Dataset Information

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

ABSTRACT:

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.

Funding

This study was supported by competitive grants from the Spanish Ministry of Science, Innovation and Universities (BIO2015-67580-P, PGC2018-097019-B-I00, PID2019-106814RB-I00 and SAF2016-80843-R), through the Carlos III Institute of Health-Fondo de Investigacion Sanitaria grant PRB3 (IPT17/0019 - ISCIII-SGEFI / ERDF, ProteoRed), CIBERCV and CIBERDEM, the Fundacio MaratoTV3 (grant 122/C/2015) and "la Caixa" Banking Foundation (project HR17-00247). The PESA study is co-funded equally by the Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain, and Banco Santander, Madrid, Spain. The ILERVAS study was funded by the Diputacio de Lleida. The study also receives funding from the Instituto de Salud Carlos III (PI15/02019; PI18/00610; RD16/0009) and the FEDER funds. The CNIC is supported by the Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia, Innovacion y Universidades (MCNU) and the Pro CNIC Foundation.

SUBMITTER: Nunez E

PROVIDER: S-EPMC8844841 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Publications

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

Núñez Estefanía E Fuster Valentín V Gómez-Serrano María M Valdivielso José Manuel JM Fernández-Alvira Juan Miguel JM Martínez-López Diego D Rodríguez José Manuel JM Bonzon-Kulichenko Elena E Calvo Enrique E Alfayate Alvaro A Bermudez-Lopez Marcelino M Escola-Gil Joan Carles JC Fernández-Friera Leticia L Cerro-Pardo Isabel I Mendiguren José María JM Sánchez-Cabo Fátima F Sanz Javier J Ordovás José María JM Blanco-Colio Luis Miguel LM García-Ruiz José Manuel JM Ibáñez Borja B Lara-Pezzi Enrique E Fernández-Ortiz Antonio A Martín-Ventura José Luis JL Vázquez Jesús J

EBioMedicine 20220210

<h4>Background</h4>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.<h4>Methods</h4>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 ...[more]

PMID: 35152150

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Dataset Information

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

Background

Methods

Findings

Interpretation

Funding

Publications

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

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