Advances in understanding the molecular basis of frontotemporal dementia
Bibliographic record
Abstract
Over the past decade, numerous studies have identified the causative genes and pathological proteins in most cases of frontotemporal dementia (FTD). Most recently, abnormal repeat expansion in theC9orf72 gene was identified as a major cause of the disorder. Rademakers et al. discuss how these discoveries have improved our understanding of the molecular basis of FTD, and highlight how these findings will translate into improved patient care. Frontotemporal dementia (FTD) is a clinical syndrome with a heterogeneous molecular basis. Until recently, the underlying cause was known in only a minority of cases that were associated with abnormalities of the tau protein or gene. In 2006, however, mutations in the progranulin gene were discovered as another important cause of familial FTD. That same year, TAR DNA-binding protein 43 (TDP-43) was identified as the pathological protein in the most common subtypes of FTD and amyotrophic lateral sclerosis (ALS). Since then, substantial efforts have been made to understand the functions and regulation of progranulin and TDP-43, as well as their roles in neurodegeneration. More recently, other DNA/RNA binding proteins (FET family proteins) have been identified as the pathological proteins in most of the remaining cases of FTD. In 2011, abnormal expansion of a hexanucleotide repeat in the gene C9orf72 was found to be the most common genetic cause of both FTD and ALS. All common FTD-causing genes have seemingly now been discovered and the main pathological proteins identified. In this Review, we highlight recent advances in understanding the molecular aspects of FTD, which will provide the basis for improved patient care through the development of more-targeted diagnostic tests and therapies.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".