A novel temporal‐predominant neuro‐astroglial tauopathy associated with <i>TMEM106B</i> gene polymorphism in FTLD/ALS‐TDP
Bibliographic record
Abstract
Polymorphisms in TMEM106B, a gene on chromosome 7p21.3 involved in lysosomal trafficking, correlates to worse neuropathological, and clinical outcomes in frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) with TDP-43 inclusions. In a small cohort of C9orf72 expansion carriers, we previously found an atypical, neuroglial tauopathy in cases harboring a TMEM106B rs1990622 A/A genotype. To test whether TMEM106B genotype affects the risk of developing atypical tauopathy under a recessive genotype model (presence versus absence of two major alleles: A/A vs. A/G and G/G). We characterized the atypical tauopathy neuropathologically and determined its frequency by TMEM106B rs1990622 genotypes in 90 postmortem cases with a primary diagnosis of FTLD/ALS-TDP [mean age at death 65.5 years (±8.1), 40% female]. We investigated the effect of this new atypical tauopathy on demographics and clinical and neuropsychological metrics. We also genotyped TMEM106B in an independent series with phenotypically similar cases. Sixteen cases (16/90, 17.7 %) showed the temporal-predominant neuro-astroglial tauopathy, and 93.7% of them carried an A/A genotype (vs. ~35% in a population cohort). The odds ratio of FTLD/ALS-TDP individuals with the A/A genotype showing neuro-astroglial tauopathy was 13.9. Individuals with this tauopathy were older at onset (p = 0.01). The validation cohort had a similarly high proportion of rs1990622 A/A genotype. TDP-43 and tau changes co-occur in a subset of neurons. Our data add to the growing body of evidence that TMEM106B polymorphisms may modulate neurodegeneration. A distinctive medial temporal predominant, 4-repeat, neuro-astroglial tauopathy strongly correlates to TMEM106B A/A genotype in FTLD/ALS-TDP cases.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".