title: Knowledge-based analysis of genetic associations of rheumatoid arthritis to inform studies searching for pleiotropic genes: a literature review and network analysis.
abstract: BACKGROUND
  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.
authors.affiliation: College of Biomedical Engineering, Capital Medical University, 10 Xitoutiao Youanmen Fengtai, Beijing, 100069, People's Republic of China. zhengwyy@ccmu.edu.cn.
authors.forename: Weiying
authors.initials: W
authors.lastname: Zheng
authors.affiliation: College of Biomedical Engineering, Capital Medical University, 10 Xitoutiao Youanmen Fengtai, Beijing, 100069, People's Republic of China. raoshaoq@gdmc.edu.cn.|Institute of Medical Systems Biology and School of Public Health, Guangdong Medical College, 1 Xin Cheng Avenue, Songshan Lake, Dongguan, 523808, Guangdong, People's Republic of China. raoshaoq@gdmc.edu.cn.
authors.forename: Shaoqi
authors.initials: S
authors.lastname: Rao
mesh_terms: D001172:Arthritis, Rheumatoid / Q000175:diagnosis / Q000453:epidemiology / Q000235:genetics*; D053263:Gene Regulatory Networks / Q000235:genetics; D058685:Genetic Pleiotropy / Q000235:genetics*; D020022:Genetic Predisposition to Disease / Q000453:epidemiology / Q000235:genetics; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D051188:Knowledge Bases; D020641:Polymorphism, Single Nucleotide / Q000235:genetics