Challenges in Alzheimer's Disease Diagnostic Work-Up: Amyloid Biomarker Incongruences

The Association Between Positive Amyloid-PET and Cognitive Decline Is Not Always Supportive of Alzheimer's Disease: Suggestions from a Case Report

Amyloid-β deposition is the pathological hallmark of both cerebral amyloid angiopathy and Alzheimer's disease dementia, clinical conditions that can share cognitive decline and positive Amyloid-PET scan. A case is reported involving an 82-year-old Italian female who presented initially a memory deficit, later transient focal neurologic episodes, and finally two symptomatic lobar intracerebral hemorrhages. In light of these events, MRI and PET imaging findings, acquired before cerebral hemorrhages, are reconsidered and discussed, highlighting the utility of Amyloid-PET in supporting an in vivo diagnosis of cerebral amyloid angiopathy.

A data-driven approach to complement the A/T/(N) classification system using CSF biomarkers

AIMS

The AT(N) classification system not only improved the biological characterization of Alzheimer's disease (AD) but also raised challenges for its clinical application. Unbiased, data-driven techniques such as clustering may help optimize it, rendering informative categories on biomarkers' values.

METHODS

We compared the diagnostic and prognostic abilities of CSF biomarkers clustering results against their AT(N) classification. We studied clinical (patients from our center) and research (Alzheimer's Disease Neuroimaging Initiative) cohorts. The studied CSF biomarkers included Aβ(1-42), Aβ(1-42)/Aβ(1-40) ratio, tTau, and pTau.

RESULTS

The optimal solution yielded three clusters in both cohorts, significantly different in diagnosis, AT(N) classification, values distribution, and survival. We defined these three CSF groups as (i) non-defined or unrelated to AD, (ii) early stages and/or more delayed risk of conversion to dementia, and (iii) more severe cognitive impairment subjects with faster progression to dementia.

CONCLUSION

We propose this data-driven three-group classification as a meaningful and straightforward approach to evaluating the risk of conversion to dementia, complementary to the AT(N) system classification.

Cerebral amyloid load determination in a clinical setting: interpretation of amyloid biomarker discordances aided by tau and neurodegeneration measurements

BACKGROUND

Alzheimer's disease (AD) diagnosis can be hindered by amyloid biomarkers discordances.

OBJECTIVE

We aim to interpret discordances between amyloid positron emission tomography (Amy-PET) and cerebrospinal fluid (CSF) (Aβ₄₂ and Aβ_42/40), using Amy-PET semiquantitative analysis, [¹⁸F]fluorodeoxyglucose (FDG)-PET pattern, and CSF assays.

METHOD

Thirty-six subjects with dementia or mild cognitive impairment, assessed by neuropsychological tests, structural and functional imaging, and CSF assays (Aβ₄₂, Aβ_42/40, p-tau, t-tau), were retrospectively examined. Amy-PET and FDG-PET scans were analyzed by visual assessment and voxel-based analysis. SUVR were calculated on Amy-PET scans.

RESULTS

Groups were defined basing on the agreement among CSF Aβ₄₂ (A), CSF Aβ_42/40 Ratio (R), and Amy-PET (P) dichotomic results ( ±). In discordant groups, CSF assays, Amy-PET semiquantification, and FDG-PET patterns supported the diagnosis suggested by any two agreeing amyloid biomarkers. In groups with discordant CSF Aβ₄₂, the ratio always agrees with Amy-PET results, solving both false-negative and false-positive Aβ₄₂ results, with Aβ₄₂ levels close to the cut-off in A + R-P- subjects. The A + R + P- group presented high amyloid deposition in relevant areas, such as precuneus, posterior cingulate cortex (PCC) and dorsolateral frontal inferior cortex at semiquantitative analysis.

CONCLUSION

The amyloid discordant cases could be overcome by combining CSF Aβ₄₂, CSF ratio, and Amy-PET results. The concordance of any 2 out of the 3 biomarkers seems to reveal the remaining one as a false result. A cut-off point review could avoid CSF Aβ₄₂ false-negative results. The regional semiquantitative Amy-PET analysis in AD areas, such as precuneus and PCC, could increase the accuracy in AD diagnosis.