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Review
. 2015 Aug 8;17(1):202.
doi: 10.1186/s13075-015-0715-1.

Knowledge-based analysis of genetic associations of rheumatoid arthritis to inform studies searching for pleiotropic genes: a literature review and network analysis

Affiliations
Review

Knowledge-based analysis of genetic associations of rheumatoid arthritis to inform studies searching for pleiotropic genes: a literature review and network analysis

Weiying Zheng et al. Arthritis Res Ther. .

Abstract

Introduction: Pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. Gene variants directly affect the normal processes of a series of physiological and biochemical reactions, and therefore cause a variety of diseases traits to be changed accordingly. Moreover, a shared genetic susceptibility mechanism may exist between different diseases. Therefore, shared genes, with pleiotropic effects, are important to understand the sharing pathogenesis and hence the mechanisms underlying comorbidity.

Methods: In this study, we proposed combining genome-wide association studies (GWAS) and public knowledge databases to search for potential pleiotropic genes associated with rheumatoid arthritis (RA) and eight other related diseases. Here, a GWAS-based network analysis is used to recognize risk genes significantly associated with RA. These RA risk genes are re-extracted as potential pleiotropic genes if they have been proved to be susceptible genes for at least one of eight other diseases in the OMIM or PubMed databases.

Results: In total, we extracted 116 potential functional pleiotropic genes for RA and eight other diseases, including five hub pleiotropic genes, BTNL2, HLA-DRA, NOTCH4, TNXB, and C6orf10, where BTNL2, NOTCH4, and C6orf10 are novel pleiotropic genes identified by our analysis.

Conclusions: This study demonstrates that pleiotropy is a common property of genes associated with disease traits. Our results ascertained the shared genetic risk profiles that predisposed individuals to RA and other diseases, which could have implications for identification of molecular targets for drug development, and classification of diseases.

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Figures

Fig. 1
Fig. 1
A pleiotropic interaction network of RA. a The pleiotropic SNP-SNP interaction network; b the derived gene-gene interaction network. In b, 13 red nodes are RA-susceptible genes, and 14 yellow nodes are susceptible genes for one or more of eight other diseases. SNP single nucleotide polymorphism, RA rheumatoid arthritis
Fig. 2
Fig. 2
The gene-disease network of C6orf10 and its interaction genes
Fig. 3
Fig. 3
RA pleiotropic genes replicated in MalaCards and HuGENavigator databases. a Pleiotropic genes of RA in MalaCards. b Pleiotropic genes of RA in HuGENavigator. RA rheumatoid arthritis

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