New Insight into Human Disc Degeneration by Gene Expression Profiling
Bibliographic record
Abstract
Introduction Intervertebral disc (IVD) degeneration is characterized by the breakdown of extracellular matrix molecules and is often associated with inflammatory processes. Hence, anabolic, anti-catabolic, or anti-inflammatory treatments have been considered to retard or reverse early degenerative changes in the IVD. However, there is still a lack of fundamental knowledge about the molecular transformations in the degenerative compared with the native healthy discs. More detailed understanding of the molecular mechanisms will be essential to develop specific therapeutic strategies. In the present study, microarray and quantitative gene expression analysis were used to compare expression profiles of cells from healthy and degenerative human IVDs. The aim is to identify significantly dysregulated molecules or pathways that can potentially be targeted for regenerative therapy. Materials and Methods Annulus fibrosus (AF) and nucleus pulposus (NP) tissues were obtained from human lumbar discs through organ donation program and in accordance with the local and institutional ethical guidelines. Harvested tissue was assigned to either the “healthy” (Thompson disc degeneration grade I-II) or the “degenerative” group (Thompson grade III-IV). Cells were isolated from tissues using sequential pronase and collagenase digestion. Total RNA was extracted from isolated cells using a TRI-Spin method. Samples were processed and subjected to Affymetrix Whole Human Genome DNA microarray profiling. After correspondence analysis for data correction, expression differences between healthy and degenerative AF and NP cells, respectively, were analyzed. Genes with most significant expression divergences were further assessed using quantitative real time RT-PCR. Results For both NP and AF, n = 8 healthy and n = 16 degenerative RNA samples were profiled by microarray. Biostatistical analysis revealed that 237 genes were differentially regulated between degenerative and healthy human AF cells, while 178 genes were differentially regulated between degenerative and healthy NP cells. Specifically, 119 (AF) and 66 (NP) genes were found up-regulated, whereas 118 (AF) and 112 (NP) genes were down-regulated in the degenerative group. Quantitative gene expression analysis was performed for the most significantly differentially regulated genes in n = 8 healthy and n = 10 degenerative RNA samples. While some genes were specifically modulated in the AF or NP cells, several genes showed significant differential regulation ( p < 0.05) by degeneration status. Genes up-regulated in degenerative compared with healthy IVD cells included activated leukocyte cell adhesion molecule (ALCAM), cyclin D1 (CCND1), insulin-like growth factor binding protein 3 (IGFBP3), interferon-induced protein with tetratricopeptide repeats 2 (IFIT2), magnesium transporter 1 (MAGT1), and tissue factor pathway inhibitor (TFPI). Significantly down-regulated genes in degenerative compared with healthy IVD cells, include dickkopf 1 homolog (DKK1), forkhead box F2 (FOXF2), lectin galactoside-binding-like (LGALSL), lipoprotein lipase (LPL), and mannosidase (MAN2B2). Moreover, modulation of distinct molecular pathways could be recognized. Conclusion The present data demonstrates upregulation of signaling factors and antagonists, growth factors and their inhibitors, and chemotactic factors in degenerative cells. Moreover, factors involved in matrix turnover were down-regulated. Improved insight in the differential regulation of distinct molecules and pathways may ultimately allow specific treatment on a molecular basis. Further validation at the protein expression level will be required to evaluate their potential as therapeutic target or as biomarkers for predicting the state of degenerative process in the discs. Disclosure of Interest S. Grad: Conflict with AO Foundation Collaborative Research Program Annulus Fibrosus Repair R. Gawri: None declared L. Haglund: None declared J. Ouellet: Conflict with DePuySynthes, AO Foundation, AONA F. Mwale: None declared L. Creemers: Conflict with Dutch Arthritis Association J. Rutges: None declared W. Gallagher: None declared P. O'Gaora: None declared Pandit: None declared M. Alini: Conflict with AO Foundation Collaborative Research Program Annulus Fibrosus Repair
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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 | 0.000 | 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) | 0.000 | 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".