Nontargeted and Targeted Metabolic Profile of Metabolic Syndrome Patients: A Study Based on Yi and Han Populations in Yunnan

Yan-mei Ji¹Ni Guo¹Wen-jun Li¹Xian-yu He¹Meng-yao Dao¹Ni Meng¹Dan Zhou¹Hai-tao Tian¹Ting Pi²Xiao-feng Zong¹Qing Xiong³Zhong-juan Wang^2*Xing-fang Jin^1*

• ¹Department of Cardiovascular Surgery, Yan’an Hospital Affiliated to Kunming Medical University, Clinical Medical Research Center for Cardiovascular Disease of Yunnan Province, Kunming, China
• ²Department of Pharmacy, Yan'an Hospital Affiliated to Kunming Medical University, Kunming, China
• ³Department of Endocrinology, Yan'an Hospital Affiliated to Kunming Medical University, Kunming, China

Objective: Ultra-high-performance liquid chromatography-time-of-flight mass spectrometry (UHPLC-TOF-MS) was employed to analyze serum metabolites and metabolic pathways associated with metabolic syndrome (MS) in the Yi and Han populations of Yunnan. Methods: Participants included individuals diagnosed with MS and healthy controls from the Yi and Han populations of Yunnan. Serum nontargeted and amino acid-targeted metabolomics analyses were conducted to identify differential serum metabolites (DEMs) and metabolic pathways associated with MS pathogenesis in these two ethnic groups. Results: Nontargeted metabolomics analysis revealed 2,762 DEMs in the MS group of the Han population, while 1,535 DEMs were identified in the MS group of the Yi population [variable importance in projection (VIP)>1, P<0.05]. Venn analysis highlighted common and unique DEMs between the two populations. KEGG pathway analysis identified seven significantly enriched pathways in the Han group and five in the Yi group, primarily involving amino acid synthesis and metabolism. To investigate the role of amino acids in MS, serum levels of 71 endogenous amino acids were quantified. In the MS group of the Han population, 19 differential amino acids were identified, significantly enriched in pathways related to D-glutamine and D-glutamate metabolism, as well as cysteine and methionine metabolism. In the Yi population, six differential amino acids were identified, with significant enrichment in D-glutamine and D-glutamate metabolism, sulfur metabolism, and valine, leucine, and isoleucine biosynthesis. Conclusion: Our study investigates metabolic differences in metabolic syndrome (MS) between Yi and Han populations through nontargeted and targeted metabolomics approaches, identifying both common and unique metabolites and metabolic pathways associated with MS, especially amino acid metabolic disorders, including glycine, serine, and threonine metabolism, D-glutamine and D-glutamate metabolism, which may play critical roles in regulating different metabolic dysfunctions and worth further exploration in MS pathogenesis, which might provide insights for the effective prevention and treatment of MS in various populations.