Long-term mortality effects of particulate air pollution have been investigated in a causal analytic frame, while causal evidence for associations with gaseous air pollutants remains extensively lacking, especially for carbon monoxide (CO) and sulfur dioxide (SO2). In this study, we estimated the causal relationship of long-term exposure to nitrogen dioxide (NO2), CO, SO2, and ozone (O3) with mortality. Utilizing the data from National Morbidity, Mortality, and Air Pollution Study, we applied a variant of difference-in-differences (DID) method with conditional Poisson regression and generalized weighted quantile sum regression (gWQS) to investigate the independent and joint effects. Independent exposures to NO2, CO, and SO2 were causally associated with increased risks of total, nonaccidental, and cardiovascular mortality, while no evident associations with O3 were identified in the entire population. In gWQS analyses, an interquartile range-equivalent increase in mixture exposure was associated with a relative risk of 1.067 (95% confidence interval: 1.010-1.126) for total mortality, 1.067 (1.009-1.128) for nonaccidental mortality, and 1.125 (1.060-1.193) for cardiovascular mortality, where NO2 was identified as the most significant contributor to the overall effect. This nationwide DID analysis provided causal evidence for independent and combined effects of NO2, CO, SO2, and O3 on increased mortality risks among the US general population.

BACKGROUND: Neuropsychiatric disorders and cervical cancer exert substantial influences on women\'s health. Furthermore, neuropsychiatric disorders frequently manifest as common symptoms in cancer patients, potentially increasing the risk of malignant neoplasms. This study aimed to identify neuropsychiatric disorders that are genetically and causally related to cervical cancer and to investigate the molecular mechanisms underlying these associations.
METHODS: GWAS data related to nine neuropsychiatric disorders, namely, schizophrenia, bipolar disorder, autism spectrum disorder, Parkinson\'s disease, anxiety, Alzheimer\'s disease, mood disorders, depression, and alcohol dependence, were obtained to calculate heritability (h2) and genetic correlation (rg) with cervical cancer using linkage disequilibrium score regression (LDSC). Mendelian randomization (MR) analysis of the two cohorts was employed to assess the causal effects. Shared gene expression pattern analysis was subsequently conducted to investigate the molecular mechanism underlying these significant associations.
RESULTS: Anxiety, mood disorders, depression, and alcohol dependence were genetically correlated with cervical cancer (all adjusted P < 0.05). Only depression was causally related to cervical cancer in both the discovery (ORIVW: 1.41, PIVW = 0.02) and replication cohorts (ORIVW: 1.80, PIVW = 0.03) in the MR analysis. Gene expression pattern analysis revealed that 270 genes related to depression and cervical cancer, including tumour necrosis factor (TNF), were significantly upregulated in cervical cancer patients, while vascular endothelial growth factor A (VEGFA), transcription factor AP-1 (JUN), and insulin-like growth factor I (IGF-I) were associated with prognosis in cervical cancer patients (all P < 0.05). These overlapping genes implicated the involvement of multiple biological mechanisms, such as neuron death, the PI3K-Akt signalling pathway, and human papillomavirus infection.
CONCLUSIONS: Genetic, causal and molecular evidence indicates that depression increases the risk of cervical cancer. The TNF, VEGFA, JUN, and IGF-1 genes and the neuron death, PI3K-Akt, and human papillomavirus infection signalling pathways may possibly explain this association.

UNASSIGNED: Observational studies have indicated that obesity is a risk factor for anorectal abscess (ARB). However, it remains unclear whether a causal genetic relationship exists between obesity and ARB.
UNASSIGNED: Univariate and multivariate Mendelian randomization (MR) were conducted using data from a large, published genome-wide association study (GWAS) of European ancestry to infer a causal relationship between obesity and ARB. Inverse variance weighted (IVW) analysis served as the primary analysis method, with results reported as odds ratios (OR).
UNASSIGNED: MR analysis revealed that body mass index (BMI) positively affects ARB (OR 1.974, 95% confidence interval (CI) 1.548-2.519, p = 4.34 × 10-8). The weighted median method (OR = 1.879, 95% CI 1.248-2.829, p = 0.002) and Bayesian model averaging (BMA) (OR = 1.88, 95% CI 1.477-2.392, p = 2.85 × 10-7) also demonstrated consistent results. Subsequently, the impact of several obesity-related characteristics on ARB was assessed. Body fat percentage (BF), whole body fat mass (FM), waist circumference (WC), and hip circumference (HC) were found to be causally associated with an increased risk of ARB. However, these associations vanished after adjusting for BMI effects.
UNASSIGNED: The study confirms a positive causal effect of obesity on ARB, highlighting that reasonable weight control is an important strategy to reduce the incidence of ARB.

