Title: Identification of Genes for a Complex Trait: Examples from Hypertension
Volume: 7
Issue: 1
Author(s): A. Binder
Affiliation:
Keywords:
complex trait, hypertension, linkage, association, evolutionary, genetics, haplotype
Abstract: Essential hypertension (EH) affects ≉20% of the adult population, and has a multifactorial origin arising from an interaction between susceptibility genes and environmental factors. Several strategies and methods have been used to identify hypertension susceptibility genes. This review is thought to highlight current strategies for a better understanding of their limitations and strengths in a complex trait like EH. Linkage analysis is less effective at identifying common variants with modest effects typical for complex traits, and has therefore proved to be largely unsuccessful in EH. No candidate gene was assessed by a human linkage study so far. Possible redesigns of the linkage approach for complex diseases may include larger sample sizes and dense marker maps. Genetic association studies may be an effective approach to the problems posed by complex traits. With the explosion of genotyping technologies, genome-wide association studies have become feasible, and small-scale association studies have become plentiful. The different types of association studies are reviewed and issues that are important to consider when interpreting association studies of complex traits are discussed. Properly defined phenotypes, large enough sample cohorts to achieve sufficient statistical power, carefully matched samples to avoid population stratification are all integral parts of a high-quality association study. Multiple testing often results in false-positive results by chance, and inconclusive results may arise from ignoring linkage disequilibrium of the tested polymorphism, an effect avoidable by haplotype analysis. A new evolutionary development of the candidate gene approach is introduced which will extent traditional association study settings gaining better understanding of complex diseases like hypertension and might give better chances to evaluate association studies for their functional relevance.
