Aberrant CpG Islands’ Hypermethylation of ABCB1 in Mesenchymal Stem Cells of Patients with Steroid-associated Osteonecrosis
Bibliographic record
Abstract
OBJECTIVE: Patients carrying an ABCB1 polymorphism have a higher risk of developing osteonecrosis of the femoral head (ONFH). We investigated whether aberrant dinucleotide CpG islands' hypermethylation of ABCB1 gene existed in mesenchymal stem cells (MSC) of patients with ONFH, which results in cell dysfunction. METHODS: Bone marrow was collected from the proximal femur of patients with glucocorticoid (GC)-associated ONFH (n = 22) and patients with new femoral neck fractures (n = 25). MSC were isolated by density gradient centrifugation. We investigated cell viability, intracellular reactive oxygen species (ROS) level, mitochondrial membrane potential (MMP), the amount of P-glycoprotein (P-gp) and ABCB1 transcripts, and methylation at CpG islands of ABCB1 promoter from both the femoral neck fractures group and the GC-associated ONFH group treated with or without the DNA methyltransferase inhibitor, 5'-Aza-2-deoxycytidine (5'-Aza-dC). RESULTS: We observed that MSC from GC-associated ONFH groups showed reduced proliferation ability, elevated ROS levels, and depressed MMP when compared with the other 2 groups. Low levels of P-gp and ABCB1 transcript, as well as ABCB1 gene hypermethylation, in patients with GC-associated ONFH were also noted. Treatment with 5'-Aza-dC rapidly restored ABCB1 expression. Analysis of general expression revealed that aberrant CpG islands' hypermethylation of ABCB1 caused sensitivity to GC and induced changes in the proliferation and oxidative stress of MSC under GC administration. CONCLUSION: These data suggest that aberrant CpG islands' hypermethylation of ABCB1 gene may be responsible for individual differences in the development of GC-associated ONFH.
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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".