Enrichment of Rare Variants of Hemophagocytic Lymphohistiocytosis Genes in Systemic Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Our objective was to evaluate whether there is an enrichment of rare variants in familial hemophagocytic lymphohistiocytosis (HLH)-associated genes among patients with systemic juvenile idiopathic arthritis (sJIA) with or without macrophage activation syndrome (MAS). METHODS: Targeted sequencing of HLH genes (LYST, PRF1, RAB27A, STX11, STXBP2, UNC13D) was performed in patients with sJIA from an established cohort. Sequence data from control participants were obtained in silico (database of Genotypes and Phenotypes: phs000280.v8.p2). Rare variant association testing (RVT) was performed with sequence kernel association test package. Significance was defined as P < 0.05 after 100,000 permutations. RESULTS: Sequencing data from 524 sJIA cases were jointly called and harmonized with exome-derived target data from 3,000 controls. Quality control operations produced a set of 480 cases and 2,924 ancestrally matched control participants. RVT of cases and controls revealed a significant association with rare protein-altering variants (minor allele frequency [MAF] < 0.01) of STXBP2 (P = 0.020) and ultrarare variants (MAF < 0.001) of STXBP2 (P = 0.006) and UNC13D (P = 0.046). A subanalysis of 32 cases with known MAS and 90 without revealed a significant difference in the distribution of rare UNC13D variants (P = 0.0047) between the groups. Additionally, patients with sJIA more often carried two or more HLH variants than did controls (P = 0.007), driven largely by digenic combinations involving LYST. CONCLUSION: We identified an enrichment of rare HLH variants in patients with sJIA compared with controls, driven by STXBP2 and UNC13D. Biallelic variation in HLH genes was associated with sJIA, driven by LYST. Only UNC13D displayed enrichment in patients with MAS. This suggests that HLH variants may contribute to the pathophysiology of sJIA, even without MAS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".