Clément Abi Nader, Ribaldi Federica, Frisoni Giovanni B, Garibotto Valentina, Robert Philippe, Ayache Nicholas, Lorenzi Marco
Université Côte d'Azur, Inria Sophia Antipolis, Epione Research Project, Sophia-Antipolis, France.
Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, Hospitals and University of Geneva, Geneva, Switzerland.
Neurobiol Aging. 2022 May;113:73-83. doi: 10.1016/j.neurobiolaging.2021.12.015. Epub 2022 Feb 23.
SimulAD is a computational disease progression model (DPM) originally developed on the ADNI database to simulate the evolution of clinical and imaging markers characteristic of AD, and to quantify the disease severity (DS) of a subject. In this work, we assessed the validity of this estimated DS, as well as the generalization of the DPM., by applying SimulAD on a new cohort from the Geneva Memory Center (GMC). The differences between the estimated DS of healthy, mild cognitive impairment and AD dementia groups were statistically significant (p-values < 0.05; d ≥ 0.8). DS correlated with MMSE (ρ = -0.55), hippocampal atrophy (ρ = -0.62), glucose hypometabolism (ρ = -0.67), amyloid burden (ρ = 0.31) and tau deposition (ρ = 0.62) (p-values < 0.01). Based on the dynamics estimated on the ADNI cohort, we simulated a DPM for the subjects of the GMC cohort. The difference between the temporal evolution of similar biomarkers simulated on the ADNI and GMC cohorts remained below 10%. This study illustrates the robustness and good generalization of SimulAD, highlighting its potential for clinical and pharmaceutical studies.
SimulAD是一种计算疾病进展模型（DPM），最初基于阿尔茨海默病神经影像学倡议（ADNI）数据库开发，用于模拟阿尔茨海默病（AD）临床和影像学标志物的演变，并量化受试者的疾病严重程度（DS）。在这项研究中，我们通过将SimulAD应用于来自日内瓦记忆中心（GMC）的一个新队列，评估了这种估计的DS的有效性以及DPM的泛化能力。健康、轻度认知障碍和AD痴呆组估计的DS之间的差异具有统计学意义（p值<0.05；效应量d≥0.8）。DS与简易精神状态检查表（MMSE）（ρ = -0.55）、海马萎缩（ρ = -0.62）、葡萄糖代谢减退（ρ = -0.67）、淀粉样蛋白负荷（ρ = 0.31）和tau蛋白沉积（ρ = 0.62）相关（p值<0.01）。基于在ADNI队列上估计的动态变化，我们为GMC队列的受试者模拟了一个DPM。在ADNI和GMC队列上模拟的相似生物标志物的时间演变差异保持在10%以下。这项研究说明了SimulAD的稳健性和良好的泛化能力，突出了其在临床和药物研究中的潜力。
