Disease Genes and Gene Regulation by microRNAs

Abstract

The approach to biology and genetics has been markedly influenced by recent discoveries, namely, non-proteincoding RNAs [1], the annotation of single nucleotide polymorphisms (SNPs) by the HapMap Project [2], and the assembly of these SNPs onto computerized chips (microarrays) to pursue genome-wide association studies [3], This issue discusses the application and progress of these new discoveries as they relate to the biology and genetics of disease. The application of genetics to the pursuit of genes responsible for single-gene disorders received a major boost in the 1980s. The work of Nakamura et al. [4] and Murray et al. [5] made available hundreds of highly informative DNA markers consisting of short repeats that span the human genome. These markers coupled with polymerase chain reaction greatly accelerated mapping the chromosomal location (locus) of genes responsible for disease. The past two decades have been the golden age for single-gene disorders. It is estimated there are 6,000 inherited singlegene disorders, of which the genes for more than 2,000 have been identified [6]. However, single-gene disorders are rare and have a prevalence of less than one tenth of 1%. In contrast, diseases such as coronary artery disease (CAD), the number one killer, are common yet have a large genetic component. The technology to pursue the mapping of loci associated with common diseases would have to wait. These common diseases are polygenic with multiple genes contributing to their genetic predisposition; thus, each gene exerts only minimal effect on the phenotype. Thus, several genes acting in concert are required to induce the phenotype. To map the chromosomal locus of a gene with minimal effect on the phenotype requires not hundreds of DNA markers but hundreds of thousands of DNA markers. It also requires thousands of unrelated cases and controls analyzed for gene frequency in cases versus controls, referred to as a case-control association study. The preferred approach is to genotype with hundreds of thousands of markers selected to span the whole genome. Then, in an unbiased fashion, one can determine which markers are more common in cases (risk variant) or more common in controls (protective variant). In 2005, the technology arrived in the form of a microarray with 500,000 SNPs [7] and the necessary high throughput platform [3]. In 2007, two groups simultaneously mapped the first risk variant, 9p21, for CAD [8] and myocardial infarction [9]. The pursuit was intense, and in just 5 years, more than 400 chromosomal loci have been mapped to be associated with disease [10]. The case-control association study method and its genome-wide application referred to as genome-wide association study (GWAS) has been a remarkable success. The GWAS method has been dissected and analyzed in three reviews of this issue. The authors analyzed the advantages and disadvantages of the GWAS and provide a progress report on their application to cardiovascular disease in particular, CAD and hypertension. The ultimate application of these loci in the prevention, diagnoses and treatment of disease will require identification of the causative sequence and its function. We have already been R. Roberts The John & Jennifer Ruddy Canadian Cardiovascular Genetics Centre, Ottawa, ON, Canada K1Y 4W7 e-mail: rroberts@ottawaheart.ca