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Non-Alzheimer’s disease pathophysiology in the elderly

Prof. Philip Scheltens, Amsterdam UMC, the Netherlands
EAN 2020
Primary central nervous system pathologies leading to cognitive decline include a variety of only partially known conditions that can coexist to various extents with Alzheimer’s disease (AD) pathology. Availability of biomarkers as well as clinical profiling is still limited. In a lecture, Prof. Philip Scheltens (Amsterdam UMC, the Netherlands) focused on suspected non-Alzheimer’s disease pathophysiology (SNAP) [1].

Prof. Scheltens explained that SNAP is a biomarker-based concept denoting AD-like neurodegeneration in individuals without β-amyloidosis. Its prevalence is 20-30% in cognitive healthy individuals; it accounts for 20-40% of patients presenting to memory clinics. SNAP may be caused by cerebrovascular disorders, mixed pathologies (dementia with Lewy bodies, frontotemporal lobar degeneration), or non-AD neurodegeneration, such as primary age-related tauopathy (PART) and limbic-predominant age-related TDP-43 encephalopathy (LATE).

In the ATN system of the National Institute on Ageing-Alzheimer's Association (NIA-AA), 8 major AD biomarkers are divided into 3 pathophysiology-based binary categories. “A” refers to the value of a β-amyloid biomarker (amyloid-PET or cerebrospinal fluid [CSF] Aβ1-42); “T,” the value of a tau biomarker (CSF phosphorylated tau, or tau-PET); and “N,” biomarkers of neurodegeneration or neuronal injury ([18F]-fluorodeoxyglucose-PET, structural MRI, CSF total tau, or neurofilament light chain).

AD risk in individuals with SNAP or with A-T-N- is almost equal. In individuals with mild cognitive impairment (MCI), however, SNAP predicts progression to AD, with a highly variable percentage. In a Dutch study, 3-year progression from SNAP with MCI to AD was 24%, 4 times higher than cognitive healthy individuals [2].

Prof. Scheltens argued that the concept of SNAP is still useful, but that it is now referred to as “non-AD pathophysiology”. This concept is part of a research framework (see Table) proposed by the NIA-AA to define AD pathologies based on ATN profiles [3].

Table. ATN-profiles and corresponding biomarker categories [3].

Table. ATN-profiles and corresponding biomarker categories [3].

1. Scheltens F. Symposium SYMP08, EAN 2020.

2. Vos SJB, et al. Brain. 2015;138(Pt 5):1327-38.

3. Jack Jr CR, et al. Alzheimers Dement. 2018;14(4):535-62.

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