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. 2022 Nov 23;20:457. doi: 10.1186/s12916-022-02660-2

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© The Author(s) 2022

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 3 — MR forest plot of significant biomarkers on ER-negative breast cancer liability. Biomarkers of nominal significance in IVW MR analyses are shown in descending order of significance. The forest plot in the centre displays the odds ratio of the effect of a SD increase in genetically predicted biomarker concentration on overall breast cancer liability as a square, with error bars representing the 95% CI. In addition to the main analysis based on IVW MR, we include sensitivity analyses based on the weighted median, MR-Egger, MR-PRESSO, and MVMR accounting for known pleiotropic pathways. N. SNPs, number of SNPs; CI, confidence interval; Int. P-value, intercept P-value of MR-Egger; BMI, body mass index. An asterisk (*) indicates nominal significance. Two asterisks (**) indicate FDR-corrected significance