Circulating cell-free RNA signatures for the characterization and diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)

People living with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) experience heterogeneous and debilitating symptoms that lack sufficient biological explanation, compounded by the absence of accurate, noninvasive diagnostic tools. To address these challenges, we explored circulating cell-free RNA (cfRNA) as a blood-borne bioanalyte to monitor ME/CFS. cfRNA is released into the bloodstream during cellular turnover and reflects dynamic changes in gene expression, cellular signaling, and tissue-specific processes. We profiled cfRNA in plasma by RNA sequencing for 93 ME/CFS cases and 75 healthy sedentary controls, then applied machine learning to develop diagnostic models and advance our understanding of ME/CFS pathobiology. A generalized linear model with least absolute shrinkage selector operator regression trained on condition-specific signatures achieved a test-set AUC of 0.81 and an accuracy of 77%. Immune cfRNA deconvolution revealed differences in platelet-derived cfRNA between cases and controls, as well as elevated levels of plasmacytoid dendritic, monocyte, and T cell–derived cfRNA in ME/CFS. Biological network analysis further implicated immune dysfunction in ME/CFS, with signatures of cytokine signaling and T cell exhaustion. These findings demonstrate the utility of RNA liquid biopsy as a minimally invasive tool for unraveling the complex biology behind chronic illnesses. Overall design: Blood-plasma derived cell-free RNA was isolated and sequenced from 93 patients diagnosed with ME/CFS and 75 healthy sedentary control individuals. The sequencing data was then analyzed to identify blood biomarkers for machine learning diagnostic classifiers and to deepen our biological understanding of ME/CFS.

肌痛性脑脊髓炎/慢性疲劳综合征（myalgic encephalomyelitis/chronic fatigue syndrome, ME/CFS）患者会出现异质性且致残性的临床症状，此类症状缺乏充分的生物学解释，且尚无准确的非侵入性诊断工具，进一步加重了诊疗困境。为应对上述挑战，我们探索将循环游离RNA（circulating cell-free RNA, cfRNA）作为血液源性生物分析物，用于ME/CFS的监测。循环游离RNA在细胞更新过程中释放入血液循环，可反映基因表达、细胞信号传导及组织特异性进程的动态变化。我们对93例ME/CFS患者与75例健康久坐对照者的血浆cfRNA进行了RNA测序分析，随后应用机器学习方法构建诊断模型，以深化对ME/CFS病理生物学的认知。基于疾病特异性特征训练的、采用最小绝对收缩选择算子（least absolute shrinkage selector operator, LASSO）回归的广义线性模型，在测试集上取得了0.81的曲线下面积（AUC）与77%的准确率。免疫cfRNA反卷积分析显示，患者与对照者的血小板源性cfRNA存在显著差异，且ME/CFS患者体内浆细胞样树突状细胞、单核细胞及T细胞源性cfRNA水平升高。生物网络分析进一步证实免疫功能异常与ME/CFS相关，且存在细胞因子信号传导与T细胞耗竭的特征性改变。本研究结果证明，RNA液体活检可作为一种微创工具，用于解析慢性疾病背后的复杂生物学机制。
整体实验设计：从93例确诊为ME/CFS的患者与75例健康久坐对照个体中分离血浆来源的循环游离RNA并进行测序，随后对测序数据进行分析，以筛选可用于机器学习诊断分类器的血液生物标志物，并深化对ME/CFS的生物学认知。