UNASSIGNED: The relationship between blood lipids, lipid-modifying medications, and cancer risk has been under investigation for some time. Recent studies suggest that lipid-lowering medications might influence melanoma outcomes, though findings remain controversial. Our study aims to clarify the potential causal relationship between lipid-lowering drugs commonly used and melanoma incidence through a comprehensive Mendelian randomization (MR) analysis.
UNASSIGNED: Genetic variations within an LDL-related drug target gene (LDL-cholesterol from a genome-wide association study) served as proxies for exposure to lipid-lowering drugs. We conducted a two-sample Mendelian randomization analysis using inverse variance weighting (IVW), MR-Egger, and weighted median approaches. The MR-PRESSO test and pleiotropy_test were utilized to identify and adjust for horizontal pleiotropy. Stability and reliability of the Mendelian randomization findings were assessed using the leave-one-out method, Cochran\'s Q test, and funnel plot analysis. Odds ratios (OR) were employed to evaluate the causal relationship between genetic proxies of lipid-lowering drugs and melanoma risk.
UNASSIGNED: IVW analysis revealed that HMGCR gene expression is linked to a decreased risk of melanoma [OR: 0.624(0.439-0.888); p = 0.008]. Conversely, PCSK9 gene expression is tied to an elevated risk of melanoma [OR: 1.233(1.026-1.484); p = 0.025]. No significant association was observed between NPC1L1 and melanoma.
UNASSIGNED: HMGCR inhibitors (statins) may increase melanoma risk, while PCSK9 inhibitors (evolocumab, alirocumab) could potentially decrease melanoma risk.

UNASSIGNED: Several observational studies suggested an association between rheumatoid arthritis (RA) and bronchiectasis. Nevertheless, the presence of a causal relationship between these conditions is yet to be determined. This study aimed to investigate whether genetically predicted RA is associated with the risk of bronchiectasis and vice versa.
UNASSIGNED: We obtained RA genome-wide association study (GWAS) data from FinnGen consortium, and bronchiectasis GWAS data from IEU Open GWAS project. Univariate Mendelian randomization (MR) analysis was performed using inverse variance weighted (IVW) estimation as the main method. Furthermore, bidirectional and replication MR analysis, multivariate MR (MVMR), Mediation analysis, and sensitivity analyses were conducted to validate the findings.
UNASSIGNED: In the UVMR analysis, the IVW results revealed that RA had an increased risk of bronchiectasis (OR = 1.18, 95% CI = 1.10-1.27; p = 2.34 × 10-6). In the reverse MR analysis, no evidence of a causal effect of bronchiectasis on the risk of RA was detected. Conversely, in the replication MR analysis, RA remained associated with an increased risk of bronchiectasis. Estimates remained consistent in MVMR analyses after adjusting for the prescription of non-steroidal anti-inflammatory drugs (NSAIDs) and glucocorticoids. Immunosuppressants were found to mediate 58% of the effect of the RA on bronchiectasis. Sensitivity analyses confirmed the stability of these associations.
UNASSIGNED: This study demonstrated a positive causal relationship between RA and an increased risk of bronchiectasis, offering insights for the early prevention of bronchiectasis in RA patients and shedding new light on the potential role of immunosuppressants as mediators in promoting the effects of RA on bronchiectasis.

