Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers
BackgroundPrevious 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 ca...
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Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1201479/full |
| _version_ | 1797692944689397760 |
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| author | Qiubo Wang Qiubo Wang Zhimiao Wang Mingyou Chen Wei Mu Zhenxing Xu Mei Xue |
| author_facet | Qiubo Wang Qiubo Wang Zhimiao Wang Mingyou Chen Wei Mu Zhenxing Xu Mei Xue |
| author_sort | Qiubo Wang |
| collection | DOAJ |
| description | BackgroundPrevious 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.MethodIn 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.ResultsOur 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.ConclusionAt 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. |
| first_indexed | 2024-03-12T02:34:57Z |
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| language | English |
| last_indexed | 2024-03-12T02:34:57Z |
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| spelling | doaj.art-836123bff3464e9ea6a1490680d8c68a2023-09-04T19:03:15ZengFrontiers Media S.A.Frontiers in Public Health2296-25652023-09-011110.3389/fpubh.2023.12014791201479Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkersQiubo Wang0Qiubo Wang1Zhimiao Wang2Mingyou Chen3Wei Mu4Zhenxing Xu5Mei Xue6Department of Cardiology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Medicine and Health Key Laboratory of Cardiac Electrophysiology and Arrhythmia, Jinan, ChinaShandong First Medical University and Shandong Academy of Medical Sciences, Jinan, ChinaDepartment of Cardiology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Medicine and Health Key Laboratory of Cardiac Electrophysiology and Arrhythmia, Jinan, ChinaDepartment of Cardiology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Medicine and Health Key Laboratory of Cardiac Electrophysiology and Arrhythmia, Jinan, ChinaDepartment of Cardiology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Medicine and Health Key Laboratory of Cardiac Electrophysiology and Arrhythmia, Jinan, ChinaDepartment of Cardiology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Medicine and Health Key Laboratory of Cardiac Electrophysiology and Arrhythmia, Jinan, ChinaDepartment of Cardiology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Medicine and Health Key Laboratory of Cardiac Electrophysiology and Arrhythmia, Jinan, ChinaBackgroundPrevious 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.MethodIn 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.ResultsOur 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.ConclusionAt 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.https://www.frontiersin.org/articles/10.3389/fpubh.2023.1201479/fullparticulate mattercardiovascular diseasescardiovascular biomarkersMendelian randomizationcausal association |
| spellingShingle | Qiubo Wang Qiubo Wang Zhimiao Wang Mingyou Chen Wei Mu Zhenxing Xu Mei Xue Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers Frontiers in Public Health particulate matter cardiovascular diseases cardiovascular biomarkers Mendelian randomization causal association |
| 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 | particulate matter cardiovascular diseases cardiovascular biomarkers Mendelian randomization causal association |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1201479/full |
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