Evidence map›Paper›PMID 39649256›Full record

ArticleArchives of medical science : AMS2024

Causal associations of ambient particulate matter 10 and Alzheimer's disease: result from a two-sample multivariable Mendelian randomization study.

Zehan Huang, Guodong He, Shuo Sun, Yingqing Feng, Yuqing Huang

Abstract read
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Article in Archives of medical science : AMS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zehan HuangDepartment of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Guodong HeResearch Department of Medical Sciences, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Shuo SunDepartment of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Yingqing FengHypertension Research Laboratory, Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Yuqing HuangHypertension Research Laboratory, Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Alzheimer's disease (AD) and ambient particulate matter 10 (PM10) have been associated in epidemiological studies. However, the relationship between PM10 and risk of AD has not been proven to be causal. Thus we used two-sample multivariable Mendelian randomization (MR) to examine this relationship. Material and methods: Genome-wide association studies (GWAS) for PM10 from UK Biobank, AD from EBI GWAS and IEU OpenGWAS were used for discovery and replication, respectively. Pooled meta-analysis of the inverse variance weighted (IVW) method was the main method. Sensitivity analyses included MR-Egger regression, weighted median, weighted mode and leave-one-out methods. The multivariable MR model adjusted for education. The MR estimates of causality association were expressed as odds ratios (OR) and corresponding 95% confidence intervals (CI). Results: There were in total 17 and 19 genetic variants associated with PM10 in the discovery and replication steps, respectively. In the univariate MR, pooled meta-analysis of genetically predicted PM10 was associated with a 99% increased risk of AD (95% CI: 1.25, 3.15, Conclusions: Increased PM10 levels were found to be significantly related to an increased risk of AD. This study provided evidence of genetic prediction of a causal relationship between PM10 and the risk of AD, suggesting that air pollution control may have significant implications for the prevention of AD.

Indexed as

air pollutionAlzheimer’s diseaseMendelian randomizationparticulate matter 10

Identifiers

PMID39649256
PMCPMC11623180

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.