UNASSIGNED: Diabetes mellitus (DM) may promote the occurrence of epilepsy through mechanisms, such as inflammation, immune imbalance, and cerebrovascular injury, caused by metabolic abnormalities. However, evidence for the effects of DM and blood glucose (BG) on the risk of epilepsy is limited. Herein, this study used the Mendelian randomization (MR) method to investigate the potential causal associations of DM and BG-related indexes with epilepsy.
UNASSIGNED: In this two-sample MR study, summary statistics data of the genome-wide association studies (GWASs) on exposures, including type 1 diabetes mellitus (T1DM), T2DM, fasting glucose, and glycated hemoglobin (HbAlc), were extracted from the MRC-Integrative Epidemiology Unit (MRC-IEU). The GWAS data on study outcomes, including epilepsy, focal epilepsy, and generalized epilepsy, were obtained from the FinnGen consortium. MR-Egger regression was used to examine horizontal pleiotropism of instrumental variables (IVs), and Cochran\'s Q statistics was used to quantify the heterogeneity. MR analysis methods including inverse variance weighted (IVW) tests, weighted median, and MR-Egger were utilized to investigate the causal associations between DM and BG-related indexes with epilepsy. The evaluation indexes were odds ratios (ORs) and 95% confidence intervals (CIs). Reverse causal association analyses were also performed. In addition, IVW-radial and leave-one-out tests were utilized for sensitivity analyses.
UNASSIGNED: IVW estimates suggested that T1DM has potential causal associations with epilepsy (OR = 1.057, 95% CI: 1.031-1.084) and generalized epilepsy (OR = 1.066, 95% CI: 1.018-1.116). No significant reverse causal associations of T1DM with epilepsy or generalized epilepsy were found (all P > 0.05). In addition, sensitivity analysis results identified no outlier, indicating that the associations of T1DM with epilepsy and generalized epilepsy were relatively robust.
UNASSIGNED: Patients with T1DM had a potential risk of developing epilepsy, and prompt treatment of DM and dynamic monitoring may be beneficial to prevent epilepsy in this high-risk population. However, the causal associations of DM and BG with epilepsy may warrant further verification.

The goal was to explore the effect of interleukin-6 (IL6) and C reactive protein (CRP) on malignant melanoma (MM) using two-sample Mendelian randomization.
UNASSIGNED: Data for this study were obtained from the IEU Open GWAS project website for genome-wide association study data (GWAS) on interleukin-6, C reactive protein levels and malignant melanoma. Inverse variance weighted (IVW) method was mainly used and supplemented with MR-Egger regression and weighted median. Finally, horizontal multivariate validity and heterogeneity tests were performed to assess the stability and reliability of the results.
UNASSIGNED: The results of univariate two-sample MR analyses showed no significant effect of CRP on MM: inverse variance weighting method (OR=0.999, 95% CI: 0.998-1.001, P=0.343), MR-Egger regression (OR= 1.000, 95% CI: 0.998-1.001, P= 0.180), and weighted median method (OR= 0.999, 95% CI: 0.997 to 1.000, P= 0.583), and weighted model (OR= 0.999, 95% CI: 0.998 to 1.001, P= 0.328). Also,IL-6 had no significant effect on MM: inverse variance weighting method (OR= 1.001, 95% CI: 0.999 to 1.002, P=0.461), MR-Egger regression (OR= 1.000, 95% CI: 0.997 to 1.004, P= 0.910), weighted median method (OR= 1.000, 95% CI: 0.998 to 1.002, P= 0.749), and weighted mode (OR= 1.000, 95% CI: 0.998 to 1.002, P= 0.820).
UNASSIGNED: There was no causal relationship between C-reactive protein and IL-6 on the risk of malignant melanoma.

UNASSIGNED: Blood counts and biochemical markers are among the most common tests performed in hospitals and most readily accepted by patients, and are widely regarded as reliable biomarkers in the literature. The aim of this study was to assess the causal relationship between blood counts, biochemical indicators and pulmonary arterial hypertension (PAH).
UNASSIGNED: A two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between blood counts and biochemical indicators with PAH. The genome-wide association study (GWAS) for blood counts and biochemical indicators were obtained from the UK Biobank (UKBB), while the GWAS for PAH were sourced from the FinnGen Biobank. Inverse variance weighting (IVW) was used as the primary analysis method, supplemented by three sensitivity analyses to assess the robustness of the results. And we conducted an observational study using data from National Health and Nutrition Examination Survey (NHANES) 2003-2018 to verify the relationship.
UNASSIGNED: The MR analysis primarily using the IVW method revealed genetic variants of platelet count (OR=2.51, 95% CI 1.56-4.22, P<0.001), platelet crit(OR=1.87, 95% CI1.17-7.65, P=0.022), direct bilirubin (DBIL)(OR=1.71, 95%CI 1.18-2.47,P=0.004), insulin-like growth factor (IGF-1)(OR=0.51, 95% CI 0.27-0.96, P=0.038), Lipoprotein A (Lp(a))(OR=0.66, 95% CI 0.45-0.98, P=0.037) and total bilirubin (TBIL)(OR=0.51, 95% CI 0.27-0.96, P=0.038) were significantly associated with PAH. In NHANES, multivariate logistic regression analyses revealed a significant positive correlation between platelet count and volume and the risk of PAH, and a significant negative correlation between total bilirubin and PAH.
UNASSIGNED: Our study reveals a causal relationship between blood counts, biochemical indicators and pulmonary arterial hypertension. These findings offer novel insights into the etiology and pathological mechanisms of PAH, and emphasizes the important value of these markers as potential targets for the prevention and treatment of PAH.

