High-Dimensional Multi-Block Analysis of Factors Associated with Thrombin Generation Potential

Hadrien Lorenzo, Misbah Razzaq, Jacob Odeberg, P. Morange, J. Saracco, D. Alexandre, R. Thiébaut
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引用次数: 2

Abstract

The identification of novel biological factors associated with thrombin generation, a key biomarker of the coagulation process, remains a relevant strategy to disentangle pathophysiological mechanisms underlying the risk of venous thrombosis (VT). As part of the MARseille THrombosis Association Study (MARTHA), we measured whole blood DNA methylation levels, plasma levels of 300 proteins, 3 thrombin generation biomarkers (endogeneous thrombin potential, peak and lagtime), clinical and genetic data in 700 patients with VT. The application of a novel high-dimensional multi-levels statistical methodology we recently developed, the data driven sparse Partial Least Square method (ddsPLS), on the MARTHA datasets enabled us 1/ to confirm the role of a known mutation of the variability of endogenous thrombin potential and peak, 2/ to identify a new signature of 7 proteins strongly associated with lagtime.
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凝血酶生成潜能相关因素的高维多块分析
凝血酶是凝血过程的关键生物标志物,发现与凝血酶产生相关的新生物学因素,仍然是解开静脉血栓形成风险的病理生理机制的相关策略。作为马赛血栓关联研究(MARTHA)的一部分,我们测量了700名VT患者的全血DNA甲基化水平、300种蛋白质的血浆水平、3种凝血酶生成生物标志物(内源性凝血酶电位、峰值和滞后时间)、临床和遗传数据。应用我们最近开发的一种新型高维多层统计方法,数据驱动的稀疏偏最小二乘法(ddsPLS),在MARTHA数据集上,我们1/确认了内源性凝血酶电位和峰值变异性的已知突变的作用,2/确定了与滞后时间密切相关的7种蛋白质的新特征。
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