GALNT2 rs4846914 SNP Is Associated with Obesity, Atherogenic Lipid Traits, and ANGPTL3 Plasma Level
Bibliographic record
Abstract
N-Acetylgalactosaminyltransferase 2 (GALNT2) is associated with serum lipid levels, insulin resistance, and adipogenesis. Additionally, angiopoietin-like (ANGPTL) proteins have emerged as regulators of lipoprotein lipase and lipid metabolism. In this study, we evaluated the association between GALNT2 rs4846914 variant, known for its association with lipid levels in European cohorts, with plasma levels of ANGPTL proteins, apolipoproteins, lipids, and obesity traits in individuals of Arab ethnicity. GALNT2 rs4846914 was genotyped in a cohort of 278 Arab individuals from Kuwait. Plasma levels of ANGPTL3 and ANGPTL8 were measured by ELISA and apolipoproteins by Luminex multiplexing assay. Allele-based association tests were performed with Bonferroni-corrected p-value thresholds. The GALNT2 rs4846914_G allele was associated with increased ANGPTL3 (p-values ≤ 0.05) but not with ANGPTL8 plasma levels. The allele was associated significantly with higher BMI and weight (p-values < 0.003), increased ApoC1 levels (p-values ≤ 0.006), and reduced HDL levels (p-values ≤ 0.05). Individuals carrying the GG genotype showed significantly decreased HDL and increased BMI, WC, ApoC1, and TG. Interactions exist between (AG+GG) genotypes and measures of percentage body fat, ApoA1A, ApoC1, and ApoB48-mediated HDL levels. GALNT2 is confirmed further as a potential link connecting lipid metabolism and obesity and has the potential to be a drug target for treating obesity and dyslipidemia.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".