Motivation: Systematic analysis of connection between proteins, their cellular function and phenotypic manifestations in disease is a central problem of biological and clinical research. The solution to this problem requires the development of new approaches to link the rapidly growing dataset of gene-disease associations with the many complex and overlapping phenotypes of human disease. Results: We analyze genetic skin disorders and suggest a manually designed set of elementary phenotypes whose combinations define diseases as points in a multidimensional space, providing a basis for phenotypic disease clustering. Placing the known gene-disease associations in the context of this space reveals new patterns that suggest previously unknown functional links between proteins, signaling pathways and disease phenotypes. For example, analysis of telangiectasias (spider vein diseases) reveals a previously unrecognized interplay between the TGF-β signaling pathway and pentose phosphate pathway. This interaction may mediate glucose-dependent regulation of TGF-β signaling, providing a clue to the known association between angiopathies and diabetes and implying new gene candidates for mutational analysis and drug targeting.
ASJC Scopus subject areas
- Statistics and Probability
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics