<scp><i>GBA</i></scp> and <scp><i>APOE</i></scp> Impact Cognitive Decline in Parkinson's Disease: A 10‐Year Population‐Based Study
Bibliographic record
Abstract
BACKGROUND: Common genetic variance in apolipoprotein E (APOE), β-glucocerebrosidase (GBA), microtubule-associated protein tau (MAPT), and α-synuclein (SNCA) has been linked to cognitive decline in Parkinson's disease (PD), although studies have yielded mixed results. OBJECTIVES: To evaluate the effect of genetic variants in APOE, GBA, MAPT, and SNCA on cognitive decline and risk of dementia in a pooled analysis of six longitudinal, non-selective, population-based cohorts of newly diagnosed PD patients. METHODS: 1002 PD patients, followed for up to 10 years (median 7.2 years), were genotyped for at least one of APOE-ε4, GBA mutations, MAPT H1/H2, or SNCA rs356219. We evaluated the effect of genotype on the rate of cognitive decline (Mini-Mental State Examanation, MMSE) using linear mixed models and the development of dementia (diagnosed using standardized criteria) using Cox regression; multiple comparisons were accounted for using Benjamini-Hochberg corrections. RESULTS: Carriers of APOE-ε4 (n = 281, 29.7%) and GBA mutations (n = 100, 10.3%) had faster cognitive decline and were at higher risk of progression to dementia (APOE-ε4, HR 3.57, P < 0.001; GBA mutations, HR 1.76, P = 0.001) than non-carriers. The risk of cognitive decline and dementia (HR 5.19, P < 0.001) was further increased in carriers of both risk genotypes (n = 23). No significant effects were observed for MAPT or SNCA rs356219. CONCLUSIONS: GBA and APOE genotyping could improve the prediction of cognitive decline in PD, which is important to inform the clinical trial selection and potentially to enable personalized treatment © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".