Causal relationship between particulate matter 2.5 and hypothyroidism: A two-sample Mendelian randomization study

Association Between Long-Term Exposure to Environmental Fine Particulate Matter and the Prevalence of Thyroid Disorders: A National Cross-Sectional Study in China

Background: Exposure to particles with an aerodynamic diameter of ≤2.5 μm (PM2.5) is associated with the occurrence of thyroid dysfunction among pregnant women and neonates, but it is not known if this association occurs in the general population. We aimed to determine the association of prolonged exposure to PM2.5 with the prevalence of thyroid disorders among adults in China. Methods: A nationally representative cross-sectional study of thyroid disorders, iodine status, and diabetes status was carried out in all 31 provinces across China from 2015 to 2017. In total, 73,900 adults aged 18 years and older were included. Serum concentrations of thyroid hormones, thyrotropin, and thyroid antibodies and the urine iodine concentration were measured. The environmental concentration of PM2.5 for each participant's residential address at a spatial resolution of 1 × 1 km was estimated. Results: The average long-term exposure to PM2.5 at residential addresses was 66.41 μg/m3, ranging from 17.58 μg/m3 to 120.40 μg/m3. Compared with that of individuals with lower exposure levels, the prevalence of thyroid diseases such as autoimmune thyroiditis and subclinical hypothyroidism was greater in those with PM2.5 concentrations within the third quartile range (60.18 to 73.78 μg/m3). Compared with those in the first quartile (17.58 to 46.38 μg/m3), participants in the highest PM2.5 quartile (73.78 to 120.40 μg/m3) presented an increased risk of overt hypothyroidism (OR 1.23 [CI 0.94-1.61]), subclinical hypothyroidism (1.10 [1.01-1.21]), autoimmune thyroiditis (1.09 [1.00-1.18]), and thyroglobulin antibody positivity (1.17 [1.07-1.29]). However, there was no association between PM2.5 exposure and overt hyperthyroidism, subclinical hyperthyroidism, Graves' disease, or thyroid peroxidase antibody positivity (p > 0.05). Each 10 μg/m³ increase in the PM2.5 concentration was associated with an increased risk of overt hypothyroidism (OR 1.05 [1.00-1.11]), subclinical hypothyroidism (1.02 [1.00-1.03]), and thyroglobulin antibody positivity (1.02 [1.00-1.04]). Furthermore, a nearly linear exposure-response relationship was observed between long-term PM2.5 exposure and thyroglobulin antibody positivity. Conclusions: PM2.5 exposure was associated with thyroid disorders among Chinese adults. A dose-response relationship between PM2.5 exposure and autoimmune thyroiditis, as well as thyroglobulin antibody positivity, was also observed.

The causal relationship between anti-diabetic drugs and gastrointestinal disorders: a drug-targeted mendelian randomization study

BACKGROUND

The incidence of diabetic gastrointestinal diseases is increasing year by year. This study aimed to investigate the causal relationship between antidiabetic medications and gastrointestinal disorders, with the goal of reducing the incidence of diabetes-related gastrointestinal diseases and exploring the potential repurposing of antidiabetic drugs.

METHODS

We employed a two-sample Mendelian randomization (TSMR) design to investigate the causal association between antidiabetic medications and gastrointestinal disorders, including gastroesophageal reflux disease (GERD), gastric ulcer (GU), chronic gastritis, acute gastritis, Helicobacter pylori infection, gastric cancer (GC), functional dyspepsia (FD), irritable bowel syndrome (IBS), ulcerative colitis (UC), Crohn's disease (CD), diverticulosis, and colorectal cancer (CRC). To identify potential inhibitors of antidiabetic drug targets, we collected single-nucleotide polymorphisms (SNPs) associated with metformin, GLP-1 receptor agonists, SGLT2 inhibitors, DPP-4 inhibitors, insulin, and its analogs, thiazolidinediones, sulfonylureas, and alpha-glucosidase inhibitors from published genome-wide association study statistics. We then conducted a drug-target Mendelian randomization (MR) analysis using inverse variance weighting (IVW) as the primary analytical method to assess the impact of these inhibitors on gastrointestinal disorders. Additionally, diabetes was selected as a positive control.

