空气污染与阿尔茨海默病因果关联的两样本孟德尔随机化研究

doi:10.3969/j.issn.1674-8115.2025.01.010

上海交通大学学报（医学版） ›› 2025, Vol. 45 ›› Issue (1): 87-94.doi: 10.3969/j.issn.1674-8115.2025.01.010

空气污染与阿尔茨海默病因果关联的两样本孟德尔随机化研究

张迎迎¹(), 张俊瑶¹, 宋际伟², 王声杰², 姚俊岩²()

^1.上海交通大学医学院附属第一人民医院麻醉科，上海 200080
^2.同济大学附属东方医院麻醉科，上海 200120

收稿日期:2024-06-10 接受日期:2024-10-02 出版日期:2025-01-28 发布日期:2025-01-17
通讯作者: 姚俊岩，博士，主任医师；电子信箱：sunshineyao@163.com。
作者简介:张迎迎（1999—），女，硕士生；电子信箱：yingying1232022@163.com。
基金资助:
国家自然科学基金(82171183);上海市浦东新区卫生健康委员会医学人才培养项目(PWR12023-01)

Two-sample Mendelian randomization study on the causal association between air pollution and Alzheimer′s disease

ZHANG Yingying¹(), ZHANG Junyao¹, SONG Jiwei², WANG Shengjie², YAO Junyan²()

^1.Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
^2.Department of Anesthesiology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, China

Received:2024-06-10 Accepted:2024-10-02 Online:2025-01-28 Published:2025-01-17
Contact: YAO Junyan, E-mail: sunshineyao@163.com.
Supported by:
National Natural Science Foundation of China(82171183);Medical Talent Training Program of Shanghai Pudong New Area Health Commission(PWR12023-01)

摘要/Abstract

摘要：

目的·利用两样本孟德尔随机化（Mendelian randomization，MR）的方法探究空气污染与阿尔茨海默病（Alzheimer′s disease，AD）发病风险之间的因果关系。方法·基于全基因组关联研究（genome-wide association study，GWAS）的数据，采用两样本MR分析评估空气污染与AD发病风险的因果关系。以空气污染指标包括细颗粒物（particulate matter 2.5，PM_2.5）、粗颗粒物（particulate matter 2.5-10，PM_2.5-10）、可吸入颗粒物（particulate matter 10，PM₁₀）、二氧化氮以及氮氧化物为暴露因素，从英国生物银行（UK Biobank）数据库中获得其汇总数据。PM_2.5的数据集包括暴露人群423 796例，包含9 851 867个单核苷酸多态性（single nucleotide polymorphisms，SNPs）的关联分析；PM_2.5-10的数据集包括暴露人群423 796例，包含9 851 867个SNPs的关联分析；PM₁₀的数据集包括暴露人群455 314例，包含9 851 867个SNPs的关联分析；二氧化氮的数据集包括暴露人群456 380例，包含9 851 867个SNPs的关联分析；氮氧化物的数据集包括暴露人群456 380例，包含9 851 867个SNPs的关联分析。以AD为结局因素，从国际阿尔茨海默病基因组学项目（International Genomics of Alzheimer′s Project，IGAP）中获得AD的数据。AD的数据集包括患者25 580例和对照人群48 466例，包含7 067 513个SNPs的关联分析。以与AD显著相关的SNPs作为工具变量，以逆方差加权（inverse variance weighted，IVW）法为主要分析方法，选择加权中位数法、MR-Egger回归、基于众数的简单估计和基于众数的加权估计4种方法进行质量控制，并通过异质性检验、基因多效性检验和敏感性分析来评估研究结果的可靠性。结果·异质性检验（IVW法和MR-Egger回归）显示，空气污染指标与AD的SNP之间不存在异质性（均P>0.05）。基因多效性检验（MR-Egger回归）显示，未检测到多效性（P>0.05）。敏感性分析显示，PM_2.5的研究结果稳定。IVW法的分析结果发现，在欧洲人群中PM_2.5（P<0.001）与AD之间存在统计学关联，而PM_2.5-10（P=0.664）、PM₁₀（P=0.664）、二氧化氮（P=0.284）、氮氧化物（P=0.567）这4种因素与AD之间不存在统计学关联。结论·PM_2.5暴露与AD发病风险之间存在显著的因果关系，PM_2.5的暴露会增加AD的发病风险，但尚未发现PM_2.5-10、PM₁₀、二氧化氮和氮氧化物暴露导致AD发病风险增加的证据。

