Identification of the immune-related biomarkers in Behcet's disease by plasma proteomic analysis.

ABSTRACT:

Background

This study aimed to investigate the expression profile of immune response-related proteins of Behcet's disease (BD) patients and identify potential biomarkers for this disease.

Methods

Plasma was collected from BD patients and healthy controls (HC). Immune response-related proteins were measured using the Olink Immune Response Panel. Differentially expressed proteins (DEPs) were used to construct prediction models via five machine learning algorithms: naive Bayes, support vector machine, extreme gradient boosting, random forest, and neural network. The prediction performance of the five models was assessed using the area under the curve (AUC) value, recall (sensitivity), specificity, precision, accuracy, F1 score, and residual distribution. Subtype analysis of BD

SUBMITTER: Liu H 

PROVIDER: S-EPMC10233985 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature