Genome-Wide Microarray Expression Analysis of CD4+ T Cells from Nonobese Diabetic Congenic Mice Identifies <i>Cd55</i> (<i>Daf1</i>) and <i>Acadl</i> as Candidate Genes for Type 1 Diabetes
Bibliographic record
Abstract
NOD.Idd3/5 congenic mice have insulin-dependent diabetes (Idd) regions on chromosomes 1 (Idd5) and 3 (Idd3) derived from the nondiabetic strains B10 and B6, respectively. NOD.Idd3/5 mice are almost completely protected from type 1 diabetes (T1D) but the genes within Idd3 and Idd5 responsible for the disease-altering phenotype have been only partially characterized. To test the hypothesis that candidate Idd genes can be identified by differential gene expression between activated CD4+ T cells from the diabetes-susceptible NOD strain and the diabetes-resistant NOD.Idd3/5 congenic strain, genome-wide microarray expression analysis was performed using an empirical Bayes method. Remarkably, 16 of the 20 most differentially expressed genes were located in the introgressed regions on chromosomes 1 and 3, validating our initial hypothesis. The two genes with the greatest differential RNA expression on chromosome 1 were those encoding decay-accelerating factor (DAF, also known as CD55) and acyl-coenzyme A dehydrogenase, long chain, which are located in the Idd5.4 and Idd5.3 regions, respectively. Neither gene has been implicated previously in the pathogenesis of T1D. In the case of DAF, differential expression of mRNA was extended to the protein level; NOD CD4+ T cells expressed higher levels of cell surface DAF compared with NOD.Idd3/5 CD4+ T cells following activation with anti-CD3 and -CD28. DAF up-regulation was IL-4 dependent and blocked under Th1 conditions. These results validate the approach of using congenic mice together with genome-wide analysis of tissue-specific gene expression to identify novel candidate genes in T1D.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".