POS0082 EXPLORING THE GENETIC BASIS OF CLINICAL HETEROGENEITY IN GIANT CELL ARTERITIS
Bibliographic record
Abstract
Background: Giant cell arteritis (GCA) is a large-vessel vasculitis primarily affecting the aorta and its branches. GCA presents with a wide range of clinical manifestations, reflecting its complex and heterogeneous nature. These disease features include cranial symptoms such as headache, vision abnormalities, and ischemic stroke, as well as the association with polymyalgia rheumatica. This clinical variability complicates diagnosis and management of GCA. Objectives: The aim of this study was to identify genetic risk factors associated with key clinical manifestations of GCA by testing genome-wide association. Methods: Genomic data from 3,498 patients with GCA and 15,550 healthy controls from a previous study [1] were analyzed to investigate the genetic background associated with GCA-related manifestations. Patients with GCA were stratified according to the presence/absence of clinical phenotypes (shown in Table 1 along with their respective sample sizes). Three logistic regression analyses were performed for each trait, adjusting for the first 10 principal components and sex as covariates, comparing: i) manifestation-positive patients and unaffected controls, ii) manifestation-negative patients and unaffected controls, and iii) patients with and without the considered manifestation. A signal was considered specifically associated with a clinical phenotype if it reached genome-wide significance (p < 5×10⁻⁸) in the case-control comparison and also nominal significance in intra-case comparisons. The HLA region was excluded from the analysis due to its high linkage disequilibrium and complex genetic architecture. Gene annotation was conducted based on SNP-to-gene distance and functional information, including expression and protein quantitative trait locus (eQTL/pQTL) data from blood and vascular tissues. Results: Thirteen non-HLA significant genetic associations across seven distinct GCA-related manifestations were identified: early disease onset, polymyalgia rheumatica, visual manifestations, severe ischemic manifestations, jaw claudication, arm or leg claudication, and irreversible occlusive disease (Figure 1). No significant association was found for permanent visual loss. These loci exhibited notable effect sizes and comprised novel associations for this pathology. Key findings included: RHOQ , associated with visual manifestations (rs6746695, p=4.14×10⁻⁸, OR=3.19), which regulates angiogenesis via Notch signaling [2]; IL22RA1 , associated with jaw claudication (rs72663289, p=1.36×10⁻8, OR=3.13), an interleukin receptor that has been described to be upregulated in GCA-affected arteries, as well as peripheral blood mononuclear cells and plasma from patients with GCA [3]; and OTUD1 , associated with the absence of polymyalgia rheumatica (rs138303599, OR=6.10, p=1.01×10-10), which can promote inflammation and remodeling in cardiac tissue by affecting STAT3 [4, 5]. Additionally, the gene P4HA2 , previously identified as involved in GCA, was found to be specifically associated with late-onset cases (rs419291, p=2.89×10⁻⁸, OR=1.19). Conclusion: This study represents the first genome-wide association analysis of GCA-specific manifestations, deepening our understanding of the genetic basis underlying the disease's clinical heterogeneity. These findings may lead to earlier diagnosis, improved monitoring of disease activity, and more targeted therapeutic strategies for this complex condition. REFERENCES: [1] Borrego-Yaniz G, Ortiz-Fernández L, Madrid-Paredes A, et al (2024) Risk loci involved in giant cell arteritis susceptibility: a genome-wide association study. Lancet Rheumatol 6:e374–e383. [2] Bridges E, Sheldon H, Kleibeuker E, et al (2020) RHOQ is induced by DLL4 and regulates angiogenesis by determining the intracellular route of the Notch intracellular domain. Angiogenesis 23:493–513. [3] Zerbini A, Muratore F, Boiardi L, et al (2018) Increased expression of interleukin-22 in patients with giant cell arteritis. Rheumatology (Oxford) 57:64–72. [4] Wang M, Han X, Yu T, et al (2023) OTUD1 promotes pathological cardiac remodeling and heart failure by targeting STAT3 in cardiomyocytes. Theranostics 13:2263–2280. [5] Oikawa D, Gi M, Kosako H, et al (2022) OTUD1 deubiquitinase regulates NF-κB- and KEAP1-mediated inflammatory responses and reactive oxygen species-associated cell death pathways. Cell Death Dis 13:694. Acknowledgements: NIL . Disclosure of Interests: None declared . © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".