Intergenerational influences of paternal combat-related trauma on offspring behavioral and brain function
Bibliographic record
Abstract
Post-traumatic stress (PTS) is a debilitating mental health condition that is highly prevalent in Veteran populations owing to their increased exposure to combat-related trauma. PTS is associated with numerous comorbid conditions including major depressive disorder, anxiety, and chronic pain. Although the causal mechanisms are currently unknown, paternal trauma has been linked to an increased risk for pathology in their offspring. Therefore, using a preclinical model of combat trauma, we examined the relationship between paternal PTS and offspring socio-emotional functioning, pain perception, and gene expression changes pertinent to HPA-axis functioning, reward processing, and epigenetic regulation. Paternally experienced trauma produced persistent changes in sire anxiety, anhedonia, and sociability, as well as elevated levels of corticosterone and changes to gene expression. In addition, the paternal experiences prior to conception changed offspring behaviour and gene expression but did not modify the offspring’s stress response in adolescence. Offspring born to fathers who experienced trauma exhibited changes to nociceptive sensitivity, social and anxiety-like behaviour, as well as changes in expression of 5HT1A , 5HT2A, Comt, Dnmt3a, Drd2, FKBP5, NR3C1, Maoa , and Mecp2 in the adrenal gland, hippocampus, hypothalamus, prefrontal cortex, and thalamus. These results suggest that trauma in fathers may alter expression of genes that contribute to an increased risk for the development of mental health conditions, such as PTS and chronic pain, in their offspring. This model of paternally induced intergenerational transmission could be used to explore the efficacy of future therapeutic strategies to ameliorate some risk imparted upon offspring by Veteran fathers living with PTS.
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 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 | 0.000 | 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) | 0.001 | 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 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".