Dataset Information

Potential role of new molecular plasma signatures on cardiovascular risk stratification in asymptomatic individuals.

ABSTRACT: 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.

SUBMITTER: Baldan-Martin M

PROVIDER: S-EPMC5859270 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Potential role of new molecular plasma signatures on cardiovascular risk stratification in asymptomatic individuals.

Baldan-Martin Montserrat M Lopez Juan A JA Corbacho-Alonso Nerea N Martinez Paula J PJ Rodriguez-Sanchez Elena E Mourino-Alvarez Laura L Sastre-Oliva Tamara T Martin-Rojas Tatiana T Rincón Raul R Calvo Eva E Vazquez Jesus J Vivanco Fernando F Padial Luis R LR Alvarez-Llamas Gloria G Ruiz-Hurtado Gema G Ruilope Luis M LM Barderas Maria G MG

Scientific reports 20180319 1

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<sup>®</sup>), 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 ...[more]

PMID: 29555916

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Project description:Background: Epigenetic regulation, including DNA methylation, plays a major role in shaping the identity and function of immune cells. Innate and adaptive immune cells recruited into tumor tissues contribute to the formation of the tumor immune microenvironment (TIME), which is closely involved in tumor progression in breast cancer (BC). However, the specific methylation signatures of immune cells have not been thoroughly investigated yet. Additionally, it remains unknown whether immune cells-specific methylation signatures can identify subgroups and stratify the prognosis of BC patients. Methods: DNA methylation profiles of six immune cell types from eight datasets downloaded from the Gene Expression Omnibus were collected to identify immune cell-specific hypermethylation signatures (IC-SHMSs). Univariate and multivariate cox regression analyses were performed using BC data obtained from The Cancer Genome Atlas to identify the prognostic value of these IC-SHMSs. An unsupervised clustering analysis of the IC-SHMSs with prognostic value was performed to categorize BC patients into subgroups. Multiple Cox proportional hazard models were constructed to explore the role of IC-SHMSs and their relationship to clinical characteristics in the risk stratification of BC patients. Integrated discrimination improvement (IDI) was performed to determine whether the improvement of IC-SHMSs on clinical characteristics in risk stratification was statistically significant. Results: A total of 655 IC-SHMSs of six immune cell types were identified. Thirty of them had prognostic value, and 10 showed independent prognostic value. Four subgroups of BC patients, which showed significant heterogeneity in terms of survival prognosis and immune landscape, were identified. The model incorporating nine IC-SHMSs showed similar survival prediction accuracy as the clinical model incorporating age and TNM stage [3-year area under the curve (AUC): 0.793 vs. 0.785; 5-year AUC: 0.735 vs. 0.761]. Adding the IC-SHMSs to the clinical model significantly improved its prediction accuracy in risk stratification (3-year AUC: 0.897; 5-year AUC: 0.856). The results of IDI validated the statistical significance of the improvement (p < 0.05). Conclusions: Our study suggests that IC-SHMSs may serve as signatures of classification and risk stratification in BC. Our findings provide new insights into epigenetic signatures, which may help improve subgroup identification, risk stratification, and treatment management.

Dataset Information

Potential role of new molecular plasma signatures on cardiovascular risk stratification in asymptomatic individuals.

Publications

Potential role of new molecular plasma signatures on cardiovascular risk stratification in asymptomatic individuals.

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