Increased Risk of Autoimmune Disease in Families with Wegener’s Granulomatosis
Bibliographic record
Abstract
OBJECTIVE: The etiology of Wegener's granulomatosis (WG) is unknown. Susceptibility genes for WG that also affect the risks of other autoimmune/inflammatory diseases have been identified, indicating the existence of shared interdisease genetic susceptibilities. To determine the effect, on a population level, of shared susceptibility on disease risk, we assessed the occurrence of autoimmune/inflammatory disease in first-degree relatives of patients with WG. METHODS: In the Swedish Hospital Discharge Register we identified 2288 individuals discharged with the diagnosis of WG between 1970 and 2003. Through linkage to the Swedish Multi-generation Register we identified 787 parents, 1212 siblings, and 3650 children of these patients. From the Register of Total Population we identified 10 controls for each patient with WG, and 65,000 of their first-degree relatives. Through linkage to the nationwide Outpatients Register, we identified autoimmune/inflammatory disease among all relatives. Relative risks were estimated as hazard ratio (HR) using Cox regression. The study period was 2001-2006. RESULTS: Biological first-degree relatives of patients with WG were at a moderately increased risk of any autoimmune/inflammatory disease (HR 1.32, 95% CI 1.18-1.49), including specific associations with, for example, multiple sclerosis (HR 1.92, 95% CI 1.16-3.16), Sjögren's syndrome (HR 2.00, 95% CI 1.07-3.73), and seropositive rheumatoid arthritis (HR 1.54, 95% CI 1.09-2.19). CONCLUSION: Relatives of patients with WG are at increased risk of being diagnosed with other autoimmune/inflammatory diseases, indicating shared susceptibility between WG and other auto-immune/inflammatory disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".