关键词: 阿尔茨海默病, 空气污染, 孟德尔随机化, 因果推断

Abstract:

Objective ·To explore the causal relationship between air pollution and the risk of Alzheimer′s disease (AD) by using two-sample Mendelian randomization (MR). Methods ·Based on the data from the genome-wide association study (GWAS), a two-sample MR analysis was conducted to evaluate the causal relationship between air pollution and the risk of AD. Air pollution indicators, including particulate matter 2.5 (PM_2.5), particulate matter 2.5-10 (PM_2.5-10), particulate matter 10 (PM₁₀), nitrogen dioxide and nitrogen oxides, were used as exposure factors, and summarized data were aggregated from the UK Biobank database. The PM_2.5 dataset included 423 796 cases, with correlation analysis conducted on 9 851 867 single nucleotide polymorphisms (SNPs); the PM_2.5-10 dataset included 423 796 cases, with correlation analysis conducted on 9 851 867 SNPs; the PM₁₀ dataset included 455 314 cases, with correlation analysis conducted on 9 851 867 SNPs; the nitrogen dioxide dataset included 456 380 cases, with correlation analysis conducted on 9 851 867 SNPs; the nitrogen oxides dataset included 456 380 cases, with correlation analysis conducted on 9 851 867 SNPs. AD was used as the outcome factor, and data were obtained from the International Genomics of Alzheimer′s Project (IGAP). The AD dataset included 25 580 cases and 48 466 controls, with correlation analysis of 7 067 513 SNPs. SNPs significantly associated with AD were used as instrumental variables. The main analysis was conducted by using the inverse variance weighted (IVW) method, and four methods including weighted median, MR-Egger regression, mode-based simple estimation and mode-based weighted estimation were used for quality control. Heterogeneity testing, gene pleiotropy testing and sensitivity analysis were conducted to assess the reliability of the study results. Results ·Heterogeneity testing indicated no evidence of heterogeneity among SNPs associated with air pollution indicators and AD (both IVW and MR-Egger results, P>0.05). Gene pleiotropy testing did not detect any pleiotropic effects (MR-Egger results, P>0.05). Sensitivity analysis confirmed the stability of the PM_2.5 results. IVW analysis revealed a statistically significant association between PM_2.5 and AD in European populations (P<0.001), while no statistically significant associations were observed between PM_2.5-10 (P=0.664), PM₁₀ (P=0.664), nitrogen dioxide (P=0.284), nitrogen oxides (P=0.567) and AD. Conclusion ·There is a significant causal relationship between PM_2.5 exposure and the risk of AD, with PM_2.5 exposure increasing the incidence of AD. However, no evidence has been found to suggest that PM_2.5-10, PM₁₀, nitrogen dioxide or nitrogen oxides cause an increased risk of AD.

Key words: Alzheimer′s disease (AD), air pollution, Mendelian randomization (MR), causal inference

中图分类号:

R749.1

张迎迎, 张俊瑶, 宋际伟, 王声杰, 姚俊岩. 空气污染与阿尔茨海默病因果关联的两样本孟德尔随机化研究[J]. 上海交通大学学报（医学版）, 2025, 45(1): 87-94.

ZHANG Yingying, ZHANG Junyao, SONG Jiwei, WANG Shengjie, YAO Junyan. Two-sample Mendelian randomization study on the causal association between air pollution and Alzheimer′s disease[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2025, 45(1): 87-94.

