Novel Genetic Locus of Visceral Fat and Systemic Inflammation
Bibliographic record
Abstract
CONTEXT: Visceral fat (VF), more than fat elsewhere in the body [mostly subcutaneous fat (SF)], promotes systemic inflammation and related disease. The mechanisms of preferentially visceral accumulation of body fat are largely unknown. OBJECTIVE: To identify genetic loci and mechanistic pathways of preferential accumulation of VF and associated low-grade systemic inflammation. DESIGN: Genome-wide association study (GWAS). SETTING AND PARTICIPANTS: Population-based cohort of 1586 adolescents (aged 12 to 19 years) and adults (aged 36 to 65 years). MAIN OUTCOME MEASURES: Abdominal VF and SF were measured with MRI, total body fat (TBF) was assessed with bioimpedance, and low-grade systemic inflammation was examined by serum C-reactive protein (CRP) measurement. RESULTS: This GWAS of preferential accumulation of VF identified a significant locus on chromosome 6 at rs803522 (P = 1.1 × 10-9 or 4.3 × 10-10 for VF adjusted for SF or TBF, respectively). The major allele was associated with more VF; the association was similar in adolescents and adults. The allele was also associated with higher CRP level, but this association was stronger in adults than adolescents (P for interaction = 4.5 × 10-3). In adults, VF was a significant mediator (P = 1.9× 10-4) in the association between the locus and CRP, explaining 30% of the mediation. The locus was near ATG5, encoding an autophagy molecule reported to modulate adipocyte size and macrophage polarization. CONCLUSION: A genetic locus near ATG5 regulates preferential accumulation of VF (vs SF) in youth and adulthood and contributes to the development of systemic inflammation in adulthood.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".