A271 EFFECT OF ANTI-TNF AGENTS ON DNA METHYLATION IN PERIPHERAL BLOOD OF PATIENTS WITH INFLAMMATORY BOWEL DISEASE
Bibliographic record
Abstract
Abstract Background Despite the success and ongoing use of tumor necrosis factor inhibitors (TNFi) in the treatment of inflammatory bowel disease (IBD), there are no predictors of response to therapy. While much research has gone into understanding genetic risks for IBD, less work has been done exploring epigenetic associations with treatment. Hence, we wondered whether epigenetic changes were associated with failure of TNFi in IBD. Aims Describe the association of TNFi response with DNA methylation in patients with IBD. Methods Participants ≥18 years with IBD (N=169) were selected from the Inflammation, Microbiome, and Alimentation: Gastro-Intestinal and Neuropsychiatric Effects (IMAGINE) Strategy for Patient Oriented Research (SPOR) Network. At enrollment participants completed a questionnaire that included their disease diagnosis, therapy, smoking history, and disease activity using the validated IBD Symptom Inventory (IBDSI). Patients provided whole blood samples that were processed for and run on Illumina DNA methylation arrays. Results The 169 patients were in three treatment groups: TNFi naïve (N=98, never exposed to an anti-TNF agent), TNFi responder (N=32, inactive disease on anti-TNF agent), and TNFi nonresponder (N=39, active disease not on any biologic at time of enrollment). The mean symptom score (SIBDSI) was different across the three groups (pampersand:003C0.001): TNFi nonresponders having a higher SIBDSI (24 ± 6.1) than the TNFi naïve (9.1 ± 5.5) or responder (8.3 ± 4.3) treatment groups. Relative proportions of leukocyte populations were estimated using DNA methylation. CD4 and CD8 T cell and B cell counts were higher (pampersand:003C0.05) in the nonresponders and responders versus TNFi naïve group. Neutrophil counts were lower (pampersand:003C0.05) in the TNFi nonresponders and responders compared to the TNFi naïve group (Figure 1). There was a trend towards increased epigenetic estimates of age acceleration (pampersand:003E0.05) in nonresponders versus responders and TNFi naïve patients, likely driven by disease activity (data not shown). Epigenome-wide analysis of the three groups revealed 16 CpGs for responder versus naïve (e.g. CDK5 regulatory subunit-associated protein 1-like 1 (CDKAL1), and two CpGs for nonresponders versus responders (Table 1). This includes a CpG for guanine nucleotide-binding protein subunit gamma-2 (GNG2) that was shared between the two comparisons. Conclusions Exposure to TNFi is associated with changes in peripheral leukocyte populations independent of response to treatment, indicating a TNFi effect. This implies that anti-TNF treatment is having some effect on patients even if there is clinical nonresponse. Differentially expressed CpGs implicates possible markers of response to treatment, particularly CDKAL1, a gene that has been associated with TNFi response in psoriasis. Funding Agencies Guts and Roses Charity
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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 | 0.001 |
| 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) | 0.003 | 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".