Article Text
Statistics from Altmetric.com
Recent advances in functional genomics have fostered the vision of a future health care that will be tailored to the specific needs of a person by using detailed genetic information about disease predisposition, disease progression, and the response to preventive or therapeutic medication.1,2 To confirm that this concept of personalised medicine is viable, proof of principle studies are required, entailing extensive efforts to identify and functionally characterise individual gene variants in human populations and their association with disease or therapy related phenotypes. For this purpose, as well as for the ultimate widespread genetic testing that may result from these studies, practical, cost efficient methods of analysing thousands of genes in large human populations for all possible sequence variants are critically important. Such methods are currently not available, the main stumbling block being the high costs associated with comprehensive genotyping of large numbers of DNA samples. Costs are determined to some extent by intellectual property rights on the genes and gene variants (in fee for service testing3), but mostly by the type of assay that is used. When a genetic test can be based on one or few mutations, the costs are generally low, owing to the recent increase in assays capable of confirming the presence or absence of a previously known mutation or single nucleotide polymorphism (SNP).4 Unfortunately, even relatively simple monogenic diseases, such as cystic fibrosis, can be caused by many different mutations in the same gene and it will never be possible to test only for a limited number of variants.5
The situation is different for the genetic component of complex diseases. The question here is if such diseases involve combinations of a few common SNP haplotypes or many rare alleles.6 Recent results indicate that most gene variants occur at low frequency, …