RESULTS

Sulfonylureas were found to significantly reduce the risk of CD (IVW: OR [95% CI] = 0.986 [0.978, 0.995], p = 1.99 × 10- 3), GERD (IVW: OR [95% CI] = 0.649 [0.452, 0.932], p = 1.90 × 10- 2), and chronic gastritis (IVW: OR [95% CI] = 0.991 [0.982, 0.999], p = 4.50 × 10- 2). However, they were associated with an increased risk of GU development (IVW: OR [95%CI] = 2 0.761 [1.259, 6.057], p = 1 0.12 × 10- 2).

CONCLUSIONS

The results indicated that sulfonylureas had a positive effect on the prevention of CD, GERD, and chronic gastritis but a negative effect on the development of gastric ulcers. However, our research found no causal evidence for the impact of metformin, GLP-1 agonists, SGLT2 inhibitors, DPP 4 inhibitors, insulin and its analogs, thiazolidinediones, or alpha-glucosidase inhibitors on gastrointestinal diseases.

Association between air pollution and skin cutaneous melanoma: A Mendelian randomization study

There has been a consistent and notable increase in the global prevalence of skin cutaneous melanoma (SKCM). Although genetic factors are closely associated with the occurrence and development of melanoma, the potential influence of environmental factors cannot be overlooked. The existing literature lacks a definitive consensus on the correlation between air pollution and the incidence rate of SKCM. This study seeks to investigate the causal relationship between air pollution, specifically focusing on particulate matter (PM) 2.5, PM2.5-10, PM10, and nitrogen oxides, and the risk of SKCM. A 2-sample Mendelian randomization (MR) method was applied, utilizing extensive publicly accessible genome-wide association studies summary datasets within European populations. The primary analytical method employed was the inverse variance weighted method. Supplementary methods, including the weighted median model, MR-Egger, simple model, and weighted model, were chosen to ensure robust analysis. Heterogeneity assessment was conducted using Cochran's Q test. To identify potential pleiotropy, both MR-Egger regression and the MR-PRESSO global test were employed. Additionally, a sensitivity analysis was performed using the leave-one-out method. The analysis revealed no statistically significant association between air pollution and SKCM risk, with specific findings as follows: PM2.5 (P = .485), PM2.5-10 (P = .535), PM10 (P = .136), and nitrogen oxides (P = .745). While some results exhibited heterogeneity, all findings demonstrated an absence of pleiotropy. This study did not find substantive evidence supporting a causal relationship between air pollution and the risk of SKCM within European populations. The comprehensive MR analysis, encompassing various pollutants, suggests that environmental factors such as air pollution may not be significant contributors to the development of SKCM.

Potential causal associations of PM2.5 and osteoporosis: a two-sample mendelian randomization study

Background: Observational studies suggest a potential association between atmospheric particulate matter 2.5 (PM2.5) and osteoporosis, but a causal association is unclear due to the presence of confounding factors. Methods: We utilized bone mineral density indices at four specific sites to represent osteoporosis: femoral neck (FN-BMD), lumbar spine (LS-BMD), forearm (FA-BMD), and heel (HE-BMD). The PM2.5 data was obtained from the UK Biobank database, while the datasets for FN-BMD, LS-BMD, and FA-BMD were obtained from the GEFOS database, and the dataset for HE-BMD was obtained from the EBI database. A two-sample Mendelian randomization analysis was conducted using mainly the inverse variance weighted method, horizontal pleiotropy and heterogeneity were also assessed. Results: The results indicated that PM2.5 was not correlated with a decrease in FN-BMD (β: -0.305, 95%CI: -0.762, 0.153), LS-BMD (β: 0.134, 95%CI: -0.396, 0.666), FA-BMD (β: -0.056, 95%CI: -1.172,1.060), and HE-BMD (β: -0.084, 95%CI: -0.261,0.093). Additionally, acceptable levels of horizontal pleiotropy and heterogeneity were observed. Conclusion: In contrast to most observational studies, our research did not discover a potential causal relationship between PM2.5 and the development of osteoporosis.

