Novel Insights into the Link between Rheumatoid Arthritis and Malignant Lymphoma: A Multi-Stage Study of Observational and Genetic Analyses

Objective To investigate complex relationship between rheumatoid arthritis (RA) and malignant lymphoma (ML).

Methods Prospective analysis was conducted in participants from UK Biobank to evaluate associations between RA and subsequent ML risk. We estimated genome-wide genetic correlations by utilizing publicly available European genome-wide association (GWAS) summary statistics. Then cross-trait pleiotropic analysis was performed to identify shared signals and genes. Functional annotation, tissue-specific and cell-specific analysis were performed to determine biofunctions of shared genetic signals. Finally, two-sample Mendelian randomization (MR) was conducted to explore causal interactions between diseases.

Results Our results demonstrated strong positive associations between RA and ML and its subsets both in epidemiological and genetical evidence. Cross-trait pleiotropic analysis identified 20 shared loci (e.g., 11q23.3 and 20q13.12) with high colocalization evidence, which could be mapped to 67 pleiotropic genes, such as CD40, ITPR3, TNFRSF14 and MAPK3. CD40 was found to increase the risk of RA but reduce the risk of lymphoma. MAPK3 was identified as a potential drug target for both RA and lymphoma. Genome-wide gene-set enrichment analysis revealed shared mechanisms between different trait pairs, particularly in pathways related to B cell activation and T cell selection. Functional enrichment of pleiotropic genes highlighted lymphocyte proliferation, activation, and chromatin remodeling. These sharing mechanisms may be at work in tissues such as whole blood, spleen, terminal ileum, and EBV-transformed lymphocytes. We also identified co-localization evidence and enrichment in multiple immune cell subsets, especially B cells and T cells. Finally, MR analysis confirmed that RA onset increases the risk of lymphoma.

Conclusions These results support the shared genetic basis underlying RA and ML and have important implications for identifying potential intervention and druggable targets.

No relevant conflicts of interest to declare.