Zhou Hao, Balint Diana, Shi Qiaojuan, Vartanian Tim, Kriegel Martin A, Brito Ilana
Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.
Weill Cornell Medicine, New York, New York, USA.
Ann Rheum Dis. 2025 Jan;84(1):93-105. doi: 10.1136/ard-2024-225829. Epub 2025 Jan 2.
This study aims to elucidate the microbial signatures associated with autoimmune diseases, particularly systemic lupus erythematosus (SLE) and inflammatory bowel disease (IBD), compared with colorectal cancer (CRC), to identify unique biomarkers and shared microbial mechanisms that could inform specific treatment protocols.
We analysed metagenomic datasets from patient cohorts with six autoimmune conditions-SLE, IBD, multiple sclerosis, myasthenia gravis, Graves' disease and ankylosing spondylitis-contrasting these with CRC metagenomes to delineate disease-specific microbial profiles. The study focused on identifying predictive biomarkers from species profiles and functional genes, integrating protein-protein interaction analyses to explore effector-like proteins and their targets in key signalling pathways.
Distinct microbial signatures were identified across autoimmune disorders, with notable overlaps between SLE and IBD, suggesting shared microbial underpinnings. Significant predictive biomarkers highlighted the diverse microbial influences across these conditions. Protein-protein interaction analyses revealed interactions targeting glucocorticoid signalling, antigen presentation and interleukin-12 signalling pathways, offering insights into possible common disease mechanisms. Experimental validation confirmed interactions between the host protein glucocorticoid receptor (NR3C1) and specific gut bacteria-derived proteins, which may have therapeutic implications for inflammatory disorders like SLE and IBD.
Our findings underscore the gut microbiome's critical role in autoimmune diseases, offering insights into shared and distinct microbial signatures. The study highlights the potential importance of microbial biomarkers in understanding disease mechanisms and guiding treatment strategies, paving the way for novel therapeutic approaches based on microbial profiles.
NCT02394964.
本研究旨在阐明与自身免疫性疾病相关的微生物特征,特别是与结直肠癌(CRC)相比,系统性红斑狼疮(SLE)和炎症性肠病(IBD)的微生物特征,以识别独特的生物标志物和共同的微生物机制,为特定的治疗方案提供依据。
我们分析了来自患有六种自身免疫性疾病(SLE、IBD、多发性硬化症、重症肌无力、格雷夫斯病和强直性脊柱炎)患者队列的宏基因组数据集,并将这些数据集与CRC宏基因组进行对比,以描绘疾病特异性的微生物谱。该研究专注于从物种谱和功能基因中识别预测性生物标志物,整合蛋白质-蛋白质相互作用分析,以探索关键信号通路中的效应样蛋白及其靶点。
在自身免疫性疾病中识别出了不同的微生物特征,SLE和IBD之间存在显著重叠,表明存在共同的微生物基础。重要的预测性生物标志物突出了这些疾病中微生物的多种影响。蛋白质-蛋白质相互作用分析揭示了针对糖皮质激素信号传导、抗原呈递和白细胞介素-12信号通路的相互作用,为可能的共同疾病机制提供了见解。实验验证证实了宿主蛋白糖皮质激素受体(NR3C1)与特定肠道细菌衍生蛋白之间的相互作用,这可能对SLE和IBD等炎症性疾病具有治疗意义。
我们的研究结果强调了肠道微生物群在自身免疫性疾病中的关键作用,为共同和独特的微生物特征提供了见解。该研究突出了微生物生物标志物在理解疾病机制和指导治疗策略方面的潜在重要性,为基于微生物谱的新型治疗方法铺平了道路。
NCT02394964。