Truncation mutations in ABCA1 suppress normal upregulation of full-length ABCA1 by 9-cis-retinoic acid and 22-R-hydroxycholesterol
Bibliographic record
Abstract
Mutations in ABCA1 uniformly decrease plasma HDL-cholesterol (HDL-C) and reduce cholesterol efflux, yet different mutations in ABCA1 result in different phenotypic effects in heterozygotes. For example, truncation mutations result in significantly lower HDL-C and apoliprotein A-I (apoA-I) levels in heterozygotes compared with nontruncation mutations, suggesting that truncation mutations may negatively affect the wild-type allele. To specifically test this hypothesis, we examined ABCA1 protein expression in response to 9-cis-retinoic acid (9-cis-RA) and 22-R-hydroxycholesterol (22-R-OH-Chol) in a collection of human fibroblasts representing eight different mutations and observed that truncation mutations blunted the response to oxysterol stimulation and dominantly suppressed induction of the remaining full-length allele to 5-10% of wild-type levels. mRNA levels between truncation and nontruncation mutations were comparable, suggesting that ABCA1 expression was suppressed at the protein level. Dominant negative activity of truncated ABCA1 was recapitulated in an in vitro model using transfected Cos-7 cells. Our results suggest that the severe reduction of HDL-C in patients with truncation mutations may be at least partly explained by dominant negative suppression of expression and activity of the remaining full-length ABCA1 allele. These data suggest that ABCA1 requires a physical association with itself or other molecules for normal function and has important pharmacogenetic implications for individuals with truncation mutations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".