Table_1_Shared and Unique Patterns of DNA Methylation in Systemic Lupus Erythematosus and Primary Sjögren's Syndrome.pdf

Objectives: To perform a cross-comparative analysis of DNA methylation in patients with systemic lupus erythematosus (SLE), patients with primary Sjögren's syndrome (pSS), and healthy controls addressing the question of epigenetic sharing and aiming to detect disease-specific alterations.
Methods: DNA extracted from peripheral blood from 347 cases with SLE, 100 cases with pSS, and 400 healthy controls were analyzed on the Human Methylation 450k array, targeting 485,000 CpG sites across the genome. A linear regression model including age, sex, and blood cell type distribution as covariates was fitted, and association p-values were Bonferroni corrected. A random forest machine learning classifier was designed for prediction of disease status based on DNA methylation data.
Results: We established a combined set of 4,945 shared differentially methylated CpG sites (DMCs) in SLE and pSS compared to controls. In pSS, hypomethylation at type I interferon induced genes was mainly driven by patients who were positive for Ro/SSA and/or La/SSB autoantibodies. Analysis of differential methylation between SLE and pSS identified 2,244 DMCs with a majority of sites showing decreased methylation in SLE compared to pSS. The random forest classifier demonstrated good performance in discerning between disease status with an area under the curve (AUC) between 0.83 and 0.96.
Conclusions: The majority of differential DNA methylation is shared between SLE and pSS, however, important quantitative differences exist. Our data highlight neutrophil dysregulation as a shared mechanism, emphasizing the role of neutrophils in the pathogenesis of systemic autoimmune diseases. The current study provides evidence for genes and molecular pathways driving common and disease-specific pathogenic mechanisms.

研究目的：本研究旨在对系统性红斑狼疮（SLE）患者、原发性干燥综合征（pSS）患者与健康对照者的DNA甲基化水平开展交叉比较分析，探讨表观遗传共享现象，并识别疾病特异性的甲基化改变。
研究方法：本研究采用人类甲基化450K芯片（Human Methylation 450k array），对347例SLE患者、100例pSS患者以及400例健康对照者的外周血提取的DNA进行检测，该芯片可靶向覆盖基因组中485000个CpG位点。本研究拟合了以年龄、性别及血细胞类型分布作为协变量的线性回归模型，并对关联P值进行邦费罗尼校正。此外，本研究构建了基于DNA甲基化数据的随机森林机器学习分类器，用于疾病状态预测。
研究结果：本研究确立了一组共4945个SLE与pSS患者相较于健康对照者共有的共享差异甲基化CpG位点（DMCs）。在pSS患者中，I型干扰素诱导基因的低甲基化现象主要由Ro/SSA和/或La/SSB自身抗体阳性的患者所驱动。对SLE与pSS患者之间的甲基化差异进行分析，共识别出2244个DMCs，其中大多数位点在SLE患者中相较于pSS患者呈现甲基化水平降低。本研究构建的随机森林分类器在区分疾病状态方面表现良好，曲线下面积（AUC）介于0.83至0.96之间。
研究结论：大多数DNA甲基化差异在SLE与pSS患者中是共享的，但二者仍存在重要的定量差异。本研究数据凸显了中性粒细胞失调作为一种共享机制的重要性，强调了中性粒细胞在系统性自身免疫疾病发病机制中的作用。本研究为驱动常见及疾病特异性致病机制的基因与分子通路提供了证据支持。