Identification of Susceptibility Loci in <i>IL6</i>, <i>RPS9</i>/<i>LILRB3</i>, and an Intergenic Locus on Chromosome 21q22 in Takayasu Arteritis in a Genome‐Wide Association Study
Bibliographic record
Abstract
OBJECTIVE: Takayasu arteritis is a rare large vessel vasculitis with incompletely understood etiology. This study was undertaken to perform the first unbiased genome-wide association analysis of Takayasu arteritis. METHODS: Two independent cohorts of patients with Takayasu arteritis from Turkey and North America were included in our study. The Turkish cohort consisted of 559 patients and 489 controls, and the North American cohort consisted of 134 patients and 1,047 controls of European ancestry. Genotyping was performed using the Omni1-Quad and Omni2.5 genotyping arrays. Genotyping data were subjected to rigorous quality control measures and subsequently analyzed to discover genetic susceptibility loci for Takayasu arteritis. RESULTS: We identified genetic susceptibility loci for Takayasu arteritis with a genome-wide level of significance in IL6 (rs2069837) (odds ratio [OR] 2.07, P = 6.70 × 10(-9)), RPS9/LILRB3 (rs11666543) (OR 1.65, P = 2.34 × 10(-8)), and an intergenic locus on chromosome 21q22 (rs2836878) (OR 1.79, P = 3.62 × 10(-10)). The genetic susceptibility locus in RPS9/LILRB3 lies within the leukocyte receptor complex gene cluster on chromosome 19q13.4, and the disease risk variant in this locus correlates with reduced expression of multiple genes including the inhibitory leukocyte immunoglobulin-like receptor gene LILRB3 (P = 2.29 × 10(-8)). In addition, we identified candidate susceptibility genes with suggestive levels of association (P < 1 × 10(-5)) with Takayasu arteritis, including PCSK5, LILRA3, PPM1G/NRBP1, and PTK2B. CONCLUSION: Our findings indicate novel genetic susceptibility loci for Takayasu arteritis and uncover potentially important aspects of the pathophysiology of this form of vasculitis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".