Menzies Institute for Medical Research, University of Tasmania, Hobart 7000, Australia.
Mater Research Institute, Translational Research Institute, South Brisbane 4101, Australia.
Brain. 2023 Jun 1;146(6):2464-2475. doi: 10.1093/brain/awac420.
Understanding how variations in the plasma and brain proteome contribute to multiple sclerosis susceptibility can provide important insights to guide drug repurposing and therapeutic development for the disease. However, the role of genetically predicted protein abundance in multiple sclerosis remains largely unknown. Integrating plasma proteomics (n = 3301) and brain proteomics (n = 376 discovery; n = 152 replication) into multiple sclerosis genome-wide association studies (n = 14 802 cases and 26 703 controls), we employed summary-based methods to identify candidate proteins involved in multiple sclerosis susceptibility. Next, we evaluated associations of the corresponding genes with multiple sclerosis at tissue-level using large gene expression quantitative trait data from whole-blood (n = 31 684) and brain (n = 1194) tissue. Further, to assess transcriptional profiles for candidate proteins at cell-level, we examined gene expression patterns in immune cell types (Dataset 1: n = 73 cases and 97 controls; Dataset 2: n = 31 cases and 31 controls) for identified plasma proteins, and in brain cell types (Dataset 1: n = 4 cases and 5 controls; Dataset 2: n = 5 cases and 3 controls) for identified brain proteins. In a longitudinal multiple sclerosis cohort (n = 203 cases followed up to 15 years), we also assessed the corresponding gene-level associations with the outcome of disability worsening. We identified 39 novel proteins associated with multiple sclerosis risk. Based on five identified plasma proteins, four available corresponding gene candidates showed consistent associations with multiple sclerosis risk in whole-blood, and we found TAPBPL upregulation in multiple sclerosis B cells, CD8+ T cells and natural killer cells compared with controls. Among the 34 candidate brain proteins, 18 were replicated in a smaller cohort and 14 of 21 available corresponding gene candidates also showed consistent associations with multiple sclerosis risk in brain tissue. In cell-specific analysis, six identified brain candidates showed consistent differential gene expression in neuron and oligodendrocyte cell clusters. Based on the 39 protein-coding genes, we found 23 genes that were associated with disability worsening in multiple sclerosis cases. The findings present a set of candidate protein biomarkers for multiple sclerosis, reinforced by high concordance in downstream transcriptomics findings at tissue-level. This study also highlights the heterogeneity of cell-specific transcriptional profiles for the identified proteins and that numerous candidates were also implicated in disease progression. Together, these findings can serve as an important anchor for future studies of disease mechanisms and therapeutic development.
了解血浆和大脑蛋白质组中的变异如何导致多发性硬化症易感性,可以为疾病的药物再利用和治疗开发提供重要的见解。然而,遗传预测的蛋白质丰度在多发性硬化症中的作用在很大程度上仍然未知。我们将血浆蛋白质组学(n = 3301)和大脑蛋白质组学(n = 376 个发现;n = 152 个复制)整合到多发性硬化症全基因组关联研究(n = 14802 例病例和 26703 例对照)中,我们采用基于汇总的方法来鉴定与多发性硬化症易感性相关的候选蛋白。接下来,我们使用来自全血(n = 31684)和大脑(n = 1194)组织的大型基因表达定量性状数据,在组织水平上评估相应基因与多发性硬化症的关联。此外,为了评估候选蛋白在细胞水平上的转录谱,我们检查了在确定的血浆蛋白的免疫细胞类型(数据集 1:n = 73 例和 97 例对照;数据集 2:n = 31 例和 31 例对照)和在确定的大脑蛋白的大脑细胞类型(数据集 1:n = 4 例和 5 例对照;数据集 2:n = 5 例和 3 例对照)中的基因表达模式。在一个纵向多发性硬化症队列(n = 203 例随访 15 年)中,我们还评估了相应基因与残疾恶化结果的关联。我们确定了 39 个与多发性硬化症风险相关的新蛋白。基于 5 个确定的血浆蛋白,4 个可用的相应候选基因在全血中显示出与多发性硬化症风险的一致关联,我们发现 TAPBPL 在多发性硬化症 B 细胞、CD8+T 细胞和自然杀伤细胞中上调,与对照组相比。在 34 个候选大脑蛋白中,18 个在较小的队列中得到复制,21 个可用的相应候选基因中有 14 个在大脑组织中也显示出与多发性硬化症风险的一致关联。在细胞特异性分析中,六个确定的大脑候选物在神经元和少突胶质细胞簇中显示出一致的差异基因表达。基于 39 个蛋白编码基因,我们发现了 23 个与多发性硬化症病例残疾恶化相关的基因。研究结果提供了一组多发性硬化症候选蛋白生物标志物,下游组织水平的转录组学发现具有高度一致性,进一步证实了这一点。本研究还强调了确定蛋白的细胞特异性转录谱的异质性,并且许多候选蛋白也与疾病进展有关。总之,这些发现可以为疾病机制和治疗开发的未来研究提供重要的依据。