使用尿金属和人口统计数据预测老年人认知障碍的机器学习框架。

IF 2.8 3区 生物学 Q2 GENETICS & HEREDITY
Frontiers in Genetics Pub Date : 2025-06-25 eCollection Date: 2025-01-01 DOI:10.3389/fgene.2025.1631228
Fengchun Ren, Xiao Zhao, Qin Yang, Huaqiang Liao, Yudong Zhang, Xuemei Liu
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引用次数: 0

摘要

引言:老年人的认知障碍是一个重大的全球公共卫生问题,环境金属暴露正在成为一个主要的风险因素。然而,多种金属的综合影响和人口变量的调节作用仍未得到充分探讨。方法:本研究分析了四个NHANES周期(1999-2000年、2001-2002年、2011-2012年、2013-2014年)的数据,包括1230名年龄≥60岁的参与者。结合人口统计学变量,对尿中9种金属和肌酐的浓度进行量化。使用数字符号替代测试、CERAD单词学习测试和动物流畅性测试的数据驱动四分位数阈值对认知状态进行分类。通过灵敏度(SN)、特异性(SP)、准确性(ACC)、马修斯相关系数(MCC)和AUC对6种机器学习算法进行训练和评估。结果:eXtreme gradient boosting (XGBoost)模型在所有指标上均表现优异(SN = 0.78, SP = 0.84, ACC = 0.81, MCC = 0.62, AUC = 0.90),并被选择用于后续解释。SHAP分析确定教育水平、年龄、种族/民族和肌酐为主要预测因子。铊和钼含量升高以及钡含量降低也会导致认知风险。最终,为预测模型部署了一个用户友好的web服务器,并可在http://bio-medical.online/admxp/.Discussion上免费访问:相关的web服务器可以访问风险筛查,并支持老龄化人口的精确预防策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A machine learning framework for predicting cognitive impairment in aging populations using urinary metal and demographic data.

Introduction: Cognitive impairment in older adults poses a significant global public health concern, with environmental metal exposure emerging as a major risk factor. However, the combined effects of multiple metals and the modulatory roles of demographic variables remain insufficiently explored.

Methods: This study analyzed data from four NHANES cycles (1999-2000, 2001-2002, 2011-2012, 2013-2014), comprising 1,230 participants aged ≥ 60 years. Urinary concentrations of nine metals and creatinine were quantified in conjunction with demographic variables. Cognitive status was classified using data-driven quartile thresholds on the Digit Symbol Substitution Test, CERAD Word-Learning Test, and Animal Fluency tests. Six machine learning algorithms were trained and evaluated using sensitivity (SN), specificity (SP), accuracy (ACC), Matthews correlation coefficient (MCC) and AUC.

Results: The eXtreme gradient boosting (XGBoost) model demonstrated superior performance across all metrics (SN = 0.78, SP = 0.84, ACC = 0.81, MCC = 0.62, AUC = 0.90), and was selected for subsequent interpretation. SHAP analysis identified educational level, age, race/ethnicity, and creatinine as primary predictors. Elevated thallium and molybdenum levels and reduced barium levels also contributed to cognitive risk. Ultimately, a user-friendly webserver was deployed for the predictive model and is freely accessed at http://bio-medical.online/admxp/.

Discussion: The associated webserver enables accessible risk screening and underpins precision prevention strategies in aging populations.

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来源期刊
Frontiers in Genetics
Frontiers in Genetics Biochemistry, Genetics and Molecular Biology-Molecular Medicine
CiteScore
5.50
自引率
8.10%
发文量
3491
审稿时长
14 weeks
期刊介绍: Frontiers in Genetics publishes rigorously peer-reviewed research on genes and genomes relating to all the domains of life, from humans to plants to livestock and other model organisms. Led by an outstanding Editorial Board of the world’s leading experts, this multidisciplinary, open-access journal is at the forefront of communicating cutting-edge research to researchers, academics, clinicians, policy makers and the public. The study of inheritance and the impact of the genome on various biological processes is well documented. However, the majority of discoveries are still to come. A new era is seeing major developments in the function and variability of the genome, the use of genetic and genomic tools and the analysis of the genetic basis of various biological phenomena.
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