Unbiased plasma proteomics discovery of biomarkers for improved detection of subclinical atherosclerosis

Estefanía Núñez, Valentín Fuster, María Gómez-Serrano, José Manuel Valdivielso, Juan Miguel Fernández-Alvira, Diego Martínez-López, José Manuel Rodríguez, Elena Bonzon-Kulichenko, Enrique Calvo, Alvaro Alfayate, Marcelino Bermudez-Lopez, Joan Carles Escola-Gil, Leticia Fernández-Friera, Isabel Cerro-Pardo, José María Mendiguren, Fátima Sánchez-Cabo, Javier Sanz, José María Ordovás, Luis Miguel Blanco-Colio, José Manuel García-RuizBorja Ibáñez, Enrique Lara-Pezzi, Antonio Fernández-Ortiz, José Luis Martín-Ventura, Jesús Vázquez

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


Background: Imaging of subclinical atherosclerosis improves cardiovascular risk prediction on top of traditional risk factors. However, cardiovascular imaging is not universally available. This work aims to identify circulating proteins that could predict subclinical atherosclerosis. Methods: Hypothesis-free proteomics was used to analyze plasma from 444 subjects from PESA cohort study (222 with extensive atherosclerosis on imaging, and 222 matched controls) at two timepoints (three years apart) for discovery, and from 350 subjects from AWHS cohort study (175 subjects with extensive atherosclerosis on imaging and 175 matched controls) for external validation. A selected three-protein panel was further validated by immunoturbidimetry in the AWHS population and in 2999 subjects from ILERVAS cohort study. Findings: PIGR, IGHA2, APOA, HPT and HEP2 were associated with subclinical atherosclerosis independently from traditional risk factors at both timepoints in the discovery and validation cohorts. Multivariate analysis rendered a potential three-protein biomarker panel, including IGHA2, APOA and HPT. Immunoturbidimetry confirmed the independent associations of these three proteins with subclinical atherosclerosis in AWHS and ILERVAS. A machine-learning model with these three proteins was able to predict subclinical atherosclerosis in ILERVAS (AUC [95%CI]:0.73 [0.70–0.74], p < 1 × 10−99), and also in the subpopulation of individuals with low cardiovascular risk according to FHS 10-year score (0.71 [0.69–0.73], p < 1 × 10−69). Interpretation: Plasma levels of IGHA2, APOA and HPT are associated with subclinical atherosclerosis independently of traditional risk factors and offers potential to predict this disease. The panel could improve primary prevention strategies in areas where imaging is not available.

Original languageEnglish
Article number103874
StatePublished - Feb 2022


  • APOA
  • Biomarkers
  • HPT
  • IGHA2
  • Proteomics
  • Subclinical atherosclerosis


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