STUDENTJAMA. The clinical relevance of genomic variation.

Abstract

DRIVEN BY THE RECENT SEQUENCING OF THE HUMAN GEnome, the field of genetics has evolved to include the study of interindividual genomic variation. This emerging discipline focuses on the 0.1% of our genome that makes each individual genetically unique. Understanding genomic variation may improve the prediction of disease susceptibility, prognosis, and response to drug therapy, although a number of challenges will need to be addressed before this approach can be integrated into standard clinical practice. The study of interindividual genomic variation involves the identification and evaluation of single-nucleotide polymorphisms (SNPs), which are sites of variability in the nucleotide sequence of the human genome, as well as haplotypes, which are collections of SNPs that are inherited in blocks. Unlike genetic mutations, SNPs represent sites of genetic variability where the least common allele is present in at least 1% of the population. Although genetic mutations account for many rare, highly penetrant, monogenic diseases such as cystic fibrosis and sickle cell anemia, common conditions such as ischemic heart disease are thought to result from an interplay between multiple SNPs and environmental or lifestyle factors. Molecular technologies have recently enabled the mapping of SNPs across the human genome, an advance that will facilitate the study of how collections of polymorphisms may act in concert to influence clinical outcomes. The study of SNPs may lead to improved prediction of disease susceptibility and prognosis. Individuals with polymorphisms in apolipoprotein (Apo) E4 have an increased likelihood of developing Alzheimer disease in old age. Specific polymorphisms in 2C and 1-adrenergic receptors appear to act in synergy to increase the risk for heart failure. An SNP in the promoter region of the gene encoding the serotonin transporter was found to moderate the influence of stressful life events on the onset of depression. SNPs may also modify the penetrance of disease mutations. The clinical outcome of certain patients with cystic fibrosis, for example, may be influenced by a polymorphism in the promoter region of the gene encoding mannose-binding lectin. Identification of SNPs may also help individualize drug therapy, with the goal of maximizing efficacy and limiting toxicity. Individual differences in the genes encoding drug targets, metabolic enzymes, and transport proteins may contribute to the variation in drug response commonly observed in patients. More than 20 SNPs, for example, have been identified in the cytochrome (CYP) p450 system, a family of hepatic enzymes that metabolize the majority of drugs used in clinical practice. Some SNPs decrease the activity of these enzymes and lead to increased drug levels and risk of toxicity, while others increase their activity and result in subtherapeutic concentrations. Tailoring drug dosage to unique SNP profiles may therefore represent a more rational approach to prescribing drugs. Patients who have CYP269 polymorphisms, for example, have a higher risk of bleeding when taking warfarin, and could thus be given lower doses. Despite the potential value of studying SNPs, there are important limitations to this approach. First, there are considerable analytic challenges in identifying multiple SNPs across the genome that collectively increase the risk for particular diseases or outcomes. Second, some diseases that can be predicted by SNPs may not be preventable, creating difficult clinical and ethical dilemmas about whether such tests should be performed. Third, some SNPs may be more prevalent in certain racial and ethnic groups, potentially leading to inequalities in the application of genetic information to clinical care. Without extensive study, it is also uncertain how genetic risks (particularly when small) should be used in conjunction with other risk factors to guide clinical decisions. For instance, a variant of the cardiac sodium channel gene SCN5A present in 13.2% of African Americans leads to a slightly increased risk for cardiac arrhythmia. The overall risk for this outcome, however, is also influenced by a number of other factors including hypokalemia, the use of specific medications, and the presence of structural heart disease. Despite these challenges and limitations, the potential benefit of using SNPs to guide medical practice is fueling the development of improved SNP maps and a human haplotype map that incorporates genomic data from different ethnic groups.