Heritability enrichment implicates microglia in Parkinson’s disease pathogenesis
Bibliographic record
Abstract
Abstract Objective Understanding how different parts of the immune system contribute to pathogenesis in Parkinson’s disease is a burning challenge with important therapeutic implications. We studied enrichment of common variant heritability for Parkinson’s disease stratified by immune and brain cell types. Methods We used summary statistics from the most recent meta-analysis of genome-wide association studies in Parkinson’s disease and partitioned heritability using linkage disequilibrium score regression, stratified for specific cell types as defined by open chromatin regions. We also validated enrichment results using a polygenic risk score approach and intersected disease-associated variants with epigenetic data and expression quantitative loci to nominate and explore a putative microglial locus. Results We found significant enrichment of Parkinson’s disease risk heritability in open chromatin regions of microglia and monocytes. Genomic annotations overlapped substantially between these two cell types, and only the enrichment signal for microglia remained significant in a joint model. We present evidence suggesting P2RY12 , a key microglial gene and target for the anti-thrombotic agent clopidogrel, as the likely driver of a significant Parkinson’s disease association signal on chromosome 3. Interpretation Our results provide further support for the importance of immune mechanisms in PD pathogenesis, highlight microglial dysregulation as a contributing etiological factor and nominate a targetable microglial gene candidate as a pathogenic player. Immune processes can be modulated by therapy, with potentially important clinical implications for future treatment in Parkinson’s disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".