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. 2022 Mar 8;12:3764. doi: 10.1038/s41598-022-07829-6

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© The Author(s) 2022, corrected publication 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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Separation of ASD (n = 40) and age-matched healthy (n = 40) subjects using principal component analysis. The analysis was performed using five variables: potassium (K), sodium (Na), lactate dehydrogenase (LDH), glutathione S-transferase (GST), and mitochondrial respiratory chain complex I (MRC1). Table (top right) shows variable contributions to the first principal component. Graph (bottom) shows the results of Monte Carlo simulation with eigenvalues plotted for raw data and 50th and 95th percentile simulated data. Results of Kaiser–Meyer–Olkin measure of sampling adequacy (KMO) and Bartlett’s test of sphericity are indicated. Figure panels were compiled in Microsoft PowerPoint Slide Presentation Software, Microsoft 365, Microsoft.com. PCA panel (top) was generated in BioNumerics version 6.6, Applied Maths, Austin, Texas, https://www.bionumerics.com. Monte Carlo simulation panel (bottom) was generated in IBM SPSS Statistics for Windows, Version 27.0, IBM Corp., Armonk, New York, https://www.ibm.com.