Munhoz Danielle Dias, Fonseca Dennyson Leandro M, Filgueiras Igor Salerno, Dias Haroldo Dutra, Nakaya Helder I, Jurisica Igor, Ochs Hans D, Schimke Lena F, Rizzo Luiz Vicente, Cabral-Marques Otavio
Experimental Biology Laboratory Prof. Dr. Geraldo Medeiros-Neto, Hospital Israelita Albert Einsten, Sao Paulo, Brazil.
Interunit Postgraduate Program on Bioinformatics, Institute of Mathematics and Statistics (IME), University of Sao Paulo (USP), Sao Paulo, SP, Brazil.
Front Immunol. 2025 Apr 9;16:1509805. doi: 10.3389/fimmu.2025.1509805. eCollection 2025.
Uveitis accounts for up to 25% of global legal blindness and involves intraocular inflammation, classifed as infectious or non-infectious. Its complex pathophysiology includes dysregulated cytokines, particularly interferons (IFNs). However, the global signature of type I, II, and III interferon-regulated genes (Interferome) remains largely uncharacterized in uveitis.
In this study, we conducted an integrative systems biology analysis of blood transcriptome data from 169 non-infectious uveitis patients (56 isolated uveitis, 113 systemic disease-associated uveitis) and 82 healthy controls.
Modular co-expression analysis identified distinct cytokine signaling networks, emphasizing interleukin and interferon pathways. A meta-analysis revealed 110 differentially expressed genes (metaDEGs) in isolated uveitis and 91 in systemic disease-associated uveitis, predominantly linked to immune responses. The Interferome database confirmed a predominance of type I and II IFN signatures in both groups. Pathway enrichment analysis highlighted inflammatory responses, including cytokine production (IL-8, IL1-β, IFN-γ, β, and α) and toll-like receptor signaling (TLR4, TLR7, TLR8, CD180). Principal component analysis emphasized the IFN signature's discriminative power, particularly in systemic disease-associated uveitis. Machine learning identified IFN-associated genes as robust predictors, while linear discriminant analysis pinpointed CCR2, CD180, GAPT, and PTGS2 as key risk factors in isolated uveitis and CA1, SIAH2, and PGS in systemic disease-associated uveitis.
These findings highlight IFN-driven imune dysregulation and potential molecular targets for precision therapies in uveitis.
葡萄膜炎占全球法定失明病例的25%，涉及眼内炎症，分为感染性和非感染性。其复杂的病理生理学包括细胞因子失调，尤其是干扰素（IFN）。然而，I型、II型和III型干扰素调节基因的全球特征（干扰素组）在葡萄膜炎中仍基本未得到表征。
在本研究中，我们对169例非感染性葡萄膜炎患者（56例孤立性葡萄膜炎、113例系统性疾病相关性葡萄膜炎）和82例健康对照者的血液转录组数据进行了综合系统生物学分析。
模块共表达分析确定了不同的细胞因子信号网络，突出了白细胞介素和干扰素途径。荟萃分析显示，孤立性葡萄膜炎中有110个差异表达基因（metaDEG），系统性疾病相关性葡萄膜炎中有91个，主要与免疫反应相关。干扰素组数据库证实两组中I型和II型干扰素特征均占主导。通路富集分析突出了炎症反应，包括细胞因子产生（IL-8、IL1-β、IFN-γ、β和α）和Toll样受体信号传导（TLR4、TLR7、TLR8、CD180）。主成分分析强调了干扰素特征的判别能力，尤其是在系统性疾病相关性葡萄膜炎中。机器学习确定与干扰素相关的基因为强大的预测因子，而线性判别分析确定CCR2、CD180、GAPT和PTGS2为孤立性葡萄膜炎的关键危险因素，CA1、SIAH2和PGS为系统性疾病相关性葡萄膜炎的关键危险因素。
这些发现突出了干扰素驱动的免疫失调以及葡萄膜炎精准治疗的潜在分子靶点。
