Abstract 43: The Hypofunctional GPER P16L Variant is Associated With a Gene Dosage-Related Increase in Plasma LDL Cholesterol
Bibliographic record
Abstract
Introduction: Estrogen deficiency is linked with dyslipidemia, especially in postmenopausal women, through a poorly understood mechanism. GPER is a recently recognized GPCR which is activated by estrogens. However, the role of GPER in mediating estrogen’s effects on lipid metabolism is unknown. We recently identified a common hypofunctional missense variant of GPER, namely P16L (allele frequency ~ 20%). We studied association of this with plasma LDL cholesterol levels. Further, we studied the role of GPER in regulating expression of the LDL receptor. Methods: Our discovery cohort was a genetically isolated population of Northern European descent (n=415), and our validation cohort consisted of 505 normal, healthy subjects 18-56 years of age from London, Ontario. Genomic DNA was extracted from whole blood and genotyped for GPER using a dedicated TaqMan assay. Additionally we examined the role of GPER on the regulation of LDL receptor expression by treatment with the GPER agonist, G1. Results: In the discovery cohort, the GPER P16L genetic variant was associated with a significant gene-dosage related increase in LDL cholesterol (CC [homozygous wild type] =3.18±0.84 (mean+SD); CT [heterozygote] =3.25±0.80; and TT [homozygous variant] =4.25±0.87 mmol/L, p<0.05). Total cholesterol concentrations followed a similar gradient across genotypes. In the validation cohort, the GPER P16L genetic variant was associated with a similar significant gene-dosage related increase in LDL cholesterol (CC =2.16±0.67; CT [heterozygote] =2.29±0.67; TT =2.40±0.84 mmol/L, p<0.05). In HepG2 cells expressing GPER, G1 mediated a concentration-dependent increase in LDL receptor expression. Pre-treating the cells with the GPER antagonist G15 attenuated the effect of G1 on LDL receptor upregulation. Further, downregulation of GPER expression via infection with a shGPER construct also attenuated G1's effect on LDL receptor upregulation. Conclusion: GPER activation upregulates LDL receptor expression. Further, carrying the hypofunctional P16L genetic variant of GPER, increases plasma LDL cholesterol in humans. In aggregate these data suggest an important role of GPER in regulation of LDL receptor expression and consequently LDL metabolism.
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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) | 0.001 | 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) | 0.007 | 0.001 |
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".