82 resultados para cardiometabolic biomarkers
Resumo:
Background— Cardiovascular risk estimation by novel biomarkers needs assessment in disease-free population cohorts, followed up for incident cardiovascular events, assaying the serum and plasma archived at baseline. We report results from 2 cohorts in such a continuing study.
Methods and Results— Thirty novel biomarkers from different pathophysiological pathways were evaluated in 7915 men and women of the FINRISK97 population cohort with 538 incident cardiovascular events at 10 years (fatal or nonfatal coronary or stroke events), from which a biomarker score was developed and then validated in the 2551 men of the Belfast Prospective Epidemiological Study of Myocardial Infarction (PRIME) cohort (260 events). No single biomarker consistently improved risk estimation in FINRISK97 men and FINRISK97 women and the Belfast PRIME Men cohort after allowing for confounding factors; however, the strongest associations (with hazard ratio per SD in FINRISK97 men) were found for N-terminal pro-brain natriuretic peptide (1.23), C-reactive protein (1.23), B-type natriuretic peptide (1.19), and sensitive troponin I (1.18). A biomarker score was developed from the FINRISK97 cohort with the use of regression coefficients and lasso methods, with selection of troponin I, C-reactive protein, and N-terminal pro-brain natriuretic peptide. Adding this score to a conventional risk factor model in the Belfast PRIME Men cohort validated it by improved c-statistics (P=0.004) and integrated discrimination (P<0.0001) and led to significant reclassification of individuals into risk categories (P=0.0008).
Conclusions— The addition of a biomarker score including N-terminal pro-brain natriuretic peptide, C-reactive protein, and sensitive troponin I to a conventional risk model improved 10-year risk estimation for cardiovascular events in 2 middle-aged European populations. Further validation is needed in other populations and age groups.
Resumo:
Aims: To evaluate the role of novel biomarkers in early detection of acute myocardial infarction (MI) in patients admitted with acute chest pain.
Methods and results: A prospective study of 664 patients presenting to two coronary care units with chest pain was conducted over 3 years from 2003. Patients were assessed on admission: clinical characteristics, ECG (electrocardiogram), renal function, cardiac troponin T (cTnT), heart fatty acid binding protein (H-FABP), glycogen phosphorylase-BB, NT-pro-brain natriuretic peptide, D-dimer, hsCRP (high sensitivity C-reactive protein), myeloperoxidase, matrix metalloproteinase-9, pregnancy associated plasma protein-A, soluble CD40 ligand. A =12 h cTnT sample was also obtained. MI was defined as cTnT = 0.03 µg/L. In patients presenting <4 h of symptom onset, sensitivity of H-FABP for MI was significantly higher than admission cTnT (73 vs. 55%; P = 0.043). Specificity of H-FABP was 71%. None of the other biomarkers challenged cTnT. Combined use of H-FABP and cTnT (either one elevated initially) significantly improved the sensitivities of H-FABP or cTnT (85%; P = 0.004). This combined approach also improved the negative predictive value, negative likelihood ratio, and the risk ratio.
Conclusion: Assessment of H-FABP within the first 4 h of symptoms is superior to cTnT for detection of MI, and is a useful additional biomarker for patients with acute chest pain.
Resumo:
Azaspiracids are a class of recently discovered algae-derived shellfish toxins. Their distribution globally is on the increase with mussels being most widely implicated in azaspiracid-related food poisoning events. Evidence that these toxins were bound to proteins in contaminated mussels has been shown recently. In the present study characterization of these proteins in blue mussels, Mytilus edulis, was achieved using a range of advanced proteomics tools. Four proteins present only in the hepatopancreas of toxin-contaminated mussels sharing identity or homology with cathepsin D, superoxide dismutase, glutathione S-transferase Pi, and a bacterial flagellar protein have been characterized. Several of the proteins are known to be involved in self-defense mechanisms against xenobiotics or up-regulated in the presence of carcinogenic agents. These findings would suggest that azaspiracids should now be considered and evaluated as potential tumorigenic compounds. The presence of a bacterial protein only in contaminated mussels was an unexpected finding and requires further investigation. The proteins identified in this study should assist with development of urgently required processes for the rapid depuration of azaspiracid-contaminated shellfish. Moreover they may serve as early warning indicators of shellfish exposed to this family of toxins. Molecular & Cellular Proteomics 8: 1811-1822, 2009.
Resumo:
Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.