Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications
| dc.contributor.author | Lyra, Clelia de Oliveira | |
| dc.contributor.author | Bellot, Paula Emília Nunes Ribeiro | |
| dc.contributor.author | Braga, Erik Sobrinho | |
| dc.contributor.author | Omage, Folorunsho Bright | |
| dc.contributor.author | Nunes, Francisca Leide da Silva | |
| dc.contributor.author | Lima, Severina Carla Vieira Cunha | |
| dc.contributor.author | Marchioni, Dirce Maria Lobo | |
| dc.contributor.author | Pedrosa, Lucia Fatima Campos | |
| dc.contributor.author | Barbosa, Fernando | |
| dc.contributor.author | Tasic, Ljubica | |
| dc.contributor.author | Evangelista, Karine Cavalcanti Maurício Sena | |
| dc.date.accessioned | 2024-03-18T20:01:55Z | |
| dc.date.available | 2024-03-18T20:01:55Z | |
| dc.date.issued | 2023-07 | |
| dc.description.resumo | 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 | pt_BR |
| dc.identifier.citation | BELLOT, Paula Emília Nunes Ribeiro; BRAGA, Erik Sobrinho; OMAGE, Folorunsho Bright; NUNES, Francisca Leide da Silva; LIMA, Severina Carla Vieira Cunha; LYRA, Clélia Oliveira; MARCHIONI, Dirce Maria Lobo; PEDROSA, Lucia Fatima Campos; BARBOSA, Fernando; TASIC, Ljubica; EVANGELISTA, Karine Cavalcanti Maurício Sena. Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications. Scientific Reports, [S.l.], v. 13, n. 1, p. 1-13, 20 jul. 2023. DOI: 10.1038/s41598-023-38703-8. Disponível em: https://www.nature.com/articles/s41598-023-38703-8. Acesso em: 4 mar. 2024. | pt_BR |
| dc.identifier.doi | http://dx.doi.org/10.1038/s41598-023-38703-8 | |
| dc.identifier.uri | https://repositorio.ufrn.br/handle/123456789/57877 | |
| dc.language | en | pt_BR |
| dc.publisher | Scientific Reports | pt_BR |
| dc.rights | Attribution 3.0 Brazil | * |
| dc.rights.uri | http://creativecommons.org/licenses/by/3.0/br/ | * |
| dc.subject | Lipid metabolites | pt_BR |
| dc.subject | Obesity | pt_BR |
| dc.subject | Biomarkers | pt_BR |
| dc.subject | Cardiometabolic risk | pt_BR |
| dc.title | Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications | pt_BR |
| dc.type | article | pt_BR |
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