Abstract
BackgroundSystems biological approach of molecular connectivity map has reached to a great interest to understand the gene functional similarities between the diseases. In this study, we developed a computational framework to build molecular connectivity maps by integrating mutated and differentially expressed genes of neurological and psychiatric diseases to determine its relationship with aging.ResultsThe systematic large-scale analyses of 124 human diseases create three classes of molecular connectivity maps. First, molecular interaction of disease protein network generates 3632 proteins with 6172 interactions, which determines the common genes/proteins between diseases. Second, Disease-disease network includes 4845 positively scored disease-disease relationships. The comparison of these disease-disease pairs with Medical Subject Headings (MeSH) classification tree suggests 25% of the disease-disease pairs were in same disease area. The remaining can be a novel disease-disease relationship based on gene/protein similarity. Inclusion of aging genes set showed 79 neurological and 20 psychiatric diseases have the strong association with aging. Third and lastly, a curated disease biomarker network was created by relating the proteins/genes in specific disease contexts, such analysis showed 73 markers for 24 diseases. Further, the overall quality of the results was achieved by a series of statistical methods, to avoid insignificant data in biological networks.ConclusionsThis study improves the understanding of the complex interactions that occur between neurological and psychiatric diseases with aging, which lead to determine the diagnostic markers. Also, the disease-disease association results could be helpful to determine the symptom relationships between neurological and psychiatric diseases. Together, our study presents many research opportunities in post-genomic biomarkers development.
Highlights
Systems biological approach of molecular connectivity map has reached to a great interest to understand the gene functional similarities between the diseases
In this study, we developed a novel computational framework (Figure. 1) to build disease-protein network (DPN) (Figure. 2), disease-disease network (DDN) (Figure. 3) and common pathway molecular network (CPN)
Our approach of integrating mutated and differentially expressed diseases genes allow us to validate the neurological and psychiatric relationships with aging. This approach helps to predict the disease specific biomarkers for the potential diagnosis. We showed that this approach was effective in constructing a statistically significant molecular connectivity map of 124 diseases with 3632 proteins
Summary
Systems biological approach of molecular connectivity map has reached to a great interest to understand the gene functional similarities between the diseases. We developed a computational framework to build molecular connectivity maps by integrating mutated and differentially expressed genes of neurological and psychiatric diseases to determine its relationship with aging. Systems biology is an indispensable approach to study the complex mechanisms of any disease or disorders. We had taken an integrated approach of mutated and differentially regulating genes and exploring diseasome network that corresponds to the neurological and psychiatric diseases. Such integrative approach will improve the confidence of finding specific markers for diseases. There is an increasing prevalence rate [8,9] and lack of molecular diagnosis for most of the neurological disorders [10,11]
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