Brain-immune correlates of quality of life in adolescents with chronic musculoskeletal pain
Bibliographic record
Abstract
Chronic musculoskeletal (MSK) pain affects a substantial proportion of youth, with 5 % reporting high-impact symptoms. Chronic pain in youth leads to multifaceted negative consequences that profoundly affect adolescents' quality of life (QoL) and future outcomes. Recent studies suggest that neuro-immune interactions significantly contribute to chronic pain. However, how systemic immune dysregulation influences brain function, and how these brain changes affect well-being and functioning in chronic pain remains unclear. This study aims to examine the convergence between immune function and brain processing during a multisensory task to identify novel mechanistic pathways that may explain reduced QoL in adolescents with chronic MSK pain (N = 129). We used a multisensory fMRI task designed to mimic the unpleasant sensory experiences that adolescents and adults with chronic pain often encounter in daily life. Higher task-evoked activation in the rostral anterior cingulate and dorsomedial prefrontal cortices (rACC-dmPFC), which support threat appraisal and response regulation, was associated with lower physical QoL (pFWE = 0.005). Lower physical QoL was also associated with augmented functional connectivity between the rACC-dmPFC region and sensory processing areas in the somatosensory (pFWE = 0.002) and visual (pFWE = 0.049) cortices. Higher systemic pro-inflammatory activity in immature neutrophils was also associated with lower physical QoL (p = 0.01). Furthermore, task-evoked brain activation in the rACC-dmPFC partially mediated the relationship between neutrophil-mediated inflammatory responses and reduced physical QoL. These findings suggest a potential neuro-immune pathway through which systemic immune alterations may affect brain function and QoL in adolescents with chronic MSK pain.
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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".