LMNA R482Q Mutation in Partial Lipodystrophy Associated with Reduced Plasma Leptin Concentration*
Bibliographic record
Abstract
Mutations in LMNA, which encodes lamins A and C, have been found in patients with autosomal dominant Dunnigan-type familial partial lipodystrophy (FPLD). We analyzed the relationship between plasma leptin and the rare LMNA R482Q mutation in 23 adult FPLD subjects compared with 25 adult family controls with normal LMNA in an extended Canadian FPLD kindred. We found that the LMNA Q482/R482 genotype was a significant determinant of plasma leptin, the ratio of plasma leptin to body mass index (BMI), plasma insulin, and plasma C peptide (P= 0.015, P = 0.0007, P = 0.0004, and P < 0.0001, respectively), but not BMI (P = 0.67). Family members who were heterozygous for LMNA Q482/R482 had significantly lower plasma leptin and leptin:BMI ratio than unaffected R482/R482 homozygotes. Fasting plasma concentrations of insulin and C peptide were both significantly higher in LMNA Q482/R482 heterozygotes than in R482/R482 homozygotes. Multivariate regression analysis revealed that the LMNA R482Q genotype accounted for 40.9%, 48.2%, 86.9%, and 81.0%, respectively, of the attributable variation in log leptin, leptin:BMI ratio, log insulin, and log C peptide (P = 0.013, P = 0.0007, P = 0.0002 and P < 0.0001, respectively). The results indicate that a rare FPLD mutation in LMNA determines the plasma leptin concentration. It remains to be established whether the reduction in leptin results from the reduced adipose tissue mass in FPLD or from another subcellular effect of mutant LMNA. It also remains to be established whether the insulin resistance in FPLD is a consequence of the reduced plasma leptin or of another functional change resulting from mutant LMNA.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".