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. 2023 Feb 2;14:571. doi: 10.1038/s41467-023-36256-y

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© The Author(s) 2023

Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — a Phenotypic and genetic correlations between paired fecal and blood metabolites for the top 30 metabolites that are ranked by phenotypic correlations. Phenotypic correlations between paired fecal and blood metabolites are estimated by partial Spearman correlation analysis, adjusted by age, sex and BMI. Genetic correlations are calculated using bivariate GREML analysis. Correlations with FDR < 0.05 and $∣ r ∣$ > 0.3 (red dashed lines) are considered significant. FDR is controlled by the Benjamini-Hochberg method. *FDR < 0.05, **FDR < 0.01, *** FDR < 0.005. The results for remaining metabolites are shown in Supplementary Fig. 2. For genetic correlation analysis, there are 38 metabolites that do not converged during the calculation process and thus have no results. b The overlap between significant phenotypic and genetic correlations. All statistical tests are two-sided. Source data are provided as a Source Data file.