Department of Neurology, UMass Chan Medical School, Worcester, MA, USA.
Department of Dermatology, UMass Chan Medical School, Worcester, MA, USA.
Sci Rep. 2024 Sep 18;14(1):21793. doi: 10.1038/s41598-024-67769-1.
Multiple sclerosis (MS) is an inflammatory demyelinating disease with heterogeneous clinical presentations and variable long-term disability accumulation. There are currently no standard criteria to accurately predict disease outcomes. In this study we investigated the cross-sectional relationship between disease phenotype and immune-modulating cytokines and chemokines in cerebrospinal fluid (CSF). We analyzed CSF from 20 DMT-naïve MS patients using Olink Proteomics' Target 96 Inflammation panel and correlated the resulting analytes with respect to (1) disease subtype, (2) patient age and sex, (3) extent of clinical disability, and (4) MRI segmental brain volumes. We found that intrathecal IL-4 correlated with higher Expanded Disability Status Scale (EDSS) scores and longer 25-foot walk times, and CD8A correlated with decreased thalamic volumes and longer 9-hole peg test times. Male sex was associated with higher FGF-19 expression, and Tumefactive MS with elevated CCL4. Several inflammatory markers were correlated with older age at the time of LP. Finally, higher intrathecal IL-33 correlated with increased MS lesion burden and multi-compartment brain atrophy. This study confirms immune heterogeneity underlying CSF profiles in MS, but also identifies several inflammatory protein biomarkers that may be of use for predicting clinical outcomes in future algorithms.
多发性硬化症(MS)是一种炎症性脱髓鞘疾病,具有不同的临床表现和不同的长期残疾累积。目前尚无准确预测疾病结局的标准标准。在这项研究中,我们研究了疾病表型与脑脊液(CSF)中免疫调节细胞因子和趋化因子之间的横断面关系。我们使用 Olink Proteomics 的 Target 96 炎症面板分析了 20 名未经 DMT 治疗的 MS 患者的 CSF,并根据以下方面分析了所得分析物:(1)疾病亚型,(2)患者年龄和性别,(3)临床残疾程度,和(4)MRI 节段性脑容量。我们发现,鞘内 IL-4 与更高的扩展残疾状况量表(EDSS)评分和更长的 25 英尺步行时间相关,而 CD8A 与丘脑体积减小和 9 孔钉测试时间延长相关。男性与更高的 FGF-19 表达相关,肿块型 MS 与 CCL4 升高相关。几个炎症标志物与 LP 时的年龄较大相关。最后,鞘内 IL-33 表达较高与 MS 病变负荷增加和多腔脑萎缩有关。这项研究证实了 MS 中 CSF 特征背后的免疫异质性,但也确定了一些炎症蛋白生物标志物,这些标志物可能有助于在未来的算法中预测临床结局。