DNA Methylation of the MHC Region in Rheumatoid Arthritis: Perspectives and Challenges
Bibliographic record
Abstract
The MHC, which covers a region about 4 Mb at 6p21.3, is one of the most polymorphic regions in the human genome. With a high density of more than 200 genes, most of which are directly involved in the immune response to self or non-self antigens, MHC genes have long been associated with a wide range of complex human diseases, including autoimmune or inflammatory diseases and cancer. Rheumatoid arthritis (RA) is a systemic autoimmune disease; recent investigations in large genome-wide association studies using single-nucleotide polymorphisms have confirmed the correlation of classic HLA genes and non-classic HLA genes with RA in many populations1,2. Functional and structural analyses indicate that these genetic variants reside in the peptide-binding groove, which may affect the binding affinity of the citrullinated peptides, and eventually lead to the development of RA1,3. However, because of the heterogeneity among ethnic groups and clinical subtypes, the major RA-risk allele in MHC is quite different among different populations. For example, HLA-DRB1*04 includes the *04:01 and *04:04 alleles, which are the dominant RA-risk alleles in whites4, whereas DRB1*04:05/*0901 are the major RA-risk alleles in Asians, specifically for RA patients positive for anticitrullinated protein antibodies (ACPA)5,6. A recent … Address correspondence to W. Qiu or Y. Liu, 130 Dong An Road, Shanghai, China. Email: qiuwq{at}fudan.edu.cn; yliu39{at}fudan.edu.cn.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".