Rare copy number variation in extremely impulsively violent males
Bibliographic record
Abstract
The genetic correlates of extreme impulsive violence are poorly understood, and there have been no studies that have systematically characterized a large group of affected individuals both clinically and genetically. We performed a genome-wide rare copy number variant (CNV) analysis in 281 males from four Czech prisons who met strict clinical criteria for extreme impulsive violence. Inclusion criteria included age ≥ 18 years, an ICD-10 diagnosis of Dissocial Personality Disorder, and the absence of an organic brain disorder. Participants underwent a structured psychiatric assessment to diagnose extreme impulsive violence and then provided a blood sample for genetic analysis. DNA was genotyped and CNVs were identified using Illumina HumanOmni2.5 single-nucleotide polymorphism array platform. Comparing with 10851 external population controls, we identified 828 rare CNVs (frequency ≤ 0.1% among control samples) in 264 participants. The CNVs impacted 754 genes, with 124 genes impacted more than once (2-25 times). Many of these genes are associated with autosomal dominant or X-linked disorders affecting adult behavior, cognition, learning, intelligence, specifically expressed in the brain and relevant to synapses, neurodevelopment, neurodegeneration, obesity and neuropsychiatric phenotypes. Specifically, we identified 31 CNVs of clinical relevance in 31 individuals, 59 likely clinically relevant CNVs in 49 individuals, and 17 recurrent CNVs in 65 individuals. Thus, 123 of 281 (44%) individuals had one to several rare CNVs that were indirectly or directly relevant to impulsive violence. Extreme impulsive violence is genetically heterogeneous and genomic analysis is likely required to identify, further research and specifically treat the causes in affected individuals.
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 | 0.000 |
| 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 | 0.000 |
| 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 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".