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...

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Principais autores: Lyra, Clelia de Oliveira, Bellot, Paula Emília Nunes Ribeiro, Braga, Erik Sobrinho, Omage, Folorunsho Bright, Nunes, Francisca Leide da Silva, Lima, Severina Carla Vieira Cunha, Marchioni, Dirce Maria Lobo, Pedrosa, Lucia Fatima Campos, Barbosa, Fernando, Tasic, Ljubica, Evangelista, Karine Cavalcanti Maurício Sena
Formato: article
Idioma:English
Publicado em: Scientific Reports
Assuntos:
Lipid metabolites
Obesity
Biomarkers
Cardiometabolic risk
Endereço do item:https://repositorio.ufrn.br/handle/123456789/57877
http://dx.doi.org/10.1038/s41598-023-38703-8
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spelling ri-123456789-578772024-03-18T20:01:55Z Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications Lyra, Clelia de Oliveira Bellot, Paula Emília Nunes Ribeiro Braga, Erik Sobrinho Omage, Folorunsho Bright Nunes, Francisca Leide da Silva Lima, Severina Carla Vieira Cunha Marchioni, Dirce Maria Lobo Pedrosa, Lucia Fatima Campos Barbosa, Fernando Tasic, Ljubica Evangelista, Karine Cavalcanti Maurício Sena Lipid metabolites Obesity Biomarkers Cardiometabolic risk 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 2024-03-18T20:01:55Z 2024-03-18T20:01:55Z 2023-07 article 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. https://repositorio.ufrn.br/handle/123456789/57877 http://dx.doi.org/10.1038/s41598-023-38703-8 en Attribution 3.0 Brazil http://creativecommons.org/licenses/by/3.0/br/ application/pdf Scientific Reports
institution Repositório Institucional
collection RI - UFRN
language English
topic Lipid metabolites
Obesity
Biomarkers
Cardiometabolic risk
spellingShingle Lipid metabolites
Obesity
Biomarkers
Cardiometabolic risk
Lyra, Clelia de Oliveira
Bellot, Paula Emília Nunes Ribeiro
Braga, Erik Sobrinho
Omage, Folorunsho Bright
Nunes, Francisca Leide da Silva
Lima, Severina Carla Vieira Cunha
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
description 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
format article
author Lyra, Clelia de Oliveira
Bellot, Paula Emília Nunes Ribeiro
Braga, Erik Sobrinho
Omage, Folorunsho Bright
Nunes, Francisca Leide da Silva
Lima, Severina Carla Vieira Cunha
Marchioni, Dirce Maria Lobo
Pedrosa, Lucia Fatima Campos
Barbosa, Fernando
Tasic, Ljubica
Evangelista, Karine Cavalcanti Maurício Sena
author_facet Lyra, Clelia de Oliveira
Bellot, Paula Emília Nunes Ribeiro
Braga, Erik Sobrinho
Omage, Folorunsho Bright
Nunes, Francisca Leide da Silva
Lima, Severina Carla Vieira Cunha
Marchioni, Dirce Maria Lobo
Pedrosa, Lucia Fatima Campos
Barbosa, Fernando
Tasic, Ljubica
Evangelista, Karine Cavalcanti Maurício Sena
author_sort Lyra, Clelia de Oliveira
title Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications
title_short Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications
title_full Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications
title_fullStr Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications
title_full_unstemmed Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications
title_sort plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications
publisher Scientific Reports
publishDate 2024
url https://repositorio.ufrn.br/handle/123456789/57877
http://dx.doi.org/10.1038/s41598-023-38703-8
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