Classification models using circulating neutrophil transcripts can detect unruptured intracranial aneurysm.

ABSTRACT:

Background

Intracranial aneurysms (IAs) are dangerous because of their potential to rupture. We previously found significant RNA expression differences in circulating neutrophils between patients with and without unruptured IAs and trained machine learning models to predict presence of IA using 40 neutrophil transcriptomes. Here, we aim to develop a predictive model for unruptured IA using neutrophil transcriptomes from a larger population and more robust machine learning methods.

Methods

Neutrophil RNA extracted from the blood of 134 patients (55 with IA, 79 IA-free controls) was subjected to next-generation RNA sequencing. In a randomly-selected training cohort (n = 94), the Least Absolute Shrinkage and Selection Operator (LASSO) selected transcripts, from which we constru

SUBMITTER: Poppenberg KE 

PROVIDER: S-EPMC7565814 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature