Integrative Proteogenomic Analyses Provide Novel Interpretations of Type 1 Diabetes Risk Loci Through Circulating Proteins
Bibliographic record
Abstract
Circulating proteins may be promising biomarkers or drug targets. Leveraging genome-wide association studies of type 1 diabetes (18,942 case and 501,638 control individuals of European ancestry) and circulating protein abundances (10,708 European ancestry individuals), Mendelian randomization analyses were conducted to assess the associations between circulating abundances of 1,560 candidate proteins and the risk of type 1 diabetes, followed by multiple sensitivity and colocalization analyses, horizontal pleiotropy examinations, and replications. Bulk tissue and single-cell gene expression enrichment analyses were performed to explore candidate tissues and cell types for prioritized proteins. After validating Mendelian randomization assumptions and colocalization evidence, we found that genetically predicted circulating abundances of CTSH (odds ratio [OR] 1.17 per 1 SD increase; 95% CI 1.10–1.24), IL27RA (OR 1.13; 95% CI 1.07–1.19), SIRPG (OR 1.37; 95% CI 1.26–1.49), and PGM1 (OR 1.66; 95% CI 1.40–1.96) were associated with the risk of type 1 diabetes. These findings were consistently replicated in other cohorts. CTSH, IL27RA, and SIRPG were strongly enriched in immune system-related tissues, while PGM1 was enriched 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 may be explored as biomarkers or drug targets for type 1 diabetes. Article Highlights Identification of circulating proteins that may play a role in the pathogenesis of type 1 diabetes can provide promising targets for biomarker and drug target identification. Supported by multiple lines of evidence, circulating abundances of CTSH, IL27RA, SIRPG, and PGM1 were associated with the risk of type 1 diabetes. Tissues and cell types with enrichment of target protein-coding gene expression were identified. CTSH, IL27RA, SIRPG, and PGM1 may be explored as biomarkers or drug targets for type 1 diabetes.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".