Visceral adipose tissue tracks more closely with metabolic dysfunction than intrahepatic triglyceride in lean Asians without diabetes
Bibliographic record
Abstract
Increased visceral adipose tissue (VAT) and intrahepatic triglyceride (IHTG) are important risk factors for the development of type 2 diabetes in subjects with obesity. The relative contribution of these ectopic fat depots to cardiometabolic risk differs between populations, depends on the degree of obesity and the level of cardiorespiratory fitness, and is difficult to dissect because VAT and IHTG typically covary. The aim of this study was to evaluate the effect of an isolated increase in VAT or IHTG on insulin sensitivity and insulin secretion in apparently healthy normal-weight Asian subjects. Total body fat (dual X-ray absorptiometry), VAT and IHTG (magnetic resonance), insulin sensitivity (4-h hyperinsulinemic-euglycemic clamp), beta cell responsivity and insulin secretion rate (3-h mixed meal with mathematical modeling), and cardiorespiratory fitness (maximal oxygen consumption [V̇o2max]) were evaluated in groups of lean subjects with low or high VAT (687 ± 94 vs. 1,279 ± 197 ml, matched for IHTG; n = 13 each) and low or high IHTG (1.7 ± 0.3 vs. 6.7 ± 2.0%, matched for VAT; n = 15 each). All groups were matched for age, sex, total body fat, and V̇o2max. High-VAT subjects had ~25% lower insulin sensitivity, ~20%–40% greater beta cell responsivity and insulin secretion rate, ~35% greater fasting triglyceride concentration, and ~40% lower adiponectin concentration than low-VAT subjects (all P < 0.05). No differences were observed between low-IHTG and high-IHTG subjects. Accumulation of excess fat in the intra-abdominal area is more strongly associated with metabolic dysfunction than accumulation of liver fat in lean Asians without diabetes. NEW & NOTEWORTHY It is not known whether metabolic abnormalities in Asians without obesity track more closely with visceral or liver fat. We found an isolated increase in visceral fat was associated with reduced insulin sensitivity, greater insulin secretion, greater triglyceride, and lower adiponectin concentrations; no differences were observed with an isolated increase in liver fat. These results suggest that visceral fat is a better correlate of metabolic dysfunction than liver fat in Asians without obesity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".