Epigenetics of Personality Traits: An Illustrative Study of Identical Twins Discordant for Risk-Taking Behavior
Why this work is in the frame
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Bibliographic record
Abstract
DNA methylation differences between identical twins could account for phenotypic twin discordance of behavioral traits and diseases. High throughput epigenomic microarray profiling can be a strategy of choice for identification of epigenetic differences in phenotypically different monozygotic (MZ) twins. Epigenomic profiling of a pair of MZ twins with quantified measures of psychometric discordance identified several DNA methylation differences, some of which may have developmental and behavioral implications and are consistent with the contrasting psychometric profiles of the twins. In particular, differential methylation of CpG islands proximal to the homeobox DLX1 gene could modulate stress responses and risk taking behavior, and deserve further attention as a potential marker of aversion to danger. The epigenetic difference detected at DLX1 of approximately 1.2 fold change was used to evaluate experimental design issues such as the required numbers of technical replicates. It also enabled us to estimate the power this technique would have to detect a functionally relevant epigenetic difference given a range of 1 to 50 twin pairs. We found that use of epigenomic microarray profiling in a relatively small number (15-25) of phenotypically discordant twin pairs has sufficient power to detect 1.2 fold epigenetic changes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it