135-OR: Mapping Cis-Regulatory Programs Affecting Diabetes Risk in Pancreatic Islet Cell Types Using Single-Cell Multimodal Profiling
Bibliographic record
Abstract
Genetic variants influencing type 1 diabetes (T1D) risk identified by genome-wide association studies (GWAS) are primarily non-coding and affect cis-regulatory element (cRE) activity in specific cell types. A more detailed understanding of cell type-specific cis-regulatory programs in the pancreas is therefore crucial for deciphering the functional impact of T1D risk. Recently developed assays that generate multimodal single nucleus RNA-seq (snRNA-seq) and ATAC-seq (snATAC-seq) profiles from the same cell enable high-resolution mapping of cis-regulatory programs in specific cell types. We generated deeply sequenced data from 28 nondiabetic pancreatic islet samples from the Alberta Diabetes Institute IsletCore using 10x multiome assays. After extensive quality control and filtering, we clustered multimodal profiles from 174,819 cells and identified ten major cell types. For several cell types we identified evidence of heterogeneous sub-populations; for example, in beta cells there were six sub-populations corresponding to cellular states associated with insulin secretion, stress response, and others. We identified 263,223 cREs across all cell types and developed a novel method to predict target genes of cREs based on the correlation of multimodal profiles across single cells. In beta cells, there were 122,352 cRE-target gene links involving 16,907 unique genes. We mapped chromatin accessibility quantitative trait loci (caQTLs) for cREs in each cell type and identified a total of 14,535 caQTLs at FDR<.10. Finally, we annotated T1D risk variants from high-resolution fine-mapping of 136 T1D signals with cRE-target gene links and caQTLs. At 27 T1D signals including at the INS, MAPT, and DLK1 loci, variants affecting chromatin accessibility were linked to putative target genes in beta cells suggesting mechanisms of action at these loci. Experimental follow up of variant activity at these loci using genome editing in beta cell lines is ongoing. Disclosure H. Mummey: None. W. Elison: None. K. Korgaonkar: None. Y.S. Lee: None. J.M. Newsome Ashmus: None. P. Benaglio: Employee; Shoreline Biosciences. M.T. Miller: None. J.E. Manning Fox: None. A.L. Gloyn: Other Relationship; Genentech, Inc., Roche Pharmaceuticals. P. MacDonald: None. S. Preissl: None. K.J. Gaulton: Stock/Shareholder; Neurocrine Biosciences, Inc. Consultant; Genentech, Inc. Stock/Shareholder; Vertex Pharmaceuticals Incorporated. Funding National Institutes of Health (HG012059, DK105554, DK122607, DK114650)
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 | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".