Atherosclerosis · 2019
Identification of six cardiovascular risk biomarkers in the young population: A promising tool for early prevention.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Martínez Paula J, Baldán-Martín Montserrat, López Juan A, Martín-Lorenzo Marta, Santiago-Hernández Aránzazu, Agudiez Marta, Cabrera Martha, Calvo Eva, Vázquez Jesús, Ruiz-Hurtado Gema, Vivanco Fernando, Ruilope Luis M, Barderas María G, Alvarez-Llamas Gloria
Аннотация
BACKGROUND AND AIMS: The predictive value of traditional CV risk calculators is limited. Novel indicators of CVD progression are needed particularly in the young population. The main aim of this study was the identification of a molecular profile with added value to classical CV risk estimation.
METHODS: Eighty-one subjects (30-50 years) were classified in 3 groups according to their CV risk: healthy subjects; individuals with CV risk factors; and those who had suffered a previous CV event. The urine proteome was quantitatively analyzed and significantly altered proteins were identified between patients' groups, either related to CV risk or established organ damage. Target-MS and ELISA were used for confirmation in independent patients' cohorts. Systems Biology Analysis (SBA) was carried out to identify functional categories behind CVD.
RESULTS: 4309 proteins were identified, 75 of them differentially expressed. ADX, ECP, FETUB, GDF15, GUAD and NOTCH1 compose a fingerprint positively correlating with lifetime risk estimate (LTR QRISK). Best performance ROC curve was obtained when ECP, GDF15 and GUAD were combined (AUC = 0.96). SBA revealed oxidative stress response, dilated cardiomyopathy, signaling by Wnt and proteasome, as main functional processes related to CV risk.
CONCLUSIONS: A novel urinary protein signature is shown, which correlates with CV risk estimation in young individuals. Pending further confirmation, this six-protein-panel could help in CV risk assessment.
METHODS: Eighty-one subjects (30-50 years) were classified in 3 groups according to their CV risk: healthy subjects; individuals with CV risk factors; and those who had suffered a previous CV event. The urine proteome was quantitatively analyzed and significantly altered proteins were identified between patients' groups, either related to CV risk or established organ damage. Target-MS and ELISA were used for confirmation in independent patients' cohorts. Systems Biology Analysis (SBA) was carried out to identify functional categories behind CVD.
RESULTS: 4309 proteins were identified, 75 of them differentially expressed. ADX, ECP, FETUB, GDF15, GUAD and NOTCH1 compose a fingerprint positively correlating with lifetime risk estimate (LTR QRISK). Best performance ROC curve was obtained when ECP, GDF15 and GUAD were combined (AUC = 0.96). SBA revealed oxidative stress response, dilated cardiomyopathy, signaling by Wnt and proteasome, as main functional processes related to CV risk.
CONCLUSIONS: A novel urinary protein signature is shown, which correlates with CV risk estimation in young individuals. Pending further confirmation, this six-protein-panel could help in CV risk assessment.