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. 2024 Oct 25;103(43):e40093.
doi: 10.1097/MD.0000000000040093.

Study on serum metabolomics characteristics of obese patients with erectile dysfunction

Yong Lin  1   2 , Rirun Pan  1 , Risen Deng  1 , Shengyi Fang  3 , Hui Yang  1 , Xinan Zhang  1 , Wanjun Cheng  1
Affiliations

Study on serum metabolomics characteristics of obese patients with erectile dysfunction

Yong Lin et al. Medicine (Baltimore). .

Abstract

Erectile dysfunction (ED) is a common male sexual health problem that can be associated with obesity. This study aimed to identify serum metabolic differences and pathways related to ED in obese men using non-targeted metabolomics techniques. We included 54 obese male patients with (n = 27) and without (n = 27) ED. We collected 5 mL of fasting elbow vein blood and analyzed serum metabolites using ultra-high-performance liquid chromatography-mass spectrometry. Multivariate statistical methods (principal component analysis and orthogonal partial least squares discriminant analysis) were used to identify differential metabolites between the groups. Finally, pathway analysis using the Kyoto encyclopedia of genes and genomes database identified 4 differential metabolic pathways in obese men with ED compared to obese men without ED. A total of 77 differential metabolites were identified in obese men with ED compared to the control group (obese men without ED) using a threshold of variable importance in the projection > 1 and P < .05. Pathway analysis revealed 4 main differences: glycine, serine and threonine metabolism, glycerophospholipid metabolism, aminoacyl-tRNA biosynthesis, and D-glutamine and D-glutamate metabolism. Specific metabolites associated with these pathways included betaine aldehyde, choline, L-threonine, phosphatidylcholine, L-serine, and D-glutamine. Our findings suggest abnormalities in fatty acid metabolism, phospholipid metabolism, and amino acid metabolism between obese men with and without ED. Metabolites such as betaine aldehyde, choline, L-threonine, phosphatidylcholine, L-serine, and D-glutamine may be potential biomarkers for distinguishing obese men with ED.

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Conflict of interest statement

The authors have no conflicts of interest to disclose.

Figures

Figure 1.
Figure 1.
Quality control of the testing process. Notes: A = EIC diagram of QC samples in positive ions, B = EIC diagram of QC samples in negative ions, C = EIC diagram of QC samples and blank in positive ions, D = EIC diagram of QC samples and blank in negative ions. IS1, IS2, and IS3 are isotope labeled metabolites for quality control in detection. EIC = extracted ion current, QC=quality control.
Figure 2.
Figure 2.
Quality control of data. Notes: A = PCA diagram of QC samples and testing samples in positive ions, B = EIC diagram of QC samples and testing samples in negative ions, C = PCA-X one-dimensional distribution diagram of QC samples in positive ions, D = PCA-X one-dimensional distribution diagram of QC samples in negative ions, E = correlation analysis diagram of QC samples in positive ions, F = correlation analysis diagram of QC samples in negative ions. EIC = extracted ion current, PCA=principal component analysis, QC=quality control.
Figure 3.
Figure 3.
OPLS-DA analysis under positive and negative ion modes. Note: A = OPLS-DA analysis diagram of testing samples in positive ions, B = OPLS-DA analysis diagram of testing samples in negative ions, C = permutation test of OPLS-DA model for samples in positive ions, D = permutation test of OPLS-DA model for samples in negative ions. OPLS-DA = orthogonal partial least squares discriminant analysis.
Figure 4.
Figure 4.
Bubble plots and differential abundance plots of metabolic pathways. Notes: A = bubble diagram of metabolic pathways in positive ion mode, B = bubble diagram of metabolic pathways in negative ion mode, C = differential abundance plots of metabolic pathways in positive ion mode, D = differential abundance plots of metabolic pathways in negative ion mode. Line segments represent the up and down regulation of the pathway. A regular line segment indicates an overall up regulation of the pathway, while a negative line segment indicates an overall down regulation of the pathway. The size of the endpoint of the line segment represents the quantity of annotated substances in the pathway.
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