Martinez-Torteya Antonio, Gomez-Rueda Hugo, Trevino Victor, Farber Joshua, Tamez-Pena Jose
Departamento de Ingenieria, Division de Ingenieria y Tecnologias, Universidad de Monterrey, Morones Prieto 4500 Pte., 66238 San Pedro Garza Garcia, NL, Mexico.
Escuela de Medicina, Tecnologico de Monterrey, Morones Prieto 2916 Pte., Del Carmen, 64710 Monterrey, NL, Mexico.
Curr Alzheimer Res. 2018;15(8):751-763. doi: 10.2174/1567205015666180202095616.
Diagnosing Alzheimer's disease (AD) in its earliest stages is important for therapeutic and support planning. Similarly, being able to predict who will convert from mild cognitive impairment (MCI) to AD would have clinical implications.
The goals of this study were to identify features from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database associated with the conversion from MCI to AD, and to characterize the temporal evolution of that conversion.
We screened the publically available ADNI longitudinal database for subjects with MCI who have developed AD (cases: n=305), and subjects with MCI who have remained stable (controls: n=250). Analyses included 1,827 features from laboratory assays (n=12), quantitative MRI scans (n=1,423), PET studies (n=136), medical histories (n=72), and neuropsychological tests (n=184). Statistical longitudinal models identified features with significant differences in longitudinal behavior between cases and matched controls. A multiple-comparison adjusted log-rank test identified the capacity of the significant predictive features to predict early conversion.
411 features (22.5%) were found to be statistically different between cases and controls at the time of AD diagnosis; 385 features were statistically different at least 6 months prior to diagnosis, and 28 features distinguished early from late conversion, 20 of which were obtained from neuropsychological tests. In addition, 69 features (3.7%) had statistically significant changes prior to AD diagnosis.
Our results characterized features associated with disease progression from MCI to AD, and, in addition, the log-rank test identified features which are associated with the risk of early conversion.
在阿尔茨海默病（AD）的最早阶段进行诊断对于治疗和支持计划至关重要。同样，能够预测谁将从轻度认知障碍（MCI）转变为AD也具有临床意义。
本研究的目标是从阿尔茨海默病神经影像学倡议（ADNI）数据库中识别与从MCI转变为AD相关的特征，并描述这种转变的时间演变。
我们在公开可用的ADNI纵向数据库中筛选出已发展为AD的MCI受试者（病例：n = 305）和保持稳定的MCI受试者（对照：n = 250）。分析包括来自实验室检测（n = 12）、定量MRI扫描（n = 1,423）、PET研究（n = 136）、病史（n = 72）和神经心理学测试（n = 184）的1,827个特征。统计纵向模型识别出病例组和匹配对照组之间纵向行为有显著差异的特征。多重比较调整后的对数秩检验确定了显著预测特征预测早期转变的能力。
在AD诊断时，发现411个特征（22.5%）在病例组和对照组之间存在统计学差异；385个特征在诊断前至少6个月存在统计学差异，28个特征可区分早期和晚期转变，其中20个特征来自神经心理学测试。此外，69个特征（3.7%）在AD诊断前有统计学显著变化。
我们的结果描述了与从MCI到AD的疾病进展相关的特征，此外，对数秩检验识别出了与早期转变风险相关的特征。
