Integrative proteogenomic analyses provide novel interpretations of type 1 diabetes risk loci through circulating proteins
Bibliographic record
Abstract
Abstract Type 1 diabetes (T1D) requires new preventive measures and interventions. Circulating proteins are promising biomarkers and drug targets. Leveraging genome-wide association studies (GWASs) of T1D (18,942 cases and 501,638 controls) and circulating protein abundances (10,708 individuals), the associations between 1,565 circulating proteins and T1D risk were assessed through Mendelian randomization, followed by multiple sensitivity and colocalization analyses, examinations of horizontal pleiotropy, and replications. Genetically increased circulating abundances of CTSH, IL27RA, SIRPG, and PGM1 were associated with an increased risk of T1D, consistently replicated in other cohorts. Bulk tissue and single-cell gene expression profiles revealed strong enrichment of CTSH, IL27RA , and SIRPG in immune system-related tissues, and PGM1 in muscle and liver tissues. Among immune cells, CTSH was enriched in B cells and myeloid cells, while SIRPG was enriched in T cells and natural killer cells. These proteins warrant exploration as T1D biomarkers or drug targets in relevant tissues.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".