Department of Biomedical Engineering and Informatics, Indiana University Luddy School of Informatics, Computing and Engineering, Indianapolis, Indiana, USA.
Department of Biomedical Engineering and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Alzheimers Dement. 2024 Nov;20(11):7819-7830. doi: 10.1002/alz.14244. Epub 2024 Sep 17.
Alzheimer's disease (AD) initiates years prior to symptoms, underscoring the importance of early detection. While amyloid accumulation starts early, individuals with substantial amyloid burden may remain cognitively normal, implying that amyloid alone is not sufficient for early risk assessment.
Given the genetic susceptibility of AD, a multi-factorial pseudotime approach was proposed to integrate amyloid imaging and genotype data for estimating a risk score. Validation involved association with cognitive decline and survival analysis across risk-stratified groups, focusing on patients with mild cognitive impairment (MCI).
Our risk score outperformed amyloid composite standardized uptake value ratio in correlation with cognitive scores. MCI subjects with lower pseudotime risk score showed substantial delayed onset of AD and slower cognitive decline. Moreover, pseudotime risk score demonstrated strong capability in risk stratification within traditionally defined subgroups such as early MCI, apolipoprotein E (APOE) ε4+ MCI, APOE ε4- MCI, and amyloid+ MCI.
Our risk score holds great potential to improve the precision of early risk assessment.
Accurate early risk assessment is critical for the success of clinical trials. A new risk score was built from integrating amyloid imaging and genetic data. Our risk score demonstrated improved capability in early risk stratification.
阿尔茨海默病（AD）在出现症状前多年就已开始，这凸显了早期检测的重要性。虽然淀粉样蛋白的积累很早就开始了，但有大量淀粉样蛋白负担的个体可能仍然认知正常，这意味着淀粉样蛋白本身不足以进行早期风险评估。
鉴于 AD 的遗传易感性，提出了一种多因素拟时间方法，用于整合淀粉样蛋白成像和基因型数据来估计风险评分。验证涉及与认知下降的关联以及跨风险分层组的生存分析，重点是轻度认知障碍（MCI）患者。
我们的风险评分在与认知评分的相关性方面优于淀粉样蛋白复合标准化摄取比值。具有较低拟时间风险评分的 MCI 患者表现出 AD 的发病显著延迟和认知下降更慢。此外，拟时间风险评分在传统定义的亚组（如早期 MCI、载脂蛋白 E（APOE）ε4+MCI、APOE ε4-MCI 和淀粉样蛋白+MCI）内的风险分层中具有很强的能力。
我们的风险评分具有提高早期风险评估准确性的巨大潜力。
准确的早期风险评估对于临床试验的成功至关重要。从整合淀粉样蛋白成像和遗传数据构建了一个新的风险评分。我们的风险评分在早期风险分层方面表现出更好的能力。
