RNA in Plasma Extracellular Vesicles of Adolescent Rhesus Macaques Reveals Immune, Bioenergetic, and Microbial Imprints of Early-Life Adversity: An Exploratory Analysis
Bibliographic record
Abstract
BACKGROUND: Exposure to early-life adversity (ELA), including childhood maltreatment, is one of the most significant risk factors for the emergence of psychosomatic disorders in adolescence and adulthood. Most investigations into biological processes that have been perturbed by ELA have profiled DNA methylation in whole blood and coalesced around perturbations of immunobiology being centrally insulted by ELA. METHODS: To identify novel molecular signatures that are enduringly perturbed by childhood maltreatment, we isolated circulating extracellular vesicles (EVs) from plasma collected from adolescent rhesus macaques that had either experienced nurturing maternal care (n = 7; 3 female, 4 male) or maltreatment in infancy (n = 6; 3 female, 3 male). Next, we profiled the RNA found in these EVs. RESULTS: RNA associated with genes related to translation, ATP (adenosine triphosphate) synthesis, mitochondrial function, and immune response were downregulated in circulating EVs collected from adolescent macaques that had experienced maltreatment during infancy, while those involved in ion transport, metabolism, and cell differentiation were upregulated in these EVs. Additionally, a significant proportion of EV RNA aligned to the microbiome and maltreatment during infancy altered the diversity of microbiome-associated RNA signatures found in EVs. CONCLUSIONS: Our findings provide evidence that alterations in RNA associated with immune function, cellular energetics, and the microbiome in circulating EVs may serve as enduring biomarkers of prior exposure to ELA. As a corollary, perturbations of these RNA profiles may offer novel molecular insight into how biology can remain altered long after the shadow of ELA has passed.
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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".