Exome sequencing identifies rare damaging variants in the ATB8B4 and ABCA1 genes as novel risk factors for Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: Damaging rare variants in the TREM2, SORL1 and ABCA7 genes have been associated with an increased risk of developing Alzheimer's Disease (AD) with odds ratios that were not observed since the identification of the main AD genetic risk factor, the APOE-ε4 allele. Here, we aimed to identify additional AD-associated genes by investigating the burden of rare damaging variants in the exomes of AD cases and controls. METHOD: On a single server, we analyzed in two stages, the data from 52,270 exome sequences from several independent datasets from Europe and the United States. After comprehensive QC, Stage-1 and Stage-2 datasets comprised in total 16,396 AD cases (5,672 EOAD) and 18,107 controls with European ancestry. All detected non-synonymous and loss-of-function rare variants were prioritized by REVEL and LOFTEE, and analyzed in a per-gene burden analysis. After a Stage-1 discovery analysis, we replicated findings in an independent dataset (Stage-2). We combined the Stage-1 and Stage-2 datasets and determined, for each gene, the features of the variants that drive the burden-associations. RESULTS: We confirmed the AD-association of rare damaging variants SORL1, TREM2, ABCA7, and newly identified a significant AD-association of rare damaging variants in the ATP8B4 and ABCA1 genes. In addition, we find a strong indication for the AD-association of ADAM10 and SRC genes (Stage-2 p<0.05). For most genes, we observed a larger effect size for LOF variants compared to missense variants (Figure-A). High-impact variants in these genes are mostly extremely rare and enriched in AD patients with early ages at onset (Figure-B). CONCLUSION: We identified, for the first time, the AD-association of rare damaging variants in two genes: (i) microglial ATP8B4 which is involved in phospholipid transport, and (ii) ABCA1 which plays a critical role in lipidation of apoE thereby supporting Aβ processing. Further, we found strong evidence for the AD-association of damaging variants in ADAM10 and SRC genes. ADAM10 is involved in the proteolytic processing of APP, while SRC is a Non-Receptor Tyrosine Kinase which binds PTK2B/Pyk2, a known AD risk factor. Together, our study provides further evidence for the role of Aβ and microglia in AD pathophysiology.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".