Genome-wide association studies with experimental validation identify a protective role for B lymphocytes against chronic post-surgical pain
Bibliographic record
Abstract
BACKGROUND: Chronic post-surgical pain (CPSP) significantly impacts patients' recovery and quality of life. Although environmental risk factors are well-established, genetic risk remains less understood. METHODS: A meta-analysis of genome-wide association studies followed by partitioned heritability was performed on 1350 individuals across five surgery types: hysterectomy, mastectomy, abdominal, hernia, and knee. In subsequent animal studies, withdrawal thresholds to evoked mechanical stimulation were measured in Rag1 null mutant and wild-type mice after plantar incision and laparotomy. Cell sorting by flow cytometry tracked recruitment of immune cell types. RESULTS: We discovered 77 genome-wide significant single-nucleotide polymorphism (SNP) hits, distributed among 24 loci and 244 genes. Meta-analysis of all cohorts estimated a SNP-based narrow-sense heritability for CPSP at ∼39%, indicating a substantial genetic contribution. Partitioned heritability analysis across a wide variety of tissues revealed enrichment of heritability in immune system-related genes, particularly those associated with B and T cells. Rag1 null mutant mice lacking both T and B cells exhibited exacerbated and prolonged allodynia up to 42 days after surgery, which was rescued by B-cell transfer. Recruitment patterns of B cells but not T cells differed significantly during the first 7 days after injury in the footpad, lymph nodes, and dorsal root ganglia. CONCLUSIONS: These findings suggest a key protective role for the adaptive immune system in the development of chronic post-surgical pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".