What monozygotic twins discordant for phenotype illustrate about mechanisms influencing genetic forms of neurodegeneration
Bibliographic record
Abstract
As monozygotic (MZ) twins are believed to be genetically identical, discordance for disease phenotype between MZ twins has been used in genetic research to understand the contribution of genetic vs environmental factors in disease development. However, recent studies show that MZ twins can differ both genetically and epigenetically. Screening MZ twins for genetic and/or epigenetic differences could be a useful and novel approach to identify modifying factors influencing phenotypic expression of disease. MZ twins that are phenotypically discordant for monogenic diseases are of special interest. Such occurrences have been described for Huntington's disease, spinocerebellar ataxias, as well as for familial forms of Alzheimer's disease. By comparing MZ twins that are phenotypically discordant, crucial factors influencing the phenotypic expression of the disease could be identified, which may be of relevance for understanding disease pathogenesis and variability in disease phenotype. Overall, understanding the crucial factors in development of a neurodegenerative disorder will have relevance for predictive testing, preventive treatment and could help to identify novel therapeutic targets.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".