Distribution, type, and origin of <i>Parkin</i> mutations: Review and case studies
Bibliographic record
Abstract
Early-onset Parkinson's disease (PD) has been associated with different mutations in the Parkin gene (PARK2). To study distribution and type of Parkin mutations, we carried out a comprehensive literature review that demonstrated two prominent types of mutations among 379 unrelated mutation carriers: exon rearrangements involving exon 3, 4, or both, and alterations in exons 2 and 7, suggesting mutational hot spots or founders. To elucidate the origin of 14 recurrent Parkin mutations in our samples, we carried out a detailed haplotype analysis at the PARK2 locus. Thirty-eight mutation-positive individuals, available family members, and 62 mutation-negative individuals were genotyped. We determined allele frequencies and linkage disequilibrium (LD) to evaluate the significance of shared haplotypes. We observed no LD between markers at PARK2. Our data support a common founder for the most frequent Parkin point mutation (924C>T; exon 7) and indicate a mutational hot spot as cause of a common small deletion (255/256delA; exon 2). Furthermore, the most frequent Parkin exon deletion (Ex4del) arose independently in 2 of our subjects. However, it also occurred as the result of a founder mutation in 2 cases that shared identical deletion break points. This study provides evidence for both mutational hot spots and founder mutations as a source of recurrent mutations in Parkin, regardless of the mutation type.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".