Data Mining in Genomics and ProteomicsView this Special Issue
Research article | Open Access
Jonathan D. Wren, Harold R. Garner, "Data-Mining Analysis Suggests an Epigenetic Pathogenesis for Type 2 Diabetes", BioMed Research International, vol. 2005, Article ID 908475, 9 pages, 2005. https://doi.org/10.1155/JBB.2005.104
Data-Mining Analysis Suggests an Epigenetic Pathogenesis for Type 2 Diabetes
The etiological origin of type 2 diabetes mellitus (T2DM) has long been controversial. The body of literature related to T2DM is vast and varied in focus, making a broad epidemiological perspective difficult, if not impossible. A data-mining approach was used to analyze all electronically available scientific literature, over 12 million Medline records, for “objects” such as genes, diseases, phenotypes, and chemical compounds linked to other objects within the T2DM literature but were not themselves within the T2DM literature. The goal of this analysis was to conduct a comprehensive survey to identify novel factors implicated in the pathology of T2DM by statistically evaluating mutually shared associations. Surprisingly, epigenetic factors were among the highest statistical scores in this analysis, strongly implicating epigenetic changes within the body as causal factors in the pathogenesis of T2DM. Further analysis implicates adipocytes as the potential tissue of origin, and cytokines or cytokine-like genes as the dysregulated factor(s) responsible for the T2DM phenotype. The analysis provides a wealth of literature supporting this hypothesis, which—if true—represents an important paradigm shift for researchers studying the pathogenesis of T2DM.
Copyright © 2005 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.