Association of LIPC -250G/A and -514C/T polymorphisms and hypertension: a systematic review and meta-analysis
Bibliographic record
Abstract
Hypertension is the most common chronic disease, and most important risk factor for cardiovascular disease. This meta-analysis aimed to explore the association between hepatic lipase gene (LIPC) gene -250G/A (rs2070895) and -514C/T (rs1800588) polymorphisms and the susceptibility to hypertension. Published studies were searched using the PubMed, Embase and Cochrane Library databases. Newcastle-Ottawa Scale (NOS) was used to assess the quality of the included studies. Sensitivity analysis was performed using “leave one out” method. Egger’s test was used to evaluate the publication bias. The random effect model was used to calculate the pooled effect size if P < 0.05 or I 2 ≥ 50%; otherwise, the fixed effect model was selected. Four eligible studies, including 2599 participants, were enrolled in the included studies from 2007 to 2014. Quality evaluation revealed that each study had high NOS scores ranged from 5 to 7. The LIPC rs1800588 polymorphism was not found to be associated with the susceptibility to hypertension under all genetic models (T vs C, P = 0.38; CT vs CC, P = 0.46; TT vs CC, P = 0.38; TT vs CC + CT, P = 0.54; TT + CT vs CC, P = 0.34). Notably, the frequencies of the AA+GA genotypes of LIPC rs2070895 polymorphism were related to an increased risk of hypertension (AA+GA vs. GG, OR = 1.1954, 95% CI: 1.0001–1.4288, P = 0.05). The LIPC rs2070895 polymorphism was found to be related to an increased risk of hypertension. However, LIPC rs1800588 polymorphism was not associated with the susceptibility to hypertension.
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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.038 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".