Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death.
Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death.
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DOI：
10.7554/elife.64827
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发表时间：
2021-03-11
期刊：
影响因子：
7.7
通讯作者：
Peters JE
中科院分区：
文献类型：
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作者：
Gisby J;Clarke CL;Medjeral-Thomas N;Malik TH;Papadaki A;Mortimer PM;Buang NB;Lewis S;Pereira M;Toulza F;Fagnano E;Mawhin MA;Dutton EE;Tapeng L;Richard AC;Kirk PD;Behmoaras J;Sandhu E;McAdoo SP;Prendecki MF;Pickering MC;Botto M;Willicombe M;Thomas DC;Peters JE
终末期肾病（ESKD）患者感染严重COVID-19的风险很高。我们测量了住院和非住院ESKD患者COVID-19系列血液样本中的436种循环蛋白（n = 256个样本，来自55名患者）。与51名未感染患者进行比较，发现221种差异表达蛋白，在46名COVID-19患者的单独亚队列中结果一致。203种蛋白与临床严重程度相关，包括IL6、单核细胞募集标记物（如CCL2、CCL7）、中性粒细胞激活（如蛋白酶-3）和上皮损伤（如KRT19）。机器学习确定了严重程度的预测因子，包括IL18BP、CTSD、GDF15和KRT19。联合模型的生存分析揭示了69个死亡预测因子。使用线性混合模型进行纵向建模，发现32种蛋白质在严重和非严重疾病中表现出不同的时间谱，包括整合素和粘附分子。这些数据涉及严重COVID-19病理中的上皮损伤、先天免疫激活和白细胞-内皮相互作用，并为确定药物靶点提供了资源。COVID-19从一些人的轻微疾病到另一些人的致命疾病不等。患有严重疾病的患者往往年龄较大，并且有潜在的医疗问题。肾衰竭患者患严重或致命COVID-19的风险特别高。COVID-19重症患者的炎症水平很高，会对身体周围的组织造成损害。许多针对炎症的药物已经被开发出来用于治疗其他疾病。因此，为了重新利用现有药物或设计新的治疗方法，确定哪些蛋白质会导致COVID-19中的炎症是很重要的。在这里，Gisby, Clarke， Medjeral-Thomas等人测量了肾衰竭患者血液中的436种蛋白质，并比较了患有COVID-19的患者与未患有COVID-19的患者之间的水平。这表明，COVID-19患者体内数百种与炎症和组织损伤有关的蛋白质水平升高。Gisby等人结合统计学和机器学习分析，探索了可能预测更严重疾病进展的蛋白质数据。总共有200多种蛋白质与疾病严重程度有关，69种蛋白质与死亡风险增加有关。追踪血液蛋白水平随时间的变化，进一步揭示了轻度和重度疾病之间的差异。将这些数据与没有肾衰竭的人对COVID-19的类似研究进行比较，发现了许多相似之处。这表明，这些发现可能更普遍地适用于COVID-19患者。确定导致严重COVID-19的蛋白质——而不仅仅是与之相关——是重要的下一步，可能有助于选择治疗严重COVID-19的新药。
End-stage kidney disease (ESKD) patients are at high risk of severe COVID-19. We measured 436 circulating proteins in serial blood samples from hospitalised and non-hospitalised ESKD patients with COVID-19 (n = 256 samples from 55 patients). Comparison to 51 non-infected patients revealed 221 differentially expressed proteins, with consistent results in a separate subcohort of 46 COVID-19 patients. Two hundred and three proteins were associated with clinical severity, including IL6, markers of monocyte recruitment (e.g. CCL2, CCL7), neutrophil activation (e.g. proteinase-3), and epithelial injury (e.g. KRT19). Machine-learning identified predictors of severity including IL18BP, CTSD, GDF15, and KRT19. Survival analysis with joint models revealed 69 predictors of death. Longitudinal modelling with linear mixed models uncovered 32 proteins displaying different temporal profiles in severe versus non-severe disease, including integrins and adhesion molecules. These data implicate epithelial damage, innate immune activation, and leucocyte–endothelial interactions in the pathology of severe COVID-19 and provide a resource for identifying drug targets. COVID-19 varies from a mild illness in some people to fatal disease in others. Patients with severe disease tend to be older and have underlying medical problems. People with kidney failure have a particularly high risk of developing severe or fatal COVID-19. Patients with severe COVID-19 have high levels of inflammation, causing damage to tissues around the body. Many drugs that target inflammation have already been developed for other diseases. Therefore, to repurpose existing drugs or design new treatments, it is important to determine which proteins drive inflammation in COVID-19. Here, Gisby, Clarke, Medjeral-Thomas et al. measured 436 proteins in the blood of patients with kidney failure and compared the levels between patients who had COVID-19 to those who did not. This revealed that patients with COVID-19 had increased levels of hundreds of proteins involved in inflammation and tissue injury. Using a combination of statistical and machine learning analyses, Gisby et al. probed the data for proteins that might predict a more severe disease progression. In total, over 200 proteins were linked to disease severity, and 69 with increased risk of death. Tracking how levels of blood proteins changed over time revealed further differences between mild and severe disease. Comparing this data with a similar study of COVID-19 in people without kidney failure showed many similarities. This suggests that the findings may apply to COVID-19 patients more generally. Identifying the proteins that are a cause of severe COVID-19 – rather than just correlated with it – is an important next step that could help to select new drugs for severe COVID-19.