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Background <p>Autophagy is associated with the development of rheumatoid arthritis (RA), but its genetic pathological mechanisms remain incompletely understood. In this study, we employed summary-data-based Mendelian randomization (SMR) and co-localization analysis to systematically investigate the relationship between autophagy-related genes and RA.</p> Methods <p>We obtained summary data on blood methylation (mQTL), gene expression (eQTL), and protein abundance (pQTL) from respective quantitative trait locus (QTL) studies. Genetic association data for RA were primarily derived from the FinnGen database, with validation performed using the UK Biobank (UKB) and GWAS Catalog databases. SMR analysis was conducted to evaluate the association between molecular characteristics of autophagy-related genes and RA. Subsequently, co-localization analysis was performed to determine whether the identified signals share the same causal genetic variants.</p> Results <p>After integrating mQTL-eQTL multi-omics data, we identified two key autophagy genes, <i>BCL2L1</i> and <i>RAF1</i>, which may have a causal relationship with RA. Significant associations were found for <i>BCL2L1</i> (cg12873919, cg13989999) and <i>RAF1</i> (cg26432171) in the SMR analysis of autophagy-related mQTL, eQTL, and GWAS data (p SMR &lt; 0.05). In the integrated mQTL-eQTL SMR analysis, cg12873919 (p SMR = 1.40E-07, OR = 0.82, 95% CI [0.76–0.88]), cg13989999 (p SMR = 1.43E-06, OR = 0.78, 95% CI [0.71–0.87]), and cg26432171 (p SMR = 9.18E-09, OR = 1.83, 95% CI [1.49–2.25]) were all significantly validated. Methylation of cg12873919 and cg13989999 in <i>BCL2L1</i> was associated with increased <i>BCL2L1</i> expression, consistent with their negative impact on RA risk. Conversely, the cg26432171 site in <i>RAF1</i> showed a positive correlation between gene methylation and expression. In the eQTL-GWAS SMR analysis, <i>MAPK3</i> expression (p SMR = 7.24E-05, OR = 0.91, 95% CI [0.87–0.95]) was negatively correlated with RA risk, a finding supported by co-localization analysis (PPH4 &gt; 0.5), suggesting that this gene may inhibit RA pathogenesis by regulating the autophagy process. Furthermore, protein level analysis also supported the protective role of <i>MAPK3</i> (p SMR = 7.53E-05, OR = 0.89, 95% CI [0.84–0.94]).</p> Conclusion <p>We identified that autophagy-related genes <i>BCL2L1</i> and <i>RAF1</i> may be associated with RA risk, providing strong evidence from multi-omics data. This study identifies autophagy genes related to RA, potentially offering new insights into the pathogenesis of RA.</p>

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Multi-omics study on autophagic dysfunction molecular network in the pathogenesis of rheumatoid arthritis

  • 期刊论文

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  • 发表日期：

    2025年3月5日

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  • Ping Jiang,
  • Yichen Zhao,
  • Youji Jia,
  • Honghong Ma,
  • Yajuan Guo,
  • Wei Yan,
  • Xiaobing Xi

摘要

Background

Autophagy is associated with the development of rheumatoid arthritis (RA), but its genetic pathological mechanisms remain incompletely understood. In this study, we employed summary-data-based Mendelian randomization (SMR) and co-localization analysis to systematically investigate the relationship between autophagy-related genes and RA.

Methods

We obtained summary data on blood methylation (mQTL), gene expression (eQTL), and protein abundance (pQTL) from respective quantitative trait locus (QTL) studies. Genetic association data for RA were primarily derived from the FinnGen database, with validation performed using the UK Biobank (UKB) and GWAS Catalog databases. SMR analysis was conducted to evaluate the association between molecular characteristics of autophagy-related genes and RA. Subsequently, co-localization analysis was performed to determine whether the identified signals share the same causal genetic variants.

Results

After integrating mQTL-eQTL multi-omics data, we identified two key autophagy genes, BCL2L1 and RAF1, which may have a causal relationship with RA. Significant associations were found for BCL2L1 (cg12873919, cg13989999) and RAF1 (cg26432171) in the SMR analysis of autophagy-related mQTL, eQTL, and GWAS data (p SMR < 0.05). In the integrated mQTL-eQTL SMR analysis, cg12873919 (p SMR = 1.40E-07, OR = 0.82, 95% CI [0.76–0.88]), cg13989999 (p SMR = 1.43E-06, OR = 0.78, 95% CI [0.71–0.87]), and cg26432171 (p SMR = 9.18E-09, OR = 1.83, 95% CI [1.49–2.25]) were all significantly validated. Methylation of cg12873919 and cg13989999 in BCL2L1 was associated with increased BCL2L1 expression, consistent with their negative impact on RA risk. Conversely, the cg26432171 site in RAF1 showed a positive correlation between gene methylation and expression. In the eQTL-GWAS SMR analysis, MAPK3 expression (p SMR = 7.24E-05, OR = 0.91, 95% CI [0.87–0.95]) was negatively correlated with RA risk, a finding supported by co-localization analysis (PPH4 > 0.5), suggesting that this gene may inhibit RA pathogenesis by regulating the autophagy process. Furthermore, protein level analysis also supported the protective role of MAPK3 (p SMR = 7.53E-05, OR = 0.89, 95% CI [0.84–0.94]).

Conclusion

We identified that autophagy-related genes BCL2L1 and RAF1 may be associated with RA risk, providing strong evidence from multi-omics data. This study identifies autophagy genes related to RA, potentially offering new insights into the pathogenesis of RA.