Department of Applied Math and Statistics, Johns Hopkins University, Baltimore, MD 21218, USA.
Neuroimage. 2012 Nov 15;63(3):1478-86. doi: 10.1016/j.neuroimage.2012.07.059. Epub 2012 Aug 3.
While neurodegenerative diseases are characterized by steady degeneration over relatively long timelines, it is widely believed that the early stages are the most promising for therapeutic intervention, before irreversible neuronal loss occurs. Developing a therapeutic response requires a precise measure of disease progression. However, since the early stages are for the most part asymptomatic, obtaining accurate measures of disease progression is difficult. Longitudinal databases of hundreds of subjects observed during several years with tens of validated biomarkers are becoming available, allowing the use of computational methods. We propose a widely applicable statistical methodology for creating a disease progression score (DPS), using multiple biomarkers, for subjects with a neurodegenerative disease. The proposed methodology was evaluated for Alzheimer's disease (AD) using the publicly available AD Neuroimaging Initiative (ADNI) database, yielding an Alzheimer's DPS or ADPS score for each subject and each time-point in the database. In addition, a common description of biomarker changes was produced allowing for an ordering of the biomarkers. The Rey Auditory Verbal Learning Test delayed recall was found to be the earliest biomarker to become abnormal. The group of biomarkers comprising the volume of the hippocampus and the protein concentration amyloid beta and Tau were next in the timeline, and these were followed by three cognitive biomarkers. The proposed methodology thus has potential to stage individuals according to their state of disease progression relative to a population and to deduce common behaviors of biomarkers in the disease itself.
虽然神经退行性疾病的特征是在相对较长的时间内稳定退化，但人们普遍认为，在发生不可逆转的神经元丧失之前，早期阶段是最有希望进行治疗干预的。开发治疗反应需要对疾病进展进行精确测量。然而，由于早期阶段在很大程度上是无症状的，因此很难获得疾病进展的准确测量。具有数百个经过数年观察并具有数十个经过验证的生物标志物的纵向数据库正在变得可用，从而允许使用计算方法。我们提出了一种广泛适用的统计方法，用于使用多个生物标志物为患有神经退行性疾病的受试者创建疾病进展评分 (DPS)。使用公开的 AD 神经影像学倡议 (ADNI) 数据库评估了该方法在阿尔茨海默病 (AD) 中的应用，为数据库中的每个受试者和每个时间点生成了阿尔茨海默病 DPS 或 ADPS 评分。此外，还生成了生物标志物变化的通用描述，允许对生物标志物进行排序。Rey 听觉言语学习测试延迟回忆被发现是最早出现异常的生物标志物。接下来是包含海马体体积和蛋白质浓度β淀粉样蛋白和 Tau 的一组生物标志物，然后是三个认知生物标志物。因此，该方法有可能根据个体相对于人群的疾病进展状态对其进行分期，并推断疾病本身中生物标志物的常见行为。
