4.6 Article

Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics

Journal

FRONTIERS IN GENETICS
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2021.656545

Keywords

rheumatoid arthritis; systemic lupus erythematosus; harmonic mean P-value; conjunction conditional false discover rate; pleiotropic genes

Funding

  1. Youth Foundation of Humanity and Social Science - Ministry of Education of China [18YJC910002]
  2. Natural Science Foundation of Jiangsu Province of China [BK20181472]
  3. China Postdoctoral Science Foundation [2018M630607, 2019T120465]
  4. QingLan Research Project of Jiangsu Province for Outstanding Young Teachers
  5. Six-Talent Peaks Project in Jiangsu Province of China [WSN-087]
  6. Training Project for Youth Teams of Science and Technology Innovation at Xuzhou Medical University [TD202008]
  7. Postdoctoral Science Foundation of Xuzhou Medical University
  8. National Natural Science Foundation of China [81402765]
  9. Statistical Science Research Project from National Bureau of Statistics of China [2014LY112]
  10. Social Development Project of Xuzhou City [KC20062]

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The study revealed a significant genetic correlation between rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). Through multiple-tissue eQTL weighted integrative analysis and ccFDR method, 14 potential pleiotropic genes associated with both diseases were identified, including four novel genes. These genes are involved in relevant autoimmune pathways.
Background Clinical and epidemiological studies have suggested systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are comorbidities and common genetic etiologies can partly explain such coexistence. However, shared genetic determinations underlying the two diseases remain largely unknown. Methods Our analysis relied on summary statistics available from genome-wide association studies of SLE (N = 23,210) and RA (N = 58,284). We first evaluated the genetic correlation between RA and SLE through the linkage disequilibrium score regression (LDSC). Then, we performed a multiple-tissue eQTL (expression quantitative trait loci) weighted integrative analysis for each of the two diseases and aggregated association evidence across these tissues via the recently proposed harmonic mean P-value (HMP) combination strategy, which can produce a single well-calibrated P-value for correlated test statistics. Afterwards, we conducted the pleiotropy-informed association using conjunction conditional FDR (ccFDR) to identify potential pleiotropic genes associated with both RA and SLE. Results We found there existed a significant positive genetic correlation (r(g) = 0.404, P = 6.01E-10) via LDSC between RA and SLE. Based on the multiple-tissue eQTL weighted integrative analysis and the HMP combination across various tissues, we discovered 14 potential pleiotropic genes by ccFDR, among which four were likely newly novel genes (i.e., INPP5B, OR5K2, RP11-2C24.5, and CTD-3105H18.4). The SNP effect sizes of these pleiotropic genes were typically positively dependent, with an average correlation of 0.579. Functionally, these genes were implicated in multiple auto-immune relevant pathways such as inositol phosphate metabolic process, membrane and glucagon signaling pathway. Conclusion This study reveals common genetic components between RA and SLE and provides candidate associated loci for understanding of molecular mechanism underlying the comorbidity of the two diseases.

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