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Open Access Research article

Cross-pollination of research findings, although uncommon, may accelerate discovery of human disease genes

Marlena Duda1, Tristan Nelson1 and Dennis P Wall12*

Author Affiliations

1 The Center for Biomedical Informatics, Harvard Medical School, Boston, MA, USA

2 Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA

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BMC Medical Genetics 2012, 13:114  doi:10.1186/1471-2350-13-114

Published: 28 November 2012

Abstract

Background

Technological leaps in genome sequencing have resulted in a surge in discovery of human disease genes. These discoveries have led to increased clarity on the molecular pathology of disease and have also demonstrated considerable overlap in the genetic roots of human diseases. In light of this large genetic overlap, we tested whether cross-disease research approaches lead to faster, more impactful discoveries.

Methods

We leveraged several gene-disease association databases to calculate a Mutual Citation Score (MCS) for 10,853 pairs of genetically related diseases to measure the frequency of cross-citation between research fields. To assess the importance of cooperative research, we computed an Individual Disease Cooperation Score (ICS) and the average publication rate for each disease.

Results

For all disease pairs with one gene in common, we found that the degree of genetic overlap was a poor predictor of cooperation (r2=0.3198) and that the vast majority of disease pairs (89.56%) never cited previous discoveries of the same gene in a different disease, irrespective of the level of genetic similarity between the diseases. A fraction (0.25%) of the pairs demonstrated cross-citation in greater than 5% of their published genetic discoveries and 0.037% cross-referenced discoveries more than 10% of the time. We found strong positive correlations between ICS and publication rate (r2=0.7931), and an even stronger correlation between the publication rate and the number of cross-referenced diseases (r2=0.8585). These results suggested that cross-disease research may have the potential to yield novel discoveries at a faster pace than singular disease research.

Conclusions

Our findings suggest that the frequency of cross-disease study is low despite the high level of genetic similarity among many human diseases, and that collaborative methods may accelerate and increase the impact of new genetic discoveries. Until we have a better understanding of the taxonomy of human diseases, cross-disease research approaches should become the rule rather than the exception.