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Physiologic Interpretation of GWAS Signals for Type 2 Diabetes

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Disease Gene Identification

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1706))

Abstract

This chapter reviews both statistical and physiologic issues related to the pathophysiologic effects of genetic variation in the context of type 2 diabetes. The goal is to review current methodologies used to analyze disease-related quantitative traits for those who do not have extensive quantitative and physiologic background, as an attempt to bridge that gap. We leverage mathematical modeling to illustrate the strengths and weaknesses of different approaches and attempt to reinforce with real data analysis. Topics reviewed include phenotype selection, phenotype specificity, multiple variant analysis via the genetic risk score, and consideration of multiple disease-related phenotypes. Type 2 diabetes is used as the example, not only because of the extensive existing knowledge at the genetic, physiologic, clinical, and epidemiologic levels, but also because type 2 diabetes has been at the forefront of complex disease genetics, with many examples to draw from.

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  1. Departments of Preventive Medicine and Physiology & Biophysics, Keck School of Medicine of USC, 2250 Alcazar Street, CSC-204, Los Angeles, CA, 90089-9073, USA

    Richard M. Watanabe

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Watanabe, R.M. (2018). Physiologic Interpretation of GWAS Signals for Type 2 Diabetes. In: DiStefano, J. (eds) Disease Gene Identification. Methods in Molecular Biology, vol 1706. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7471-9_18

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