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Results: 3

1.
Figure 2

Figure 2. From: Epistasis and Its Implications for Personal Genetics.

Panel of Genetic Markers for Type 2 Diabetes Provided by 23andMe for Each of the Authors
The profile of author A (gray bars) is associated with an overall slight decrease in risk under a multiplicative model, whereas the profile of author B (black bars) is associated with a slightly increased risk. Note that all adjusted odds ratios for individual genotypes are between 0.8 and 1.2.

Jason H. Moore, et al. Am J Hum Genet. 2009 September 11;85(3):309-320.
2.
Figure 3

Figure 3. From: Epistasis and Its Implications for Personal Genetics.

Low-Hanging and High-Hanging Genetic Fruit
Under the assumption that common diseases have a complex genetic architecture, we expect there to be few SNPs with moderate to large independent and additive main effects on disease susceptibility (i.e., low-hanging fruit). Rather, most SNPs of interest will be nestled in the branches and will only be found by embracing the complexity of the genotype-to-phenotype mapping relationship that is likely to be characterized by nonlinear gene-gene interactions and other phenomena such as gene-environment interaction and locus heterogeneity.

Jason H. Moore, et al. Am J Hum Genet. 2009 September 11;85(3):309-320.
3.
Figure 1

Figure 1. From: Epistasis and Its Implications for Personal Genetics.

A Simple Biochemical Systems Model that Is Consistent with a Complex Genetic Model
(A) Penetrance function showing an exclusive OR (XOR) pattern of high-risk (shaded) and low-risk (unshaded) genotype combinations for two biallelic SNPs.
(B) A Petri net model of a biochemical system under the control of the two SNPs from the genetic model in (A). SNPA controls the diameter of the “arc” or “pipe” carrying molecules of type 1, which are converted to molecules of type 2 at a constant rate governed by the first “transition” (lightning) on the left (wider pipes = larger diameter). SNPA is pleiotropic and also controls the rate at which molecules of type 2 are converted to molecules of type 3 (wider lightning bolts = faster rate). SNPB controls the arc or pipe carrying molecules of type 2 to the second transition, which converts them to molecules of type 3. When executed as part of a threshold model, the output of this system matches the distribution of high-risk and low-risk genotypes. This Petri net model demonstrates that a simple biochemical systems model can underlie a nonlinear genetic model.

Jason H. Moore, et al. Am J Hum Genet. 2009 September 11;85(3):309-320.

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