reasons for failure is due to designing the disease-modifying clinical trials at the advanced stage of the disease when irreversible brain damage has already occurred. Diagnosis of the preclinical stage of AD and therapeutic intervention at this phase, with a perfect target, are key points to slowing the progression of the disease. Various AD biomarkers hold enormous promise for identifying individuals with preclinical AD and predicting the development of AD dementia in the future, but no single AD biomarker has the capability to distinguish the AD preclinical stage. A combination of complimentary AD biomarkers in cerebrospinal fluid (Aβ₄₂, tau, and phosphor-tau), non-invasive neuroimaging, and genetic evidence of AD can detect preclinical AD in the in-vivo ante mortem brain. Neuroimaging studies have examined region-specific cerebral blood flow (CBF) and microstructural changes in the preclinical AD brain. Functional MRI (fMRI), diffusion tensor imaging (DTI) MRI, arterial spin labeling (ASL) MRI, and advanced PET have potential application in preclinical AD diagnosis. A well-validated simple framework for diagnosis of preclinical AD is urgently needed. This article proposes a comprehensive preclinical AD diagnostic algorithm based on neuroimaging, CSF biomarkers, and genetic markers.

Keywords: Alzheimer's disease; CSF; diagnosis; differential; neuroimaging (anatomic and functional); preclinical Alzheimer's disease.

Figure 1

A hypothetical model for detecting preclinical Alzheimer's disease (AD). Disease severity increases with aging, the major risk factor for an AD. Two disease trajectories represent brain morphology changes (red) and clinical AD symptoms (blue). Neurodegeneration due to aging shown by the broken black line. The model shows the hypothetical deviation of the changes in brain morphology trajectory and symptoms trajectory, and where they cross a horizontal line of disease detectability. The preclinical AD can be detected before the onset of AD symptoms (modified from Khan, 2016).

Figure 2

A simple framework for comprehensive diagnosis preclinical Alzheimer's disease (AD). The framework includes three diagnostic modalities: neuroimaging to detect the earliest evidence of neurodegeneration in brain areas susceptible to AD pathology, genetic markers associated with an AD, and biomarker testing to detect abnormalities associated with an AD.