ASSESSING METABOLIC CHANGES IN ATHLETES WITH ISCHEMIC HEART FAILURE AND CHRONIC KIDNEY DISEASE USING ULTRA PERFORMANCE LIQUID CHROMATOGRAPHY-HIGH RESOLUTION MASS SPECTROMETRY (UPLC-HRMS)

Authors

  • Haiyan Wu Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming,650000, Yunnan, China.
  • Wenbin Liu Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200000, China.
  • Lunzhao Yi Faculty of Agriculture and Food, Kunming University of Science and Technology, Kunming,650000, Yunnan, China.
  • Hong Zhang Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming,650000, Yunnan, China.
  • Kunzhi Li Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming,650000, Yunnan, China.
  • Yan Zhao Department of Cardiovascular Medicine, The First People's Hospital of Yunnan Province, Kunming,650000, Yunnan, China.
  • Xiaoxue Ding Department of Cardiovascular Medicine, The First People's Hospital of Yunnan Province, Kunming,650000, Yunnan, China.

Keywords:

Heart failure, Chronic kidney disease, Metabolomics, Biomarkers, UPLC-HRMS, PLS-DA

Abstract

Objective: To explore the implications of ischemic heart failure (HF) and its progression to chronic kidney disease (CKD) in athletic individuals through advanced metabolomic profiling. Methods: This study examined systolic HF from ischemic origins and CKD resulting from ischemic HF in athletes. Participants included 32 patients with ischemic HF, 15 with HF-induced CKD, and 47 healthy athletic controls, all assessed between January 2017 and April 2018. Plasma samples were analyzed using ultra-high performance liquid chromatography–high resolution mass spectrometry (UPLC-HRMS), with data processed through Partial Least Squares-Discriminant Analysis (PLS-DA) to identify distinctive metabolic biomarkers. Results: Metabolic profiling revealed 78 distinct endogenous metabolites. The PLS-DA models effectively differentiated between HF and control groups, as well as HF and HF-CKD groups. Key biomarkers identified included LysoPC (18:2), choline, valine, indole, 3-indoleacrylic acid, and p-cresyl sulfate for HF; and LysoPC (18:3), γ-caprolactone, ketovaleric acid_1, and ketovaleric acid_2 for HF-CKD. These biomarkers linked primarily to disrupted lipid and amino acid metabolism pathways. Conclusion: Metabolomic profiling via UPLC-HRMS has uncovered critical metabolic shifts and biomarkers in athletes with ischemic HF and HF-related CKD, highlighting the potential for targeted management strategies to mitigate the progression of these conditions in sports medicine.

Published

2023-02-28