Global mapping of RNA N6-methyladenosine (m6A) in human subcutaneous and visceral adipose tissue reveals novel targets that correlate with clinical variables of obesity
Bibliographic record
Abstract
Abstract Background Obesity is a major health challenge and fat accumulation in visceral depots is more strongly associated with metabolic comorbidities than deposition in subcutaneous depots. Epitranscriptomic regulation of gene expression by N 6 -methyladenosine (m 6 A) influences various aspects of RNA metabolism, however the m 6 A methylome in human adipose tissue and its relationship with fat distribution has not yet been investigated in detail. Methods In this study, we performed epitranscriptomic mapping of m 6 A in intra-individually paired samples of subcutaneous (SAT) and omental visceral adipose tissue (OVAT) from women with normal weight (BMI ≤25, n = 3) and obesity (BMI ≥35, n = 10) using meRIP-seq (discovery cohort). We further investigated differential m 6 A methylation for specific target genes in a larger cohort of individuals with obesity ( n = 72, validation cohort) using meRIP-qPCR. meRIP-seq was performed for primary adipocytes from a subset of the patients ( n = 4) to account for cell type specific differences. Results We here provide the first global map of m 6 A in human adipose tissue in paired samples of SAT and OVAT. We show an overall high overlap in m 6 A sites between individuals and depots, but also distinct depot-specific differences. We identify 339 target genes showing depot-specific m 6 A methylation. Depot-specific methylation was validated for selected sites in SEMA3A , SNAP47 and PPP1R9A in a larger validation cohort. We additionally identify differentially methylated targets between lean individuals and individuals with obesity, including TSC22D1 , FMNL2 and IL1R1 . By combining data from primary adipocytes with data from corresponding bulk adipose tissue, we identified a higher number of genes containing m 6 A in non-adipocyte cells in OVAT compared to SAT. Mechanistically, we show for selected targets that m 6 A affects RNA lifetime in pre-adipocyte cell culture models. Importantly, m 6 A methylation in selected targets correlates with clinically important variables related to obesity, fat distribution and glucose metabolism. Conclusions We identify a catalogue of novel targets showing adipose tissue depot specific m 6 A methylation, with potential as biomarkers in metabolic disease. Our findings underscore the regulatory role of m 6 A in obesity and provide valuable insights for future research. The datasets generated represent a significant resource for further insight in adipose tissue biology and its implications for metabolic health.
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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) | 0.002 | 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".