Mendelian randomization prioritizes abdominal adiposity as an independent causal factor for liver fat accumulation and cardiometabolic diseases
Bibliographic record
Abstract
Abstract Background Observational studies have linked adiposity and especially abdominal adiposity to liver fat accumulation and non-alcoholic fatty liver disease. These traits are also associated with type 2 diabetes and coronary artery disease but the causal factor(s) underlying these associations remain unexplored. Methods We used a multivariable Mendelian randomization study design to determine whether body mass index and waist circumference were causally associated with non-alcoholic fatty liver disease using publicly available genome-wide association study summary statistics of the UK Biobank ( n = 461,460) and of non-alcoholic fatty liver disease (8434 cases and 770,180 control). A multivariable Mendelian randomization study design was also used to determine the respective causal contributions of waist circumference and liver fat ( n = 32,858) to type 2 diabetes and coronary artery disease. Results Using multivariable Mendelian randomization we show that waist circumference increase non-alcoholic fatty liver disease risk even when accounting for body mass index (odd ratio per 1-standard deviation increase = 2.35 95% CI = 1.31–4.22, p = 4.2e−03), but body mass index does not increase non-alcoholic fatty liver disease risk when accounting for waist circumference (0.86 95% CI = 0.54–1.38, p = 5.4e−01). In multivariable Mendelian randomization analyses accounting for liver fat, waist circumference remains strongly associated with both type 2 diabetes (3.27 95% CI = 2.89–3.69, p = 3.8e−80) and coronary artery disease (1.66 95% CI = 1.54–1.8, p = 3.4e−37). Conclusions These results identify waist circumference as a strong, independent, and causal contributor to non-alcoholic fatty liver disease, type 2 diabetes and coronary artery disease, thereby highlighting the importance of assessing body fat distribution for the prediction and prevention of cardiometabolic diseases.
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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 | 0.044 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".