Polygenic risk score association with cognitive decline in Parkinson’s Disease
Bibliographic record
Abstract
Abstract Background Cognitive impairment is a common and debilitating symptom in Parkinson’s disease (PD) with high variability in individual trajectory of decline. We sought to explore heterogeneity in the trajectory of individual cognitive change in a cohort of early stage PD patients and test association to cumulative genetic risk identified in large scale Genome Wide Association Studies (GWAS). Method Using longitudinal measures of the Montreal Cognitive Assessment (MoCA) we employed latent class mixed modelling (LCMM) to identify and investigate unknown populations in the Parkinson’s Progression Markers Inititative (PPMI) de‐novo PD cohort. Tranformed MoCA scores were modelled as a quadratic function of years from baseline, controlling for age, gender and motor symptom severity. Optimal group number was identified and determined using standardly advised model fit metrics. Polygenic risk scores (PRS) for five GWAS were calculated using PRSice‐2 applied to genotyping array data. Association of PRS with cognitive groups was tested using linear models and ANOVA tests. Result LCMM showed optimal fit statistics for three classes (lowest BIC, high entropy) and these groups were retained for further analysis The largest identified class (n = 240) on average, presented at baseline with higher MoCA scores and remained stable over time. The second class (n = 132) presented with lower MoCA scores and showed a slow declining trajectory whilst the smallest class (n = 13) presented with lower MoCA scores but declined at a rapid rate. Educational attainment and Alzheimer’s disease (AD) GWAS derived PRS were significantly associated with cognitive class and explained the highest amount of phenotypic variance. For PD case‐control status, only the PD PRS was significantly associated with Parkinson’s status and explained a similar level of phenotypic variation. Conclusion Latent class analysis may provide utility in subsetting longitudinal cognitive outcome groups for use in groupwise comparisons. Using this method we show evidence for association of educational attainment and AD cumulative genetic risk and worse cognitive outcomes in early PD.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".