Identification of Immune-Related Genes in Patients with Acute Myocardial Infarction Using Machine Learning Methods.

ABSTRACT:

Objective

This study aimed to analyze immune-related genes and immune cell components in the peripheral blood of patients with acute myocardial infarction (AMI).

Methods

Six datasets were obtained from the GEO repository comprising 88 healthy samples and 215 AMI samples. We performed the weighted gene co-expression analysis (WGCNA) and five machine learning (ML) methods to identify immune-related genes and construct diagnostic models. CIBERSORT algorithm was adopted for the assessment of the degree of immune infiltration. Finally, RT-PCR, immunofluorescence double and immunohistochemistry were conducted to analyze the expression level of the identification of featured immune-related genes and localization relationship in heart tissue of AMI mouse model.

Results

A tota

SUBMITTER: Zhu X 

PROVIDER: S-EPMC9174022 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature