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开发和验证一种定量邻近延伸分析仪器,该仪器与心血管风险(CVD-21)相关的 21 种蛋白质有关。

Development and validation of a quantitative Proximity Extension Assay instrument with 21 proteins associated with cardiovascular risk (CVD-21).

机构信息

Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden.

Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.

出版信息

PLoS One. 2023 Nov 14;18(11):e0293465. doi: 10.1371/journal.pone.0293465. eCollection 2023.

Abstract

BACKGROUND

Treatment of cardiovascular diseases (CVD) is a substantial burden to healthcare systems worldwide. New tools are needed to improve precision of treatment by optimizing the balance between efficacy, safety, and cost. We developed a high-throughput multi-marker decision support instrument which simultaneously quantifies proteins associated with CVD.

METHODS AND FINDINGS

Candidate proteins independently associated with different clinical outcomes were selected from clinical studies by the screening of 368 circulating biomarkers. We then custom-designed a quantitative PEA-panel with 21 proteins (CVD-21) by including recombinant antigens as calibrator samples for normalization and absolute quantification of the proteins. The utility of the CVD-21 tool was evaluated in plasma samples from a case-control cohort of 4224 patients with chronic coronary syndrome (CCS) using multivariable Cox regression analyses and machine learning techniques. The assays in the CVD-21 tool gave good precision and high sensitivity with lower level of determination (LOD) between 0.03-0.7 pg/ml for five of the biomarkers. The dynamic range for the assays was sufficient to accurately quantify the biomarkers in the validation study except for troponin I, which in the modeling was replaced by high-sensitive cardiac troponin T (hs-TnT). We created seven different multimarker models, including a reference model with NT-proBNP, hs-TnT, GDF-15, IL-6, and cystatin C and one model with only clinical variables, for the comparison of the discriminative value of the CVD-21 tool. All models with biomarkers including hs-TnT provided similar discrimination for all outcomes, e.g. c-index between 0.68-0.86 and outperformed models using only clinical variables. Most important prognostic biomarkers were MMP-12, U-PAR, REN, VEGF-D, FGF-23, TFF3, ADM, and SCF.

CONCLUSIONS

The CVD-21 tool is the very first instrument which with PEA simultaneously quantifies 21 proteins with associations to different CVD. Novel pathophysiologic and prognostic information beyond that of established biomarkers were identified by a number of proteins.

摘要

背景

心血管疾病 (CVD) 的治疗对全球医疗体系构成了重大负担。需要新的工具来通过优化疗效、安全性和成本之间的平衡来提高治疗的精准度。我们开发了一种高通量多标志物决策支持工具,该工具可同时定量与 CVD 相关的蛋白。

方法和发现

通过对 368 种循环生物标志物进行筛选,从临床研究中选择与不同临床结局独立相关的候选蛋白。然后,我们通过包括重组抗原作为校准样本,为 21 种蛋白(CVD-21)定制了一种定量 PEA 面板,用于对蛋白进行归一化和绝对定量。通过多变量 Cox 回归分析和机器学习技术,在包含 4224 名慢性冠状动脉综合征 (CCS) 患者的病例对照队列的血浆样本中评估了 CVD-21 工具的实用性。CVD-21 工具中的检测具有良好的精密度和高灵敏度,其中五种生物标志物的检测下限(LOD)在 0.03-0.7 pg/ml 之间。除了肌钙蛋白 I 外,该检测的动态范围足以在验证研究中准确地定量生物标志物,在建模中,肌钙蛋白 I 被高敏心肌肌钙蛋白 T(hs-TnT)取代。我们创建了七个不同的多标志物模型,包括一个包含 NT-proBNP、hs-TnT、GDF-15、IL-6 和胱抑素 C 的参考模型和一个仅包含临床变量的模型,用于比较 CVD-21 工具的区分价值。所有包含 hs-TnT 的生物标志物模型都为所有结局提供了类似的区分能力,例如 c 指数在 0.68-0.86 之间,优于仅使用临床变量的模型。最重要的预后生物标志物是 MMP-12、U-PAR、REN、VEGF-D、FGF-23、TFF3、ADM 和 SCF。

结论

CVD-21 工具是第一个通过 PEA 同时定量与 CVD 相关的 21 种蛋白的仪器。通过多种蛋白鉴定出了超越现有生物标志物的新的病理生理和预后信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c822/10645335/8ae019f2dd58/pone.0293465.g001.jpg

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