A two-sample Mendelian randomization analysis: causal association between chemokines and pan-carcinoma

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 5-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 correlate with better prognosis, while immune checkpoint molecules (PD-1, PD-L1) help cancer cells evade the immune system. Tumor-associated macrophages promote invasion and metastasis. Blocking molecules like CTLA-4, LAG-3, and TIM-3 enhance antitumor responses, and cytokines like IL-10 and TGF-β 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 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% CI: 0.915-0.970, P =6.76×10 -5 ), β =-0.059; MR Egger result was β =-0.095; and the weighted median result was β =-0.060. In the Finngen R10 dataset, the IVW result was OR=0.956 (95% CI: 0.907-1.01, P =0.092), β =-0.045; MR Egger result was β =-0.070; and weighted median result was β =-0.035. The β 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 ), β =-0.023; MR Egger result was β =-0.016; and the weighted median result was β =-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 ), β =-0.041; MR Egger result was β =-0.064; and weighted median result was β =-0.058. The β 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 β 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 β 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.

The Effect of Circulating Inflammatory Proteins on Endometriosis: A Mendelian Randomization Study

Background

Endometriosis is a complex gynecological condition in which endometrial fragments are implanted outside the uterus, causing pain and infertility. Although immune mediators play a vital role in endometriosis, their exact etiology remains elusive. Using Mendelian randomization (MR), this study aimed to assess the causal relationship between inflammatory proteins and endometriosis.

Methods

Genetic variants associated with inflammatory proteins were filtered from a genome-wide protein quantitative trait locus study under stringent thresholds. These variants were used as instrumental variables (IVs) to evaluate the causal effects of these inflammatory proteins on endometriosis. A two-sample MR analysis was performed with endometriosis from the UK Biobank as the outcome, and a sensitivity analysis was performed to mitigate potential confounding factors. Analyses were replicated in an independent endometriosis cohort from the FinnGen, followed by a meta-analysis of MR results from both cohorts. Finally, we assessed the causality between inflammatory proteins and the endometriosis subtypes.

Results

Independent MR analysis revealed that the genetically higher levels of CXCL5 were linked to a lower chance of having endometriosis. The causal link remained significant in the meta-analysis. Furthermore, the causality of CXCL5 expression has been identified in ovarian and pelvic peritoneal endometriosis.

Conclusion

Our MR analysis indicated that CXCL5 was associated with a decreased risk of endometriosis, suggesting that CXCL5 might have a protective effect against endometriosis. This enhances our understanding of the involvement of chemokines in endometriosis pathology and provides insights for future studies to explore the detailed mechanisms underlying CXCL5 in endometriosis.

No causal relationship between glucose and inflammatory bowel disease: a bidirectional two-sample mendelian randomization study

BACKGROUND

Association between glucose and inflammatory bowel disease (IBD) was found in previous observational studies and in cohort studies. However, it is not clear whether these associations reflect causality. Thus, this study investigated whether there is such a causal relation between elevated glucose and IBD, Crohn's disease (CD) and ulcerative colitis (UC).

METHODS

We performed a two-sample Mendelian Randomization (MR) with the independent genetic instruments identified from the largest available genome-wide association study (GWAS) for IBD (5,673 cases; 213,119 controls) and its main subtypes, CD and UC. Summarized data for glucose which included 200,622 cases and glycemic traits including HbA1c and type 2 diabetes(T2DM) were obtained from different GWAS studies. Primary and secondary analyses were conducted by preferentially using the radial inverse-variance weighted (IVW) approach. A number of other meta-analysis approach and sensitivity analyses were carried out to assess the robustness of the results.

RESULTS

We did not find a causal effect of genetically predicted glucose on IBD as a whole (OR 0.858; 95% CI 0.649-1.135; P = 0.286). In subtype analyses glucose was also suggestively not associated with Crohn's disease (OR 0.22; 95% CI 0.04-1.00; P = 0.05) and ulcerative colitis (OR 0.940; 95% CI 0.628-1.407; P = 0.762). In the other direction, IBD and its subtypes were not related to glucose and glycemic traits.

CONCLUSIONS

This MR study is not providing any evidence for a causal relationship between genetically predicted elevated glucose and IBD as well as it's subtypes UC and CD. Regarding the other direction, no causal associations could be found. Future studies with robust genetic instruments are needed to confirm this conclusion.

Cathepsins and cancer risk: a Mendelian randomization study

Background

Previous observational epidemiological studies reported an association between cathepsins and cancer, however, a causal relationship is uncertain. This study evaluated the causal relationship between cathepsins and cancer using Mendelian randomization (MR) analysis.

