Abstract

Orphan diseases (ODs) are progressive genetic disorders, which affect a small number of people. The principal fundamental aspects related to these diseases include insufficient knowledge of mechanisms involved in the physiopathology necessary to access correct diagnosis and to develop appropriate healthcare. Unlike ODs, complex diseases (CDs) have been widely studied due to their high incidence and prevalence allowing to understand the underlying mechanisms controlling their physiopathology. Few studies have focused on the relationship between ODs and CDs to identify potential shared pathways and related molecular mechanisms which would allow improving disease diagnosis, prognosis, and treatment. We have performed a computational approach to studying CDs and ODs relationships through (1) connecting diseases to genes based on genes-diseases associations from public databases, (2) connecting ODs and CDs through binary associations based on common associated genes, and (3) linking ODs and CDs to common enriched pathways. Among the most shared significant pathways between ODs and CDs, we found pathways in cancer, p53 signaling, mismatch repair, mTOR signaling, B cell receptor signaling, and apoptosis pathways. Our findings represent a reliable resource that will contribute to identify the relationships between drugs and disease-pathway networks, enabling to optimise patient diagnosis and disease treatment.

Highlights

  • Orphan diseases (ODs) or rare diseases are chronic and progressive genetic disorders affecting a small number of people

  • We identified COL2A1 associated with 19 orphan diseases, LMNA and HBB interacting with 18 ODs, PTEN and FGFR1 linked to 17 ODs, KIT related to 16 distinct ODs, and FGFR3 associated with 15 different ODs

  • Among the most important genes, we report tumor suppressor protein P53 gene (TP53) linked to 14 ODs, FGFR1 linked to 18 ODs, SDHA with 5 links, HBB with 18 links, and MECP2 linked to 7 distinct ODs

Read more

Summary

Introduction

Orphan diseases (ODs) or rare diseases are chronic and progressive genetic disorders affecting a small number of people. Goh and Choi [7] have used OMIM data to construct the human diseasome by connecting diseases that share common disease-causing genes This integrative biology approach is aimed at understanding the relationship between diseases based on the underlying biological mechanisms and is expected to improve our current knowledge of disease crosstalk, which may lead to further improvements in disease treatment. DiseaseConnect integrates comprehensive omics, literature data, and drug-related data to reveal disease and disease connectivity via common molecular mechanisms. This tool is very useful since it allows to group diseases with entirely different pathologies, leading to a similar treatment design [8]. We attempt to investigate the relationship between ODs and CDs using an integrative computational approach based on disease-gene association and gene-pathway association resources to identify potential shared molecular pathways in ODs and CDs and to provide valuable results that can be explored to improve disease diagnosis, prognosis, and treatment

Methods
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call