Novel Biomarkers in Cardiovascular Disease: Research Tools or Ready for Personalized Medicine?

Fluorescent genipin cross-linked REDV-conjugated polymeric microbubbles for human vascular endothelial cell (HVEC) targeting

Fluorescent polymeric microbubbles conjugated with REDV peptides were fabricated to achieve HVECs active targeting. The degradation, cytotoxicity and targeting features endowed them potential candidates in early molecular diagnosis for cardiovascular diseases.

Big heart data: advancing health informatics through data sharing in cardiovascular imaging

The burden of heart disease is rapidly worsening due to the increasing prevalence of obesity and diabetes. Data sharing and open database resources for heart health informatics are important for advancing our understanding of cardiovascular function, disease progression and therapeutics. Data sharing enables valuable information, often obtained at considerable expense and effort, to be reused beyond the specific objectives of the original study. Many government funding agencies and journal publishers are requiring data reuse, and are providing mechanisms for data curation and archival. Tools and infrastructure are available to archive anonymous data from a wide range of studies, from descriptive epidemiological data to gigabytes of imaging data. Meta-analyses can be performed to combine raw data from disparate studies to obtain unique comparisons or to enhance statistical power. Open benchmark datasets are invaluable for validating data analysis algorithms and objectively comparing results. This review provides a rationale for increased data sharing and surveys recent progress in the cardiovascular domain. We also highlight the potential of recent large cardiovascular epidemiological studies enabling collaborative efforts to facilitate data sharing, algorithms benchmarking, disease modeling and statistical atlases.

High-sensitivity cardiac troponin for risk prediction in patients with and without coronary heart disease

BACKGROUND

In stable patients with unknown coronary anatomy, higher levels of cardiac troponin are associated with an increased risk of cardiovascular events. It was supposed that this association might be explained by the ability of cardiac troponin to detect minor myocardial necrosis which might be caused by subclinical coronary atherosclerosis. Thus, this analysis tested if the predictive value of high-sensitivity troponin T (hsTnT) in stable patients is dependent of the presence or absence of angiographically documented coronary heart disease.

METHODS

Stable patients undergoing elective coronary angiography were enrolled (n=2046). HsTnT was determined before diagnostic procedures. The patients were followed for up to seven years. Primary endpoint was all-cause mortality or non-fatal myocardial infarction. All endpoints were adjudicated by independent physicians. Results were adjusted to a clinical model including independent clinical predictors of the primary endpoint.

RESULTS

Out of the 2046 patients enrolled, 1236 (60%) had a diagnosis of obstructive coronary heart disease. HsTnT predicted independently the primary endpoint (adjusted HR 1.33, 95%-CI 1.21-1.46, P<0.001). The use of hsTnT in addition to the clinical model significantly improved discrimination (c-statistic: 0.751 to 0.773, P<0.001) as well as reclassification of the primary endpoint (NRI=0.362, P<0.001). This significant improvement persisted across various subsets and was independent of the presence of clinically detectable coronary heart disease and other variables.

CONCLUSION

The use of hsTnT in addition to clinical variables significantly improves discrimination and reclassification of patients with respect to all-cause mortality or non-fatal myocardial infarction irrespective of the presence of clinically detectable coronary heart disease.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov (Identifier: NCT00457236).

Contextualised urinary biomarker analysis facilitates diagnosis of paediatric obstructive sleep apnoea

BACKGROUND

Intrinsic variance of the urine proteome limits the discriminative power of proteomic analysis and complicates potential biomarker detection in the context of paediatric sleep disorders.

METHODS AND RESULTS

Using a rigorous workflow for proteomic analysis of urine, we demonstrate that gender and diurnal effects constitute two important sources of variability in healthy children. In the context of disease, complex pathophysiological perturbations magnify these proteomic differences and therefore require contextualised biomarker analysis. Indeed, by performing biomarker discovery in a gender- and diurnal-dependent manner, we identified ∼30-fold more candidate biomarkers of paediatric obstructive sleep apnoea (OSA), a highly prevalent condition in children characterised by repetitive episodes of intermittent hypoxia and hypercapnia, and sleep fragmentation in the context of recurrent upper airway obstructive events during sleep. Remarkably, biomarkers were highly specific for gender and sampling time as poor overlap (∼3%) was observed in the proteins identified in boys and girls across morning and bedtime samples.

CONCLUSIONS

As no clinical basis to explain gender-specific effects in OSA or healthy children is apparent, we propose that implementation of contextualised biomarker strategies will be applicable to a broad range of human diseases, and may be specifically applicable to paediatric OSA.