Haplotypes and gene expression implicate the <i>MAPT</i> region for Parkinson disease
Bibliographic record
Abstract
BACKGROUND: Microtubule-associated protein tau (MAPT) has been associated with several neurodegenerative disorders including forms of parkinsonism and Parkinson disease (PD). We evaluated the association of the MAPT region with PD in a large cohort of familial PD cases recruited by the GenePD Study. In addition, postmortem brain samples from patients with PD and neurologically normal controls were used to evaluate whether the expression of the 3-repeat and 4-repeat isoforms of MAPT, and neighboring genes Saitohin (STH) and KIAA1267, are altered in PD cerebellum. METHODS: Twenty-one single-nucleotide polymorphisms (SNPs) in the region of MAPT on chromosome 17q21 were genotyped in the GenePD Study. Single SNPs and haplotypes, including the H1 haplotype, were evaluated for association to PD. Relative quantification of gene expression was performed using real-time RT-PCR. RESULTS: After adjusting for multiple comparisons, SNP rs1800547 was significantly associated with PD affection. While the H1 haplotype was associated with a significantly increased risk for PD, a novel H1 subhaplotype was identified that predicted a greater increased risk for PD. The expression of 4-repeat MAPT, STH, and KIAA1267 was significantly increased in PD brains relative to controls. No difference in expression was observed for 3-repeat MAPT. CONCLUSIONS: This study supports a role for MAPT in the pathogenesis of familial and idiopathic Parkinson disease (PD). Interestingly, the results of the gene expression studies suggest that other genes in the vicinity of MAPT, specifically STH and KIAA1267, may also have a role in PD and suggest complex effects for the genes in this region on PD risk.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".