Methods

We used publicly available genome-wide association study (GWAS) data for bidirectional MR analysis. Inverse variance weighting (IVW) was used as the primary MR method of MR analysis.

Results

After correction for the False Discovery Rate (FDR), two cathepsins were found to be significantly associated with cancer risk: cathepsin H (CTSH) levels increased the risk of lung cancer (OR = 1.070, 95% CI = 1.027-1.114, P = 0.001, PFDR = 0.009), and CTSH levels decreased the risk of basal cell carcinoma (OR = 0.947, 95% CI = 0.919-0.975, P = 0.0002, P FDR = 0.002). In addition, there was no statistically significant effect of the 20 cancers on the nine cathepsins. Some unadjusted low P-value phenotypes are worth mentioning, including a positive correlation between cathepsin O (CTSO) and breast cancer (OR = 1.012, 95% CI = 1.001-1.025, P = 0.041), cathepsin S (CTSS) and pharyngeal cancer (OR = 1.017, 95% CI = 1.001-1.034, P = 0.043), and CTSS and endometrial cancer (OR = 1.055, 95% CI = 1.012-1.101, P = 0.012); and there was a negative correlation between cathepsin Z and ovarian cancer (CTSZ) (OR = 0.970, 95% CI = 0.949-0.991, P = 0.006), CTSS and prostate cancer (OR = 0.947, 95% CI = 0.902-0.944, P = 0.028), and cathepsin E (CTSE) and pancreatic cancer (OR = 0.963, 95% CI = 0.938-0.990, P = 0.006).

Conclusion

Our MR analyses showed a causal relationship between cathepsins and cancers and may help provide new insights for further mechanistic and clinical studies of cathepsin-mediated cancer.

The genetic causal relationship between type 2 diabetes, glycemic traits and venous thromboembolism, deep vein thrombosis, pulmonary embolism: a two-sample Mendelian randomization study

OBJECTIVE

To investigate the genetic underpinnings of the association between type 2 diabetes (T2D), glycemic indicators such as fasting glucose (FG), fasting insulin (FI), and glycated hemoglobin (GH), and venous thromboembolism (VTE), encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE), thereby contributing novel insights to the scholarly discourse within this domain.

METHODS

Genome-wide association study (GWAS) summary data pertaining to exposures (T2D, FG, FI, GH) and outcomes (VTE, DVT, PE) were acquired from the IEU Open GWAS database, encompassing participants of European descent, including both male and female individuals. Two-sample Mendelian randomization (MR) analyses were conducted utilizing the TwoSampleMR and MRPRESSO packages within the R programming environment. The primary analytical approach employed was the random-effects inverse variance weighted (IVW) method. Heterogeneity was assessed via Cochran's Q statistic for MR-IVW and Rucker's Q statistic for MR-Egger. Horizontal pleiotropy was evaluated using the intercept test of MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) analysis, with the latter also employed for outlier detection. Additionally, a "Leave one out" analysis was conducted to ascertain the influence of individual single nucleotide polymorphisms (SNPs) on MR results.

RESULTS

The random-effects IVW analysis revealed a negative genetic causal association between T2D) and VTE (P = 0.008, Odds Ratio [OR] 95% confidence interval [CI] = 0.896 [0.827-0.972]), as well as between FG and VTE (P = 0.002, OR 95% CI = 0.655 [0.503-0.853]), GH and VTE (P = 0.010, OR 95% CI = 0.604 [0.412-0.884]), and GH and DVT (P = 0.002, OR 95% CI = 0.413 [0.235-0.725]). Conversely, the random-effects IVW analysis did not detect a genetic causal relationship between FI and VTE (P > 0.05), nor between T2D, FG, or FI and DVT (P > 0.05), or between T2D, FG, FI, or GH and PE (P > 0.05). Both the Cochran's Q statistic for MR-IVW and Rucker's Q statistic for MR-Egger indicated no significant heterogeneity (P > 0.05). Moreover, the intercept tests of MR Egger and MR-PRESSO suggested the absence of horizontal pleiotropy (P > 0.05). MR-PRESSO analysis identified no outliers, while the "Leave one out" analysis underscored that the MR analysis was not influenced by any single SNP.

CONCLUSION

Our investigation revealed that T2D, FG, and GH exhibit negative genetic causal relationships with VTE at the genetic level, while GH demonstrates a negative genetic causal relationship with DVT at the genetic level. These findings furnish genetic-level evidence warranting further examination of VTE, DVT, and PE, thereby making a contribution to the advancement of related research domains.