ORCID Profile
0000-0002-1382-1153
Current Organisation
KU Leuven
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Publisher: Oxford University Press (OUP)
Date: 21-03-2023
Abstract: Coronary artery disease (CAD) is multifactorial, caused by complex pathophysiology, and contributes to a high burden of mortality worldwide. Urinary proteomic analyses may help to identify predictive biomarkers and provide insights into the pathogenesis of CAD. Urinary proteome was analysed in 965 participants using capillary electrophoresis coupled with mass spectrometry. A proteomic classifier was developed in a discovery cohort with 36 in iduals with CAD and 36 matched controls using the support vector machine. The classifier was tested in a validation cohort with 115 in iduals who progressed to CAD and 778 controls and compared with two previously developed CAD-associated classifiers, CAD238 and ACSP75. The Framingham and SCORE2 risk scores were available in 737 participants. Bioinformatic analysis was performed based on the CAD-associated peptides. The novel proteomic classifier was comprised of 160 urinary peptides, mainly related to collagen turnover, lipid metabolism, and inflammation. In the validation cohort, the classifier provided an area under the receiver operating characteristic curve (AUC) of 0.82 [95% confidence interval (CI): 0.78–0.87] for the CAD prediction in 8 years, superior to CAD238 (AUC: 0.71, 95% CI: 0.66–0.77) and ACSP75 (AUC: 0.53 and 95% CI: 0.47–0.60). On top of CAD238 and ACSP75, the addition of the novel classifier improved the AUC to 0.84 (95% CI: 0.80–0.89). In a multivariable Cox model, a 1-SD increment in the novel classifier was associated with a higher risk of CAD (HR: 1.54, 95% CI: 1.26–1.89, P & 0.0001). The new classifier further improved the risk reclassification of CAD on top of the Framingham or SCORE2 risk scores (net reclassification index: 0.61, 95% CI: 0.25–0.95, P = 0.001 0.64, 95% CI: 0.28–0.98, P = 0.001, correspondingly). A novel urinary proteomic classifier related to collagen metabolism, lipids, and inflammation showed potential for the risk prediction of CAD. Urinary proteome provides an alternative approach to personalized prevention.
Publisher: Oxford University Press (OUP)
Date: 10-09-2021
DOI: 10.1093/AJH/HPAB139
Abstract: To address to what extent central hemodynamic measurements, improve risk stratification, and determine outcome-based diagnostic thresholds, we constructed the International Database of Central Arterial Properties for Risk Stratification (IDCARS), allowing a participant-level meta-analysis. The purpose of this article was to describe the characteristics of IDCARS participants and to highlight research perspectives. Longitudinal or cross-sectional cohort studies with central blood pressure measured with the SphygmoCor devices and software were included. The database included 10,930 subjects (54.8% women median age 46.0 years) from 13 studies in Europe, Africa, Asia, and South America. The prevalence of office hypertension was 4,446 (40.1%), of which 2,713 (61.0%) were treated, and of diabetes mellitus was 629 (5.8%). The peripheral and central systolic/diastolic blood pressure averaged 129.5/78.7 mm Hg and 118.2/79.7 mm Hg, respectively. Mean aortic pulse wave velocity was 7.3 m per seconds. Among 6,871 participants enrolled in 9 longitudinal studies, the median follow-up was 4.2 years (5th–95th percentile interval, 1.3–12.2 years). During 38,957 person-years of follow-up, 339 participants experienced a composite cardiovascular event and 212 died, 67 of cardiovascular disease. IDCARS will provide a unique opportunity to investigate hypotheses on central hemodynamic measurements that could not reliably be studied in in idual studies. The results of these analyses might inform guidelines and be of help to clinicians involved in the management of patients with suspected or established hypertension.
Publisher: Informa UK Limited
Date: 30-08-2021
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 04-08-2020
No related grants have been discovered for Jesus Melgarejo.