Genome-wide contribution of common short-tandem repeats to Parkinson’s disease genetic risk
Bibliographic record
Abstract
Parkinson's disease is a complex neurodegenerative disorder with a strong genetic component, for which most known disease-associated variants are single nucleotide polymorphisms (SNPs) and small insertions and deletions (indels). DNA repetitive elements account for >50% of the human genome; however, little is known of their contribution to Parkinson's disease aetiology. While select short tandem repeats (STRs) within candidate genes have been studied in Parkinson's disease, their genome-wide contribution remains unknown. Here we present the first genome-wide association study of STRs in Parkinson's disease. Through a meta-analysis of 16 imputed genome-wide association study cohorts from the International Parkinson's Disease Genomic Consortium (IPDGC), totalling 39 087 individuals (16 642 cases and 22 445 controls of European ancestry), we identified 34 genome-wide significant STR loci (P < 5.34 × 10-6), with the strongest signal located in KANSL1 [chr17:44 205 351:[T]11, P = 3 × 10-39, odds ratio = 1.31 (95% confidence interval = 1.26-1.36)]. Conditional-joint analyses suggested that four significant STRs mapping nearby NDUFAF2, TRIML2, MIRNA-129-1 and NCOR1 were independent from known risk SNPs. Including STRs in heritability estimates increased the variance explained by SNPs alone. Gene expression analysis of STRs (eSTRs) in RNA sequencing data from 13 brain regions identified significant associations of STRs influencing the expression of multiple genes, including known Parkinson's disease genes. Further functional annotation of candidate STRs revealed that significant eSTRs within NUDFAF2 and ZSWIM7 overlap with regulatory features and are associated with change in the expression levels of nearby genes. Here, we show that STRs at known and novel candidate loci contribute to Parkinson's disease risk and have functional effects in disease-relevant tissues and pathways, supporting previously reported disease-associated genes and giving further evidence for their functional prioritization. These data represent a valuable resource for researchers currently dissecting Parkinson's disease risk loci.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".