Philip Scheltens

Injury Markers but not Amyloid Markers are Associated with Rapid Progression from Mild Cognitive Impairment to Dementia in Alzheimer's Disease

Alzheimers disease (AD) is a common cause of mild cognitive impairment (MCI). However, the time between the diagnosis of MCI and the diagnosis of dementia is highly variable. In this study we investigated which known risk factors and biomarkers of AD pathology were associated with rapid progression from MCI to dementia. Of the 203 subjects with MCI, 91 progressed to AD-type dementia and were considered to have MCI-AD at baseline. Subjects with MCI-AD were older, more frequently female and carrier of the APOE-ε4 allele, had lower scores on the Mini-Mental State Examination (MMSE), more medial temporal lobe atrophy (MTA) and lower levels of Aβ1-42 and increased levels of t-tau and p-tau in the cerebrospinal fluid (CSF) compared to subjects without AD-type dementia at follow up. Of the 91 subjects with MCI-AD, we had data available of CSF (n = 56), MTA (n = 76), and APOE-genotype (n = 63). Among the subjects with MCI-AD, MTA (hazard ratio (HR) 2.2, p = 0.004) and low MMSE score (HR 2.0 p = 0.007) were associated with rapid progression to dementia. High CSF t-tau (HR 1.7, p = 0.07) and p-tau (1.7, p = 0.08) tended to be associated with rapid progression to dementia. CSF Aβ1-42, APOE status, age, gender, and educational level were not associated with time to dementia. Our findings implicate a different role for biomarkers in diagnosis and prognosis of MCI-AD. While amyloid markers can be used to identify MCI-AD, injury markers may predict rapid progression to dementia.

Single-Domain Amnestic Mild Cognitive Impairment Identified by Cluster Analysis Predicts Alzheimer's Disease in the European Prospective DESCRIPA Study

Background/Aims: To identify prodromal Alzheimers disease (AD) subjects using a data-driven approach to determine cognitive profiles in mild cognitive impairment (MCI). Methods: A total of 881 MCI subjects were recruited from 20 memory clinics and followed for up to 5 years. Outcome measures included cognitive variables, conversion to AD, and biomarkers (e.g. CSF, and MRI markers). Two hierarchical cluster analyses (HCA) were performed to identify clusters of subjects with distinct cognitive profiles. The first HCA included all subjects with complete cognitive data, whereas the second one selected subjects with very mild MCI (MMSE ≥28). ANOVAs and ANCOVAs were computed to examine whether the clusters differed with regard to conversion to AD, and to AD-specific biomarkers. Results: The HCAs identified 4-cluster solutions that best reflected the sample structure. One cluster (aMCIsingle) had a significantly higher conversion rate (19%), compared to subjective cognitive impairment (SCI, p < 0.0001), and non-amnestic MCI (naMCI, p = 0.012). This cluster was the only one showing a significantly different biomarker profile (Aβ42, t-tau, APOE ε4, and medial temporal atrophy), compared to SCI or naMCI. Conclusion: In subjects with mild MCI, the single-domain amnestic MCI profile was associated with the highest risk of conversion, even if memory impairment did not necessarily cross specific cut-off points. A cognitive profile characterized by isolated memory deficits may be sufficient to warrant applying prevention strategies in MCI, whether or not memory performance lies below specific z-scores. This is supported by our preliminary biomarker analyses. However, further analyses with bigger samples are needed to corroborate these findings.