# Screening and molecular functional analysis of telomere-related genes in abdominal aortic aneurysms based on bioinformatics

## TL;DR

This study explores telomere-related genes in abdominal aortic aneurysms to find new biomarkers and potential drug targets for treatment.

## Contribution

The study identifies KLF15 and ZBTB16 as key telomere-related biomarkers linked to immune infiltration and AAA progression.

## Key findings

- KLF15 and ZBTB16 were prioritized as significant biomarkers associated with immune-inflammatory responses in AAA.
- Overexpression of ZBTB16 reduced inflammation, apoptosis, and migration in vascular smooth muscle cells.
- Single-cell analysis confirmed ZBTB16 enrichment in B cells and its role in suppressing AAA progression.

## Abstract

Abdominal aortic aneurysm (AAA) is a life-threatening vascular condition characterized by progressive aortic dilation. However, no effective pharmacotherapies exist to halt its progression. This study aimed to investigate telomere-related molecular signatures in AAA to identify potential targets for therapeutic development.

We obtained the dataset GSE57691, including the RNA-expression data of AAA and normal control samples, from the GEO database. Weighted Gene Co-expression Network Analysis (WGCNA) was performed using the “WGCNA” package to identify AAA phenotype-related gene modules, and differential expression analysis of differentially expressed genes (DEGs) was conducted using the “limma” package. Biomarker identification was achieved through LASSO and Support Vector Machine (SVM) algorithms using the “glmnet” and “e1071” packages. GSEA_4.2.2 was utilized for gene enrichment analysis, and “CIBERSORT” and “estimate” were employed for immune infiltration. An independent single-cell RNA-seq dataset (GSE237230) was analyzed using the Seurat pipeline to characterize the cellular landscape and validate biomarker expression at single-cell resolution. Finally, the hTFtarget and Encori databases were utilized to construct the transcriptional regulatory network, and the “oncoPredict” package was employed to identify potential drugs. We verified the reliability of the model genes in vitro via the quantification assays (qPCR, western blot and ELISA) and the phenotypic determination assays (flow cytometry and trans-well).

Following WGCNA, AAA-related modules (MEmagenta/MEpink) were identified. Intersecting gene modules, DEGs, and telomere genes yielded eight candidates, among which KLF15 and ZBTB16 were prioritized via Lasso and SVM. Low expression of these biomarkers correlated with immune-inflammatory activation, whereas high expression was linked to a suppressive microenvironment that alleviated AAA progression. Furthermore, a transcriptional regulatory network was constructed, identifying key target mRNAs and potential drugs. Single-cell analysis confirmed distinct clusters and specific enrichment of ZBTB16 in B cells. Angiotensin II (Ang II) treatment downregulated KLF15 and ZBTB16 in T/G HA-VSMCs. Overexpression of ZBTB16 attenuated Ang II-induced inflammation, apoptosis, and migration and suppressed MMP-2/9 levels, indicating inhibited migratory activity.

We analyzed telomere-related signatures in AAA and identified two crucial biomarkers linked to the immune infiltration of patients. Our findings furthered the understanding of telomere signatures in AAA progression.