A25: The Association of Immunogenetic and Environmental Factors with Disease Course in Patients with Juvenile Idiopathic Inflammatory Myopathies
Bibliographic record
Abstract
Background/Purpose: Three disease courses can be distinguished in patients with juvenile idiopathic inflammatory myopathies (JIIM): monocyclic (M), polycyclic (P), and chronic continuous (CC). Predictors of disease course could result in improved therapy and help focus research efforts. We examined the association of immunogenetic and environmental factors with disease course in a large JIIM cohort. Methods: We enrolled 240 Caucasian patients with JIIM (204 dermato‐, 21 poly‐, and 15 overlap myositis) diagnosed from 1980–2010 in the US and Canada into IRB‐approved studies. The ratio of girls to boys was 3:1. Median age at diagnosis was 7 years (IQR: 5–12). Physician questionnaires with clinical and demographic data and patient blood samples were obtained. Follow‐up was through medical record review. The disease course classification was as follows: M—no active disease and off medication within 2 years of diagnosis (n = 62); P—disease recurrence after definite remission (n = 62); and CC—persistent disease or continuation of medication for more than 2 years (n = 116). Genetic data included: high resolution HLA‐DRB1 and HLA‐DQA1 alleles, and peptide binding motifs; immunoglobulin gamma heavy and kappa light chain phenotypes and allotypes; and TNFα (−238, −308), IL‐1α (−889, +4845), and IL‐1β (−511, −3953) polymorphisms. Environmental data included: documentation of infections within 6 months prior to illness onset; average and highest ultraviolet (UV) index for the month prior to illness onset and prior to diagnosis based on residential location; season of illness onset; and geoclimatic regions and planting zones of residential location at illness onset. Results: HLA‐DRB1*1501 was present more frequently in the M group (22%) compared to the P (5%; OR [95% CI]=5.7 [1.1–29.0]; p=0.04) and CC groups (7%; OR=4.0 [12.4–1.3]; p=0.02). In patients with dermatomyositis only, the F25 peptide binding was present less frequently in the M group (18%) compared to the P (41%; OR = 0.3 [0.1–0.8]; p = 0.02) and CC groups (39%; OR = 0.3 [0.1–0.8]; p = 0.02). The other HLA alleles and peptide binding motifs, immunoglobulin gamma heavy and kappa light chain phenotypes and allotypes, and cytokine polymorphisms (including TNFα‐308) were not associated with disease course. Infections 6 months prior to illness onset were more often present in the P group (40%) compared to the M (18%; OR = 3.0 [1.3–7.2]; p = 0.01) and CC groups (21%; OR = 2.5 [1.2–5.2]; p = 0.01). Three‐quarter of these infections were respiratory. In girls, the average UV index in the month before diagnosis was higher in the P group (median [IQR] = 5.7 [4.0–6.6]) compared to the M group (median [IQR] = 4.3 [1.2–5.6]; p = 0.01). Season of illness onset, geoclimatic regions, and planting zones did not differ among the 3 disease courses. Conclusion: Immunogenetic factors, including HLA alleles, and environmental factors, including a history of preceding infections and the UV index at diagnosis, were significantly associated with disease course in this population of Caucasian patients with JIIM. Future studies are needed to confirm these associated factors and to identify the value of these factors in determining prognosis.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".