Causal effects of exposure to ambient air pollution on cancer risk: Insights from genetic evidence

Air pollution has been increasingly linked to cancer risk. However, the genetic causality between air pollution and cancer risk remains poorly understood. To elucidate the potential roles of air pollution (NOx, NO2, PM2.5, PM course, and PM10) in the risk of 18 specific-site cancers, large-scale genome-wide association studies with a novel Mendelian randomization (MR) method were employed. Our MR analyses revealed significant associations between certain air pollutants and specific types of cancer. Specifically, a positive association was observed between NOx exposure and squamous cell lung cancer (OR: 1.96, 95%CI: 1.07-3.59, p = 0.03) as well as esophageal cancer (OR: 1.002, 95%CI: 1.001-1.003, p = 0.005). Genetically predicted NO2 exposure was found to be a risk factor for endometrial cancer (OR 1.41, 95%CI: 1.03-1.94, p = 0.03) and ovarian cancer (OR: 1.49, 95%CI: 1.14-1.95, p = 0.0037). Additionally, genetically predicted PM2.5 exposure was associated with an increased risk of ER+ breast cancer (OR: 1.24, 95%CI: 1.03-1.5, p = 0.02) and ER- breast cancer (OR: 2.57, 95%CI: 1.05-6.3, p = 0.04). PM course exposure was identified as a risk factor for glioma (OR: 487.28, 95%CI: 13.08-18,153, p = 0.0008), while PM10 exposure exerted a detrimental effect on mesothelioma (OR: 114.75, 95%CI: 1.14-11,500.11, p = 0.04) and esophageal cancer (OR: 1.01, 95%CI: 1.007-1.02, p = 0.03). These findings underscored the importance of mitigating air pollution to reduce the burden of cancer and highlight the need for further investigations to elucidate the underlying mechanisms involved in these associations.

Particulate matter 2.5 causally increased genetic risk of autism spectrum disorder

BACKGROUND

Growing evidence suggested that particulate matter (PM) exhibit an increased risk of autism spectrum disorder (ASD). However, the causal association between PM and ASD risk remains unclear.

METHODS

We performed two-sample Mendelian randomization (MR) analyses, using instrumental variables (IVs) sourced from the largest genome-wide association studies (GWAS) databases. We employed three MR methods: inverse-variance weighted (IVW), weighted median (WM), and MR-Egger, with IVW method serving as our primary MR method. Sensitivity analyses were performed to ensure the stability of these findings.

RESULTS

The MR results suggested that PM2.5 increased the genetic risk of ASD (β = 2.41, OR = 11.13, 95% CI: 2.54-48.76, P < 0.01), and similar result was found for PM2.5 absorbance (β = 1.54, OR = 4.67, 95% CI: 1.21-18.01, P = 0.03). However, no such association was found in PM10 (β = 0.27, OR = 1.30, 95% CI: 0.72-2.36, P = 0.38). After adjusting for the false discovery rate (FDR) correction, our MR results remain consistent. Sensitivity analyses did not find significant heterogeneity or horizontal pleiotropy.

CONCLUSIONS

Our findings indicate that PM2.5 is a potential risk factor for ASD. Effective strategies to mitigate air pollutants might lead to a reduced incidence of ASD.

Causal relationship between particulate matter 2.5 and infectious diseases: A two-sample Mendelian randomization study

Background

Previous observational studies suggested a correlation between particulate matter 2.5 (PM2.5) and infectious diseases, but causality remained uncertain. This study utilized Mendelian randomization (MR) analysis to investigate causal relationships between PM2.5 concentrations and various infectious diseases (COVID-19 infection, hospitalized COVID-19, very severe COVID-19, urinary tract infection, bacterial pneumonia, and intestinal infection).

Methods

Inverse variance weighted (IVW) was the primary method for evaluating causal associations. For significant causal estimates, multiple sensitivity tests were further performed: (i) three additional MR methods (MR-Egger, weighted median, and maximum likelihood method) for supplementing IVW; (ii) Cochrane's Q test for assessing heterogeneity; (iii) MR-Egger intercept test and MR-PRESSO global test for evaluating horizontal pleiotropy; (iv) leave-one-out sensitivity test for determining the stability.

