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P1–197: The Alzheimer's Disease Progression Score (ADPS) can predict the transition from MCI to Alzheimer's disease
Author(s) -
Jedynak Bruno,
Ye Zhou,
Lang Andrew,
Tang Runze,
Jedynak Pierre,
Prince Jerry
Publication year - 2013
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2013.05.420
Subject(s) - dementia , biomarker , disease , neuroimaging , medicine , oncology , alzheimer's disease neuroimaging initiative , cognitive impairment , alzheimer's disease , imaging biomarker , psychology , psychiatry , radiology , magnetic resonance imaging , biology , biochemistry
diagnostic group would also exhibit heterogeneity with possible clinical implications. Methods: 138 ADNI subjects diagnosed with amnestic mild cognitive impairment were clustered into four groups based on 11 baseline MRI, cerebrospinal fluid, and serum biomarkers. The clusters were characterized and then cluster membership was used as a predictor in regression models to determine whether there were differences between the groups with respect to longitudinal atrophy, cognitive trajectory, and time to conversion. Results: Four clusters emerged with distinct biomarker patterns. The first cluster (n1⁄420) was biologically difficult to distinguish from normal controls and could only be cognitively distinguished from normal controls on tests of memory (Figure 1). The first cluster performed substantially better than the rest of the mild cognitive impairment subjects on tests of cognitive function and rarely converted to Alzheimer’s disease during the observation period. The second and fourth clusters (n1⁄4 60, n1⁄47) had characteristics of early Alzheimer’s pathology, with more severe abnormalities and almost universal conversion to dementia in the fourth cluster. The third cluster (n 1⁄4 51) showed the most severe atrophy but had tau levels which were barely abnormal. Despite this unusual biomarker profile, a substantial proportion of the subjects in the third cluster converted to clinical Alzheimer’s disease at a rate that did not differ from the two presumed Alzheimer’s clusters. Conclusions: There is substantial biological heterogeneity among the ADNImild cognitive impairment subjects. Even subjects whowere clinically very similar and had the same rate of conversion to clinical Alzheimer’s disease showed a great deal of heterogeneity in their MRI and cerebrospinal fluid biomarkers.