Causal drift, robust signaling, and complex disease.

Area of Science:

• Genetics
• Systems Biology
• Computational Biology

Background:

• Complex polygenic diseases often arise from mutations in regulatory circuits.
• These circuits can exhibit robustness, masking the effects of individual DNA mutations.

Purpose of the Study:

• To demonstrate how mutational robustness can hinder the identification of genetic disease determinants.
• To introduce and explain the concept of "causal drift" in the context of complex diseases.

Main Methods:

• Mathematical modeling of the insulin signaling pathway, a key pathway implicated in type 2 diabetes.
• Utilizing multiple measures to assess parameter importance within the modeled pathway.
• Simulating population evolution through parameter space via DNA mutations.

Main Results:

• A single genetic determinant crucial in one genetic background is largely irrelevant in others.
• Mutations causing disease in one population may have no effect in another due to "causal drift".
• The genetic basis of complex diseases can vary randomly over time and across populations.

Conclusions:

• Mutational robustness and causal drift complicate the discovery of genetic disease determinants.
• Causal drift challenges the reliability of inferring complex disease mechanisms from non-human model organisms.
• Understanding causal drift is crucial for advancing research into complex polygenic diseases.