GWAS on short tandem repeats identifies novel genetic mechanisms in Alzheimer’s disease
Bibliographic record
Abstract
Abstract Genome-wide association studies (GWASs) are typically based on the analysis of single nucleotide polymorphisms (SNPs) and often exclude more complex genetic variants, such as short tandem repeats (STRs). Here, we report the results of GWAS analyses systematically assessing the role of STRs, both imputed and directly genotyped by whole genome sequencing (WGS), on risk for Alzheimer’s disease (AD) in a large collection of ∼330,000 individuals (3,287 AD cases; 47,048 AD-by-proxy cases, 283,111 controls) from the UK biobank. Using imputed (or WGS-derived) STR genotype data, we identified 14 (WGS: one) independent loci showing evidence for genome-wide significant association with AD risk. While most identified loci had already been highlighted by SNP-based GWAS, we detected new STR-based signals near the genes SNX32 (chr. 11q13) and WBS1 (chr. 17q11). In addition, we delineated several other loci where STRs (and not SNPs) either represent the lead signal ( ABCA7 ) or make substantial contributions to the SNP-driven associations ( HLA-DRB1, MINDY/ADAM10 , and APOE ). Heritability analyses estimated that STRs account for at least 3% of the total phenotypic variance of AD in this dataset. Aligning our top STRs with DNA methylation and transcriptome profiles from human brain samples suggests that several STRs may unfold their effects by impacting gene expression. Future work needs to confirm our results and delineate the likely considerable role that STRs play in the genetic makeup of 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".