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Identification and Experimental Validation of PANoptosis Key Genes for Constructing a PANoptosis Risk Diagnostic Model in Intervertebral Disc Degeneration

Background Intervertebral disc degeneration (IDD) represents a significant health concern globally. This study aimed to identify the PANoptosis key genes (PKGs) associated with IDD and construct a risk diagnosis model METHODS: Single-cell sequencing, machine learning algorithms, and LASSO regression were employed to identify PKGs and develop a risk model. The expression of identified PKGs was validated in human IDD clinical tissues using qRT-PCR, Western blot, and immunohistochemistry. The therapeutic effect of…

By the Truvace desk1 min read1 sourcePeer-reviewedTRV-2026-1230· cite & verify
Identification and Experimental Validation of PANoptosis Key Genes for Constructing a PANoptosis Risk Diagnostic Model in Intervertebral Disc Degeneration
Hospital Universitari Doctor Peset, València 05 by 19Tarrestnom65. CC BY-SA 4.0 · https://creativecommons.org/licenses/by-sa/4.0

In brief

By October 2026, researchers reported using single-cell sequencing and machine learning to pinpoint seven PANoptosis-related genes associated with intervertebral disc degeneration and to build a risk diagnosis model. They validated expression patterns in patient nucleus pulposus samples and tested ACSBG1 knockdown in rats.

The work matters because it moves from computational gene selection to tissue-level confirmation and an in vivo therapeutic demonstration, suggesting a diagnostic and targetable pathway for a common spine condition. What remains uncertain from the text is model performance metrics, patient cohort size, and durability or safety of ACSBG1 targeting beyond the reported histology.

Main points

  1. Study identified seven representative PANoptosis key genes: ACSBG1, FXYD1, APCS, CEACAM1, ERAP2, ABL1, and FZD3 for intervertebral disc degeneration.
  2. Risk model was built from those genes and linked to immune infiltration, particularly neutrophils.
  3. Clinical validation by qRT-PCR, Western blot, and immunohistochemistry showed four genes upregulated and three downregulated in patient nucleus pulposus tissues.
  4. In vivo testing showed ACSBG1 knockdown preserved disc structure and increased proteoglycan content in rats.

The gain

Researchers used machine learning and LASSO regression on single-cell data to identify seven PANoptosis key genes and build a validated IDD risk diagnosis model, with experimental knockdown of ACSBG1 reducing degeneration in a rat model.

The rundown

The team combined single-cell sequencing with machine learning and LASSO regression to select seven PKGs and construct the risk model, then performed immune infiltration analysis.

Validation included qRT-PCR, Western blot, and immunohistochemistry on human IDD clinical nucleus pulposus tissues, confirming directional expression changes, and histological analysis of a rat IDD model after ACSBG1 knockdown.

Sources

  1. Peer-reviewedThe Journal of Gene Medicine2026-10-01

The debate