Functional characterization of a promoter polymorphism that drives ACSL5 gene expression in skeletal muscle and associates with diet‐induced weight loss
Bibliographic record
Abstract
Diet-induced weight loss is affected by a wide range of factors, including genetic variation. Identifying functional polymorphisms will help to elucidate mechanisms that account for variation in dietary metabolism. Previously, we reported a strong association between a common single nucleotide polymorphism (SNP) rs2419621 (C>T) in the promoter of acyl-CoA synthetase long chain 5 (ACSL5), rapid weight loss in obese Caucasian females, and elevated ACSL5 mRNA levels in skeletal muscle biopsies. Here, we showed by electrophoretic mobility shift assay (EMSA) that the T allele creates a functional cis-regulatory E-box element (CANNTG) that is recognized by the myogenic regulatory factor MyoD. The T allele promoted MyoD-dependent activation of a 1089-base pair ACSL5 promoter fragment in nonmuscle CV1 cells. Differentiation of skeletal myoblasts significantly elevated expression of the ACSL5 promoter. The T allele sustained promoter activity 48 h after differentiation, whereas the C allele showed a significant decline. These results reveal a mechanism for elevated transcription of ACSL5 in skeletal muscle of carriers of the rs2419621(T) allele, associated with more rapid diet-induced weight loss. Natural selection favoring promoter polymorphisms that reduced expression of catabolic genes in skeletal muscle likely accounts for the resistance of obese individuals to dietary intervention.
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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".