Abstract 402: Adiponectin Receptor 3 is Associated With Endothelial Nitric Oxide Synthase Dysfunction and Predicts Insulin Resistance in South Asians
Bibliographic record
Abstract
Type 2 diabetes (T2DM) is a global epidemic affecting over 400 million people and causes significant morbidity and mortality. T2DM has a strong association with cardiovascular disease (CVD), the number one cause of death globally with 17.5 million deaths per year. A precursor of T2DM, insulin resistance is central to the development of T2DM and is a risk factor for CVD. Insulin resistance is difficult to diagnose and individuals are often untreated prior to the onset of T2DM or CVD. South Asians are more likely to have insulin resistance, diabetes and cardiovascular disease when compared to age matched European cohorts. The molecular mechanisms of why South Asians are predisposed to insulin resistance and consequently cardiovascular disease were investigated using induced pluripotent stem cells (iPSCs) derived endothelial cells (iPSC-EC). Endothelial cells line blood vessels of the cardiovascular system. Unlike previous models, iPSC-EC are unique because they contain the individual's genetic information and the environmental influences retained in epigenetic marks are removed via reprogramming and differentiation. iPSC-ECs from insulin resistant South Asians show evidence of impaired insulin signaling as evidenced by decreased Akt phosphorylation, and paradoxically overexpression of eNOS and adiponectin receptor 3. In the cellular milieu of prediabetes, insulin resistance iPSC-ECs show impaired tubule formation and nitric oxide release. When adiponectin receptor 3 expression is suppressed using siRNA, eNOS expression decreases and expression of components of the insulin signaling cascade are improved to levels observed in control iPSC-ECs. Multiple linear regression modeling of clinical characteristics and gene and cellular phenotype was used to develop a scoring system that predicts a patient’s risk of developing insulin resistance and hence subsequently diabetes and cardiovascular complications. To our knowledge, this is the first iPSC-derived endothelial cell risk calculator with the potential to identify South Asian patients at risk for developing insulin resistance and cardiovascular disease before disease onset, which would allow for the early implementation of interventions that prevent morbidity and mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".