A Scoring Model Using Multi-Metabolites Based on Untargeted Metabolomics for Assessing Dyslipidemia in Korean Individuals with Obesity.

ABSTRACT:

Background/objectives

Metabolite risk score (MRS), which considers the collective effects of metabolites closely reflecting a phenotype, is a new approach for disease assessment, moving away from focusing solely on individual biomarkers. This study aimed to investigate a metabolite panel for dyslipidemia and verify the diagnostic efficacy of MRS on dyslipidemia.

Methods

Key metabolite identification and MRS establishment were conducted in the discovery set, and MRS validation was performed in the replication set, with 50 healthy individuals and 50 dyslipidemia patients in each set. The MRS was constructed using key metabolites, identified via UPLC-MS/MS analysis, employing a weighted approach based on linear regression analysis.

Results

N-acetylisoputreanine-γ-lactam

SUBMITTER: Yang SG 

PROVIDER: S-EPMC12029618 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature