In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine
In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine
复制标题
深入的血清蛋白质组学揭示了银屑病严重程度和对中药反应的生物标志物
DOI：
10.7150/thno.31144
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发表时间：
2019-01-01
期刊：
影响因子：
12.4
通讯作者：
Yu, Xiaobo
中科院分区：
文献类型：
--
作者：
Xu, Meng;Deng, Jingwen;Yu, Xiaobo
血清和血浆包含丰富的生物信息，这些信息反映了身体的生理和病理状况，因此是疾病生物标志物的一种有价值的样本类型。然而，由于血清中蛋白质浓度范围广泛，对血清蛋白质组进行全面分析具有挑战性。
方法：为了应对这一挑战，我们开发了一种新型的深度血清蛋白质组学平台，通过结合从数据独立采集质谱（DIA - MS）和可定制抗体微阵列获得的数据，能够分析跨越约10个数量级的血清蛋白质组。
结果：以银屑病作为概念验证疾病模型，我们在我们的深度血清蛋白质组学平台上对来自健康对照以及接受中药（银屑灵）治疗前后的银屑病患者的50份血清蛋白质组进行了筛选。我们在银屑病患者中鉴定出106种差异表达的蛋白质，这些蛋白质参与与银屑病相关的生物过程，例如凝血、炎症、细胞凋亡和血管生成信号通路。此外，无偏聚类和主成分分析揭示了58种可区分健康志愿者和银屑病患者的蛋白质，以及12种可区分对银屑灵有反应者和无反应者的蛋白质。为了进一步证明我们平台的临床实用性，我们对血清蛋白质组和银屑病活动进行了相关性分析，并发现银屑病面积和严重程度指数（PASI）评分与三种血清蛋白质（PI3、CCL22、IL - 12B）呈正相关。
结论：综上所述，这些结果证明了我们的深度血清蛋白质组学平台在识别银屑病和其他免疫介导疾病的特定诊断和预测生物标志物方面的临床实用性。
Serum and plasma contain abundant biological information that reflect the body's physiological and pathological conditions and are therefore a valuable sample type for disease biomarkers. However, comprehensive profiling of the serological proteome is challenging due to the wide range of protein concentrations in serum.Methods: To address this challenge, we developed a novel in-depth serum proteomics platform capable of analyzing the serum proteome across similar to 10 orders or magnitude by combining data obtained from Data Independent Acquisition Mass Spectrometry (DIA-MS) and customizable antibody microarrays.Results: Using psoriasis as a proof-of-concept disease model, we screened 50 serum proteomes from healthy controls and psoriasis patients before and after treatment with traditional Chinese medicine (YinXieLing) on our in-depth serum proteomics platform. We identified 106 differentially-expressed proteins in psoriasis patients involved in psoriasis-relevant biological processes, such as blood coagulation, inflammation, apoptosis and angiogenesis signaling pathways. In addition, unbiased clustering and principle component analysis revealed 58 proteins discriminating healthy volunteers from psoriasis patients and 12 proteins distinguishing responders from non-responders to YinXieLing. To further demonstrate the clinical utility of our platform, we performed correlation analyses between serum proteomes and psoriasis activity and found a positive association between the psoriasis area and severity index (PASI) score with three serum proteins (PI3, CCL22, IL-12B).Conclusion: Taken together, these results demonstrate the clinical utility of our in-depth serum proteomics platform to identify specific diagnostic and predictive biomarkers of psoriasis and other immune-mediated diseases.