外围风险因素及其在社区中基于生物标志物的痴呆症查中的作用
Yi-Han Hu1, Osorio Meirelles1, Eric J Shiroma1
1Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, Maryland, USA.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 24, 2024
概括
外围风险因素 (PRF) 与痴呆症等血生物标志物 (如GFAP和NfL) 有关. 纳入这些因素可以轻微提高痴呆症预测的准确性,强调它们在评估神经退行性疾病风险方面的重要性.
科学领域:
- 神经科学是一个神经科学.
- 生物标志物研究 生物标志物研究
- 老年学是一门学科.
背景情况:
- 外围风险因素 (PRFs) 可能反映系统性健康,而不是直接的脑病理.
- 血生物标志物,如质纤维酸性蛋白 (GFAP),神经丝光链 (NfL) 和总tau,正在研究痴呆症预测.
- 了解外围因素和这些生物标志物之间的相互作用对于准确的痴呆症评估至关重要.
研究的目的:
- 探索外围风险因素和痴呆症等离子体生物标志物 (GFAP,NfL,总tau) 之间的关联.
- 评估这些协会在预测未来痴呆症中的作用.
- 使用机器学习识别影响神经退行性生物标志物水平的关键外围因素.
主要方法:
- 利用了来自年龄,基因/环境敏感性-雷克雅未克研究 (2002-2015年) 的数据,其中有4353名参与者 (平均年龄76.6岁).
- 在910名参与者的子样本中,分析了他们的PRF和血生物标志物.
- 305个社会人口学,临床,实验室,感官和生活方式变量被分组成34个集群进行分析.
主要成果:
- 在血生物标志物和与血红蛋白,红细胞分布和炎症相关的集群之间发现了显著的关联,超出了年龄和eGFR.
- 将这些外围因素集群纳入预测模型,提高了痴呆症生物标志物的精度和灵敏度.
- 观察到整体预测准确度的适度改善 (例如,GFAP AUC从0.17增加到0.34).
结论:
- 外围风险因素与痴呆症等离子体生物标志物有显著的关联.
- 考虑外围因素可以提高痴呆症生物标志物的预测准确度.
- 机器学习确定了血红蛋白和红细胞分布集群作为影响神经退行性生物标志物的关键外围因素,适度改善了发生痴呆症的预测.
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