Human molecular mechanisms of lumbar disc degeneration: A scoping review
Bibliographic record
Abstract
Study Design: Scoping review. Objective: To synthesize current knowledge of molecular mechanisms underlying human lumbar disc degeneration (LDD) and identify knowledge gaps to be addressed by future research. Summary of Background Data: Chronic low back pain (CLBP) is a leading cause of disability worldwide. Epidemiological studies based on radiologic findings suggest that patients with LDD are more likely to develop CLBP. Despite many reviews on disc degeneration, no systematic synthesis has focused on the molecular mechanisms of LDD using human tissue models. Methods: A systematic search of 12 databases identified 8310 studies. After applying screening criteria, 159 studies analyzing human lumbar degenerative disc tissues from adult patients with radiologically diagnosed LDD were eligible for data extraction. Studies with sample sizes <20, tissues from organ donors or non-lumbar regions, or findings based solely on animal data or public repositories ( e.g. , Gene Expression Omnibus) without clinical validation were excluded from the final synthesis. Results and Conclusions: Twenty-nine studies were selected for the synthesis of findings. Current evidence converges on dysregulated lipid metabolism, including impaired phosphatidylcholine synthesis and oxidized low-density lipoprotein signaling via LOX-1; ferroptosis and pyroptosis driven by iron overload and mitochondrial DNA–mediated inflammasome activation; and interleukins (IL-21, IL-17A) that enhance TNF-α–mediated catabolic and inflammatory signaling. Epigenetic regulators (SIRT1 and BRD4), posttranscriptional/translational proteins (TRIM21, Piezo1, YAP1, CHSY3, FSTL1, and IGFBP5), and noncoding RNAs further modulate extracellular matrix homeostasis, cell cycle progression, apoptosis, and inflammation, often through NF-κB and MAPK pathways. Despite their clinical relevance, the included studies had several major limitations: small sample sizes, limited phenotypic profiling and stratification, demographically unbalanced cohorts, and reliance on in vitro or animal models for experimental data. Future studies should integrate multi-omics, imaging, and clinical data to enhance mechanistic insight and support the development of targeted therapies for LDD.
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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 | 0.017 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.024 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".