Mapping complex disease traits with global gene expression

Abstract

Genome-wide association (GWA) studies have identified many new loci associated with human disease, but the association signals have yet to be translated into a proper understanding of which gene or genetic elements are mediating disease susceptibility at particular loci. The functional effects of DNA polymorphism on multifactorial disease are infrequently mediated through mutations that alter protein function, and variation in gene expression is likely to be a more important mechanism underlying susceptibility to complex disease. Transcript abundances of genes are directly modified by polymorphism in regulatory elements and transcript abundances can be considered as quantitative traits that can be mapped with considerable power. These have been named expression QTLs (eQTLs). This Review explores the value of systematic identification of eQTLs as one means of characterizing the function of loci underlying complex disease traits. The combination of whole-genome genetic association studies and measurement of global gene expression allows the systematic identification of eQTLs. The resulting comprehensive eQTL maps provide an important source of reference for categorizing both cis and trans effects on disease-associated SNPs on gene expression. In addition to providing information about the biological control of gene expression, such data aid in interpreting the results of GWA studies. The availability of systematically generated eQTL information provides immediate insight into a probable biological basis for the disease associations, and can help to identify networks of genes involved in disease pathogenesis. First, we briefly introduce the principles and current methods of eQTL mapping and describe the basis of eQTLs. We then explore the relevance of these results to disease gene identification. The limits of current eQTL mapping data are discussed, as is the expected impact of new technologies, international efforts to extend results to new samples and tissues and how cell lines might be tested with stimuli relevant to disease.