A new study published in PLOS Computational Biology shows that genes associated with hereditary diseases occur throughout the human body.
The study, by Esti Yeger-Lotem et al., used network biology to model the interactions between proteins associated with diseases such as Parkinson's in different tissues. Using these networks, they show that proteins carrying the disease are found throughout the body.
In tissues vulnerable to hereditary diseases, the networked proteins had unique interactions relevant for the mechanism of the disease. Disease causing genes tend to be more highly expressed. The authors demonstrated through several examples that tissue-specific protein interaction can highlight disease mechanisms, and thus, owing to their small number, provide a powerful filter for interrogating the origins of disease.
These results offer a powerful filter that can enhance the search for new therapeutic targets for many hereditary diseases.
All works published in PLOS Computational Biology are open access, which means that everything is immediately and freely available. Use this URL in your coverage to provide readers access to the paper upon publication: http://www.ploscompbiol.org/article/info:doi/pcbi.1003632
Contact:
Dr. Esti Yeger-Lotem
Phone: +972-8-6428675
Email: estiyl@bgu.ac.il
Citation: Barshir R, Shwartz O, Smoly IY, Yeger-Lotem E (2014) Comparative Analysis of Human Tissue Interactomes Reveals Factors Leading to Tissue-Specific Manifestation of Hereditary Diseases. PLoS Comput Biol 10(6): e1003632. doi:10.1371/journal.pcbi.1003632
Funding: This research was supported by the European Union Seventh Programme under the FP7-PEOPLE-MCA-IRG Funding scheme through grant agreement nu [256360]; by the Israel Cancer Association, Israel; and by the Israel Science Foundation administered by the Israel Academy of Sciences and Humanities through grant number 860/13 (to EYL). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
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PLoS Computational Biology