Cell lineage-specific genome-wide DNA methylation analysis of patients with paediatric-onset systemic lupus erythematosus
Bibliographic record
Abstract
Patients with paediatric-onset systemic lupus erythematosus (SLE) often present with more severe clinical courses than adult-onset patients. Although genome-wide DNA methylation (DNAm) profiling has been performed in adult-onset SLE patients, parallel data on paediatric-onset SLE are not available. Therefore, we undertook a genome-wide DNAm study in paediatric-onset SLE patients across multiple blood cell lineages. The DNAm profiles of four purified immune cell lineages (CD4 + T cells, CD8 + T cells, B cells and neutrophils) and whole blood were compared in 16 Chinese patients with paediatric-onset SLE and 13 healthy controls using the Illumina HumanMethylationEPIC BeadChip. Comparison of DNAm in whole blood and within each independent cell lineage identified a consistent pattern of loss of DNAm at 21 CpG sites overlapping 15 genes, which represented a robust, disease-specific DNAm signature for paediatric-onset SLE in our cohort. In addition, cell lineage-specific changes, involving both loss and gain of DNAm, were observed in both novel genes and genes with well-described roles in SLE pathogenesis. This study also highlights the importance of studying DNAm changes in different immune cell lineages rather than only whole blood, since cell type-specific DNAm changes facilitated the elucidation of the cell type-specific molecular pathophysiology of SLE.
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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 | 0.001 | 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".