Association of <i>LIPA</i> Gene Polymorphisms With Obesity‐Related Metabolic Complications Among Severely Obese Patients
Bibliographic record
Abstract
The lipase A, lysosomal acid, cholesterol esterase enzyme (LIPA) is involved in the hydrolysis of triglycerides (TGs) and cholesteryl esters (CEs) delivered to lysosomes. LIPA deficiency in human causes two distinct phenotypes characterized by intracellular storage of CE and derangements in the control of cholesterol production, namely the Wolman disease (WD) and the CE storage disease (CESD). To test the potential association of LIPA gene polymorphisms with obesity-related metabolic complications, promoter, exons, and intronic flanking regions of the LIPA gene were first sequenced in 25 individuals. From the 14 common polymorphisms identified, 12 tagging single-nucleotide polymorphisms (tSNPs) were genotyped in a cohort of 1,751 obese individuals. After adjustments for the effect of age, sex, diabetes, and medication, the C allele of SNP rs1051338 was associated with lower blood pressure (BP; systolic (SBP) P = 0.004; diastolic (DBP) P = 0.006). Three of the tested SNPs were associated with modifications of the plasma lipid profile. The G/G genotype of rs2071509 was associated with higher high-density lipoprotein cholesterol (HDL-C) levels (P = 0.009) and minor allele of rs1131706 was also associated with higher HDL-C (P = 0.004) and an association between rs3802656 and total cholesterol (total-C)/HDL-C ratio was identified (P = 0.04). These results thus suggest that LIPA polymorphisms contribute to the interindividual variability observed in obesity-related metabolic complications.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".