CpG methylation in the TGFB1 and IL-6 gene promoters serve as surrogate biomarkers for diagnosis of IBD in children
Bibliographic record
Abstract
Abstract Crohn’s disease (CD) and ulcerative colitis (UC) are recurrent, chronic forms of inflammatory bowel diseases (IBD), the diagnosis of which can entail long delays. The delays can lead to disease presentation with complications and high morbidity. Therefore, better diagnostic markers for IBD are required. We investigated whether methylation marks in the TGFB1 and IL-6 gene promoters could be of diagnostic utility in IBD. To this end, we conducted a case-control study using peripheral blood DNA samples from 67 CD and 37 UC pediatric patients, and from 43 age-matched healthy controls. The patients were recruited from three pediatric gastroenterology clinics across Canada. The DNA samples were processed to identify methylation sites (CpG) across the promoter regions of the TGFB1 and IL-6 genes using the Sequenom technology. After implementing quality control measures, and initial non-parametric univariate (Man-Whitney U test) analyses, multivariate logistic regression analyses was carried out to identify models with the best fit (Akaike Information Criteria) and the greatest discriminatory capabilities (Area Under the Receiver Operating Curve). Logistic regression analysis showed that a model comprising 14 TGFB1 CpG sites had high discriminatory ability to separate CD from controls (AUC=0.94). Similarly, a logistic model comprising 9 CpG sites in the TGFB1 gene had near perfect ability to discriminate between UC and controls (AUC=0.99). A logistic model comprising three CpG sites in the TGFB1 gene had moderate ability (AUC=0.81) to discriminate between CD and UC. In conclusion, CpG methylation in the TGFB1 gene promoter has high discriminative power for identifying CD and UC, and could serve as an important diagnostic markers.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".