☆ 4.7 Article

Aggrecan: a new biomarker for acute type A aortic dissection

SCIENTIFIC REPORTS (2021)

Journal

SCIENTIFIC REPORTS

Volume 11, Issue 1, Pages -

Publisher

NATURE RESEARCH

DOI: 10.1038/s41598-021-89653-y

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Funding

Deutsche Stiftung fur Herzforschung [F/37/11]
Deutsches Zentrum fur Herz Kreislauf Forschung [DZHK_B 19 SE]
Deutsche Forschungsgemeinschaft [KR3770/7-3, KR3770/11-1, KR3770/14-1]
Projekt DEAL

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Abstract

ACAN in plasma samples shows significantly higher levels in ATAAD patients compared to patients with other cardiovascular conditions or healthy volunteers. It may serve as a reliable potential biomarker for detecting ATAAD with high sensitivity and specificity.

Acute type A aortic dissection (ATAAD) constitutes a life-threatening aortic pathology with significant morbidity and mortality. Without surgical intervention the usual mortality rate averages between 1 and 2% per hour. Thus, an early diagnosis of ATAAD is of pivotal importance to direct the affected patients to the appropriate treatment. Preceding tests to find an appropriate biomarker showed among others an increased aggrecan (ACAN) mRNA expression in aortic tissue of ATAAD patients. As a consequence, we investigated whether ACAN is a potential biomarker for diagnosing ATAAD. Mean ACAN protein concentration showed a significantly higher plasma concentration in ATAAD patients (38.59 ng/mL, n=33) compared to plasma of patients with thoracic aortic aneurysms (4.45 ng/mL, n=13), patients with myocardial infarction (11.77 ng/mL, n=18) and healthy volunteers (8.05 ng/mL, n=12). Cardiac enzymes like creatine kinase MB and cardiac troponin T showed no correlation with ACAN levels in ATAAD patients. Receiver-operator characteristics (ROC) curve analysis for ATAAD patients versus control subjects an optimum discrimination limit of ACAN plasma levels at 14.3 ng/mL with a corresponding sensitivity of 97% and specificity of 81%. According to our findings ACAN is a reliable potential biomarker in plasma samples to detect ATAAD with high sensitivity and specificity.

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Prediction of in-hospital death following acute type A aortic dissection

Junquan Chen, Yunpeng Bai, Hong Liu, Mingzhen Qin, Zhigang Guo

Summary: The study aimed to create a prediction model for in-hospital death in Chinese patients with acute type A aortic dissection (ATAAD). A retrospective derivation cohort of 340 patients from Tianjin and a retrospective validation cohort of 153 patients from Nanjing were used. Variable selection was done using least absolute shrinkage and selection operator analysis, and risk scoring was done using logistic regression coefficients. A risk classifier was established based on independent baseline data using a multivariable logistic model. The prediction performance was evaluated using the receiver operating characteristic curve (ROC). Individualized clinical decision-making was conducted using decision curve analysis (DCA). The risk prediction model showed good performance in predicting in-hospital death in ATAAD patients.

FRONTIERS IN PUBLIC HEALTH (2023)