UNASSIGNED: Metabolic abnormalities are closely tied to the development of ovarian cancer (OC), yet the relationship between anthropometric indicators as risk indicators for metabolic abnormalities and OC lacks consistency.
UNASSIGNED: The Mendelian randomization (MR) approach is a widely used methodology for determining causal relationships. Our study employed summary statistics from the genome-wide association studies (GWAS), and we used inverse variance weighting (IVW) together with MR-Egger and weighted median (WM) supplementary analyses to assess causal relationships between exposure and outcome. Furthermore, additional sensitivity studies, such as leave-one-out analyses and MR-PRESSO were used to assess the stability of the associations.
UNASSIGNED: The IVW findings demonstrated a causal associations between 10 metabolic factors and an increased risk of OC. Including \"Basal metabolic rate\" (OR= 1.24, P= 6.86×10-4); \"Body fat percentage\" (OR= 1.22, P= 8.20×10-3); \"Hip circumference\" (OR= 1.20, P= 5.92×10-4); \"Trunk fat mass\" (OR= 1.15, P= 1.03×10-2); \"Trunk fat percentage\" (OR= 1.25, P= 8.55×10-4); \"Waist circumference\" (OR= 1.23, P= 3.28×10-3); \"Weight\" (OR= 1.21, P= 9.82×10-4); \"Whole body fat mass\" (OR= 1.21, P= 4.90×10-4); \"Whole body fat-free mass\" (OR= 1.19, P= 4.11×10-3) and \"Whole body water mass\" (OR= 1.21, P= 1.85×10-3).
UNASSIGNED: Several metabolic markers linked to altered fat accumulation and distribution are significantly associated with an increased risk of OC.

OBJECTIVE: Recent research extends our knowledge of plasma lipid species, building on established links between serum lipid levels and Type 2 Diabetes Mellitus (T2DM) risk. Identifying the causal roles of these lipid species is key to improving T2DM risk assessment.
RESULTS: This study employs Mendelian randomization (MR) to investigate the causal relationship between 179 lipid species across 13 lipid categories and T2DM. Summary-level data were sourced from genome-wide association studies. The primary analytical methods included the inverse variance weighted (IVW) approach and the Wald ratio, complemented by a series of sensitivity analyses to ensure the robustness of results. The IVW analysis reveals a significant causal association between elevated levels of ceramide (d40:2) (OR = 1.071, 95% CI 1.034-1.109, P = 1.36 × 10-4), sphingomyelin (d38:1) (OR = 1.052, 95% CI 1.028-1.077, P = 1.80 × 10-5), and triacylglycerol (56:8) (OR = 1.174, 95% CI 1.108-1.243, P = 4.65 × 10-8), and an increased risk of T2DM. Conversely, Wald ratio analysis indicates that higher levels of phosphatidylcholine (O-16:1_16:0) (OR = 0.928, 95% CI 0.892-0.966, P = 2.37 × 10-4), phosphatidylcholine (O-16:1_20:4) (OR = 0.932, 95% CI 0.897-0.967, P = 2.37 × 10-4), and phosphatidylcholine (O-18:2_20:4) (OR = 0.872, 95% CI 0.812-0.935, P = 1.24 × 10-4) are significantly associated with a reduced risk of T2DM. Furthermore, suggestive causal evidence for 22 additional lipid species was identified.
CONCLUSIONS: This MR study establishes a causal relationship between specific lipid classes in modulating the risk of T2DM. It offers new insights for risk assessment and potential therapeutic targets in T2DM.