Mendelian study on air pollution and membranous nephropathy outcomes associations.

Membranous nephropathy (MN) is an autoimmune disease of the kidney glomerulus, which mainly leads to nephrotic syndrome. This study investigates the associations between air pollution and MN risk and from an epigenomic perspective. In this study, we examine the associations between genetically predicted deoxyribonucleic acid methylation related to air pollution and MN risk. The data of air pollution included particulate matter (PM) with a diameter of 2.5 µm or less (PM2.5), PM with a diameter between 2.5 and 10 µm (PM2.5-10), PM with a diameter of 10 µm or less (PM10), nitrogen dioxide, and nitrogen oxides. Inverse variance weighted method was used as the main analysis method, and weighted median model and Mendelian randomization-Egger methods were selected for quality control. To assess the reliability of the results of the analyses, heterogeneity test, horizontal pleiotropy test, and the leave-one-out method were applied. There was a causal relationship between nitrogen oxides and MN risk (P = .010). Other types of air pollution were found no statistical association with MN disease (PM2.5: P = .378; PM2.5-10: P = .111; PM10: P = .035; nitrogen dioxide: P = .094). There was no heterogeneity or pleiotropy in the results. Our study suggests the association between nitrogen oxides and membrane nephropathy (MN) risk from the genetic perspective. This provides a theoretical basis for the prevention of MN disease.

The association between immune cells and breast cancer: insights from mendelian randomization and meta-analysis.

BACKGROUND: Breast cancer (BC) is the most common cancer among women worldwide, with 2.3 million new cases and 685,000 deaths annually. It has the highest incidence in North America, Europe, and Australia and lower rates in parts of Asia and Africa. Risk factors include age, family history, hormone replacement therapy, obesity, alcohol consumption, and lack of physical activity. BRCA1 and BRCA2 gene mutations significantly increase the risk. The five-year survival rate is over 90% in developed countries but lower in developing ones. Early screening and diagnosis, using mammography and MRI, are crucial for reducing mortality. In recent years, significant progress has been made in studying BC immunophenotyping, particularly in multicolor flow cytometry, molecular imaging techniques, and tumor microenvironment analysis. These technologies improve diagnosis, classification, and detection of minimal residual disease. Novel immunotherapies targeting the tumor microenvironment, like CAR-T cell therapy, show high efficiency and fewer side effects. High levels of tumor-infiltrating lymphocytes (TILs) correlate with better prognosis, while immune checkpoint molecules (PD-1, PD-L1) help cancer cells evade the immune system. Tumor-associated macrophages (TAMs) promote invasion and metastasis. Blocking molecules like CTLA-4, LAG-3, and TIM-3 enhance anti-tumor responses, and cytokines like IL-10 and TGF-ß aid tumor growth and immune evasion. Mendelian randomization (MR) studies use genetic variants to reduce confounding bias and avoid reverse causation, providing robust causal inferences about immune cell phenotypes and BC. This approach supports the development of precision medicine and personalized treatment strategies for BC. METHODS: This study aims to conduct Mendelian Randomization (MR) analysis on 731 immune cell phenotypes with BC in the BCAC and Finngen R10 datasets, followed by a meta-analysis of the primary results using the inverse-variance weighted (IVW) method and multiple corrections for the significance p values from the meta-analysis. Specifically, the study is divided into three parts: First, data on 731 immune cell phenotypes and BC are obtained and preprocessed from the GWAS Catalog and Open GWAS (BCAC) and the Finngen R10 databases. Second, MR analysis is performed on the 731 immune cell phenotypes with BC data from the BCAC and Finngen R10 databases, followed by a meta-analysis of the primary results using the IVW method, with multiple corrections for the significance p values from the meta-analysis. Finally, the positively identified immune cell phenotypes are used as outcome variables, and BC as the exposure variable for reverse MR validation. RESULTS: The study found that two immune phenotypes exhibited strong significant associations in MR analysis combined with meta-analysis and multiple corrections. For the immune phenotype CD3 on CD28+ CD4-CD8- T cells, the results were as follows: In the BCAC dataset, the IVW result was Odds Ratio (OR) = 0.942 (95% confidence interval (CI) = 0.915 ~ 0.970, P = 6.76 × 10-5), ß = -0.059; MR Egger result was ß = -0.095; and the weighted median result was ß = -0.060. In the Finngen R10 dataset, the IVW result was OR = 0.956 (95% CI = 0.907 ~ 1.01, P = 0.092), ß = -0.045; MR Egger result was ß = -0.070; and weighted median result was ß = -0.035. The ß values were consistent in direction across all three MR methods in both datasets. The meta-analysis of the IVW results from both datasets showed OR = 0.945 (95% CI = 0.922 ~ 0.970, P = 1.70 × 10-5). After Bonferroni correction, the significant P-value was P = 0.01, confirming the immune phenotype as a protective factor against BC. For the immune phenotype HLA DR on CD33- HLA DR+, the results were as follows: In the BCAC dataset, the IVW result was OR = 0.977 (95% CI = 0.964 ~ 0.990, P = 7.64 × 10-4), ß = -0.023; MR Egger result was ß = -0.016; and the weighted median result was ß = -0.019. In the Finngen R10 dataset, the IVW result was OR = 0.960 (95% CI = 0.938 ~ 0.983, P = 6.51 × 10-4), ß = -0.041; MR Egger result was ß = -0.064; and weighted median result was ß = -0.058. The ß values were consistent in direction across all three MR methods in both datasets. The meta-analysis of the IVW results from both datasets showed OR = 0.973 (95% CI = 0.961 ~ 0.984, P = 3.80 × 10-6). After Bonferroni correction, the significant P-value was P = 0.003, confirming this immune phenotype as a protective factor against BC. When the immune cell phenotypes CD3 on CD28+ CD4-CD8- T cells and HLA DR on CD33- HLA DR+ were used as outcomes and BC was used as exposure, the data processing and analysis procedures were the same. The MR analysis results are as follows: Data from the FinnGen database regarding the effect of positive immune phenotypes on malignant neoplasm of the breast indicated a ß coefficient of -0.011, OR = 0.99 (95% CI = -0.117 ~ 0.096, P = 0.846); data from the BCAC database regarding favorable immune phenotypes for BC demonstrated a ß coefficient of -0.052, OR = 0.095 (95% CI = -0.144 ~ 0.040, P = 0.266). The results suggest insufficient evidence in both databases to indicate that BC inversely affects these two immune cell phenotypes. CONCLUSIONS: Evidence suggests that the immune cell phenotypes CD3 on CD28+ CD4-CD8- T cells and HLA DR on CD33- HLA DR+ protect against BC. This protective effect may be achieved through various mechanisms, including enhancing immune surveillance to recognize and eliminate tumor cells; secreting cytokines to inhibit tumor cell proliferation and growth directly; triggering apoptotic pathways in tumor cells to reduce their number; modulating the tumor microenvironment to make it unfavorable for tumor growth and spread; activating other immune cells to boost the overall immune response; and inhibiting angiogenesis to reduce the tumor's nutrient supply. These mechanisms work together to help protect BC patients and slow disease progression. Both immune cell phenotypes are protective factors for BC patients and can be targeted to enhance their function and related pathways for BC treatment.

