Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis

孟德尔随机化 全基因组关联研究 免疫系统 人类白细胞抗原 计算生物学 医学 生物信息学 生物 肿瘤科 免疫学 基因 单核苷酸多态性 遗传学 基因型 抗原 遗传变异
作者
Weiwei Pang,Yisheng Cai,Chong Cao,Furong Zhang,Qin Zeng,Danyang Liu,Ning Wang,Xiaochao Qu,Xiang‐Ding Chen,Hong‐Wen Deng,Lijun Tan
出处
期刊:Frontiers in Immunology [Frontiers Media SA]
卷期号:15 被引量:1
标识
DOI:10.3389/fimmu.2024.1334479
摘要

Background The immune microenvironment assumes a significant role in the pathogenesis of osteoarthritis (OA). However, the current biomarkers for the diagnosis and treatment of OA are not satisfactory. Our study aims to identify new OA immune-related biomarkers to direct the prevention and treatment of OA using multi-omics data. Methods The discovery dataset integrated the GSE89408 and GSE143514 datasets to identify biomarkers that were significantly associated with the OA immune microenvironment through multiple machine learning methods and weighted gene co-expression network analysis (WGCNA). The identified signature genes were confirmed using two independent validation datasets. We also performed a two-sample mendelian randomization (MR) study to generate causal relationships between biomarkers and OA using OA genome-wide association study (GWAS) summary data (cases n = 24,955, controls n = 378,169). Inverse-variance weighting (IVW) method was used as the main method of causal estimates. Sensitivity analyses were performed to assess the robustness and reliability of the IVW results. Results Three signature genes (FCER1G, HLA-DMB, and HHLA-DPA1) associated with the OA immune microenvironment were identified as having good diagnostic performances, which can be used as biomarkers. MR results showed increased levels of FCER1G (OR = 1.118, 95% CI 1.031-1.212, P = 0.041), HLA-DMB (OR = 1.057, 95% CI 1.045 -1.069, P = 1.11E-21) and HLA-DPA1 (OR = 1.030, 95% CI 1.005-1.056, P = 0.017) were causally and positively associated with the risk of developing OA. Conclusion The present study identified the 3 potential immune-related biomarkers for OA, providing new perspectives for the prevention and treatment of OA. The MR study provides genetic support for the causal effects of the 3 biomarkers with OA and may provide new insights into the molecular mechanisms leading to the development of OA.
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