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      Genetic causal relationship between gut microbiota and basal cell carcinoma: A two‐sample mendelian randomization study

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          Abstract

          Objective

          Research has previously established connections between the intestinal microbiome and the progression of some cancers. However, there is a noticeable gap in the literature in regard to using Mendelian randomisation (MR) to delve into potential causal relationships between the gut microbiota (GM) and basal cell carcinoma (BCC). Therefore, the purpose of our study was to use MR to explore the causal relationship between four kinds of GM (Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae) and BCC.

          Methods

          We used genome‐wide association study (GWAS) data and MR to explore the causal relationship between four kinds of GM and BCC. This study primarily employed the random effect inverse variance weighted (IVW) model for analysis, as complemented by additional methods including the simple mode, weighted median, weighted mode and MR‒Egger methods. We used heterogeneity and horizontal multiplicity to judge the reliability of each analysis. MR‐PRESSO was mainly used to detect and correct outliers.

          Results

          The random‐effects IVW results showed that Bacteroides (OR = 0.936, 95% CI = 0.787–1.113, p = 0.455), Streptococcus (OR = 0.974, 95% CI = 0.875–1.083, p = 0.629), Proteobacteria (OR = 1.113, 95% CI = 0.977–1.267, p = 0.106) and Lachnospiraceae (OR = 1.027, 95% CI = 0.899–1.173, p = 0.688) had no genetic causal relationship with BCC. All analyses revealed no horizontal pleiotropy, heterogeneity or outliers.

          Conclusion

          We found that Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae do not increase the incidence of BCC at the genetic level, which provides new insight for the study of GM and BCC.

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          Most cited references55

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          A global reference for human genetic variation

          The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
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            Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

            Background: The number of Mendelian randomization analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. However, some genetic variants may not be valid instrumental variables, in particular due to them having more than one proximal phenotypic correlate (pleiotropy). Methods: We view Mendelian randomization with multiple instruments as a meta-analysis, and show that bias caused by pleiotropy can be regarded as analogous to small study bias. Causal estimates using each instrument can be displayed visually by a funnel plot to assess potential asymmetry. Egger regression, a tool to detect small study bias in meta-analysis, can be adapted to test for bias from pleiotropy, and the slope coefficient from Egger regression provides an estimate of the causal effect. Under the assumption that the association of each genetic variant with the exposure is independent of the pleiotropic effect of the variant (not via the exposure), Egger’s test gives a valid test of the null causal hypothesis and a consistent causal effect estimate even when all the genetic variants are invalid instrumental variables. Results: We illustrate the use of this approach by re-analysing two published Mendelian randomization studies of the causal effect of height on lung function, and the causal effect of blood pressure on coronary artery disease risk. The conservative nature of this approach is illustrated with these examples. Conclusions: An adaption of Egger regression (which we call MR-Egger) can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations. The approach provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.
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              Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator

              ABSTRACT Developments in genome‐wide association studies and the increasing availability of summary genetic association data have made application of Mendelian randomization relatively straightforward. However, obtaining reliable results from a Mendelian randomization investigation remains problematic, as the conventional inverse‐variance weighted method only gives consistent estimates if all of the genetic variants in the analysis are valid instrumental variables. We present a novel weighted median estimator for combining data on multiple genetic variants into a single causal estimate. This estimator is consistent even when up to 50% of the information comes from invalid instrumental variables. In a simulation analysis, it is shown to have better finite‐sample Type 1 error rates than the inverse‐variance weighted method, and is complementary to the recently proposed MR‐Egger (Mendelian randomization‐Egger) regression method. In analyses of the causal effects of low‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol on coronary artery disease risk, the inverse‐variance weighted method suggests a causal effect of both lipid fractions, whereas the weighted median and MR‐Egger regression methods suggest a null effect of high‐density lipoprotein cholesterol that corresponds with the experimental evidence. Both median‐based and MR‐Egger regression methods should be considered as sensitivity analyses for Mendelian randomization investigations with multiple genetic variants.
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                Author and article information

                Contributors
                plastic369@163.com
                Journal
                Skin Res Technol
                Skin Res Technol
                10.1111/(ISSN)1600-0846
                SRT
                Skin Research and Technology
                John Wiley and Sons Inc. (Hoboken )
                0909-752X
                1600-0846
                19 June 2024
                June 2024
                : 30
                : 6 ( doiID: 10.1111/srt.v30.6 )
                : e13804
                Affiliations
                [ 1 ] Department of Comprehensive Plastic Surgery Plastic Surgery Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
                Author notes
                [*] [* ] Correspondence

                Qingguo Zhang, Department of Auricular Reconstruction, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.

                Email: plastic369@ 123456163.com

                Article
                SRT13804
                10.1111/srt.13804
                11187847
                38895789
                85d80229-23d8-4c20-8d83-ab8247ad3a11
                © 2024 The Author(s). Skin Research and Technology published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 May 2024
                : 27 May 2024
                Page count
                Figures: 5, Tables: 2, Pages: 10, Words: 5357
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 81571924
                Funded by: CAMS Innovation Fund for Medical Sciences
                Award ID: 2021‐I2M‐1‐068
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                June 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.4 mode:remove_FC converted:19.06.2024

                basal cell carcinoma,causality,genetics,gut microbiota,mendelian randomisation study

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