Idiopathic Pulmonary Fibrosis Is Associated With Type 1 Diabetes: A Two‐Sample Mendelian Randomization Study
Bibliographic record
Abstract
BACKGROUND: The pathogenesis of idiopathic pulmonary fibrosis (IPF) remains unclear; previous studies revealed the underlying connection between IPF and diabetes, but there is no consensual opinion. This study is aimed at examining the association between Type 1 diabetes (T1D) and IPF using Mendelian randomization (MR). METHOD: In our two-sample MR study, we selected single nucleotide polymorphisms (SNPs) that are strongly associated with T1D in a genome-wide association study (GWAS) from IEU (dataset: ebi-a-GCST005536) and obtained their corresponding effect estimates on T1D risk in an IPF GWAS from IEU (dataset: finn-b-IPF). We conducted a multivariable Mendelian randomization (MVMR) analysis to eliminate the interference of aging. RESULT: In the outcome of inverse-variance weighted (IVW) method, T1D showed a promoting effect on IPF (odds ratio (OR): 1.132, p = 0.005). The statistics passed the MR-PRESSO test, and no outliers were observed (global test p = 0.238). MVMR study was performed, and the aging-adjusted result remains almost the same (OR = 1.132, OR_95% CI: 1.034-1.239, p = 0.007). CONCLUSION: Our study shows a causal relation between T1D and IPF; further investigation should be conducted.
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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 | 0.024 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".