COGNITIVE TRAJECTORY ANALYSIS IN PATIENTS WITH MILD COGNITIVE IMPAIRMENTS DUE TO ALZHEIMER’S DISEASE

Abstract

Background: Previous studies have shown that 40-60% of mild cognitive impairment (MCI) patients are Aß positive (Aß +) on PET. However, there were few studies investigating cognitive trajectories of MCI due to AD using hypothesis-driven analysis. It would thus enable identification, summarization and communication of complex prognostic factors in longitudinal data. We identified several distinct cognitive trajectories based on longitudinal performance inMCI due to AD. Furthermore, we compared clinical features, genotypes and neuroimaging domain among subgroups classified by trajectory analysis and identified which profiles might predict MCI due to AD with poor prognosis.Methods: We used the Alzheimer’s Disease Neuroimaging Initiative (ADNI) amyloid positiveMCI patients (n1⁄4238) who underwent neuropsychological test follow-up at least three times to identify cognitive trajectories. To assess replicability, the sample was randomly divided into two subsamples of the same size (n1⁄4119), group-based trajectory analyses (GBTA) were performed to classify distinct groups based on ADAS-Cog 13 score over time. Potential predictive factors (APOE4 genotype, FDG PET SUVR, 18F-florbetapir (AV45) PET SUVR, CSF biomarkers including Ab, total tau (t-tau) and phosphorylated tau (p-tau), and brain image volume including whole brain, hippocampus, ventricle, entorhinal cortex, fusiform, and mid temporal gyrus) were analyzed among distinct groups. Results: Three distinct classes (slow-decliners, intermediate-decliners, and fast-decliners) each with linear trend were suggested. The mean age of two subsamples was lower in the slower-decliners than in the intermediate-decliners (p<0.05). APOE4 carrier (p1⁄40.004) was associated with fast-decliners and ventricle volume (p<0.001) was the smallest in the slow-decliners. In a comparison of potential predictive factors, FDG PET (p<0.001), AV45 PET SUVR (p<0.001), CSF Ab (p<0.001), CSF t-tau (p<0.05) and ptau (p<0.05), hippocampus volume ((p<0.001), entorhinal cortex volume (p<0.05), and mid temporal gyrus volume (p<0.05) were more associated with faster-decliners than slow-decliners in two subsamples.Conclusions: GBTA inMCI due to AD patients showed three distinct classes of cognitive trajectories, even in the same Aß + patients. We suggest predictive factors as showing associated factors with being classified faster-decliners in two subsamples. Prediction for rapid cognitive deterioration in MCI due to AD patients could provide precision medicine.