Center for Studies in Physics & Biology
March 10, 2015
A New Structural Approach to Genomic Discovery of Disease: Example of Adult-Onset of Diabetes
It will be shown that: (a) (1) information theory, as extended by (2), vastly improves discovery of potential risk loci; (b) an allele, rather than a SNP perspective contains more information, and is computationally superior; (c) a rigorous digitalization of genomic symbol data permits application of powerful tools, leading to a disease classifier that numerically quantifies disease likelihood.
The present methodology, which departs substantially from customary practice, proves fruitful in the investigation of Genome Wide Association Studies (GWAS). It extends naturally and successfully to predicting genomic disposition to disease, arising from large collections of weakly contributing loci.
Strong evidence will be advanced that adult onset diabetes ("type 2 diabetes", T2D) is such a candidate disease, and specific genes will be implicated. T2D is characterized by a large pool of potential disease loci. When present in sufficient number in someone then that individual is judged to have diabetes. There are virtually limitless different assemblies of the pool which can be designated as diabetes.