Institute of Cardiovascular and Medical Sciences

Genetics, Genomics and Systems Medicine

Recent examples of our work include the development of novel methods for data analysis, the discovery of the association between the UMOD locus and human hypertension, description gene expression in patients with coronary artery disease and definition of a coronary artery specific urinary biomarker pattern.

We have developed a novel method of microarray data analysis that couples model based clustering and binary classification to form clusters of 'response-relevant' genes; that is, genes that are informative when discriminating between the different values of the response (i.e. disease vs control).  This novel method of analysis can be applied to any high-dimensional data including microarray gene expression and proteomic datasets (McBride et al. Nucleic Acids Res 2010; Figure 1)

 

 

We conducted a genome wide association study in 1,621 hypertensive cases and 1, 699 controls and follow-up validation analyses in 19,845 cases and 16, 541 controls using an extreme case-control design.  We identified a locus on chromosome 16 in the 5' region of Uromodulin (UMOD) and hypertension (Padmanabhan et. al. PLOS Genetics 2010; Figure 2)

 

Figure 2. Manhattan plot of genomewide -log10 (P-value) from association analysis of blood pressure extremes in the discovery sample. The UMOD locus is on chromosome 16 showing the smallest P-values.

 

We use gene expression profiling in rodent models and humans to identify differential gene expression between disease  and control phenotypes.  This work has led to the discovery of the Gstm1 locus as functional and positional candidate gene for hypertension in the SHRSP (McBride et al. Hypertension 2002).  More recently we analysed gene expression in whole blood from patients with coronary artery disease and healthy control subjects.  This work also showed an associateion of miR92a and miR92b with changes in gene expression following a cardiac rehabilitation programme (Taurino et al. Clin Sci 2010).

 

Figure 3. Heatmap analysis of miRNA expression in patients with coronary artery disease before and after completion of the cardiac rehabilitation programme (P500 intensity units). The analysis shows relative fluorescence from green (2-fold reduction) to red (2-fold increase) of each miRNA per individual.

 

 

In our clinical proteomic studies we use capillary electrophoresis coupled to mass spectrometry (CE-MS) and particularly focus on the urinary proteome.  We have defined a 238-biomarker panel that is specific for coronary artery disease and will be used for prospective studies.  The majority of biomarkers represent changes in extracellular matrix turnover - one of the hallmarks of CVD (Delles et al. J Hypertens 2010).

 Figure 4. CE-MS profiling of urine (Panel A) defined 238 polypeptides constituting a CAD-specific polypeptide panel (Panel B). Normalized molecular weight (800-20,000 Da) in logarithmic scale is plotted against normalized migration time (18-45 min).