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: | Jeremie Lespinasse |
| Institution: | University of Bordeaux |
| Department: | ISPED (School of Public Health) |
| Country: | |
| Proposed Analysis: | Pathways to Alzheimer’s disease and related dementia are characterized by a progressive alteration of many biomarkers but data heterogeneity in longitudinal studies makes it challenging to identify the temporality of these marker changes. We considered a multivariate mixed model to analyze the repeated measures of biomarkers including cognition, brain neuroimaging and CSF levels of amyloid and tau in a French clinical cohort, the MEMENTO cohort (Dufouil et al. 2017), in which individuals with either mild cognitive impairment and/or subjective cognitive complaints have been followed over 5 years. To apprehend the underlying temporal heterogeneity of multimodal disease markers changes, the model included a latent disease time as the timescale of interest. It was based on individual random time-shift and random time-speed. Previous authors have used more or less similar methodology in order to stage individuals and study the progression of the disease according to the latent disease time. As most of them relied on the ADNI data (Li et al. 2018, Lorenzi et al. 2019, Bilgel et al. 2019), we would like to compare the results we found on the MEMENTO cohort with those we would obtain on the ADNI data. Indeed, despite differences according to the study design, the Memento cohort is a large clinical study similar to ADNI in many ways and it seems crucial to better understand how much the specification of the multivariate mixed model, the study design and the characteristics of the individuals can affect the results regarding the prediction of the disease progression and the sequence of marker impairments. 1. Dufouil, C. et al. Cognitive and imaging markers in non-demented subjects attending a memory clinic: Study design and baseline findings of the MEMENTO cohort. Alzheimer’s Res. Ther. 9, 1–13 (2017). 2. Li, D. et al. Bayesian latent time joint mixed-effects model of progression in the Alzheimer’s Disease Neuroimaging Initiative. Alzheimer’s Dement. Diagnosis, Assess. Dis. Monit. 10, 657–668 (2018). 3. Lorenzi, M., Filippone, M., Frisoni, G. B., Alexander, D. C. & Ourselin, S. Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer’s disease. Neuroimage 190, 56-68 (2019). 4. Bilgel, M. & Jedynak, B. M. Predicting time to dementia using a quantitative template of disease progression. Alzheimer’s Dement. Diagnosis, Assess. Dis. Monit. 11, 205–215 (2019). |
| Additional Investigators |
