Hui Jingni, He Dan, Liu Chen, Shi Panxing, Zhou Ruixue, Kang Meijuan, Liu Ye, Gou Yifan, Wang Bingyi, Cheng Shiqiang, Yang Xuena, Pan Chuyu, Wei Wenming, Zhang Feng
Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, 710061 Xi'an, China.
Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, 710061 Xi'an, China.
Joint Bone Spine. 2025 May;92(3):105841. doi: 10.1016/j.jbspin.2024.105841. Epub 2024 Dec 26.
This study aimed to investigate the associations of multi-omics polygenic risk score (PRS) and rheumatoid arthritis (RA) to identify potential genes/proteins and biological pathways.
Based on multi-omics data from 48,813 participants in the INTERVAL cohort, we calculated multi-omics PRS for 13,646 mRNAs (RNASeq), 308 proteins (Olink), 2380 proteins (SomaScan), 726 metabolites (Metabolon), and 141 metabolites (Nightingale). Using the generalized linear model, we first evaluated the associations between multi-omics PRS and RA in 58,813 UK Biobank participants. The Gene Ontology (GO) project and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to identify the functional pathways in RA. Furthermore, differential gene expression profile datasets were used to validate the identified genes/proteins in our study.
We identified 59 transcriptomics PRS and 29 proteomics PRS significantly associated with RA. Both proteomics and transcriptomic PRS identified HLA-DQA2 (RNASeq: OR=1.19, P=1.18×10; SomaScan: OR=1.24, P=4.43×10) and AGER (RNASeq: OR=0.91, P=4.18×10; SomaScan: OR=0.93, P=3.97×10) were significantly associated with RA. Proteomic PRS from different profiling platforms (SomaScan and Olink) identified a consistent association between TFF3 (SomaScan: OR=0.90, P=4.08×10; Olink: OR=0.93, P=4.87×10) and RA. The identified gene/proteins were mainly enriched in the NF-kappa B signaling pathway (hsa04064, P=5.06×10) and Cytokine-cytokine receptor interaction (hsa04060, P=2.49×10). In addition, a total of 12 candidate genes in our study were verified in two independent GEO datasets, such as FLOT1 and ABCF1.
Our findings provide novel insights into the involvement of identified genes/proteins and pathways in the pathogenesis of RA from multi-omics levels.
本研究旨在探讨多组学多基因风险评分（PRS）与类风湿性关节炎（RA）之间的关联，以识别潜在的基因/蛋白质和生物学途径。
基于INTERVAL队列中48813名参与者的多组学数据，我们计算了13646个mRNA（RNA测序）、308种蛋白质（Olink）、2380种蛋白质（SomaScan）、726种代谢物（Metabolon）和141种代谢物（Nightingale）的多组学PRS。使用广义线性模型，我们首先在58813名英国生物银行参与者中评估了多组学PRS与RA之间的关联。进行基因本体论（GO）项目和京都基因与基因组百科全书（KEGG）以识别RA中的功能途径。此外，使用差异基因表达谱数据集来验证我们研究中鉴定出的基因/蛋白质。
我们鉴定出59个转录组学PRS和29个蛋白质组学PRS与RA显著相关。蛋白质组学和转录组学PRS均鉴定出HLA - DQA2（RNA测序：OR = 1.19，P = 1.18×10；SomaScan：OR = 1.24，P = 4.43×10）和AGER（RNA测序：OR = 0.91，P = 4.18×10；SomaScan：OR = 0.93，P = 3.97×10）与RA显著相关。来自不同分析平台（SomaScan和Olink）的蛋白质组学PRS鉴定出TFF3（SomaScan：OR = 0.90，P = 4.08×10；Olink：OR = 0.93，P = 4.87×10）与RA之间存在一致的关联。鉴定出的基因/蛋白质主要富集于NF-κB信号通路（hsa04064，P = 5.06×10）和细胞因子-细胞因子受体相互作用（hsa04060，P = 2.49×10）。此外，我们研究中的总共12个候选基因在两个独立的GEO数据集中得到了验证，如FLOT1和ABCF1。
我们的研究结果从多组学水平为已鉴定的基因/蛋白质和途径参与RA发病机制提供了新的见解。
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