Multi-omics analysis in primary T cells elucidates mechanisms behind disease associated genetic loci
Bibliographic record
Abstract
ABSTRACT In this study, we present the most extensive dataset of chromatin conformation data with matching gene expression and chromatin accessibility from primary T cells to date. We use this data to enhance our understanding of the different mechanisms by which GWAS variants impact gene regulation and revealing how natural genetic variation alter chromatin accessibility and structure in primary cells at an unprecedented scale. Capitalizing on this vast dataset, we refine the mapping of GWAS loci to implicated regulatory elements, such as CTCF binding sites and other enhancer elements, aiding gene assignment. Importantly, we uncover BCL2L11 as the probable causal gene within the RA locus rs13396472, despite the GWAS variants’ intronic positioning relative to ACOXL and we identify mechanisms involving SESN3 dysregulation in the RA locus rs4409785. Given these genes’ significant role in T cell development and maturation, our work is vital for deepening our comprehension of autoimmune disease pathogenesis and suggesting potential treatment targets.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.004 | 0.002 |
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".