基于疾病进展模型的帕金森病患者认知障碍的时间排序
Carlos Platero1, José Ángel Pineda-Pardo2
1Health Science Technology Group, Technical University of Madrid, 28012, Madrid, Spain.
Parkinsonism & related disorders
|November 3, 2024
概括
疾病进展模型 (DPM) 可以使用生物标志物预测帕金森病 (PD) 患者的认知衰退. 这些模型估计了痴呆症的时间表,显示粉样蛋白病理在许多情况下先于认知障碍.
科学领域:
- 神经学 神经学
- 生物标志物 生物标志物
- 机器学习 机器学习
背景情况:
- 识别有认知能力下降风险的帕金森病 (PD) 患者对于有效的临床干预至关重要.
- 现有的PD认知衰退预测模型是有限的.
- 疾病进展模型 (DPM) 提供了一个新的数据驱动框架,以了解PD演变.
研究的目的:
- 开发和验证用于预测PD认知衰退的机器学习框架 (DPM).
- 为了确定DPM的最佳生物标志物组合.
- 在PD中估计从认知障碍转化到痴呆的时间表.
主要方法:
- 利用了来自帕金森病进展标记计划 (PPMI) 的423名PD患者和196名健康对照者的数据.
- 在基线和每年收集运动,神经认知和神经成像数据.
- 通过选择最佳生物标志物组合来开发DPM,以获得预测准确度.
主要成果:
- DPM框架准确地确定了PD患者在五年内面临认知能力下降的高风险.
- 建立了认知障碍到痴呆症进展的时间表.
- 发现粉样蛋白病理没有影响PD患者认知障碍的进展.
结论:
- 神经心理学测量和生物标志物,如大脑脊髓液 (CSF) 粉样蛋白β 42 (Aβ42) 和多巴胺载体缺陷,预测PD的认知衰退.
- 粉样蛋白病理往往在PD患者的痴呆症发病之前.
- 在PD中,CSF Aβ42和酸化的形状可能与老化和阿尔茨海默病患者的形状不同.
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