Paula J Martínez1, Montserrat Baldán-Martín2, Juan A López3, Marta Martín-Lorenzo1, Aránzazu Santiago-Hernández1, Marta Agudiez1, Martha Cabrera4, Eva Calvo4, Jesús Vázquez3, Gema Ruiz-Hurtado5, Fernando Vivanco6, Luis M Ruilope7, María G Barderas2, Gloria Alvarez-Llamas8. 1. Immunoallergy and Proteomics Laboratory, Department of Immunology, IIS-Fundación Jiménez Díaz, UAM, Madrid, Spain. 2. Department of Vascular Physiopathology, Hospital Nacional de Parapléjicos SESCAM, Toledo, Spain. 3. Laboratory of Cardiovascular Proteomics CNIC, Madrid, Spain. 4. Ibermutuamur, Madrid, Spain. 5. Cardiorenal Translational Laboratory, Instituto de Investigación I+12, Hospital Universitario 12 de Octubre/CIBER-CV, Madrid, Spain. 6. Department of Biochemistry and Molecular Biology, I Universidad Complutense, Madrid, Spain. 7. Cardiorenal Translational Laboratory, Instituto de Investigación I+12, Hospital Universitario 12 de Octubre/CIBER-CV, Madrid, Spain; Hypertension Unit, Hospital Universitario 12 de Octubre, Madrid, Spain; School of Doctoral Studies and Research, Universidad Europea de Madrid, Madrid, Spain. Electronic address: ruilope@icloud.com. 8. Immunoallergy and Proteomics Laboratory, Department of Immunology, IIS-Fundación Jiménez Díaz, UAM, Madrid, Spain; REDINREN, Madrid, Spain. Electronic address: galvarez@fjd.es.
Abstract
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.
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.
Authors: Maria Dolores Sanchez-Niño; Alberto Ortiz; Maria Vanessa Perez-Gomez; Soledad Pizarro-Sanchez; Carolina Gracia-Iguacel; Santiago Cano; Pablo Cannata-Ortiz; Jinny Sanchez-Rodriguez; Ana Belen Sanz Journal: J Nephrol Date: 2021-04-13 Impact factor: 3.902
Authors: María Marcos-Jubilar; Josune Orbe; Carmen Roncal; Florencio J D Machado; José Antonio Rodriguez; Alejandro Fernández-Montero; Inmaculada Colina; Raquel Rodil; Juan C Pastrana; José A Páramo Journal: Life (Basel) Date: 2021-05-01
Authors: Paula J Martinez; Marta Agudiez; Dolores Molero; Marta Martin-Lorenzo; Montserrat Baldan-Martin; Aranzazu Santiago-Hernandez; Juan Manuel García-Segura; Felipe Madruga; Martha Cabrera; Eva Calvo; Gema Ruiz-Hurtado; Maria G Barderas; Fernando Vivanco; Luis M Ruilope; Gloria Alvarez-Llamas Journal: J Mol Med (Berl) Date: 2020-09-11 Impact factor: 4.599