Results

PM2.5 concentration significantly increased the risk of hospitalized COVID-19 (OR = 1.91, 95 % CI: 1.06-3.45, P = 0.032) and very severe COVID-19 (OR = 3.29, 95 % CI: 1.48-7.35, P = 3.62E-03). However, no causal effect was identified for PM2.5 concentration on other infectious diseases (P > 0.05). Furthermore, various sensitivity tests demonstrated the reliability of significant causal relationships.

Conclusions

Overall, lifetime elevated PM2.5 concentration increases the risk of hospitalized COVID-19 and very severe COVID-19. Therefore, controlling air pollution may help mitigate COVID-19 progression.

A Mendelian randomization study on the effects of plasma lipids on irritable bowel syndrome and functional dyspepsia

Although functional gastrointestinal disorder (FGID) is a common clinical condition, its risk factors remain unclear. We performed a Mendelian randomization study to explore the association between plasma lipids and the risk of FGID. Instrumental variables closely related to six plasma lipids were obtained from the corresponding genome-wide association studies, and summary-level data on FGID, including irritable bowel syndrome (IBS) and functional dyspepsia (FD), were extracted from the FinnGen study. The primary inverse variance weighted method and other supplementary analyses were used to evaluate the causal relationship between diverse plasma lipids and FGID. For each increase in the standard deviation of triglyceride levels, there was a 12.0% increase in the risk of IBS rather than that of FD. Low- and high-density lipoprotein cholesterol, total cholesterol, apolipoprotein A, and apolipoprotein B levels were not associated with the risk of IBS or FD. Through this study, we identified the causal role of triglycerides in the pathogenesis of IBS, which could benefit further basic and clinical research.

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 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.

The Importance of Metabolic and Environmental Factors in the Occurrence of Oxidative Stress during Pregnancy

Metabolic changes in pregnant women begin in the first weeks after conception under the influence of placental hormones that affect the metabolism of all nutrients. An increased concentration of total lipids accompanies pregnancy and an increased accumulation of triglycerides in low-density lipoproteins (LDL) particles. Lipids in small dense LDL particles are more susceptible to oxidative modification than normal-density LDL particles. Unlike LDL high-density lipoproteins (HDL), lipoprotein particles have an atheroprotective role in lipid metabolism. The very growth of the fetus depends on the nutrition of both parents, so obesity is not only in the mother but also in the father. Nutritional programming of the offspring occurs through changes in lipid metabolism and leads to an increased risk for cardiometabolic diseases. Pregnancy is accompanied by an increased need for oxygen in the mitochondria of the placenta and a tendency to develop oxidative stress. Oxidative stress represents a disturbance in the balance of oxidation-reduction processes in the body that occurs due to the excessive production of free oxygen radicals that cellular homeostatic mechanisms are unable to neutralize. When the balance with the antioxidant system is disturbed, which happens when free oxygen radicals are in high concentrations, serious damage to biological molecules occurs, resulting in a series of pathophysiological and pathological changes, including cell death. Therefore, oxidative stress plays a significant role in the pathogenesis of many complications that can occur during pregnancy. The oxidative status of pregnant women is also influenced by socioeconomic living conditions, lifestyle habits, diet, smoking, and exposure to environmental air pollution. During a healthy pregnancy, the altered lipid profile and oxidative stress create an increased risk for premature birth and pregnancy-related diseases, and a predisposition to adult diseases.

Causal Associations of PM2.5 and GDM: A Two-Sample Mendelian Randomization Study

Epidemiological studies have linked particulate matter (PM2.5) to gestational diabetes mellitus (GDM). However, the causality of this association has not been established; Mendelian randomization was carried out using summary data from genome-wide association studies (GWAS). For the analysis of the causal relationship between PM2.5 and GDM, the inverse variance weighted (IVW) method was used. The exposure data came from a GWAS dataset of IEU analysis of the United Kingdom Biobank phenotypes consisting of 423,796 European participants. The FinnGen consortium provided the GDM data, which included 6033 cases and 123,000 controls. We also performed multivariate MR (MVMR), adjusting for body mass index (BMI) and smoking. As a result, we found that each standard deviation increase in PM2.5 is associated with a 73.6% increase in the risk of GDM (OR: 1.736; 95%CI: 1.226-2.457). Multivariable MR analysis showed that the effect of PM2.5 on GDM remained after accounting for BMI and smoking. Our results demonstrate a causal relationship between PM2.5 and GDM.