Causal relationship between 150 skin microbiomes and prostate cancer: insights from bidirectional mendelian randomization and meta-analysis.

Background: Despite relevant research, the relationship between skin microbiomes and prostate cancer remains controversial. This study utilizes bidirectional Mendelian randomization (MR) analysis combined with meta-analysis to explore the potential link between the two. Objective: This study aims to identify the causal relationship between 150 skin microbiomes and prostate cancer (PCa) using bidirectional Mendelian randomization (MR) and meta-analysis. Methods: This study employed a comprehensive Bidirectional Two-sample MR analysis using publicly available genetic data to ascertain the relationship between 150 skin microbiomes and PCa. We conducted extensive sensitivity analyses, tests for heterogeneity, and assessments of horizontal pleiotropy to ensure the accuracy of our results. Subsequently, we conducted a meta-analysis to strengthen our conclusions' robustness further. Finally, we performed reverse causal verification on the positive skin microbiomes and PCa. Results: After conducting a meta-analysis and multiple corrections of the MR analysis results, our findings reveal a correlation between Neisseria in dry skin and PCa risk, identifying it as a risk factor. The IVW result shows an Odds Ratio (OR) of 1.009 (95% Confidence Interval [CI]: 1.004-1.014, P = 0.027). Furthermore, the reverse MR analysis indicates the absence of an inverse causal relationship between the two. Apart from the identified skin microbiome, no significant associations were found between the other microbiomes and PCa. Conclusions: The study identified a correlation between Neisseria in dry skin, one of the 150 skin microbiomes, and the risk of developing PCa, establishing it as a risk factor for increased susceptibility to PCa.

Causal validation of the relationship between 35 blood and urine biomarkers and hyperthyroidism: a bidirectional Mendelian randomization study and meta-analysis.