图/表 7

表1 空气污染与AD因果关联研究的样本量、SNP数量及人群信息

Tab 1 Sample size， SNP counts and population information for causal association study between air pollution and AD

Exposure/outcome	Dataset	Sample size/n	Number of SNPs/n	Population	Publication year
PM_2.5	ukb-b-10 817	423 796 participants	9 851 867	European	2018
PM_2.5-10	ukb-b-12 963	423 796 participants	9 851 867	European	2018
PM₁₀	ukb-b-589	455 314 participants	9 851 867	European	2018
Nitrogen dioxide	ukb-b-2 618	456 380 participants	9 851 867	European	2018
Nitrogen oxides	ukb-b-12 417	456 380 participants	9 851 867	European	2018
AD	NG00053	25 580 cases and 48 466 controls	7 055 881 (stage 1) and 11 632 (stage 2)	European	2013

图1 两样本MR分析的研究设计Note： LD—linkage disequilibrium; IVW—inverse variance weighted; WM—weighted median.

Fig 1 Study design of the two-sample MR analysis

图2 SNP对PM2.5 和AD效应的散点图分析Note： Each black point on the plot represents an individual SNP, with its position on the exposure (horizontal axis) and the outcome (vertical axis). Error bars indicate the standard error (SE) for each SNP.

Fig 2 Scatter plot analysis of SNP effects on PM2.5 and AD

图3 PM2.5 对AD效应的森林图分析Note： The red and black bars represent the causal estimates of PM2.5 levels on the risk of AD.

Fig 3 Forest plot analysis of PM2.5 effects on AD

表2 5种空气污染指标与AD发病风险之间因果关系的MR分析

Tab 2 MR analysis of the causal relationship between five air pollution indicators and the risk of AD

Exposure	Outcome	SNP/n	MR method	P value	OR value	95%CI	Pleiotropy P value	Heterogeneity P value
PM_2.5	AD	48	MR-Egger	0.874	0.863	0.141‒5.295	0.278	0.453
			WM	0.031	2.186	1.073‒4.453
			IVW	<0.001	2.302	1.421‒3.729		0.444
			Simple mode	0.192	2.777	0.615‒12.550
			Weighted mode	0.291	2.175	0.524‒9.024
PM_2.5-10	AD	4	MR-Egger	0.432	0.905	0.741‒1.106	0.300	0.967
			WM	0.890	0.992	0.878‒1.119
			IVW	0.664	1.023	0.924‒1.131		0.576
			Simple mode	0.945	1.007	0.828‒1.225
			Weighted mode	0.782	0.980	0.860‒1.116
PM₁₀	AD	4	MR-Egger	0.432	0.905	0.741‒1.106	0.300	0.967
			WM	0.890	0.992	0.878‒1.119
			IVW	0.664	1.023	0.924‒1.131		0.576
			Simple mode	0.945	1.007	0.828‒1.225
			Weighted mode	0.782	0.980	0.860‒1.116
Nitrogen dioxide	AD	84	MR-Egger	0.973	0.978	0.271‒3.531	0.705	0.428
			WM	0.303	1.354	0.756‒2.423
			IVW	0.284	1.239	0.837‒1.834		0.457
			Simple mode	0.216	2.512	0.591‒10.670
			Weighted mode	0.294	2.063	0.538‒7.910
Nitrogen oxides	AD	67	MR-Egger	0.682	0.703	0.131‒3.764	0.563	0.206
			WM	0.892	0.960	0.536‒1.721
			IVW	0.567	1.137	0.733‒1.762		0.223
			Simple mode	0.444	0.578	0.144‒2.330
			Weighted mode	0.538	0.649	0.165‒2.549

图4 PM2.5 对AD效应的留一法敏感性分析Note： The error bars indicate the 95%CI. The red line shows the results of the randow-effects IVW analysis.

Fig 4 Leave-one-out sensitivity analysis of PM2.5 effects on AD

图5 PM2.5 对AD效应的漏斗图分析Note： Each black point on the plot represents an individual SNP, with the vertical axis displaying the effect size and the horizontal axis representing the standard error (SE). The central line indicates the overall estimated effect size. IV‒instrumental variable.

Fig 5 Funnel plot analysis of PM2.5 effects on AD

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空气污染与阿尔茨海默病因果关联的两样本孟德尔随机化研究

Two-sample Mendelian randomization study on the causal association between air pollution and Alzheimer′s disease

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