Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

letter

. 2022 Aug 30;7(16):4269–4277. doi: 10.1182/bloodadvances.2022008061

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© 2023 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

PMC Copyright notice

Figure 1. — Metabolome analysis reveals time-dependent metabolic effect of testosterone over a 12-month period. (A) RBC samples were taken from adolescent patients (N = 15) at baseline and 1 and 12 months after starting testosterone. (B) A line plot of the data normalized to 0 months revealed various descriptive variables that changed over time. (C) A principal component analysis revealed distinct clustering patterns between the baseline, 1-month, and 12-month timepoints. (D) A variable importance in projection (VIP) plot suggested that acylcarnitines as well as metabolites from glycolysis and the trichloroacetic acid (TCA) were most influential in the PLS-DA clustering pattern. (E) Pathway analysis revealed the pathways most affected by treatment duration. (F) A Spearman rank order correlation of the normalized data determined the top significant correlates to testosterone duration (P ≤ .05). (G) A line plot of diphosphoglycerate (DPG) shows that it increases over treatment duration (mean± standard error of the mean). Testosterone alters the global metabolome. (H) Hierarchal clustering analysis of the top 50 most significant metabolites by analysis of variance revealed time-dependent changes in acylcarnitines, glycolysis, and purine metabolism. (I) Separate clustering by C-means uncovered 3 groups of metabolites with distinct time-dependent trends that support the analysis of variance findings. (J) An elemental inductively coupled plasma-mass-spectrometry analysis was performed on RBC samples (N = 15) to determine cation levels. (K) Line plots revealed ion-specific trends over testosterone duration (mean ± standard error of the mean). LDL, low-density lipoprotein; PLS-DA, partial least squares discriminant analysis.

Figure 1. — Metabolome analysis reveals time-dependent metabolic effect of testosterone over a 12-month period. (A) RBC samples were taken from adolescent patients (N = 15) at baseline and 1 and 12 months after starting testosterone. (B) A line plot of the data normalized to 0 months revealed various descriptive variables that changed over time. (C) A principal component analysis revealed distinct clustering patterns between the baseline, 1-month, and 12-month timepoints. (D) A variable importance in projection (VIP) plot suggested that acylcarnitines as well as metabolites from glycolysis and the trichloroacetic acid (TCA) were most influential in the PLS-DA clustering pattern. (E) Pathway analysis revealed the pathways most affected by treatment duration. (F) A Spearman rank order correlation of the normalized data determined the top significant correlates to testosterone duration (P ≤ .05). (G) A line plot of diphosphoglycerate (DPG) shows that it increases over treatment duration (mean± standard error of the mean). Testosterone alters the global metabolome. (H) Hierarchal clustering analysis of the top 50 most significant metabolites by analysis of variance revealed time-dependent changes in acylcarnitines, glycolysis, and purine metabolism. (I) Separate clustering by C-means uncovered 3 groups of metabolites with distinct time-dependent trends that support the analysis of variance findings. (J) An elemental inductively coupled plasma-mass-spectrometry analysis was performed on RBC samples (N = 15) to determine cation levels. (K) Line plots revealed ion-specific trends over testosterone duration (mean ± standard error of the mean). LDL, low-density lipoprotein; PLS-DA, partial least squares discriminant analysis.