Assessment of genetic polymorphism associated with ATP-binding cassette transporter A1 (ABCA1) gene and fluctuations in serum lipid profile levels in patients with coronary artery disease
Bibliographic record
Abstract
BACKGROUND: Coronary artery disease (CAD) is one of the common genetic and clinical risk factors associated with cardiovascular and multifactorial disorder. ATP-binding cassette transporter A1 (ABCA1) gene plays an important role in lipid metabolism and in multiple studies associated with CAD. However, more studies are needed to identify the exact role of single nucleotide polymorphisms which may cause CAD. OBJECTIVES: gene with CAD patients in the Saudi population. METHODS: We included 315 confirmed CAD cases, and 205 non-CAD or control subjects in this case-control study. DNA isolation was carried out for all registered participants and the polymorphism g.1051G > A was genotyped with Polymerase Chain Reaction followed by Restriction Fragment Length Polymorphism analysis with EcoNI restriction enzyme. RESULTS: Modifiable risk factors such as Body Mass Index, smoking and diabetes were strongly associated and non-modifiable risk factors such as hypertension (Systolic Blood Pressure and Diastolic Blood Pressure) and serum analysis such as Fasting Blood Glucose, Total cholesterol (TC), Triglyceride (TG) and LDL-c were significantly associated in CAD cases (p < 0.05). Allele (OR-1.73;95% CI:1.33-2.26; p = 0.0004), GA vs GG (OR-2.26; 95% CI: 1.53-3.35; p = 0.0003 and dominant inheritance pattern (OR-2.23; 95% CI:1.56-3.20; p = 0.00009 was strongly associated with CAD cases and control subjects. The frequency level of use of atorvastatin was significantly different among GG, GA and AA subjects. Additionally, TC and TG levels were influenced by the presence of g.1051G > A polymorphism. CONCLUSION: is closely associated with the existence of the CAD subjects. This polymorphism could also affect the serum levels of the lipid profile, suggesting a possible occurrence of CAD in the Saudi population.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".