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      Causal relationship between immune cells and prostate cancer: a Mendelian randomization study

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          Abstract

          Introduction:

          Despite the abundance of research indicating the participation of immune cells in prostate cancer development, establishing a definitive cause-and-effect relationship has proven to be a difficult undertaking.

          Methods:

          This study employs Mendelian randomization (MR), leveraging genetic variables related to immune cells from publicly available genome-wide association studies (GWAS), to investigate this association. The primary analytical method used in this study is inverse variance weighting (IVW) analysis. Comprehensive sensitivity analyses were conducted to assess the heterogeneity and horizontal pleiotropy of the results.

          Results:

          The study identifies four immune cell traits as causally contributing to prostate cancer risk, including CD127- CD8+ T cell %CD8+ T cell (OR = 1.0042, 95%CI:1.0011–1.0073, p = 0.0077), CD45RA on CD39+ resting CD4 regulatory T cell (OR = 1.0029, 95%CI:1.0008–1.0050, p = 0.0065), CD62L− Dendritic Cell Absolute Count (OR = 1.0016; 95%CI:1.0005–1.0026; p = 0.0039), CX3CR1 on CD14+ CD16− monocyte (OR = 1.0024, 95%CI:1.0007–1.0040, p = 0.0060). Additionally, two immune cell traits are identified as causally protective factors: CD4 on monocyte (OR = 0.9975, 95%CI:0.9958–0.9992, p = 0.0047), FSC-A on plasmacytoid Dendritic Cell (OR = 0.9983, 95%CI:0.9970–0.9995, p = 0.0070). Sensitivity analyses indicated no horizontal pleiotropy.

          Discussion:

          Our MR study provide evidence for a causal relationship between immune cells and prostate cancer, holding implications for clinical diagnosis and treatment.

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          Most cited references45

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          Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases

          Horizontal pleiotropy occurs when the variant has an effect on disease outside of its effect on the exposure in Mendelian randomization (MR). Violation of the ‘no horizontal pleiotropy’ assumption can cause severe bias in MR. We developed the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test to identify horizontal pleiotropic outliers in multi-instrument summary-level MR testing. We showed using simulations that MR-PRESSO is best suited when horizontal pleiotropy occurs in <50% of instruments. Next, we applied MR-PRESSO, along with several other MR tests to complex traits and diseases, and found that horizontal pleiotropy: (i) was detectable in over 48% of significant causal relationships in MR; (ii) introduced distortions in the causal estimates in MR that ranged on average from −131% to 201%; (iii) induced false positive causal relationships in up to 10% of relationships; and (iv) can be corrected in some but not all instances.
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            The MR-Base platform supports systematic causal inference across the human phenome

            Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.
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              Avoiding bias from weak instruments in Mendelian randomization studies.

              Mendelian randomization is used to test and estimate the magnitude of a causal effect of a phenotype on an outcome by using genetic variants as instrumental variables (IVs). Estimates of association from IV analysis are biased in the direction of the confounded, observational association between phenotype and outcome. The magnitude of the bias depends on the F-statistic for the strength of relationship between IVs and phenotype. We seek to develop guidelines for the design and analysis of Mendelian randomization studies to minimize bias. IV analysis was performed on simulated and real data to investigate the effect on bias of size of study, number and choice of instruments and method of analysis. Bias is shown to increase as the expected F-statistic decreases, and can be reduced by using parsimonious models of genetic association (i.e. not over-parameterized) and by adjusting for measured covariates. Using data from a single study, the causal estimate of a unit increase in log-transformed C-reactive protein on fibrinogen (μmol/l) is shown to increase from -0.005 (P = 0.99) to 0.792 (P = 0.00003) due to injudicious choice of instrument. Moreover, when the observed F-statistic is larger than expected in a particular study, the causal estimate is more biased towards the observational association and its standard error is smaller. This correlation between causal estimate and standard error introduces a second source of bias into meta-analysis of Mendelian randomization studies. Bias can be alleviated in meta-analyses by using individual level data and by pooling genetic effects across studies. Weak instrument bias is of practical importance for the design and analysis of Mendelian randomization studies. Post hoc choice of instruments, genetic models or data based on measured F-statistics can exacerbate bias. In particular, the commonly cited rule of thumb that F > 10 avoids bias in IV analysis is misleading.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/2648984/overviewRole: Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/1822990/overviewRole: Role: Role:
                Role: Role:
                URI : https://loop.frontiersin.org/people/1019705/overviewRole: Role:
                URI : https://loop.frontiersin.org/people/573945/overviewRole: Role:
                URI : https://loop.frontiersin.org/people/1278080/overviewRole: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/575375/overviewRole: Role: Role: Role:
                Journal
                Front Cell Dev Biol
                Front Cell Dev Biol
                Front. Cell Dev. Biol.
                Frontiers in Cell and Developmental Biology
                Frontiers Media S.A.
                2296-634X
                19 March 2024
                2024
                : 12
                : 1381920
                Affiliations
                [1] 1 State Key Laboratory of Oncology in South China , Guangdong Provincial Clinical Research Center for Cancer , Sun Yat-Sen University Cancer Center , Guangzhou, China
                [2] 2 Department of Oncology , The First Affiliated Hospital of Jinan University , Guangzhou, China
                Author notes

                Edited by: Min Qi, Central South University, China

                Reviewed by: Xiaofang Guo, University of South Florida, United States

                Yihui Pan, First People’s Hospital of Changzhou, China

                *Correspondence: Jianfu Zhao, zhaojianfu@ 123456jnu.edu.cn ; Hailin Tang, tanghl@ 123456sysucc.org.cn
                [ † ]

                These authors have contributed equally to this work

                Article
                1381920
                10.3389/fcell.2024.1381920
                10985200
                38566827
                9bc57af7-cc55-414e-a4e9-f134f383d878
                Copyright © 2024 Ye, Deng, Zhang, Shao, Song, Zhao and Tang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 04 February 2024
                : 08 March 2024
                Funding
                The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
                Categories
                Cell and Developmental Biology
                Original Research
                Custom metadata
                Cancer Cell Biology

                prostate cancer,immune cells,mendelian randomization,single nucleotide polymorphism,genome-wide association studies

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