Fat Infiltration in Muscle: New Evidence for Familial Clustering and Associations With Diabetes
Bibliographic record
Abstract
OBJECTIVE: Increased fat infiltration in skeletal muscle has been associated with diabetes. Quantitative computed tomography (QCT) can be used to measure muscle density, which reflects the lipid content of skeletal muscle such that greater fat infiltration in skeletal muscle is associated with lower muscle density. The relative contribution of genetic and environmental factors to fat infiltration in skeletal muscle has not been assessed. Therefore, our aim is to determine genetic and environmental contributions to measures of skeletal muscle composition, and describe their associations with type 2 diabetes in multigenerational families of African ancestry. METHODS AND PROCEDURES: Peripheral QCT (pQCT) measures of skeletal muscle density were obtained for the calf in 471 individuals (60% women; mean 43 years) belonging to eight large, multigenerational Afro-Caribbean families (mean family size 51 individuals; 3,535 relative pairs). RESULTS: The proportion of variance in muscle density due to additive genetic effects (residual heritability) was 35.0% (P < 0.001) and significant covariates (age, gender, BMI, and parity) explained 55.0% of the total phenotypic variation in muscle density. Muscle density was lower (P < 0.001) in 62 diabetics (69.5 mg/cm(3)) than in 339 nondiabetics (74.3 mg/cm(3)) and remained significant after adjusting for age, gender, and BMI (P = 0.005) or age, gender, and waist circumference (P = 0.01). DISCUSSION: Our results provide new evidence that ectopic lipid deposition in skeletal muscle is a heritable trait and is associated with diabetes, independent of overall and central obesity in families of African heritage. Genome-wide screens and candidate gene studies are warranted to identify the genetic factors contributing to ectopic deposition of skeletal muscle fat.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".