Guidance for clinical management of pathogenic variant carriers at elevated genetic risk for ALS/FTD
Bibliographic record
Abstract
There is a growing understanding of the presymptomatic stages of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) and nascent efforts aiming to prevent these devastating neurodegenerative diseases have emerged. This progress is attributable, in no small part, to the altruism of people living with pathogenic variants at elevated genetic risk for ALS/FTD via their willingness to participate in natural history studies and disease prevention trials. Increasingly, this community has also highlighted the urgent need to develop paradigms for providing appropriate clinical care for those at elevated risk for ALS and FTD. This manuscript summarises recommendations emanating from a multi-stakeholder Workshop (Malvern, Pennsylvania, 2023) that aimed to develop guidance for at-risk carriers and their treating physicians. Clinical care recommendations span genetic testing (including counselling and sociolegal implications); monitoring for the emergence of early motor, cognitive and behavioural signs of disease; and the use of Food and Drug Administration-approved small molecule drugs and gene-targeting therapies. Lifestyle recommendations focus on exercise, smoking, statin use, supplement use, caffeine intake and head trauma, as well as occupational and environmental exposures. While the evidence base to inform clinical and lifestyle recommendations is limited, this guidance document aims to appraise carriers and clinicians of the issues and best available evidence, and also to define the research agenda that could yield more evidence-informed guidelines.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".