Biomedical Engineering Reference
In-Depth Information
Genetic Mapping
of Complex Traits
Nancy L. Saccone
Department of Genetics, Division of Human Genetics, Washington University School
of Medicine, St Louis, Missouri, USA
4.1 Introduction
This chapter surveys current major approaches to mapping genes for multifactorial human
diseases using either family-based or population-based samples. Complex, multifactorial
diseases are generally hypothesized to be attributable to the effects of multiple genes with
incomplete penetrance. Gene - gene and gene - environment interactions are also expected to
play a role in the disease etiology.
Disease gene mapping strategies may be divided into two categories that are not mutually
exclusive: linkage based and association based. Linkage mapping relies on the co-segregation
of marker genotypes with phenotype within families, thereby detecting genetic loci that affect
disease risk. Association mapping methods are designed to detect loci for which genotype or
allelic status is correlated with phenotypic status on a population level, and can be carried out
using either family samples or unrelated individuals. Association-based mapping has gained
popularity in recent years due to technological advances that allow large-scale genotyping of
single nucleotide polymorphism (SNP) markers, enabling genome-wide association studies
(GWAS) of human diseases. This popularity also stems from earlier observations of Risch
and Merikangas [1], who noted that association designs promise greater power to detect
genes for complex traits, compared with sib-pair linkage approaches.
This chapter will begin with an emphasis on association mapping, and in particular,
large-scale, GWAS, as several high-profile association-based studies are currently making
headlines. Large-scale association studies of unrelated cases and controls have reported and
replicated gene discoveries for important diseases such as diabetes [2 - 4], breast cancer [5],
smoking [6 - 9] and lung cancer [8, 10 - 12].
