Genetic Association Studies

Part of the Use R book series (USE R)


Recent technological advancements allowing for large-scale sequencing efforts present an exciting opportunity to uncover the genetic underpinnings of complex diseases. In an attempt to characterize these genetic contributors to disease, investigators have embarked in multitude on what are commonly referred to as population-based genetic association studies. These studies generally aim to relate genetic sequence information derived from unrelated individuals to a measure of disease progression or disease status. The field of genomics spans a wide array of research areas that involve the many stages of processing from genetic sequence information to protein products and ultimately the expression of a trait. The breadth of genomic investigations also includes studies of multiple organisms, ranging from bacteria to viruses to parasites to humans. In this chapter, two settings are described in which population-based genetic association studies have marked potential for uncovering disease etiology while elucidating new approaches for targeted, individualized therapeutic interventions: (1) complex disease association studies in humans; and (2) studies involving the Human Immunodeficiency Virus (HIV).

In both settings, interest lies in characterizing associations between multiple genetic polymorphisms and a measured trait. In addition, these settings share the essential need to account appropriately for patient-level covariates as potential confounders or modifiers of disease progression to make clinically meaningful conclusions. While these two settings are not comprehensive, together they provide a launching point for discussion of quantitative methods that address the challenges inherent in many genetic investigations. This chapter begins by describing types of population-based studies, which represent one class of investigations within the larger field of genomics research. Also discussed are the fundamental features of data arising from these investigations as well as the analytical challenges inherent in this endeavor.


Genetic Association Study Multilocus Genotype Candidate Gene Study Disease Trait Consensus Amino Acid 
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Copyright information

© Springer-Verlag New York 2009

Authors and Affiliations

  1. 1.University of MassachusettsSchool of Public Health & Health SciencesAmherstUSA

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