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. 2022 Feb 22;12:2991. doi: 10.1038/s41598-022-06956-4

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© The Author(s) 2022

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 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/.

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Principal component analysis of the combined miRNA and physiological parameter data. (A) Projection of the data on the first two principal components, which explain ~ 20% and 11% of the variance. PC1 imperfectly separates the healthy active individuals from sedentary at risk. (B) PCA loadings of the first 30 variables contributing most to explaining the variance in the data (as indicated on the colour scale).