Genomics and the prospects of existing and emerging therapeutics for cardiovascular diseases.

The growing knowledge about genetic influence on cardiovascular diseases (CVD) combined with the recently generated amounts of genomic data hold promise to the identification of new markers for atherosclerotic CVD. Cardiovascular pharmacogenomics and pharmacogenetics have now the potential for leading to identification of genetic contributors and therefore to the development of predictive genetic tests that could optimize drugs efficacy and minimize toxicity. Clinical studies have shown that genetic variations within cytochromes P450 (CYPs), 3-Hydroxyl-3-Methylglutaryl Coenzyme A Reductase (HMGCR) and apolipoprotein E (APOE) genes influence individual's response to lipid lowering statins. Furthermore, development of antagonists or inhibitors of molecules such as peroxisome proliferator-activated receptors (PPARs), lipoprotein-associated phospholipase A(2) (Lp-PLA(2)), angiotensin-converting enzyme (ACE), angiotensin receptors and tumor necrosis factor (TNF)-alpha could be another alternative to prevent atherosclerosis. In addition, novel molecules under the name of biologics including family of peptides such as atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP), urocortin, apelin and antimicrobial peptides (AMPs) could be considered as new targets for the prevention and treatment of CVD. In this article, we will focus mainly on recent genomic advances in the development of new markers and therapeutic agents for CVD. We present an array of molecules that could have pharmacological benefit for the treatment of heart disease. We also discuss in details new strategies including biologics, which are actually the focus of companies for clinical development of therapeutic drugs. All these efforts provide optimism and attractive promise to cure CVD.

Five-year alterations in BMI are associated with clustering of changes in cardiovascular risk factors in a gender-dependant way: the Stanislas study.

OBJECTIVE: The purpose of the present longitudinal study was to describe the associations between the 5-year changes in body mass index (BMI) and alterations in the clusters of metabolic syndrome (MS)-related factors. METHODS: The study population comprised 1099 middle-aged adults drawn from the Stanislas study. Individuals were stratified into four groups according to the 5-year changes in BMI (weight loss (<0 kg/m(2)), and weight gain (0-1, 1-2 and >2 kg/m(2))). Changes in various MS-related variables and clusters were compared between groups: anthropometric indices, blood pressure, lipid and inflammatory markers, liver enzymes, uric acid and the five summary factors extracted by using factor analysis ('risk lipids', 'liver enzymes', 'inflammation', 'protective lipids' and 'blood pressure'). RESULTS: There was a strong linear trend between increasing BMI and worsening of risk lipids and blood pressure factors for both men and women (P

P-selectin polymorphisms' influences on P-selectin serum concentrations and on their familial correlation: the STANISLAS family study.

BACKGROUND: P-selectin is an adhesion molecule known to be involved in the pathogenesis of several diseases through its major role in the initial phase of leukocytes recruitment during inflammation. However, genetic characterization of soluble P-selectin remains unclear. OBJECTIVES: In the STANISLAS cohort, we study the familial correlations of P-selectin levels and investigate the association of six P-selectin polymorphisms (C-2123G, A-1969G, S290N, N562D, V599L and T715P) and cardiovascular risk factors with P-selectin concentrations. PATIENTS/METHODS: Full phenotypic and genotypic information was available for 136 healthy families composed of both natural parents and at least one child (boys, n = 125; and girls, n = 139) aged more than 4 years. RESULTS: While no correlation was observed between spouses, family correlations of P-selectin concentrations were highly significant for sibling (0.50 +/- 0.12, P < 10(-3)) and child-parent pairs (0.42 +/- 0.04, P < 10(-3)). P-selectin haplotypes explained about 25% of the variability of P-selectin concentrations, this effect being mainly due to the additive effects of two polymorphisms, V599L and T715P. After adjusting for the effect of the P-selectin polymorphisms, the sibling and child-parent correlations decreased to (0.39 +/- 0.08, P < 10(-4)) and (0.32 +/- 0.06, P < 10(-4)), respectively. CONCLUSIONS: In the present study, we showed that two P-selectin polymorphisms, V599L and T715P, explained about 25% of the variability of P-selectin concentrations and accounted for about 40% of their family resemblance. These results would suggest a genetic influence on P-selectin concentrations beyond the contribution of the P-selectin gene.

[Pharmacogenomics and pharmacoproteomics: a strategy for cardio-vascular drugs]. / Pharmacogénomique et pharmacoprotéomique.

The development of personalized medicine will require improved knowledge of biological variability, particularly concerning the important impact of each individual's genetic makeup. A five-step strategy can be followed when trying to identify genes and gene products involved in differential responses to cardiovascular drugs: 1) Pharmacokinetic-related genes and phenotypes; (2) Pharmacodynamic targets, genes and products; (3) Cardiovascular diseases and risks depending on specific or large metabolic cycles; (4) Physiological variations of previously identified genes and proteins; (5) Environmental influences on them. After summarizing the most well known genes involved in drug metabolism, we used statins as an example. In addition to their economic impact, statins are generally considered to be of significant importance in terms of public health. Individuals respond differently to these drugs depending on multiple polymorphisms. Applying a pharmacoproteomic strategy, it is important to use available information on peptides, proteins and metabolites, generally gene products, in each of the five steps. A profiling approach dealing with genomics as well as proteomics is useful. In conclusion, the ever growing volume of available data will require an organized interpretation of variations in DNA and mRNA as well as proteins, both on the individual and population level.

Pharmacogenomics and drug response in cardiovascular disorders.

There are a total of 17 families of drugs that are used for treating the heterogeneous group of cardiovascular diseases. We propose a comprehensive pharmacogenomic approach in the field of cardiovascular therapy that considers the five following sources of variability: the genetics of pharmacokinetics, the genetics of pharmacodynamics (drug targets), genetics linked to a defined pathology and its corresponding drug therapies, the genetics of physiologic regulation, and environmental-genetic interactions. Examples of the genetics of pharmacokinetics are presented for phase I (cytochromes P450) and phase II (conjugating enzymes) drug-metabolizing enzymes and for phase III drug transporters. The example used to explain the genetics of pharmacodynamics is glycoprotein IIIa and the response to antiplatelet effects of aspirin. Genetics linked to a defined pathology and its corresponding drug therapies is exemplified by ADRB1, ACE, CETP and APOE and drug response in metabolic syndrome. The examples of cytochrome P450s, APOE and ADRB2 in relation to ethnicity, age and gender are presented to describe genetics of physiologic regulation. Finally, environmental-genetic interactions are exemplified by CYP7A1 and the effects of diet on plasma lipid levels, and by APOE and the effects of smoking in cardiovascular disease. We illustrate this five-tiered approach using examples of cardiovascular drugs in relation to genetic polymorphism.