• Langue : Français
• Discipline : Médecine. Neurologie
• Identifiant : 2019LILUM071
• Type de thèse : Doctorat de médecine
• Date de soutenance : 19/04/2019

Résumé en langue originale

Alzheimer's disease (AD) is a heterogeneous condition characterized by a long course and a variable rate of cognitive decline (CD). Factors modulating AD progression remain largely unknown. Our objectives were to determine the trajectories of CD from the prodromal stage and the demographical, clinical and biochemical factors associated with each trajectory. Methods: We collected data from a large multicentric memory clinic cohort of AD patients followed between 1997 and 2014. Inclusion criteria were as follows: Mini-mental state examination (MMSE) score 26 at first referral; 5 available MMSE scores during follow-up; final diagnosis of AD. We used a latent-process mixed model analysis to model trajectories of CD. We then focused on the subgroup of AD patients followed in a tertiary Memory Research and Resource Center (MRRC), for whom comprehensive clinical data were available, to look for the patient characteristics at baseline that differed between trajectories. Results: We included a total of 1681 AD patients, of whom 343 were followed in the MRRC. Mean age at referral was 74.6 ± 7.0 years old, 65.2% were women, 26.7% were high educated. The latentprocess mixed model analysis identified two distinct trajectories of CD: a slowly progressive (sp) group (80.8% of patients; -1.34 ! -0.88 MMSE points/year) and a rapidly progressive (rp) group (19.2%; -4.13 ! 1.48 MMSE points/year). The rp group comprised more women (71.1% vs. 63.8%, p = 0.0131). The same dual trajectory pattern was found in the MRRC subgroup. Z-scores of psychometric tests performed at first referral were significantly lower in rp group than in the sp group on memory (Z= -2.636; p < 0.01), executive and attention (Z= -3.181: p < 0.001), and visuo-construction functions (Z= -3.109; p < 0.005). Conclusion: Our data supports the existence of two AD variants characterized by different progression rates. Female gender and neuropsychological data seemed to be the best predictors of rp decline. Early identification of rpAD would contribute to improve clinical care and research.