Establishment of a Prediction Model for Different Progression of Atherosclerosis in Apoe ^-/- Mice Based on Lipidomics

Abstract

Atherosclerosis is a progressive disease with complex pathogenesis, which is characterized by dyslipidemia and changes in vascular wall composition. According to the degree of lesion, atherosclerosis can be divided into four stages:hyperlipidemia, lipid stria, fiber plaque, and AS. The present study aimed to establish a prediction model for different pathological stages of AS based on lipidomics. APOE -/- mice and C57BL/6 mice fed a normal diet were divided into seven groups according to feeding time (8, 12, 16, 20, 24, 28, and 32 weeks). The changes in lipid composition and serum content were detected by UPLC-Q-TOF. In accordance with the lipid data of each course of AS and mathematical modeling, this study established the multi-index prediction model of different processes of AS. Notably, while establishing the model, several indicators combined with such four dimension reduction methods, such as principal component logistics regression method, cumulative logistics regression method, partial least square method (PLSDA), and typical discriminant method (CDA). The error rate of the four methods to establish models were 28.5%, 16.22%, 18.24%, and 14.86%, respectively. The typical discriminant method with low judgment rate was selected for multi-index modeling, and the training and verification sets of different states verified by 50% discount cross-verification of CDA model are superior. This study showed that lipidomics combined with mathematical methods could establish a non-invasive and accurate AS prediction model.

Note:
Funding Information: The experimental funding for this article comes from the Independent topic selection project for scientific research business expenses of Basic Theory of Chinese Medicine Institute of Chinese Academy of Chinese Medical Sciences supported by“the Fundamental Research Funds for the Central public welfare research institutes”

Declaration of Interests: None to declare.

Ethics Approval Statement: This study was approved by the China Academy of Chinese Medicine Science, Institute of Basic Theory for Chinese Medicine.

Keywords: atherosclerosis, lipidomics, mathematical modeling, disease course prediction