Back

Novel Genomic Risk Loci shared between Juvenile Idiopathic Arthritis and other HLA-associated Autoimmune Diseases

Khoshfekr Rudsari, H.; Jaholkowski, P.; Bastakoti, S.; Fominykh, V.; Haftorn, K.; Shadrin, A. A.; Lie, B. A.; Andreassen, O. A.; Sanner, H.

2026-01-22 rheumatology
10.64898/2026.01.21.26344521 medRxiv
Show abstract

ObjectivesTo investigate genetic architecture and identify novel risk loci shared between juvenile idiopathic arthritis (JIA) and other human leukocyte antigen (HLA)-associated autoimmune diseases (AIDs) by leveraging genome-wide association studies (GWAS) data. MethodsWe analyzed GWAS summary statistics from over two million participants (123,997 cases and 1,843,249 controls) of European ancestry across multiple AIDs including JIA, autoimmune thyroid disease (AITD), celiac disease, inflammatory bowel disease (IBD), multiple sclerosis (MS), psoriasis (Ps), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and type 1 diabetes (T1D). The conjunctional false discovery rate (conjFDR) method was employed to identify shared genetic loci, followed by functional annotation and pathway analysis. ResultsWe identified 46 novel loci shared between JIA and various AIDs: 17 with AITD, 16 with RA, 13 with IBD, five each with MS and Ps, four with SLE, and seven with T1D. Notable shared risk genes included BACH2, UBASH3A, IRF4, IL12A-AS1, ETS1, PSMD14, FOXK1, NEK6, SP140, TNIP1, VAV3, CYP20A1, DNMT3A, LAX1, CASC15, ZC3H12C, KALRN, TBC1D1, PIK3CB, ANXA6, and HIF1A. Functional annotation revealed 170 nonsynonymous exonic variants and 478 potentially deleterious variants (CADD score > 12.37). Gene Ontology analysis consistently highlighted enrichment of T cell-related processes and immune system regulation pathways. ConclusionThis study expands the understanding of genetic architecture in JIA by identifying novel risk loci shared with other AIDs. The extensive genetic overlap and shared biological pathways, particularly in T cell-mediated immunity, suggest common pathogenic mechanisms and potential therapeutic targets across multiple autoimmune conditions.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.