Network-based analysis of genotype-phenotype correlations between different inheritance modes

Bioinformatics. 2014 Nov 15;30(22):3223-31. doi: 10.1093/bioinformatics/btu482. Epub 2014 Jul 30.

Abstract

Motivation: Recent studies on human disease have revealed that aberrant interaction between proteins probably underlies a substantial number of human genetic diseases. This suggests a need to investigate disease inheritance mode using interaction, and based on which to refresh our conceptual understanding of a series of properties regarding inheritance mode of human disease.

Results: We observed a strong correlation between the number of protein interactions and the likelihood of a gene causing any dominant diseases or multiple dominant diseases, whereas no correlation was observed between protein interaction and the likelihood of a gene causing recessive diseases. We found that dominant diseases are more likely to be associated with disruption of important interactions. These suggest inheritance mode should be understood using protein interaction. We therefore reviewed the previous studies and refined an interaction model of inheritance mode, and then confirmed that this model is largely reasonable using new evidences. With these findings, we found that the inheritance mode of human genetic diseases can be predicted using protein interaction. By integrating the systems biology perspectives with the classical disease genetics paradigm, our study provides some new insights into genotype-phenotype correlations.

Contact: haodapeng@ems.hrbmu.edu.cn or biofomeng@hotmail.com

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Disease / genetics*
  • Genetic Association Studies / methods*
  • Genotype
  • Humans
  • Inheritance Patterns
  • Mutation
  • Phenotype
  • Protein Interaction Mapping*