Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics
BackgroundClinical 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 unknow...
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Frontiers Media S.A.
2021-03-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2021.656545/full |
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| author | Haojie Lu Jinhui Zhang Zhou Jiang Meng Zhang Ting Wang Ting Wang Huashuo Zhao Huashuo Zhao Ping Zeng Ping Zeng |
| author_facet | Haojie Lu Jinhui Zhang Zhou Jiang Meng Zhang Ting Wang Ting Wang Huashuo Zhao Huashuo Zhao Ping Zeng Ping Zeng |
| author_sort | Haojie Lu |
| collection | DOAJ |
| description | BackgroundClinical 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.MethodsOur 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.ResultsWe found there existed a significant positive genetic correlation (rg = 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.ConclusionThis 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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| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-13T14:43:54Z |
| publishDate | 2021-03-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Genetics |
| spelling | doaj.art-8ec2d8aa67bc47868c8a17a91295d2292022-12-21T23:41:32ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-03-011210.3389/fgene.2021.656545656545Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary StatisticsHaojie Lu0Jinhui Zhang1Zhou Jiang2Meng Zhang3Ting Wang4Ting Wang5Huashuo Zhao6Huashuo Zhao7Ping Zeng8Ping Zeng9Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, ChinaCenter for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, ChinaCenter for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, ChinaCenter for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, ChinaBackgroundClinical 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.MethodsOur 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.ResultsWe found there existed a significant positive genetic correlation (rg = 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.ConclusionThis 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.https://www.frontiersin.org/articles/10.3389/fgene.2021.656545/fullrheumatoid arthritissystemic lupus erythematosusharmonic mean P-valueconjunction conditional false discover ratepleiotropic genes |
| spellingShingle | Haojie Lu Jinhui Zhang Zhou Jiang Meng Zhang Ting Wang Ting Wang Huashuo Zhao Huashuo Zhao Ping Zeng Ping Zeng Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics Frontiers in Genetics rheumatoid arthritis systemic lupus erythematosus harmonic mean P-value conjunction conditional false discover rate pleiotropic genes |
| title | Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics |
| title_full | Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics |
| title_fullStr | Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics |
| title_full_unstemmed | Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics |
| title_short | Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics |
| title_sort | detection of genetic overlap between rheumatoid arthritis and systemic lupus erythematosus using gwas summary statistics |
| topic | rheumatoid arthritis systemic lupus erythematosus harmonic mean P-value conjunction conditional false discover rate pleiotropic genes |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2021.656545/full |
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