Meta-analysis on correlation between genetic polymorphism of ApoE and late onset Alzheimer's disease in Chinese population
Bibliographic record
Abstract
Objective To systematically review the correlation between genetic polymorphism of apolipoprotein E (ApoE) and late onset Alzheimer's disease (LOAD) in Chinese population. Methods Taking "ApoE, late onset Alzheimer's disease, polymorphism, China and Chinese" as retrieval words, databases of PubMed, EMBASE/SCOPUS, EBSCO-CINAHL, Cochrane Library, China Biology Medicine (CBM), China National Knowledge Infrastructure (CNKI) and Wanfang Data were retrieved with computer for collecting case-control studies about the correlation between genetic polymorphism of ApoE and LOAD in Chinese population in recent 20 years. Newcastle-Ottawa Scale (NOS) was used for methodological quality assessment. Meta-analysis was conducted by using RevMan 5.0 software. Results There were a total of 249 records through preliminary searching. After eliminating 113 duplicate ones and 124 articles which did not meet the inclusion criteria and adding one article by searching the references of 27 screened articles, 13 high-quality clinical trials were finally selected (NOS score ≥ 5). A total of 3372 subjects (1360 LOAD patients and 2012 controls) were included. Meta-analysis showed that the LOAD risk in population with allele ApoEε4 was significantly higher than those with allele ApoEε3 (OR = 3.710, 95%CI:2.960-4.640; P = 0.000), while had no statistical difference from those with allele ApoEε 2. Meta-analysis also showed that the LOAD risk in those with genotype ApoEε3/ε4 (OR = 3.160, 95%CI: 2.390-4.180; P = 0.000), genotype ApoE ε 2/ε 4 (OR = 3.410, 95% CI: 2.160-5.380; P = 0.000), genotype ApoE ε 4/ε 4 (OR = 16.400, 95% CI: 8.200-32.810; P = 0.000) was significantly higher than those with genotype ApoE ε 3/ε 3, while had no statistical differences from those with genotype ApoE ε 2/ε 3 and genotype ApoE ε 2/ε 2. Conclusions The evidences indicate that ApoEε4 allele and ApoE genotype ε3/ε4, ε2/ε4 and ε4/ε4 are high risk factors for LOAD in Chinese population. DOI: 10.3969/j.issn.1672-6731.2016.01.006
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".