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

Mar 5, 2025Journal of translational medicine

Molecular networks behind faulty cell cleanup linked to rheumatoid arthritis

AI simplified

Longevity & Aging on OpenScience ↗PubMed ↗DOI ↗OA ↗

Abstract

Two key genes, BCL2L1 and RAF1, may be associated with rheumatoid arthritis (RA) risk.

BCL2L1 methylation sites cg12873919 and cg13989999 were significantly associated with reduced RA risk (p SMR < 0.05).
Increased expression of BCL2L1 is linked to the methylation of specific sites, suggesting a negative impact on RA risk.
The RAF1 methylation site cg26432171 was associated with increased RA risk, indicating a positive correlation between its gene methylation and expression.
MAPK3 expression was negatively correlated with RA risk (p SMR = 7.24E-05), suggesting a potential inhibitory role in RA pathogenesis.
The protective role of MAPK3 was further supported by protein level analysis showing a negative correlation with RA risk.

AI simplified

BACKGROUND: 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 (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.

Key numbers

0.82

BCL2L1 Methylation Odds Ratio

Odds ratio from SMR analysis for cg12873919.

1.83

RAF1 Methylation Odds Ratio

Odds ratio from SMR analysis for cg26432171.

0.91

MAPK3 Expression Odds Ratio

Odds ratio from eQTL-GWAS SMR analysis for MAPK3.

Full Text

We can’t show the full text here under this license. Use the link below to read it at the source.

View full text (PDF) ↗View full text (HTML) ↗

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

Abstract

Key numbers

Full Text

You found one interesting study. We’ll send the next 7.

what lands in your inbox each week:

Recent issues from the longevity & aging brief

Abstract

Key numbers

Full Text

Related papers

You found one interesting study. We’ll send the next 7.

what lands in your inbox each week:

Recent issues from the longevity & aging brief