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

Abstract

IntroductionPleiotropy 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.MethodsIn 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.ResultsIn 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.ConclusionsThis 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s13075-015-0715-1) contains supplementary material, which is available to authorized users.

Identification of novel genetic loci for osteoporosis and/or rheumatoid arthritis using cFDR approach

“…Among the 30 SNPs associated with both FNK BMD and RA, 18 were located within MHC region, which is the most vital genomic regions associated with RA. Those 18 SNPs are located at or near the following genes that have been reported to be related to RA: C6orf10 [ 40 ], NOTCH4 [ 41 ], HLA-DQB2 [ 42 ], HLA-DMB [ 43 ], HLA-DMA [ 43 ], and BRD2 [ 44 ]. Although we do not find any report about association between these gene and OP or related traits, some other MHC genes have been identified to be associated with OP in previous research [ 33 ].…”

Genetic Polymorphisms Associated with Rheumatoid Arthritis Development and Antirheumatic Therapy Response

“…By the in-silico constructing of an interactome between the already known RA candidate genes, about 160 other presumptive candidates were identified. Subsequently, a number of them were considered RA-associated according to the GWAS results: the NOTCH4 gene, the TNXB gene located near the MHC class III genes, the BTNL2 gene (especially rs3817963; also associated with systemic sarcoidosis), as well as the insufficiently characterised sequence C6orf10, expressed in autoimmune and some other diseases [ 49 ].…”

Notch4 and mhc class II polymorphisms are associated with hcv-related benign and malignant lymphoproliferative diseases

“…In fact, its expression seems to be relevant for the development of the central nervous system [ 37 ] and vascular system [ 38 ], and also appears to play a role in the differentiation of naive CD4+ T cells [ 39 ]. Interestingly, a very recent paper listed NOTCH4 among genes with a pleiotropic effect, meaning that it could be able to determine multiple phenotypic traits [ 40 ]. As other examples of pleiotropy, NOTCH4 variants could determine a shared genetic susceptibility mechanism between different diseases or physiological processes.…”