Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications
Lipidomics studies have indicated an association between obesity and lipid metabolism dysfunction. This study aimed to evaluate and compare cardiometabolic risk factors, and the lipidomic profle in adults and older people. A cross-sectional study was conducted with 72 individuals, divided into two s...
| Autores: | , , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2023 |
| País: | Brasil |
| Institución: | Universidade Federal do Rio Grande do Norte (UFRN) |
| Repositorio: | Repositório Institucional da UFRN |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.ufrn.br:123456789/57877 |
| Acceso en línea: | https://repositorio.ufrn.br/handle/123456789/57877 http://dx.doi.org/10.1038/s41598-023-38703-8 |
| Access Level: | acceso abierto |
| Palabra clave: | Lipid metabolites Obesity Biomarkers Cardiometabolic risk |
| Sumario: | Lipidomics studies have indicated an association between obesity and lipid metabolism dysfunction. This study aimed to evaluate and compare cardiometabolic risk factors, and the lipidomic profle in adults and older people. A cross-sectional study was conducted with 72 individuals, divided into two sex and age-matched groups: obese (body mass index—BMI≥ 30 kg/m2 ; n= 36) and nonobese (BMI < 30 kg/m2 ; n= 36). The lipidomic profles were evaluated in plasma using 1 H nuclear magnetic resonance (1 H-NMR) spectroscopy. Obese individuals had higher waist circumference (p< 0.001), visceral adiposity index (p= 0.029), homeostatic model assessment insulin resistance (HOMA-IR) (p= 0.010), and triacylglycerols (TAG) levels (p= 0.018). 1 H-NMR analysis identifed higher amounts of saturated lipid metabolite fragments, lower levels of unsaturated lipids, and some phosphatidylcholine species in the obese group. Two powerful machine learning (ML) models—knearest neighbors (kNN) and XGBoost (XGB) were employed to characterize the lipidomic profle of obese individuals. The results revealed metabolic alterations associated with obesity in the NMR signals. The models achieved high accuracy of 86% and 81%, respectively. The feature importance analysis identifed signal at 1.50–1.60 ppm (–CO–CH2–CH2–, Cholesterol and fatty acid in TAG, Phospholipids) to have the highest importance in the two models |
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