Association of Rare <i>APOE</i> Missense Variants V236E and R251G With Risk of Alzheimer Disease
Bibliographic record
Abstract
Importance: The APOE ε2 and APOE ε4 alleles are the strongest protective and risk-increasing, respectively, genetic variants for late-onset Alzheimer disease (AD). However, the mechanisms linking APOE to AD-particularly the apoE protein's role in AD pathogenesis and how this is affected by APOE variants-remain poorly understood. Identifying missense variants in addition to APOE ε2 and APOE ε4 could provide critical new insights, but given the low frequency of additional missense variants, AD genetic cohorts have previously been too small to interrogate this question robustly. Objective: To determine whether rare missense variants on APOE are associated with AD risk. Design, Setting, and Participants: Association with case-control status was tested in a sequenced discovery sample (stage 1) and followed up in several microarray imputed cohorts as well as the UK Biobank whole-exome sequencing resource using a proxy-AD phenotype (stages 2 and 3). This study combined case-control, family-based, population-based, and longitudinal AD-related cohorts that recruited referred and volunteer participants. Stage 1 included 37 409 nonunique participants of European or admixed European ancestry, with 11 868 individuals with AD and 11 934 controls passing analysis inclusion criteria. In stages 2 and 3, 475 473 participants were considered across 8 cohorts, of which 84 513 individuals with AD and proxy-AD and 328 372 controls passed inclusion criteria. Selection criteria were cohort specific, and this study was performed a posteriori on individuals who were genotyped. Among the available genotypes, 76 195 were excluded. All data were retrieved between September 2015 and November 2021 and analyzed between April and November 2021. Main Outcomes and Measures: In primary analyses, the AD risk associated with each missense variant was estimated, as appropriate, with either linear mixed-model regression or logistic regression. In secondary analyses, associations were estimated with age at onset using linear mixed-model regression and risk of conversion to AD using competing-risk regression. Results: A total of 544 384 participants were analyzed in the primary case-control analysis; 312 476 (57.4%) were female, and the mean (SD; range) age was 64.9 (15.2; 40-110) years. Two missense variants were associated with a 2-fold to 3-fold decreased AD risk: APOE ε4 (R251G) (odds ratio, 0.44; 95% CI, 0.33-0.59; P = 4.7 × 10-8) and APOE ε3 (V236E) (odds ratio, 0.37; 95% CI, 0.25-0.56; P = 1.9 × 10-6). Additionally, the cumulative incidence of AD in carriers of these variants was found to grow more slowly with age compared with noncarriers. Conclusions and Relevance: In this genetic association study, a novel variant associated with AD was identified: R251G always coinherited with ε4 on the APOE gene, which mitigates the ε4-associated AD risk. The protective effect of the V236E variant, which is always coinherited with ε3 on the APOE gene, was also confirmed. The location of these variants confirms that the carboxyl-terminal portion of apoE plays an important role in AD pathogenesis. The large risk reductions reported here suggest that protein chemistry and functional assays of these variants should be pursued, as they have the potential to guide drug development targeting APOE.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".