Synovial transcriptome-wide association study implicates novel genes underlying rheumatoid arthritis risk
Abstract Background To identify rheumatoid arthritis (RA)-associated susceptibility genes and pathways through integrating genome-wide association study (GWAS) and self-collected gene expression profile data. Methods A gene expression prediction model was built for synovium in 202 arthritic patients with matched genotype and gene expression data. Using the FUSION software performed a transcriptome-wide association study (TWAS). GWAS summary data was driven from the largest RA GWAS meta-analysis (n = 276,020). Further analyses (conditional and joint analysis, two types of causal analysis, differential expression analysis and gene-set enrichment analysis) were used to deepen our understanding of genetic architecture and comorbidity aetiology of RA. Results We identified eight conditionally independent genes associated with RA after Bonferroni corrections, of which three genes were novel, such as TPRA1 (PTWAS = 9.59 × 10− 6) and HIP1 (PTWAS = 1.47 × 10− 5). We identified four genes that showed strong causal evidence, four genes differentially expressed in RA, and explored the possibility of new uses for known drugs. Conclusions By using relevant tissues in synovium, our TWAS analysis led to the identification of previously unknown RA-associated genes, shedding new light on the underlying genetic architecture of RA..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
ResearchSquare.com - (2024) vom: 26. März Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Hu, Shou-ye [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.21203/rs.3.rs-4126672/v1 |
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XRA043005896 |
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| 520 | |a Abstract Background To identify rheumatoid arthritis (RA)-associated susceptibility genes and pathways through integrating genome-wide association study (GWAS) and self-collected gene expression profile data. Methods A gene expression prediction model was built for synovium in 202 arthritic patients with matched genotype and gene expression data. Using the FUSION software performed a transcriptome-wide association study (TWAS). GWAS summary data was driven from the largest RA GWAS meta-analysis (n = 276,020). Further analyses (conditional and joint analysis, two types of causal analysis, differential expression analysis and gene-set enrichment analysis) were used to deepen our understanding of genetic architecture and comorbidity aetiology of RA. Results We identified eight conditionally independent genes associated with RA after Bonferroni corrections, of which three genes were novel, such as TPRA1 (PTWAS = 9.59 × 10− 6) and HIP1 (PTWAS = 1.47 × 10− 5). We identified four genes that showed strong causal evidence, four genes differentially expressed in RA, and explored the possibility of new uses for known drugs. Conclusions By using relevant tissues in synovium, our TWAS analysis led to the identification of previously unknown RA-associated genes, shedding new light on the underlying genetic architecture of RA. | ||
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