Genetic analysis of the relation between <i>IL2RA</i>/<i>IL2RB</i> and rheumatoid arthritis risk

Yang, Yonghui; Yuan, Shan; Che, Meihua; Jing, Haiyin; Yuan, L.; Dong, Kuaini; Jin, Tianbo

doi:10.1002/mgg3.754

Cited by 8 publications

(6 citation statements)

References 29 publications

(25 reference statements)

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“…For instance, the absolute risk of RA at 65 years was found to be between 30.6% (95% CI = 18.5%–42.6%) and 53.8% (95% CI = 42.8%–64.9%) within the top 5% of the PRS distribution. Our PRS showed a higher estimate (OR = 1.55; 95% CI = 1.27–1.90) among high PRS individuals than the association of rare variants in IL2RA and IL2RB with RA risk reported in previous studies 26,27 …”

Section: Discussioncontrasting

confidence: 49%

Genome‐wide polygenic risk score for rheumatoid arthritis prediction in postmenopausal women

Xu,

2024

The Journal of Gene Medicine

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BackgroundRheumatoid arthritis (RA), a common autoimmune disease, exhibits a vital genetic component. Polygenic risk scores (PRS) derived from genome‐wide association studies (GWAS) offer potential utility in predicting disease susceptibility. The present study aimed to develop and validate a PRS for predicting RA risk in postmenopausal women.MethodsThe study developed a novel PRS using 225,000 genetic variants from a GWAS dataset. The PRS was developed in a cohort of 8967 postmenopausal women and validated in an independent cohort of 6269 postmenopausal women. Among the development cohort, approximately 70% were Hispanic and approximately 30% were African American. The testing cohort comprised approximately 50% Hispanic and 50% Caucasian individuals. Stratification according to PRS quintiles revealed a pronounced gradient in RA prevalence and odds ratios.ResultsHigh PRS was significantly associated with increased RA risk in individuals aged 60–70 years, ≥ 70 years, and overweight and obese participants. Furthermore, at age 65 years, individuals in the bottom 5% of the PRS distribution have an absolute risk of RA at 30.6% (95% confidence interval = 18.5%–42.6%). The risk increased to 53.8% (95% confidence interval = 42.8%–64.9%) for those in the top 5% of the PRS distribution.ConclusionsThe PRS developed in the present study is significantly associated with RA risk, showing the potential for early screening of RA in postmenopausal women. This work demonstrates the feasibility of personalized medicine in identifying high‐risk individuals for RA, indicating the need for further studies to test the utility of PRS in other populations.

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Section: Discussioncontrasting

confidence: 49%

Genome‐wide polygenic risk score for rheumatoid arthritis prediction in postmenopausal women

Xu,

2024

The Journal of Gene Medicine

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“…In the Chinese Han population, Yang Y et al. found an association between IL2RA and a decreased risk of RA ( 51 ). Furthermore, IL2RA has been identified as a susceptibility gene for autoimmune thyroid disease ( 52 ).…”

Section: Discussionmentioning

confidence: 99%

Investigating the shared genetic architecture between hypothyroidism and rheumatoid arthritis

Peng,

Huang,

Tang

et al. 2024

Front. Immunol.

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BackgroundThere is still controversy regarding the relationship between hypothyroidism and rheumatoid arthritis (RA), and there has been a dearth of studies on this association. The purpose of our study was to explore the shared genetic architecture between hypothyroidism and RA.MethodsUsing public genome-wide association studies summary statistics of hypothyroidism and RA, we explored shared genetics between hypothyroidism and RA using linkage disequilibrium score regression, ρ-HESS, Pleiotropic analysis under a composite null hypothesis (PLACO), colocalization analysis, Multi-Trait Analysis of GWAS (MTAG), and transcriptome-wide association study (TWAS), and investigated causal associations using Mendelian randomization (MR).ResultsWe found a positive genetic association between hypothyroidism and RA, particularly in local genomic regions. Mendelian randomization analysis suggested a potential causal association of hypothyroidism with RA. Incorporating gene expression data, we observed that the genetic associations between hypothyroidism and RA were enriched in various tissues, including the spleen, lung, small intestine, adipose visceral, and blood. A comprehensive approach integrating PLACO, Bayesian colocalization analysis, MTAG, and TWAS, we successfully identified TYK2, IL2RA, and IRF5 as shared risk genes for both hypothyroidism and RA.ConclusionsOur investigation unveiled a shared genetic architecture between these two diseases, providing novel insights into the underlying biological mechanisms and establishing a foundation for more effective interventions.

