Multi-Omic Candidate Screening for Markers of Severe Clinical Courses of COVID-19

被引:2
|
作者
Dutsch, Alexander [1 ,2 ]
Uhlig, Carsten [3 ]
Bock, Matthias [1 ,2 ]
Graesser, Christian [1 ,2 ]
Schuchardt, Sven [4 ]
Uhlig, Steffen [5 ]
Schunkert, Heribert [1 ,2 ]
Joner, Michael [1 ,2 ]
Holdenrieder, Stefan [3 ]
Lechner, Katharina [1 ,2 ]
机构
[1] Tech Univ Munich, German Heart Ctr Munich, Dept Cardiol, Lazarettstr 36, D-80636 Munich, Germany
[2] German Ctr Cardiovasc Res, DZHK, Partner Site Munich, Munich Heart Alliance, D-80336 Munich, Germany
[3] Tech Univ Munich Clin, German Heart Ctr Munich, Inst Lab Med, Lazarettstr 36, D-80636 Munich, Germany
[4] Fraunhofer Inst Toxicol & Expt Med ITEM, D-30625 Hannover, Germany
[5] QuoData Gesell Qualitatsmanagement & Stat, Fabeckstr 43, D-14195 Berlin, Germany
关键词
predictive diagnostics; COVID-19 longitudinal disease course; hyperinflammation; COVID-19; coagulopathy; candidate screening; multi-omics; IL-6; D-dimers; targeted prevention; personalization; HYPERTENSION; PATHOPHYSIOLOGY; INTERLEUKIN-13; PATHOGENESIS; INFLAMMATION; ASSOCIATION; CHOLESTEROL; SARS-COV-2; INFECTION; MORTALITY;
D O I
10.3390/jcm12196225
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Severe coronavirus disease 2019 (COVID-19) disease courses are characterized by immuno-inflammatory, thrombotic, and parenchymal alterations. Prediction of individual COVID-19 disease courses to guide targeted prevention remains challenging. We hypothesized that a distinct serologic signature precedes surges of IL-6/D-dimers in severely affected COVID-19 patients. Methods: We performed longitudinal plasma profiling, including proteome, metabolome, and routine biochemistry, on seven seropositive, well-phenotyped patients with severe COVID-19 referred to the Intensive Care Unit at the German Heart Center. Patient characteristics were: 65 +/- 8 years, 29% female, median CRP 285 +/- 127 mg/dL, IL-6 367 +/- 231 ng/L, D-dimers 7 +/- 10 mg/L, and NT-proBNP 2616 +/- 3465 ng/L. Results: Based on time-series analyses of patient sera, a prediction model employing feature selection and dimensionality reduction through least absolute shrinkage and selection operator (LASSO) revealed a number of candidate proteins preceding hyperinflammatory immune response (denoted Delta IL-6) and COVID-19 coagulopathy (denoted Delta D-dimers) by 24-48 h. These candidates are involved in biological pathways such as oxidative stress/inflammation (e.g., IL-1alpha, IL-13, MMP9, C-C motif chemokine 23), coagulation/thrombosis/immunoadhesion (e.g., P- and E-selectin), tissue repair (e.g., hepatocyte growth factor), and growth factor response/regulatory pathways (e.g., tyrosine-protein kinase receptor UFO and low-density lipoprotein receptor (LDLR)). The latter are host- or co-receptors that promote SARS-CoV-2 entry into cells in the absence of ACE2. Conclusions: Our novel prediction model identified biological and regulatory candidate networks preceding hyperinflammation and coagulopathy, with the most promising group being the proteins that explain changes in D-dimers. These biomarkers need validation. If causal, our work may help predict disease courses and guide personalized treatment for COVID-19.
引用
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页数:17
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