Abstract
Background and Aims: Metabolic syndrome (MetS) comprises a set of risk factors that contribute to the development of chronic and cardiovascular diseases, increasing the mortality rate. Altered lipid metabolism is associated with the development of metabolic disorders such as insulin resistance, obesity, atherosclerosis, and metabolic syndrome; however, there is a lack of knowledge about lipids compounds and the lipidic pathways associated with this condition, particularly in the Latin-American population. Innovative approaches, such as lipidomic analysis, facilitate the identification of lipid species related to these risk factors. This study aimed to assess the plasma lipidome in subjects with MetS. Methods: This correlation study included healthy adults and adults with MetS. Blood samples were analyzed. The lipidomic profile was determined using an Agilent Technologies 1260 liquid chromatography system coupled to a Q-TOF 6545 quadrupole mass analyzer with electrospray ionization. The main differences were determined between the groups. Results: The analyses reveal a distinct lipidomic profile between healthy adults and those with MetS, including increased concentrations of most identified glycerolipids -both triglycerides and diglycerides- and decreased levels of ether lipids and sphingolipids, especially sphingomyelins, in MetS subjects. Association between high triglycerides, waist circumference, and most differentially expressed lipids were found. Conclusion: Our results demonstrate dysregulation of lipid metabolism in subjects with Mets, supporting the potential utility of plasma lipidome analysis for a deeper understanding of MetS pathophysiology.
| Original language | English |
|---|---|
| Pages (from-to) | 1279-1292 |
| Number of pages | 14 |
| Journal | Journal of Diabetes and Metabolic Disorders |
| Volume | 23 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jun 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Abdominal obesity
- Insulin resistance
- Lipidomics analysis
- Metabolic Syndrome
- Metabolome
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