Hojjati Sara, Ernerudh Jan, Vrethem Magnus, Mellergård Johan, Raffetseder Johanna
Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
Department of Clinical Immunology and Transfusion Medicine in Linköping, and Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
Mult Scler Relat Disord. 2023 Dec;80:105126. doi: 10.1016/j.msard.2023.105126. Epub 2023 Nov 5.
Dimethyl fumarate (DMF) is a common treatment for multiple sclerosis (MS), but its mechanisms of action are not fully understood. Targeted proteomics offers insights into effects of DMF and biomarkers for treatment responses.
To assess influence of DMF on inflammation- and neuro-associated proteins in plasma and cerebrospinal fluid (CSF) in MS and to reveal biomarkers for predicting treatment responses.
Using the high-sensitivity and high-specificity method of proximity extension assay (PEA), we measured 182 inflammation- and neuro-associated proteins in paired plasma (n = 28) and CSF (n = 12) samples before and after one year of DMF treatment. Disease activity was evaluated through clinical examination and MRI. Statistical tests, network analysis, and regression models were used.
Several proteins including T-helper 1 (Th1)-associated proteins (CXCL10, CXCL11, granzyme A, IL-12p70, lymphotoxin-alpha) were consistently decreased in CSF, while IL-7 was increased after one year of treatment. The changes in plasma protein levels did not follow the same pattern as in CSF. Logistic regression models identified potential biomarker candidates (including plexins and neurotrophins) for prediction of treatment response.
DMF treatment induced prominent changes in CSF proteins, consistently reducing Th1-associated pro-inflammatory proteins. Neurodegeneration-related CSF proteins were able to predict treatment response. Protein biomarkers hold promise for personalized medicine.
富马酸二甲酯（DMF）是治疗多发性硬化症（MS）的常用药物，但其作用机制尚未完全明确。靶向蛋白质组学有助于深入了解DMF的作用效果以及治疗反应的生物标志物。
评估DMF对MS患者血浆和脑脊液（CSF）中炎症相关蛋白和神经相关蛋白的影响，并揭示预测治疗反应的生物标志物。
采用高灵敏度和高特异性的邻近延伸分析（PEA）方法，我们在DMF治疗一年前后，对配对的血浆样本（n = 28）和CSF样本（n = 12）中的182种炎症相关蛋白和神经相关蛋白进行了检测。通过临床检查和磁共振成像（MRI）评估疾病活动度。使用了统计检验、网络分析和回归模型。
包括辅助性T细胞1（Th1）相关蛋白（CXCL10、CXCL11、颗粒酶A、IL-12p70、淋巴毒素-α）在内的几种蛋白在CSF中持续减少，而治疗一年后IL-7增加。血浆蛋白水平的变化与CSF中的变化模式不同。逻辑回归模型确定了用于预测治疗反应的潜在生物标志物候选物（包括丛蛋白和神经营养因子）。
DMF治疗导致CSF蛋白发生显著变化，持续降低Th1相关的促炎蛋白。与神经退行性变相关的CSF蛋白能够预测治疗反应。蛋白质生物标志物有望用于个性化医疗。
