Loss-of-Function Mutations in <i>ABCA1</i> and Enhanced β-Cell Secretory Capacity in Young Adults
Bibliographic record
Abstract
Loss-of-function mutations affecting the cholesterol transporter ATP-binding cassette transporter subfamily A member 1 (ABCA1) impair cellular cholesterol efflux and are associated with reduced HDL-cholesterol (HDL-C) levels. ABCA1 may also be important in regulating β-cell cholesterol homeostasis and insulin secretion. We sought to determine whether loss-of-function ABCA1 mutations affect β-cell secretory capacity in humans by performing glucose-potentiated arginine tests in three subjects homozygous for ABCA1 mutations (age 25 ± 11 years), eight heterozygous subjects (28 ± 7 years), and eight normal control subjects pair-matched to the heterozygous carriers. To account for any effect of low HDL-C on insulin secretion, we studied nine subjects with isolated low HDL-C with no ABCA1 mutations (age 26 ± 6 years) and nine pair-matched control subjects. Homozygotes for ABCA1 mutations exhibited enhanced oral glucose tolerance and dramatically increased β-cell secretory capacity that was also greater in ABCA1 heterozygous subjects than in control subjects, with no differences in insulin sensitivity. Isolated low HDL-C subjects also demonstrated an increase in β-cell secretory capacity but in contrast to those with ABCA1 mutations, exhibited impaired insulin sensitivity, supporting β-cell compensation for increased insulin demand. These data indicate that loss-of-function mutations in ABCA1 in young adults may be associated with enhanced β-cell secretory capacity and normal insulin sensitivity and support the importance of cellular cholesterol homeostasis in regulating β-cell insulin secretion.
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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 | 0.000 |
| 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) | 0.001 | 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".