Impact of comprehensive cardiovascular risk reduction programme on risk factor clustering associated with elevated blood pressure in an Indian industrial population.

Background & objectives: Cardiovascular risk factors clustering associated with blood pressure (BP) has not been studied in the Indian population. This study was aimed at assessing the clustering effect of cardiovascular risk factors with suboptimal BP in Indian population as also the impact of risk reduction interventions. Methods: Data from 10543 individuals collected in a nation-wide surveillance programme in India were analysed. The burden of risk factors clustering with blood pressure and coronary heart disease (CHD) was assessed. The impact of a risk reduction programmme on risk factors clustering was prospectively studied in a sub-group. Results: Mean age of participants was 40.9 ± 11.0 yr. A significant linear increase in number of risk factors with increasing blood pressure, irrespective of stratifying using different risk factor thresholds was observed. While hypertension occurred in isolation in 2.6 per cent of the total population, co-existence of hypertension and >3 risk factors was observed in 12.3 per cent population. A comprehensive risk reduction programme significantly reduced the mean number of additional risk factors in the intervention population across the blood pressure groups, while it continued to be high in the control arm without interventions (both within group and between group P<0.001). The proportion of ‘low risk phenotype’ increased from 13.4 to 19.9 per cent in the intervention population and it was decreased from 27.8 to 10.6 per cent in the control population (P<0.001). The proportion of individuals with hypertension and three more risk factors decreased from 10.6 to 4.7 per cent in the intervention arm while it was increased from 13.3 to 17.8 per cent in the control arm (P<0.001). Interpretation & conclusions: Our findings showed that cardiovascular risk factors clustered together with elevated blood pressure and a risk reduction programme significantly reduced the risk factors burden.

Genomic approaches to coronary artery disease.

Coronary artery disease (CAD) is a leading cause of death and disability worldwide. In addition to lifestyle and environmental factors which are major aetiologic determinants, there is considerable familial clustering of the disease indicating a genetic component in its causation. Although the total genetic contribution to CAD risk can be quantified, the determination of the size and number of contributing effects is impossible without identifying all CAD susceptibility genes. However, despite extensive studies, strong evidence of a molecular genetic association with coronary artery disease or myocardial infarction remains elusive. Genome wide association studies have been successful in identifying robust associations of single nucleotide polymorphisms (SNP) with CAD. Identifying the causal variant and dissecting pathways linking these variants to disease process is a major challenge. Technologies from whole genome sequencing, proteomics, transcriptomics and metabolomics are now available to extend analysis to a more complete range of potential susceptibility variants, and to support more explicit modelling of the joint effects of genes and environment. The availability of these high throughput technologies does not diminish the importance of rigorous phenotyping and appropriate study designs in all the endeavours to understand the aetiopathogenesis of CAD. Combining classical epidemiology with modern genomics will require collaborative efforts within the cardiovascular disease community at both bench and bedside and this will have the potential to expand our understanding of CAD and translate discoveries into clinically useful applications that will have a major impact on public health.