Premature Atherosclerosis Associated With Monogenic Insulin Resistance
Bibliographic record
Abstract
BACKGROUND: The common insulin resistance syndrome, with obesity, dyslipidemia, hyperglycemia, and hypertension, is associated with increased risk of atherosclerosis. Early atherosclerosis in rare monogenic forms of insulin resistance, however, has not been extensively documented. Cardiovascular end points were thus evaluated in subjects with Dunnigan-type familial partial lipodystrophy (FPLD) due to mutations at LMNA codon 482. METHODS AND RESULTS: FPLD subjects >/=35 years old were stratified by genotype for either the LMNA R482Q or R482W mutation. Twenty-three subjects were heterozygous mutation carriers, and 17 were R482/R482 homozygous family control subjects. All LMNA mutation carriers had FPLD with insulin resistance. In addition, LMNA mutation carriers had significantly more type 2 diabetes, hypertension, and dyslipidemia than normal family control subjects. Eight LMNA mutation carriers had coronary heart disease (CHD), compared with 1 normal control subject (OR 5.9, 95% CI 1.2 to 30.2). Six LMNA mutation carriers had CHD end points before age 55 years, and 4 of these, all women, had been hospitalized for CABG surgery between the ages of 35 and 54 years. CONCLUSIONS: Rare LMNA mutations that underlie FPLD with insulin resistance and hyperinsulinemia are also associated with early CHD, notably in women. This suggests that abnormalities of the nuclear envelope can result in a phenotype that recapitulates most of the important attributes of the common insulin resistance syndrome, including accelerated cardiovascular disease. FPLD thus appears to be an appropriate human monogenic model for the common insulin resistance syndrome.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".