Corrigendum to “Genetics of upper limb tremor in clinical practice: a systematic literature review” [Parkinsonism and Related disorders volume “in press” (2025) PRD 107981]
Bibliographic record
Abstract
Introduction: According to the Tremor Study Group's consensus statement of the International Parkinson and Movement Disorder Society (MDS), genetics are crucial in determining tremor etiology. However, the pace of genetic discovery in movement disorders has made it difficult to stay up to date. While MDS gene lists exist for other movement disorders, none yet exist for tremor—the most common. This systematic review aims to identify disease genes causing upper limb tremor and create a list with (likely) pathogenic variants to support genetic testing. Methods: Using PRISMA methodology, we systematically reviewed the literature up to 1-1-2025. Tremor did not need to be the main movement disorder. Genes are reported when a (likely) pathogenic variant is reported in multiple unrelated individuals or in at least two independent families. Results: We identified 110 disease genes associated with tremor across 300 studies. Genes were categorized by prominent additional signs: ataxia (e.g. SCA-ATXN2, FMR1), parkinsonism (e.g. PARK-LRRK2, PARK-parkin), dystonia (e.g. DYT-ATP7B, ANO3), neurodevelopmental symptoms (e.g. DHDDS, MECP2), neuropathy (e.g. PMP22, AR), and myoclonus (e.g. SAMD12, STARD7). Conclusion: This review provides a comprehensive list of genes in which pathogenic variants may lead to upper limb tremor with additional signs. Although no genes were found to cause isolated tremor, tremor can be the first symptom. Clinicians should note that exome sequencing does not detect all relevant variant types, and that acquired causes must also be excluded. This gene list offers a practical tool to connect detailed clinical phenotyping to appropriate genetic testing in complex tremor syndromes. The authors would like to apologise for any inconvenience caused.
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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 | 0.007 | 0.089 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.408 | 0.073 |
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".