Impact of NMT1 Gene Polymorphisms on Features of the Metabolic Syndrome among Severely Obese Patients
Bibliographic record
Abstract
Introduction: N-myristoyltransferase (NMT) is implicated in myristoylation, required for biological activities of several proteins.Its gene N-myristoyltransferase 1 (NMT1) has been found to be overexpressed and hypermethylated in Visceral Adipose Tissue (VAT) of severely obese individuals with Metabolic Syndrome (MetS+) versus without (MetS-).Objective: The aim of this study was to verify the associations between NMT1 gene polymorphisms Single Nucleotide Polymorphisms (SNPs) and metabolic complications among obese subjects.Methods: Associations between SNPs and determinants of MetS were tested with 1752 obese participants undergoing a bariatric surgery.The effect of selected SNPs on methylation, and correlation with expression levels of NMT1 were verified in subgroups.Results: Rs2239921 was significantly associated with systolic (p=0.03) and diastolic (p<0.0001)blood pressures.Rs2239923 was associated with plasma High Density Lipoprotein-Cholesterol or HDL-Cholesterol (HDL-C) levels (p=0.05), while rs2269746 was associated with Low Density Lipoprotein-Cholesterol or LDL-Cholesterol (LDL-C) (p=0.006) and Total-Cholesterol (Total-C) levels (p=0.004).Rs1005136 (p=0.03),rs8066395 (p=0.03) or rs2157840 (p=0.04) were associated with plasma concentrations of C-Reactive Protein (CRP).Phenotype-associated SNPs were associated with NMT1 methylation levels of six CpG sites.NMT1 methylation levels of one CpG site, cg10755730, correlated with gene expression levels (r=0.57;p=0.04).Conclusion: These results suggest that the presence of NMT1 SNPs is associated with altered plasma lipid levels as well as with increased inflammation markers and blood pressure among severely obese patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.003 | 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".