Body Fat Distribution, Fasting Insulin Levels, and Insulin Secretion: A Bidirectional Mendelian Randomization Study
Bibliographic record
Abstract
CONTEXT: Hyperinsulinemia and adiposity are associated with one another, but the directionality of this relation is debated. OBJECTIVE: Here, we tested the direction of the causal effects of fasting insulin (FI) levels and body fat accumulation/distribution using 2-sample bidirectional Mendelian randomization (MR). METHODS: We included summary statistics from large-scale genome-wide association studies for body mass index (BMI, n = 806 834), waist to hip ratio adjusted for BMI (WHRadjBMI, n = 694 649), abdominal subcutaneous, visceral and gluteofemoral adipose tissue (n = 38 965), FI levels (n = 98 210), pancreatic islets gene expression (n = 420), and hypothalamus gene expression (n = 155). We used inverse variance-weighted and robust MR methods that relied on statistically and biologically driven genetic instruments. RESULTS: Both BMI and WHRadjBMI were positively associated with FI. Results were consistent across all robust MR methods and when variants mapped to the hypothalamus (presumably associated with food behavior) were included. In multivariable MR analyses, when waist circumference and BMI were mutually adjusted, the direct effect of waist circumference on FI was 2.43 times larger than the effect of BMI on FI. FI was not associated with adiposity. By contrast, using genetic instruments mapped to gene expression in pancreatic islets (presumably more specific to insulin secretion), insulin was positively associated with BMI and abdominal subcutaneous and gluteofemoral adipose tissue, but not with visceral adipose tissue. CONCLUSION: Although these results will need to be supported by experimental investigations, results of this MR study suggest that abdominal adiposity may be a key determinant of circulating insulin levels. Alternatively, insulin secretion may promote peripheral adipose tissue accumulation.
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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 | 0.047 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".