Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers

Bibliographic Data

ID22072530
AuthorsQiubo Wang (0000-0002-4974-791X, Shandong Provincial QianFoShan Hospital), Zhimiao Wang (0000-0003-0189-466X, Shandong Provincial QianFoShan Hospital), Mingyou Chen (0000-0003-0399-4453, Shandong Provincial QianFoShan Hospital), Wei Mu (0000-0002-1894-9172), Weijie Mu (0000-0002-5644-1142, Shandong Provincial QianFoShan Hospital), Zhenxing Xu (0000-0002-5234-2956, Shandong Provincial QianFoShan Hospital, corresponding author), Mei Xue (0000-0002-0249-9496, Shandong Provincial QianFoShan Hospital, corresponding author)
Year2023
Volume11
Pages1201479-1201479
Publication date2023-09-01
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2023.1201479
PMID37732088
OpenAlexW4386415182
LanguageEN
Citations received3
References cited79

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

Body mass index · Cardiology · Confidence interval · Confounding · Mendelian randomization · Myocardial infarction · Observational study · Odds ratio · Rosuvastatin · Single-nucleotide polymorphism · Air Quality and Health Impacts · Genetic Associations and Epidemiology · Health, Environment, Cognitive Aging · Medicine · Internal Medicine

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