Abstract

Juvenile idiopathic arthritis (JIA) is a complex rheumatic disease encompassing several clinically defined subtypes of varying severity. The etiology of JIA remains largely unknown, but genome-wide association studies (GWASs) have identified up to 22 genes associated with JIA susceptibility, including a well-established association with HLA-DRB1. Continued investigation of heritable risk factors has been hindered by disease heterogeneity and low disease prevalence. In this study, we utilized shared genomic segments (SGS) analysis on whole-genome sequencing of 40 cases from 12 multi-generational pedigrees significantly enriched for JIA. Subsets of cases are connected by a common ancestor in large extended pedigrees, increasing the power to identify disease-associated loci. SGS analysis identifies genomic segments shared among disease cases that are likely identical by descent and anchored by a disease locus. This approach revealed statistically significant signals for major histocompatibility complex (MHC) class I and class III alleles, particularly HLA-A*02:01, which was observed at a high frequency among cases. Furthermore, we identified an additional risk locus at 12q23.2– 23.3, containing genes primarily expressed by naive B cells, natural killer cells, and monocytes. The recognition of additional risk beyond HLA-DRB1 provides a new perspective on immune cell dynamics in JIA. These findings contribute to our understanding of JIA and may guide future research and therapeutic strategies.

Document Type

Article

Publication Date

4-11-2024

Notes/Citation Information

Ó 2024 The Author(s). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Digital Object Identifier (DOI)

https://doi.org/10.1016/j.xhgg.2024.100277

Funding Information

We thank the Pedigree and Population Resource of Huntsman Cancer Institute, University of Utah (funded in part by the Hunts- man Cancer Foundation) for its role in the ongoing collection, maintenance, and support of the Utah Population Database (UPDB). We also acknowledge partial support for the UPDB through grant P30 CA2014 from the National Cancer Institute, University of Utah, and from the University of Utah’s program in Personalized Health and Utah Clinical and Translational Sci- ence Institute. We thank the staff at the UPDB for their support in the identification of the JIA pedigrees. We greatly appreciate Rob Sargent and Myke Madsen for technical and programming support performing the SGS analyses, and Nicola Camp for guid- ance on feasibility and SGS concepts. The authors gratefully acknowledge the Utah Genome Project and the Chan Soon- Shiong Family Foundation for providing the funds for sequencing the study samples. The research reported in this publication was supported in part by NIH R35GM118335 (to L.B.J.) and the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number TL1TR002540. The content is solely the responsibility of the authors and does not necessarily repre- sent the official views of the National Institutes of Health.

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