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  • Title: Midregional pro-atrial natriuretic peptide in the general population/Insights from the Gutenberg Health Study.
    Author: Tzikas S, Keller T, Wild PS, Schulz A, Zwiener I, Zeller T, Schnabel RB, Sinning C, Lubos E, Kunde J, Münzel T, Lackner KJ, Blankenberg S.
    Journal: Clin Chem Lab Med; 2013 May; 51(5):1125-33. PubMed ID: 23183754.
    Abstract:
    BACKGROUND: The use of biomarkers is firmly established for the assessment of cardiovascular disease. Emerging biomarkers such as midregional pro-atrial natriuretic peptide (MR-proANP) challenge established markers regarding risk prediction and stratification ability. The aim of the present study was to describe the distribution of a contemporary MR-proANP assay in a large population-representative sample and to evaluate the association with prevalent cardiac diseases and cardiovascular risk factors. METHODS: MR-proANP was determined by the use of a contemporary commercially available assay (BRAHMS GmbH, Hennigsdorf, Germany) in a representative sample of 5000 participants from the large population-based Gutenberg Health Study. N-terminal pro B-type natriuretic peptide (NT-proBNP) was used as a comparator. RESULTS: Mean age was 55.5 ± 10.9 years. Coronary artery disease (CAD) was documented in 4.6%, heart failure (HF) in 1.5% of the study participants. We observed a moderate to strong correlation of the biomarkers with age, diabetes, hypertension, smoking, renal function, prevalence of CAD and HF. Males showed lower MR-proANP concentrations than females. MR-proANP showed no relevant correlation with BMI (ρ=-0.030) and CRP (ρ=0.039). Reference limits for MR-proANP representing the 95th/97.5th/99th percentile were determined for healthy individuals with 116/132/169 pmol/mL. CONCLUSIONS: The current analysis in a large population-based sample elucidates the correlations and distribution of MR-proANP. Its concentration in healthy individuals depends on prevalent cardiovascular diseases and classical risk factors. The reported population-based reference values might be useful for distinguishing between healthy and diseased individuals, thus improving risk stratification and triaging in various clinical settings.
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