Peripheral MicroRNA Signatures in Adolescent Depression
Bibliographic record
Abstract
Adolescent depression is linked to enduring maladaptive outcomes, chronic severity of symptoms, and poor treatment response. Identifying epigenetic signatures of adolescent depression is urgently needed to improve early prevention and intervention strategies. MicroRNAs (miRNAs) are epigenetic regulators of adolescent neurodevelopmental processes, but their role as markers and mediators of adolescent depression is unknown. Here, we examined miRNA profiles from dried blood spot samples of male and female adolescents with clinical depression and psychiatrically healthy male and female adolescents ( N = 62). We processed and sequenced these samples using a small RNA protocol tailored for miRNA identification. We identified 9 differentially expressed (DE) miRNAs (adjusted p value < .05), all of which were upregulated in adolescents with depression. At future follow-ups post blood collection, expression of miR-3613-5p, mir-30c-2, and miR-942-5p were positively associated with depression severity but not anxiety, suggesting a stronger link to persistent depression symptoms. Expression of miR-32-5p inversely correlated with hippocampal volume, highlighting a potential neurobiological basis. Common predicted gene targets of the DE miRNAs are involved in neurodevelopment, cognitive processing, and depressive disorders. These findings lay the groundwork for identifying adolescent peripheral miRNA markers that reflect neurodevelopmental pathways that shape lifelong psychopathology risk. In this discovery-phase study, we focused on a vulnerable population of adolescents with depression and utilized minimally invasive blood sampling to assess microRNA signatures of the disorder. Nine circulating microRNAs were strongly associated with a depression diagnosis. These microRNAs, which have no established link to adult depression, predicted future symptom severity and correlated with hippocampal volume and target genes involved in neurodevelopment. This research provides mechanistic insights into and new avenues for the early detection and prevention of adolescent-onset depression.
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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 | 0.001 |
| 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".