A Multicenter Study of Glucocerebrosidase Mutations in Dementia With Lewy Bodies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
IMPORTANCE: While mutations in glucocerebrosidase (GBA1) are associated with an increased risk for Parkinson disease (PD), it is important to establish whether such mutations are also a common risk factor for other Lewy body disorders. OBJECTIVE: To establish whether GBA1 mutations are a risk factor for dementia with Lewy bodies (DLB). DESIGN We compared genotype data on patients and controls from 11 centers. Data concerning demographics, age at onset, disease duration, and clinical and pathological features were collected when available. We conducted pooled analyses using logistic regression to investigate GBA1 mutation carrier status as predicting DLB or PD with dementia status, using common control subjects as a reference group. Random-effects meta-analyses were conducted to account for additional heterogeneity. SETTING: Eleven centers from sites around the world performing genotyping. PARTICIPANTS: Seven hundred twenty-one cases met diagnostic criteria for DLB and 151 had PD with dementia. We compared these cases with 1962 controls from the same centers matched for age, sex, and ethnicity. MAIN OUTCOME MEASURES: Frequency of GBA1 mutations in cases and controls. RESULTS We found a significant association between GBA1 mutation carrier status and DLB, with an odds ratio of 8.28 (95% CI, 4.78-14.88). The odds ratio for PD with dementia was 6.48 (95% CI, 2.53-15.37). The mean age at diagnosis of DLB was earlier in GBA1 mutation carriers than in noncarriers (63.5 vs 68.9 years; P < .001), with higher disease severity scores. CONCLUSIONS AND RELEVANCE: Mutations in GBA1 are a significant risk factor for DLB. GBA1 mutations likely play an even larger role in the genetic etiology of DLB than in PD, providing insight into the role of glucocerebrosidase in Lewy body disease.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it