背景/目的:伴有皮质下梗死和白质脑病的常染色体显性动脉病(CADASIL)是一种遗传性小血管疾病,可导致显著的发病率和死亡率。尽管基因诊断取得了进展,潜在的病理生理学仍未完全了解。蛋白质组学研究通过识别改变的蛋白质表达模式提供对疾病机制的见解。这里,我们进行了蛋白质组学分析,以阐明与CADASIL相关的分子通路.方法:我们招募了基因诊断的CADASIL患者和健康,基因相关的控制。使用Olink平台对血浆样品进行蛋白质组学分析,在六个面板上测量552种蛋白质。通过使用三种不同的统计方法从几种方法分析数据:探索性主成分分析(PCA)和偏最小二乘判别分析(PLS-DA)。差异表达与缓和t检验,和基因集富集分析(GSEA)。此外,生物信息学分析,包括火山地块,热图,和来自PLS-DA模型的投影变量重要性(VIP)分数被绘制。结果:CADASIL患者和对照组之间的蛋白质表达存在显着差异。RSPO1和FGF-19表现出升高的水平(p<0.05),而PPY在CADASIL患者中显示下调(p<0.05),提示它们参与了疾病的发病机制。此外,MIC-A/B表达在NOTCH3基因第4号外显子与第11号外显子突变患者之间差异显著(p<0.05),强调CADASIL潜在的免疫机制。我们使用GSEA鉴定了改变的途径,在对研究数据进行排名后应用。结论:我们的研究为CADASIL的蛋白质组学图谱提供了新的见解,识别与血管病理相关的失调蛋白,代谢失调,和免疫激活。这些发现有助于更深入地了解CADASIL病理生理学,并可能为靶向治疗策略的发展提供信息。需要进一步的研究来验证这些生物标志物并阐明它们在疾病进展中的功能作用。
Background/Objectives: Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (
CADASIL) is a hereditary small vessel disease leading to significant morbidity and mortality. Despite advances in genetic diagnosis, the underlying pathophysiology remains incompletely understood. Proteomic studies offer insights into disease mechanisms by identifying altered protein expression patterns. Here, we conducted a proteomic analysis to elucidate molecular pathways associated with
CADASIL. Methods: We enrolled genetically diagnosed
CADASIL patients and healthy, genetically related controls. Plasma samples were subjected to proteomic analysis using the Olink platform, measuring 552 proteins across six panels. The data were analyzed from several approaches by using three different statistical methods: Exploratory Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA), differential expression with moderated t-test, and gene set enrichment analysis (GSEA). In addition, bioinformatics analysis, including volcano plot, heatmap, and Variable Importance on Projection (VIP) scores from the PLS-DA model were drawn. Results: Significant differences in protein expression were observed between
CADASIL patients and controls. RSPO1 and FGF-19 exhibited elevated levels (p < 0.05), while PPY showed downregulation (p < 0.05) in
CADASIL patients, suggesting their involvement in disease pathogenesis. Furthermore, MIC-A/B expression varied significantly between patients with mutations in exon 4 versus exon 11 of the NOTCH3 gene (p < 0.05), highlighting potential immunological mechanisms underlying CADASIL. We identified altered pathways using GSEA, applied after ranking the study data. Conclusions: Our study provides novel insights into the proteomic profile of CADASIL, identifying dysregulated proteins associated with vascular pathology, metabolic dysregulation, and immune activation. These findings contribute to a deeper understanding of CADASIL pathophysiology and may inform the development of targeted therapeutic strategies. Further research is warranted to validate these biomarkers and elucidate their functional roles in disease progression.