2026-07-01T08:53:28Zhttps://repisalud.isciii.es/rest/oai/requestoai:repisalud.isciii.es:20.500.12105/65662024-09-27T10:15:09Zcom_20.500.12105_19604com_20.500.12105_2051col_20.500.12105_19607
Repisalud
author
Baldan-Martin, Montserrat
author
Lopez, Juan Antonio
author
Corbacho-Alonso, Nerea
author
Martinez, Paula J
author
Rodriguez-Sanchez, Elena
author
Mourino-Alvarez, Laura
author
Sastre-Oliva, Tamara
author
Martin-Rojas, Tatiana
author
Rincón, Raul
author
Calvo, Eva
author
Vazquez, Jesus
author
Vivanco, Fernando
author
Padial, Luis R
author
Alvarez-Llamas, Gloria
author
Ruiz-Hurtado, Gema
author
Ruilope, Luis M
author
Barderas, Maria G
funder
Instituto de Salud Carlos III
funder
Fundación Mutua Madrileña
funder
Fundación SENEFRO
funder
Unión Europea. Fondo Europeo de Desarrollo Regional (FEDER/ERDF)
funder
Sociedad Española de Cardiología
2018-11-05T08:20:09Z
2018-11-05T08:20:09Z
2018-03-19
Sci Rep. 2018; 8(1):4802
10.1038/s41598-018-23037-7
2045-2322
2045-2322
Scientific reports
29555916
http://hdl.handle.net/20.500.12105/6566
The evaluation of cardiovascular (CV) risk is based on equations derived from epidemiological data in individuals beyond the limits of middle age such as the Framingham and SCORE risk assessments. Lifetime Risk calculator (QRisk®), estimates CV risk throughout a subjects' lifetime, allowing those. A more aggressive and earlier intervention to be identified and offered protection from the consequences of CV and renal disease. The search for molecular profiles in young people that allow a correct stratification of CV risk would be of great interest to adopt preventive therapeutic measures in individuals at high CV risk. To improve the selection of subjects susceptible to intervention with aged between 30-50 years, we have employed a multiple proteomic strategy to search for new markers of early CV disease or reported CV events and to evaluate their relationship with Lifetime Risk. Blood samples from 71 patients were classified into 3 groups according to their CV risk (healthy, with CV risk factors and with a previously reported CV event subjects) and they were analyzed using a high through quantitative proteomics approach. This strategy allowed three different proteomic signatures to be defined, two of which were related to CV stratification and the third one involved markers of organ damage.
eng
Plasma
Cardiovascular risk
Asymptomatic
Biomarkers
Proteomics
SRM
Potential role of new molecular plasma signatures on cardiovascular risk stratification in asymptomatic individuals
journal article
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