Adult genetic leukoencephalopathies: identifying new entities using advanced MRI techniques, next generation sequencing and clinical profiling
Bibliographic record
Abstract
Genetic leukoencephalopathies are considered rare in the adult population. However, several lines of evidence suggest that there is a larger than expected number of adult patients with genetic leukoencephalopathies who are currently not diagnosed. The study of leukoencephalopathies - either genetically-proven or unsolved - relies greatly on MRI pattern-recognition, which allowed the characterization of the majority of genetic white matter disorders. The advent of next generation sequencing (NGS) revolutionized the field, by disclosing new phenotypes associated to known genetic white matter conditions and identifying novel genes responsible for unsolved leukoencephalopathies. The goals of my study were1.the application of advanced neuroimaging tools to define and characterize white matter abnormalities of known and novel genetic leukoencephalopathies2.the clinical and demographic characterization of subjects with adult genetic leukoencephalopathies3.the identification of genes responsible for new forms of hereditary white matter disorders, using NGS techniques.We applied an integrated approach which combined clinical phenotyping with MRI pattern-recognition and NGS data. This work led to a) the description of a cohort of 68 adult subjects with leukoencephalopathy of probable genetic origin, 59 of which were included in our study, b) the identification of the causal mutations (16 in total, 11 novel) in genes known to be associated with leukoencephalopathies in 14/59 subjects (23.7%), and c) the broadening of clinical and imaging phenotypes of known disorders: POLR3-related disorders, vanishing white matter disease, Krabbe disease, MTFMT-related disorders. We demonstrated that MRI family studies can be crucial in adult leukoencephalopathies to define the modality of transmission of unclear white matter disorders within families. In conclusion, we documented that adult genetic leukoencephalopathies are an emerging problem in clinical neurosciences. MRI family studies and the recognition of disease-specific MRI features are critical to guide the diagnostic process. Despite the access to NGS techniques, more than 70% of our subjects remain without a diagnosis. The international sharing of MRI and NGS on adult leukoencephalopathies will allow the identification of subjects with same phenotypes or mutated genes and ultimately lead to the description of new genetic entities.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".