RNA in extracellular vesicles during adolescence reveal immune, energetic and microbial imprints of early life adversity
Bibliographic record
Abstract
Exposure to early life adversity (ELA), including childhood maltreatment, is one of the most significant risk factors for the emergence of neuropsychiatric disorders in adolescence and adulthood. Despite this relationship being well established, the underlying mechanisms remain unclear. One way to achieve this understanding is to identify molecular pathways and processes that are perturbed as a consequence of childhood maltreatment. Ideally, these perturbations would be evident as changes in DNA, RNA or protein profiles in easily accessible biological samples collected in the shadow of childhood maltreatment. In this study, we isolated circulating extracellular vesicles (EVs) from plasma collected from adolescent rhesus macaques that had either experienced nurturing maternal care (CONT) or maternal maltreatment (MALT) in infancy. RNA sequencing of RNA in plasma EVs and gene enrichment analysis revealed that genes related to translation, ATP synthesis, mitochondrial function and immune response were downregulated in MALT samples, while genes involved in ion transport, metabolism and cell differentiation were upregulated. Interestingly, we found that a significant proportion of EV RNA aligned to the microbiome and that MALT altered the diversity of microbiome-associated RNA signatures found in EVs. Part of this altered diversity suggested differences in prevalence of bacterial species in CONT and MALT animals noted in the RNA signatures of the circulating EVs. Our findings provide evidence that immune function, cellular energetics and the microbiome may be important conduits via which infant maltreatment exerts effects on physiology and behavior in adolescence and adulthood. As a corollary, perturbations of RNA profiles related to immune function, cellular energetics and the microbiome may serve as biomarkers of responsiveness to ELA. Our results demonstrate that RNA profiles in EVs can serve as a powerful proxy to identify biological processes that might be perturbed by ELA and that may contribute to the etiology of neuropsychiatric disorders in the aftermath of ELA.
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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 | 0.000 | 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".