Regulatory T cells-related gene in primary sclerosing cholangitis: evidence from Mendelian randomization and transcriptome data

Jianlan Hu; Youxing Wu; Danxia Zhang; Xiaoyang Wang; Yaohui Sheng; Hui Liao; Yangpeng Ou; Zhen Chen; Baolian Shu; Ruohu Gui

doi:10.1038/s41435-024-00304-4

Regulatory T cells-related gene in primary sclerosing cholangitis: evidence from Mendelian randomization and transcriptome data

Genes Immun. 2024 Nov 5. doi: 10.1038/s41435-024-00304-4. Online ahead of print.

Authors

Jianlan Hu¹, Youxing Wu¹, Danxia Zhang¹, Xiaoyang Wang¹, Yaohui Sheng¹, Hui Liao¹, Yangpeng Ou², Zhen Chen³, Baolian Shu⁴, Ruohu Gui⁵

Affiliations

¹ Department of Gastroenterology, The Central Hospital of Hengyang City, Hengyang, Hunan Province, PR China.
² Department of Oncology, Huizhou Third People's Hospital, Guangzhou Medical University, Huizhou, Guangdong Province, PR China. [email protected].
³ Department of Intensive Care Unit, Shunde Hospital, Southern Medical University (the First people's hospital of Shunde), Foshan, Guangdong Province, PR China.
⁴ Department of Gastroenterology, The Central Hospital of Hengyang City, Hengyang, Hunan Province, PR China. [email protected].
⁵ Department of Gastroenterology, The Central Hospital of Hengyang City, Hengyang, Hunan Province, PR China. [email protected].

PMID: 39496776
DOI: 10.1038/s41435-024-00304-4

Abstract

The present study utilized large-scale genome-wide association studies (GWAS) summary data (731 immune cell subtypes and three primary sclerosing cholangitis (PSC) GWAS datasets), meta-analysis, and two PSC transcriptome data to elucidate the pivotal role of Tregs proportion imbalance in the occurrence of PSC. Then, we employed weighted gene co-expression network analysis (WGCNA), differential analysis, and 107 combinations of 12 machine-learning algorithms to construct and validate an artificial intelligence-derived diagnostic model (Tregs classifier) according to the average area under curve (AUC) (0.959) in two cohorts. Quantitative real-time polymerase chain reaction (qRT-PCR) verified that compared to control, Akap10, Basp1, Dennd3, Plxnc1, and Tmco3 were significantly up-regulated in the PSC mice model yet the expression level of Klf13, and Scap was significantly lower. Furthermore, immune cell infiltration and functional enrichment analysis revealed significant associations of the hub Tregs-related gene with M2 macrophage, neutrophils, megakaryocyte-erythroid progenitor (MEP), natural killer T cell (NKT), and enrichment scores of the autophagic cell death, complement and coagulation cascades, metabolic disturbance, Fc gamma R-mediated phagocytosis, mitochondrial dysfunction, potentially mediating PSC onset. XGBoost algorithm and SHapley Additive exPlanations (SHAP) identified AKAP10 and KLF13 as optimal genes, which may be an important target for PSC.