Genetic associations in Alzheimer’s disease: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Background Elucidation of genetic associations underlying Alzheimer’s Disease (AD) pathogenesis and progression is of prime importance in early diagnosis and drug discovery. Despite existence of innumerable studies to comprehend the genetic hallmarks of AD, inconsistencies amongst the studies in ascertaining specific genes involved in AD risk prompted this Systematic Review and Meta‐analysis. Method The review protocol was registered in Prospero (CRD42019127482). AD related Boolean search strategy was generated to retrieve case‐control studies evaluating genetic associations in AD patients from Pubmed/MEDLINE, Cochrane library, Proquest, Europe PMC, Grey literature, HuGE navigator, Latin American and Carribean Health Sciences literature published till March‐2019. Case‐control studies that defined AD diagnosis through standard diagnostic criteria were included. Preclinical and in‐silico studies were excluded. The shortlisted studies were critically appraised through New Castle Ottawa Scale (NOS) and Q‐Genie tool and the resultant data was extracted. Meta‐analysis was performed for Single Nucleotide Polymorphisms (SNPs) that were reported to be replicated in two different ethnicities by at‐least two studies through random effects model using Revman 5.3. Publication bias was assessed using Egger’s test, funnel plot, Begg and Mazumdar rank correlation test. Later, Interim Venice assessment and sensitivity analysis were executed to evaluate the credibility and versatility of the selected studies respectively. Result Among 352 285 studies retrieved, only 793 studies that met the eligibility criteria were critically appraised. This ultimately resulted in 118 studies for systematic review out of which, 23 SNPs corresponding to 15 genes were prioritized for meta‐analysis. The following SNPs were found to be significantly associated with AD risk: rs3865444 (CD33) (p = 0.04; I2 = 40%; OR [CI] = 0.88 [0.78‐0.99]), rs7561528 (BIN1) (p = 0.03; I2 = 46%; OR [CI] = 0.86 [0.76‐0.98]) and rs1801133 (MTHFR) (p = 0.007; I2 = 18%; OR [CI] = 0.73 [0.61‐0.88]). Interim Venice criteria revealed moderate credibility for seven SNPs and weak credibility for 16 SNPs. Further, sensitivity analysis confirmed the versatility of the selected studies. Conclusion Our findings acknowledged significant associations of three SNPs: rs3865444, rs7561528 and rs1801133 with Alzheimer’s risk. This evidence has to be replicated further to substantiate the role of aforesaid SNPs in AD.
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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 | 0.019 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".