Genetic Defects in Human Pericentrin Are Associated With Severe Insulin Resistance and Diabetes
Bibliographic record
Abstract
OBJECTIVE: Genetic defects in human pericentrin (PCNT), encoding the centrosomal protein pericentrin, cause a form of osteodysplastic primordial dwarfism that is sometimes reported to be associated with diabetes. We thus set out to determine the prevalence of diabetes and insulin resistance among patients with PCNT defects and examined the effects of pericentrin depletion on insulin action using 3T3-L1 adipocytes as a model system. RESEARCH DESIGN AND METHODS: A cross-sectional metabolic assessment of 21 patients with PCNT mutations was undertaken. Pericentrin expression in human tissues was profiled using quantitative real-time PCR. The effect of pericentrin knockdown on insulin action and adipogenesis in 3T3-L1 adipocytes was determined using Oil red O staining, gene-expression analysis, immunoblotting, and glucose uptake assays. Pericentrin expression and localization also was determined in skeletal muscle. RESULTS: Of 21 patients with genetic defects in PCNT, 18 had insulin resistance, which was severe in the majority of subjects. Ten subjects had confirmed diabetes (mean age of onset 15 years [range 5-28]), and 13 had metabolic dyslipidemia. All patients without insulin resistance were younger than 4 years old. Knockdown of pericentrin in adipocytes had no effect on proximal insulin signaling but produced a twofold impairment in insulin-stimulated glucose uptake, approximately commensurate with an associated defect in cell proliferation and adipogenesis. Pericentrin was highly expressed in human skeletal muscle, where it showed a perinuclear distribution. CONCLUSIONS: Severe insulin resistance and premature diabetes are common features of PCNT deficiency but are not congenital. Partial failure of adipocyte differentiation may contribute to this, but pericentrin deficiency does not impair proximal insulin action in adipocytes.
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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) | 0.001 | 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".