A Mendelian analysis of the relationships between immune cells and breast cancer

BackgroundEmerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.ResultsAccording to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ %CD4+ (p-value:1.37×10−6), CD8dim %T cell (p-value:4.62×10−43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10−5), CD27 on PB/PC (p-value:2.72×10−18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10−6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10−166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms’ p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.ConclusionThrough genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives

Association between AGTR1 (c.1166 A>C) Polymorphisms and Kidney Injury in Hypertension

Background: High blood pressure is the main cause of cardiovascular diseases. Kidney damage is one of the most common organ secondary damage to hypertension. The study of hypertension gene polymorphisms is an important means of precision treatment of primary hypertension. Objectives: The objective of this study was to explore the relationship between AGTR1 (c.1166 A>C) gene polymorphisms and hypertension combined with kidney damage, while exploring the relationship between codominant, dominant and recessive gene model and hypertension with kidney injury and the susceptibility of different genotypes to hypertension with kidney injury. Methods: The distribution of AGTR1 polymorphism in the AGTR1 in hypertensive patients (hypertension group, 292 patients) and hypertension with kidney injury patients (44 patients) were detected and compared by PCR-melting curve method. Results: The genotype distribution of hypertension and combined groups met Hardy-Weinberg equilibrium (p > 0.05); the distribution difference between the three genotypes was statistically significant (p 0.05). Conclusions: Our study identified the relationship of AGTRA (c.1166 A>C) with hypertension combined with renal injury, and compared the susceptibility of different genetic models, which may provide novel targets for precision gene therapy of hypertension. Clinical Trial Registration: URL: https://www.chictr.org.cn/indexEN.html; Unique identifier: ChiCTR2100051472

DataSheet_3_A Mendelian analysis of the relationships between immune cells and breast cancer.pdf

BackgroundEmerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.ResultsAccording to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ �4+ (p-value:1.37×10−6), CD8dim %T cell (p-value:4.62×10−43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10−5), CD27 on PB/PC (p-value:2.72×10−18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10−6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10−166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms’ p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.ConclusionThrough genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives.</p

DataSheet_2_A Mendelian analysis of the relationships between immune cells and breast cancer.pdf

BackgroundEmerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.ResultsAccording to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ �4+ (p-value:1.37×10−6), CD8dim %T cell (p-value:4.62×10−43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10−5), CD27 on PB/PC (p-value:2.72×10−18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10−6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10−166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms’ p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.ConclusionThrough genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives.</p

DataSheet_1_A Mendelian analysis of the relationships between immune cells and breast cancer.pdf

BackgroundEmerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.ResultsAccording to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ �4+ (p-value:1.37×10−6), CD8dim %T cell (p-value:4.62×10−43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10−5), CD27 on PB/PC (p-value:2.72×10−18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10−6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10−166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms’ p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.ConclusionThrough genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives.</p

Generation of an integration-free induced pluripotent stem cell (iPSC) line (SDHI001-A) from a 65-year old adult mitral valve prolapse (MVP) patient

Human iPSC line, SDHi001-A, was generated from 65-year-old male patient with mitral valve prolapse, using non-integrative reprogramming method. This cell line shows pluripotency both in vitro and in vivo, and has a normal karyotype

Table_1_A Mendelian analysis of the relationships between immune cells and breast cancer.xlsx

BackgroundEmerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.ResultsAccording to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ �4+ (p-value:1.37×10−6), CD8dim %T cell (p-value:4.62×10−43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10−5), CD27 on PB/PC (p-value:2.72×10−18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10−6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10−166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms’ p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.ConclusionThrough genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives.</p

Behavior of cooking-emitted particles in residential house with different kichen types

identifier:oai:t2r2.star.titech.ac.jp:5068480

Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer

Objective: To investigate the differential expression of microRNA (miRNA) in patients with endometrial cancer and its relationship with prognosis and survival. Method: We used The Cancer Genome Atlas (TCGA) database to analyze differentially expressed miRNAs in endometrial cancer tissues and adjacent normal tissues. In addition, we successfully screened out key microRNAs to build nomogram models for predicting prognosis and we performed survival analysis on the key miRNAs as well. Result: We identified 187 differentially expressed miRNAs, which includes 134 up-regulated miRNAs and 53 down-regulated miRNAs. Further univariate Cox regression analysis screened out 47 significantly differentially expressed miRNAs and selected 12 miRNAs from which the prognostic nomogram model for ECA patients by LASSO analysis was constructed. Survival analysis showed that high expression of hsa-mir-138-2, hsa-mir-548f-1, hsa-mir-934, hsa-mir-940, and hsa-mir-4758 as well as low-expression of hsa-mir-146a, hsa-mir-3170, hsa-mir-3614, hsa-mir-3616, and hsa-mir-4687 are associated with poor prognosis in EC patients. However, significant correlations between the expressions levels of has-mir-876 and hsa-mir-1269a and patients’ prognosis are not found. Conclusion: Our study found that 12 significantly differentially expressed miRNAs might promote the proliferation, invasion, and metastasis of cancer cells by regulating the expression of upstream target genes, thereby affecting the prognosis of patients with endometrial cancer