Background: Hyperthyroidism is an endocrine disorder with a relatively low global prevalence but significantly higher incidence among females compared to males. The onset age primarily ranges from 30 to 50, although it is not limited to this age group. Challenges in the treatment of hyperthyroidism include individualized treatment plan formulation, management of side effects, and prediction of disease progression, necessitating comprehensive consideration to achieve more effective therapy and management. Mendelian randomization studies can reveal more precise therapeutic targets between blood and urine biomarkers and hyperthyroidism, providing more decadent treatment options for the condition. Methods: The study will build upon the omics Mendelian randomization (MR) framework by conducting MR analysis using 35 blood and urine biomarkers separately for two distinct databases of hyperthyroidism. Subsequently, the results will undergo meta-analysis and multiple corrections to ensure accuracy and reliability. Finally, positive findings will undergo reverse MR validation to verify causal relationships with hyperthyroidism. Results: In the British database, the MR analysis of Total bilirubin levels about hyperthyroidism yielded an odds ratio (OR) of 1.097 (95% CI: 0.951-1.265, P = 0.205). Conversely, in the Thyroid Omics Association database, the MR analysis revealed an OR of 1.283 (95% CI: 1.122-1.467, P = 0.0002) for the same relationship. Meta-analysis of the MR analysis results from both databases, following multiple corrections, resulted in an OR of 1.192 (95% CI: 1.081-1.314, P = 0.015). Additionally, the direction of beta values in the MR analysis results from both databases was consistent. Conclusion: The urine biomarker total bilirubin levels may contribute to an increased risk of hyperthyroidism and accelerate its progression, thus representing a risk factor for the condition.

Causal relationship analysis between 35 blood/urine metabolites and gastroesophageal reflux disease: A Mendelian randomization combined meta-analysis study.

Gastroesophageal reflux disease (GERD) is a common condition worldwide. Despite numerous studies on GERD, the causal relationships between blood/urine metabolites and GERD remain unclear. This study aims to explore the causal relationships between GERD and 35 blood/urine metabolites. In this study, we conducted Mendelian randomization (MR) analyses for 35 blood/urine metabolites with GERD phenotypes from the FinnGen R10 and UKB databases separately. We then performed a meta-analysis of the inverse variance weighted results from the 2 MR analyses and applied multiple corrections to the significant P values from the meta-analysis. Finally, we conducted reverse causality validation for the corrected positive blood/urine metabolite phenotypes with GERD. After conducting MR analysis combined with meta-analysis and performing multiple corrections, we found significant positive causal associations between only 3 blood/urine metabolites and GERD, with no significant reverse associations. Among them, 2 are risk factors for the occurrence of GERD: alanine aminotransferase levels (odds ratio (OR) = 1.120, 95% confidence interval (CI) = 1.064-1.180, P = .0005) and urate levels (OR = 1.095, 95% CI = 1.044-1.147, P = .005). Additionally, sex hormone-binding globulin levels are protective against GERD (OR = 0.928, 95% CI = 0.896-0.961, P = .0009). Elevated levels of the metabolites alanine aminotransferase and urate are associated with an increased risk of GERD, identifying them as risk factors for the condition. In contrast, higher levels of SHBG are linked to a decreased risk of GERD, indicating that SHBG is a protective factor against the disease.

Is There an Association Between Hypothyroidism and Sexual Dysfunction: A Systematic Review and Cumulative Analysis.

INTRODUCTION: Many investigators have found a detrimental effect on sexual functioning developed by hypothyroidism in both sexes, but a cumulative analysis has not been conducted. AIM: This study aims to summarize and quantify the association between overt or subclinical hypothyroidism and the risk of sexual dysfunction (SD) through a meta-analysis. METHODS: 4 electronic databases were systematically searched. The quality of evidence was rated by the GRADE approach. This meta-analysis was registered on the PROSPERO (ID: CRD42020186967). MAIN OUTCOME MEASURE: The strength of the relationship between overt/subclinical hypothyroidism and SD was quantified by presenting the relative risk (RR) with its 95% confidence interval (CI). RESULTS: 7 studies involving 460 patients with hypothyroidism and 2,143 healthy controls were included in this meta-analysis. Among the 7 included studies, 2 studies were provided the data of both overt and subclinical hypothyroidism. Pooled results from 4 included studies investigating overt hypothyroidism indicated that overt hypothyroidism led to significant SD in both sexes (RR = 2.26, 95% CI: 1.42 to 3.62, P = 0.001), while synthetic RR of 5 eligible studies reporting subclinical hypothyroidism failed to find a positive association between subclinical hypothyroidism and SD (RR = 1.3, 95% CI: 0.85 to 1.99, P = 0.229), irrespective of gender (all P > 0.05). Subgroup analyses revealed that women with overt hypothyroidism rather than men with overt hypothyroidism were correlated with a significant higher risk of SD. The quality of evidence in the study of overt hypothyroidism and subclinical hypothyroidism was considered low and moderate, respectively. CONCLUSION: SD is a devastating problem in female patients with clinical hypothyroidism but insusceptible in either women or men with subclinical hypothyroidism. Clinicians should be aware of these phenomena and manage the sufferers accordingly in clinical practice. More rigorous studies are still needed to validate this evidence. Shen M, Li X, Wu W, et al. Is There an Association Between Hypothyroidism and Sexual Dysfunction: A Systematic Review and Cumulative Analysis. Sex Med 2021;9:100345.