Causal relationship between particulate matter 2.5 and diabetes: two sample Mendelian randomization

Role of air pollution exposure in the alteration of brain cortical structure: A Mendelian randomization study

BACKGROUND

Accumulating research has linked ambient air pollution exposure to alterations in cortical surface area (SA) and thickness; however, the causal inferences remain controversial. Our investigation aims to determine the causality between air pollution and brain cortical morphology using the Mendelian randomization (MR) approach.

METHODS

Public accessible genome-wide association studies data on particulate matter 2.5 (PM2.5), PM2.5 absorbance, PM10, PM2.5-10, nitrogen dioxide (NO2), and nitrogen oxides (NOX) concentration were screened to select instrumental variables. Univariable MR (UVMR) was performed to assess the causality of air pollution on brain cortical structure using five MR methods. Multivariable MR (MVMR) was further conducted to strengthen the robustness of the identified relationships by adjusting for related pollutant phenotypes, household income, and unhealthy eating habits.

RESULTS

The UVMR analysis identified fourteen causal associations between air pollution susceptibility and alterations in brain cortical morphology, with nine showing negative effects and five showing positive effects concurrently. The MVMR models indicated negative causal relationships between PM2.5 level and the SA of the inferior temporal cortex (beta [95 %CI] = -215.739 [-404.284 to -27.194], p = 0.025), NO2 level and the SA of the lateral occipital cortex (beta [95 %CI] = -548.577 [-1086.450 to -10.699], p = 0.046), and a positive correlation between PM2.5 absorbance and SA of the bankssts cortex (beta [95 %CI] = 76.491 [14.267-138.716], p = 0.016). No evidence of heterogeneity or pleiotropy was noticed.

CONCLUSIONS

Our exploration established causal relationships between air pollution exposure and brain cortical structure, underscoring the significance of mitigating air pollution to preserve brain cortical morphology.

Research on the causal relationship between fine particulate matter and type 2 diabetes mellitus: A two-sample multivariable mendelian randomization study

BACKGROUND AND AIMS

Previous research has suggested a correlation between fine particulate matter (PM2.5) and type 2 diabetes mellitus (T2DM). However, the causality was vulnerable to confounding variables.

METHODS AND RESULTS

A two-sample multivariable mendelian randomization study was designed to examine the causal connection between PM2.5 and T2DM. PM2.5 trait was investigated as exposure while T2DM-related traits as outcomes. The summary data were obtained from the Finngen database and the open genome-wide association study database. The mendelian randomization estimates were obtained using the inverse-variance weighted approach, and multiple sensitivity analyses were conducted. There were potential causal relationships between PM2.5 and T2DM (OR = 2.418; P = 0.019), PM2.5 and glycated hemoglobin (HbA1c) (OR = 1.590; P = 0.041), and PM2.5 and insulin metabolism. PM2.5 was found to have no causal effect on fasting glucose and insulin, 2-h glucose, and insulin-like growth factor binding protein-1 (P > 0.05), while had a potential protective effect against some diabetes complications.

CONCLUSIONS

Our findings indicated potential causal relationships among PM2.5 and T2DM, especially the causal relationship between PM2.5 and long-term glucose levels.

Exploring the relationship between air pollution, non-alcoholic fatty liver disease, and liver function indicators: a two-sample Mendelian randomization analysis study

Background and aims

Non-alcoholic fatty liver disease (NAFLD) is a common metabolic disorder worldwide, with an increasing incidence in recent years. While previous studies have suggested an association between the air pollutant PM2.5 and NAFLD, there is still considerable debate regarding the existence of a clear causal relationship between air pollution and NAFLD. This study aims to employ Mendelian randomization methods to evaluate the causal relationship between major air pollutants and NAFLD.

Method

We conducted Mendelian randomization analyses on a large-scale publicly available genome-wide association study (GWAS) dataset of European populations to dissect the association between air pollutants, NAFLD, and liver function indicators. We used five different analysis methods, including Inverse-variance weighted (IVW), Weighted median, MR-Egger, Simple mode, and Weighted mode, to analyze the data. We also tested for pleiotropy, heterogeneity, and sensitivity of the results.

Results

This study utilized four common exposures related to air pollution and four outcomes related to NAFLD. The results regarding the association between air pollutants and NAFLD (PM2.5: P=0.808, 95% CI=0.37-3.56; PM10: P=0.238, 95% CI=0.33-1.31; nitrogen dioxide: P=0.629, 95% CI=0.40-4.61; nitrogen oxides: P=0.123, 95% CI=0.13-1.28) indicated no statistically significant correlation between them. However, notably, there was a causal relationship between PM10 and serum albumin (ALB) levels (P=0.019, 95% CI=1.02-1.27).

Conclusion

This MR study found no evidence of a causal relationship between air pollution and NAFLD in European populations. However, a statistically significant association was observed between PM10 and ALB levels, suggesting that the air pollutant PM10 may impact the liver's ability to synthesize proteins.

Diabetes mellitus-Progress and opportunities in the evolving epidemic

Diabetes, a complex multisystem metabolic disorder characterized by hyperglycemia, leads to complications that reduce quality of life and increase mortality. Diabetes pathophysiology includes dysfunction of beta cells, adipose tissue, skeletal muscle, and liver. Type 1 diabetes (T1D) results from immune-mediated beta cell destruction. The more prevalent type 2 diabetes (T2D) is a heterogeneous disorder characterized by varying degrees of beta cell dysfunction in concert with insulin resistance. The strong association between obesity and T2D involves pathways regulated by the central nervous system governing food intake and energy expenditure, integrating inputs from peripheral organs and the environment. The risk of developing diabetes or its complications represents interactions between genetic susceptibility and environmental factors, including the availability of nutritious food and other social determinants of health. This perspective reviews recent advances in understanding the pathophysiology and treatment of diabetes and its complications, which could alter the course of this prevalent disorder.

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.

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.