A new hypothesis for type 1 diabetes risk: The at-risk allele at rs3842753 associates with increased beta cell <i>INS</i> mRNA in a meta-analysis of single cell RNA sequencing data
Bibliographic record
Abstract
ABSTRACT Type 1 diabetes is characterized by the autoimmune destruction of insulin secreting β cells. Genetic variations upstream at the insulin ( INS ) locus contribute to ~10% of type 1 diabetes heritable risk. Multiple studies showed an association between rs3842753 C/C genotype and type 1 diabetes susceptibility, but the molecular mechanisms remain unclear. To date, no large-scale studies have looked at the effect of genetic variation at rs3842753 on INS mRNA at the single cell level. We aligned all human islet single cell RNA sequencing datasets available to us in 2020 to the reference genome GRCh38.98 and genotyped rs3842753, integrating 2315 β cells and 1223 β-like cells from 13 A/A protected donors, 23 A/C heterozygous donors, and 35 C/C at-risk donors, including adults without diabetes and with type 2 diabetes. INS expression mean and variance were significantly higher in single β cells from females compared with males. Comparing across β cells and β-like cells, we found that rs3842753 C containing cells (either homozygous or heterozygous) had the highest INS expression. We also found that β cells with the rs3842753 C allele had significantly higher ER stress marker gene expression compared to the A/A homozygous genotype. These findings support the emerging concept that inherited risk of type 1 diabetes may be associated with inborn, persistent elevated insulin production which may lead to β cell ER stress and fragility.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.008 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".