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“…Some studies have shown that in patients with AS, CX3CR1 + monocytes have a specific proinflammatory transcriptome and actively participate in the activation and expansion of ILC3s, thus promoting the persistent proinflammatory status of AS [ 26 ]. The IL2RB gene is a cytokine signalling-related gene [ 27 ] that encodes the receptor of interleukin 2 (IL-2) and is associated with autoimmune and inflammatory diseases [ 28 ]. A study found that an IL2RB polymorphism (rs2281089) significantly reduced the risk of RA [ 28 ].…”

Section: Discussionmentioning

confidence: 99%

“…The IL2RB gene is a cytokine signalling-related gene [ 27 ] that encodes the receptor of interleukin 2 (IL-2) and is associated with autoimmune and inflammatory diseases [ 28 ]. A study found that an IL2RB polymorphism (rs2281089) significantly reduced the risk of RA [ 28 ]. A 10-year follow-up study of AS patients found that 14 single-nucleotide polymorphisms (SNPs) in 10 different genes distributed in AS patients were significantly associated with peripheral arthritis (PA) and that IL2RB was one of the 10 genes [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

A Predictive Disease Risk Model for Ankylosing Spondylitis: Based on Integrated Bioinformatic Analysis and Identification of Potential Biomarkers Most Related to Immunity

Gao

Hou

Chen

et al. 2023

Mediators of Inflammation

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Background. The pathogenesis of ankylosing spondylitis (AS) is still not clear, and immune-related genes have not been systematically explored in AS. The purpose of this paper was to identify the potential early biomarkers most related to immunity in AS and develop a predictive disease risk model with bioinformatic methods and the Gene Expression Omnibus database (GEO) to improve diagnostic and therapeutic efficiency. Methods. To identify differentially expressed genes and create a gene coexpression network between AS and healthy samples, we downloaded the AS-related datasets GSE25101 and GSE73754 from the GEO database and employed weighted gene coexpression network analysis (WGCNA). We used the GSVA, GSEABase, limma, ggpubr, and reshape2 packages to score immune data and investigated the links between immune cells and immunological functions by using single-sample gene set enrichment analysis (ssGSEA). The value of the core gene set and constructed model for early AS diagnosis was investigated by using receiver operating characteristic (ROC) curve analysis. Results. Biological function and immune score analyses identified central genes related to immunity, key immune cells, key related pathways, gene modules, and the coexpression network in AS. Granulysin (GNLY), Granulysin (GZMK), CX3CR1, IL2RB, dysferlin (DYSF), and S100A12 may participate in AS development through NK cells, CD8+ T cells, Th1 cells, and other immune cells and represent potential biomarkers for the early diagnosis of AS occurrence and progression. Furthermore, the T cell coinhibitory pathway may be involved in AS pathogenesis. Conclusion. The AS disease risk model constructed based on immune-related genes can guide clinical diagnosis and treatment and may help in the development of personalized immunotherapy.

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Genetic analysis of the relation between IL2RA/IL2RB and rheumatoid arthritis risk

Cited by 8 publications

References 29 publications

Genome‐wide polygenic risk score for rheumatoid arthritis prediction in postmenopausal women

Genome‐wide polygenic risk score for rheumatoid arthritis prediction in postmenopausal women

Investigating the shared genetic architecture between hypothyroidism and rheumatoid arthritis

A Predictive Disease Risk Model for Ankylosing Spondylitis: Based on Integrated Bioinformatic Analysis and Identification of Potential Biomarkers Most Related to Immunity

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