There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Adrian Noriega de la Colina |
| Institution: | Université de Montréal |
| Department: | Biomedical Sciences |
| Country: | |
| Proposed Analysis: | On the basis of the classifications resulting from the linear SVM and HPS models, we will separate the participants with MCI into 3 groups: (i) high confidence, participants who were selected by the HPS model as hits; (ii) low confidence, participants who were selected by the linear SVM model as hits but were not selected by the HPS model; and (iii) negative, participants who were not selected as hits by either algorithm. To validate whether the high-confidence patients represented individuals who are in a prodromal phase of AD, we will test whether this subgroup was enriched for progression to dementia, apolipoprotein E ε4 (APOE4) carriers, females, and participants who are positive for Aβ and τ pathology. Positivity of AD pathology was determined by CSF measurements of Aβ 1–42 peptide and total τ with cut-off values of <192 and >93 pg/mL, respectively. We implemented Monte Carlo simulations, where we selected 100,000 random subgroups out of the original MCI sample. By comparing the proportion of progressors, APOE4 carriers, females, Aβ-positive, and τ -positive participants in these null replications with the actual observed values in the HPS subgroup, we estimate a P-value (1 sided for increase). A P-value <0.05 will be interpreted as evidence of a significant enrichment, and <0.001, as strong evidence. One-way analyses of variance will be used to evaluate differences between the HPS groupings with respect to age. Post hoc Tukey’s HSD tests were performed to assess pairwise differences amongst the 3 classes (high confidence, low confidence, negative). These tests were implemented in Python with the SciPy library, version 0.19.1, and StatsModels library, version 0.8.0. To explore the effect of HPS grouping on cognitive trajectories, linear mixed-effects models were performed to evaluate the main effects of and interactions between the HPS groups and time on ADAS13 scores up to 36 months of follow-up. The models were first fit with a random effect of the participant and then were fit with random slopes (time | participant) if analyses of variance comparing the likelihood ratio suggested a significant improvement in model fit. All tests will be performed separately on the ADNI1 and ADNI2 datasets. These tests were implemented in R, version 3.3.2, with the library nlme, version 3.1.128. |
| Additional Investigators |
