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Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers
BACKGROUND: Previous observational studies have shown that the prevalence of cardiovascular diseases (CVDs) is related to particulate matter (PM). However, given the methodological limitations of conventional observational research, it is difficult to identify causality conclusively. To explore the...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507646/ https://www.ncbi.nlm.nih.gov/pubmed/37732088 http://dx.doi.org/10.3389/fpubh.2023.1201479 |
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author | Wang, Qiubo Wang, Zhimiao Chen, Mingyou Mu, Wei Xu, Zhenxing Xue, Mei |
author_facet | Wang, Qiubo Wang, Zhimiao Chen, Mingyou Mu, Wei Xu, Zhenxing Xue, Mei |
author_sort | Wang, Qiubo |
collection | PubMed |
description | BACKGROUND: Previous observational studies have shown that the prevalence of cardiovascular diseases (CVDs) is related to particulate matter (PM). However, given the methodological limitations of conventional observational research, it is difficult to identify causality conclusively. To explore the causality of PM on CVDs and cardiovascular biomarkers, we conducted a Mendelian randomization (MR) analysis. METHOD: In this study, we obtained summary-level data for CVDs and cardiovascular biomarkers including atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), ischemic stroke (IS), stroke subtypes, body mass index (BMI), lipid traits, fasting glucose, fasting insulin, and blood pressure from several large genome-wide association studies (GWASs). Then we used two-sample MR to assess the causality of PM on CVDs and cardiovascular biomarkers, 16 single nucleotide polymorphisms (SNPs) for PM2.5 and 6 SNPs for PM10 were obtained from UK Biobank participants. Inverse variance weighting (IVW) analyses under the fixed effects model were used as the main analytical method to calculate MR Estimates, followed by multiple sensitivity analyses to confirm the robustness of the results. RESULTS: Our study revealed increases in PM2.5 concentration were significantly related to a higher risk of MI (odds ratio (OR), 2.578; 95% confidence interval (CI), 1.611–4.127; p = 7.920 × 10(−5)). Suggestive evidence was found between PM10 concentration and HF (OR, 2.015; 95% CI, 1.082–3.753; p = 0.027) and IS (OR, 2.279; 95% CI,1.099–4.723; p = 0.027). There was no evidence for an effect of PM concentration on other CVDs. Furthermore, PM2.5 concentration increases were significantly associated with increases in triglyceride (TG) (OR, 1.426; 95% CI, 1.133–1.795; p = 2.469 × 10(−3)) and decreases in high-density lipoprotein cholesterol (HDL-C) (OR, 0.779; 95% CI, 0.615–0.986; p = 0.038). The PM10 concentration increases were also closely related to the decreases in HDL-C (OR, 0.563; 95% CI, 0.366–0.865; p = 8.756 × 10(−3)). We observed no causal effect of PM on other cardiovascular biomarkers. CONCLUSION: At the genetic level, our study suggested the causality of PM2.5 on MI, TG, as well HDL-C, and revealed the causality of PM10 on HF, IS, and HDL-C. Our findings indicated the need for continued improvements in air pollution abatement for CVDs prevention. |
format | Online Article Text |
id | pubmed-10507646 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105076462023-09-20 Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers Wang, Qiubo Wang, Zhimiao Chen, Mingyou Mu, Wei Xu, Zhenxing Xue, Mei Front Public Health Public Health BACKGROUND: Previous observational studies have shown that the prevalence of cardiovascular diseases (CVDs) is related to particulate matter (PM). However, given the methodological limitations of conventional observational research, it is difficult to identify causality conclusively. To explore the causality of PM on CVDs and cardiovascular biomarkers, we conducted a Mendelian randomization (MR) analysis. METHOD: In this study, we obtained summary-level data for CVDs and cardiovascular biomarkers including atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), ischemic stroke (IS), stroke subtypes, body mass index (BMI), lipid traits, fasting glucose, fasting insulin, and blood pressure from several large genome-wide association studies (GWASs). Then we used two-sample MR to assess the causality of PM on CVDs and cardiovascular biomarkers, 16 single nucleotide polymorphisms (SNPs) for PM2.5 and 6 SNPs for PM10 were obtained from UK Biobank participants. Inverse variance weighting (IVW) analyses under the fixed effects model were used as the main analytical method to calculate MR Estimates, followed by multiple sensitivity analyses to confirm the robustness of the results. RESULTS: Our study revealed increases in PM2.5 concentration were significantly related to a higher risk of MI (odds ratio (OR), 2.578; 95% confidence interval (CI), 1.611–4.127; p = 7.920 × 10(−5)). Suggestive evidence was found between PM10 concentration and HF (OR, 2.015; 95% CI, 1.082–3.753; p = 0.027) and IS (OR, 2.279; 95% CI,1.099–4.723; p = 0.027). There was no evidence for an effect of PM concentration on other CVDs. Furthermore, PM2.5 concentration increases were significantly associated with increases in triglyceride (TG) (OR, 1.426; 95% CI, 1.133–1.795; p = 2.469 × 10(−3)) and decreases in high-density lipoprotein cholesterol (HDL-C) (OR, 0.779; 95% CI, 0.615–0.986; p = 0.038). The PM10 concentration increases were also closely related to the decreases in HDL-C (OR, 0.563; 95% CI, 0.366–0.865; p = 8.756 × 10(−3)). We observed no causal effect of PM on other cardiovascular biomarkers. CONCLUSION: At the genetic level, our study suggested the causality of PM2.5 on MI, TG, as well HDL-C, and revealed the causality of PM10 on HF, IS, and HDL-C. Our findings indicated the need for continued improvements in air pollution abatement for CVDs prevention. Frontiers Media S.A. 2023-09-01 /pmc/articles/PMC10507646/ /pubmed/37732088 http://dx.doi.org/10.3389/fpubh.2023.1201479 Text en Copyright © 2023 Wang, Wang, Chen, Mu, Xu and Xue. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Wang, Qiubo Wang, Zhimiao Chen, Mingyou Mu, Wei Xu, Zhenxing Xue, Mei Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers |
title | Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers |
title_full | Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers |
title_fullStr | Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers |
title_full_unstemmed | Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers |
title_short | Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers |
title_sort | causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507646/ https://www.ncbi.nlm.nih.gov/pubmed/37732088 http://dx.doi.org/10.3389/fpubh.2023.1201479 |
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