Adipocyte Expression of SLC19A1 Links DNA Hypermethylation to Adipose Tissue Inflammation and Insulin Resistance
Bibliographic record
Abstract
Context: Insulin resistance (IR) is promoted by a chronic low-grade inflammation in white adipose tissue (WAT). The latter might be regulated through epigenetic mechanisms such as DNA methylation. The one carbon cycle (1CC) is a central metabolic process governing DNA methylation. Objective: To identify adipocyte-expressed 1CC genes linked to WAT inflammation, IR, and their causal role. Design: Cohort study. Setting: Outpatient academic clinic. Participants: Obese and nonobese subjects. Methods: Gene expression and DNA methylation arrays were performed in subcutaneous WAT and isolated adipocytes. In in vitro differentiated human adipocytes, gene knockdown was achieved by small interfering RNA, and analyses included microarray, quantitative polymerase chain reaction, DNA methylation by enzyme-linked immunosorbent assay and pyrosequencing, protein secretion by enzyme-linked immunosorbent assay, targeted metabolomics, and luciferase reporter and thermal shift assays. Main Outcome Measures: Effects on adipocyte inflammation. Results: In adipocytes from obese individuals, global DNA hypermethylation was associated positively with gene expression of proinflammatory pathways. Among the 1CC genes, IR in vivo and proinflammatory gene expression in WAT were most strongly and inversely associated with SLC19A1, a gene encoding a membrane folate carrier. SLC19A1 knockdown in human adipocytes perturbed intracellular 1CC metabolism, induced global DNA hypermethylation, and increased expression of proinflammatory genes. Several CpG loci linked SLC19A1 to inflammation; validation studies were focused on the chemokine C-C motif chemokine ligand 2 (CCL2) in which methylation in the promoter (cg12698626) regulated CCL2 expression and CCL2 secretion through altered transcriptional activity. Conclusions: Reduced SLC19A1 expression in human adipocytes induces DNA hypermethylation, resulting in increased expression of specific proinflammatory genes, including CCL2. This constitutes an epigenetic mechanism that might link dysfunctional adipocytes to WAT inflammation and IR.
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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".