Identification of SMIM1 and SEZ6L2 as Potential Biomarkers for Genes Associated with Intervertebral Disc Degeneration in Pyroptosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35578687", "kind": "science-record", "revision": 3, "content_hash": "sha256:9e21912530d491e15d31f21c55151f0ed675a0273d4731cad54b85a43e0bcdb5", "created_at": "2026-11-01T18:14:28Z", "updated_at": "2026-11-01T21:27:52Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of SMIM1 and SEZ6L2 as Potential Biomarkers for Genes Associated with Intervertebral Disc Degeneration in Pyroptosis.", "doi": "10.1155/2022/9515571", "pmid": "35578687", "authors": ["Nan Wang", "Xiyu Liu", "Xiaoyang Fang", "Shuang Chen", "Zhipeng Xi", "Xiaoyu Zhang", "Congyang Xue", "Xin Liu", "Lin Xie"], "journal": "Disease markers", "year": 2022, "abstract": "Background: Inflammatory reactions and pyroptosis play an important role in the pathology of intervertebral disc degeneration (IDD). The aim of the present study was to investigate pyroptosis in the nucleus pulposus cells (NPCs) of inflammatory induced IDD by bioinformatic methods and to search for possible diagnostic biomarkers.\nMethods: Gene expression profiles related to IDD were downloaded from the GEO database to identify differentially expressed genes (DEGs) between inflammation-induced IDD and non-inflammatory intervention samples. Pyroptosis genes were then searched for, and their expression in IDD was analyzed. Weighted gene co-expression network analysis (WGCNA) was then used to search for modules of IDD genes associated with pyroptosis and intersected with DEGs to discover candidate genes that would be diagnostically valuable. A LASSO model was developed to screen for genes that met the requirements, and ROC curves were created to clarify the diagnostic value of the genetic markers. Ultimately, the screened genes were further validated, and their diagnostic value assessed by selecting gene sets from the GEO database. RT-PCR was used to assess the mRNA expression of diagnostic markers in the nucleus pulposus (NP). Pan-cancer analysis was applied to demonstrate the expression and prognostic value of the screened genes in various tumors.\nResults: A total of 733 DEGs were identified in GSE41883 and GSE27494, which were mainly enriched in transmembrane receptor protein serine/threonine, kinase signaling pathway, response to lipopolysaccharide, and other biological processes, and they were mainly related to TGF beta signaling pathway, toll-like receptor signaling pathway, and TNF signaling pathway. A total of 81 genes related to pyroptosis were identified in the literature, and eight genes related to IDD were identified in the Veen diagram, namely, IL1A, IL1B, NOD2, GBP1, IL6, AK1, EEF2K, and PYCARD. Eleven candidate genes were obtained after locating the intersection of pyroptosis-related module genes and DEGs according to WGCNA analysis. A total of six valid genes were obtained after constructing a machine learning model, and five key genes were finally identified after correlation analysis. GSE23132 and GSE56081 validated the candidate genes, and the final IDD-related diagnostic markers were obtained as SMIM1 and SEZ6L2. RT-PCR results indicated that the mRNA expression of both was significantly elevated in IDD. The pan-cancer analysis demonstrated that SMIM1 and SEZ6L2 have important roles in the expression and prognosis of various tumors.\nConclusion: In conclusion, this research identifies SMIM1 and SEZ6L2 as important biomarkers of IDD associated with pyroptosis, which will help to unravel the development and pathogenesis of IDD and determine potential therapeutic targets.", "claims": [{"id": "claim-method", "statement": "The Cox proportional hazards regression model was constructed by the coxph function of the survival package in R software to evaluate the prognostic relationship between SMIM1 and SEZ6L2 with pan-cancer [20].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35578687", "locator": "sections[11] \"2.9. Prognosis and Survival Analysis\" paragraph 2", "quote": "The Cox proportional hazards regression model was constructed by the coxph function of the survival package in R software to evaluate the prognostic relationship between SMIM1 and SEZ6L2 with pan-cancer [20]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data are available upon request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35578687", "locator": "sections[25] \"Data Availability\" paragraph 2", "quote": "All data are available upon request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "SMIM1 and SEZ6L2 showed significant prognostic value in the pan-cancer analysis, with survival-analysis P values of 4.3e − 6 and 1.8e − 9, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35578687", "locator": "sections[21] \"3.8. Prognostic Value of SMIM1 and SEZ6L2 in Pan-Cancer\" paragraph 2", "quote": "The best cutoff value obtained in the survival analysis was 0.3231, based on which the patients were divided into high and low groups, and we finally observed a significant prognostic difference (P = 4.3e − 6) (Figure 9(d))."}, {"asset": "source:pmid:35578687", "locator": "sections[21] \"3.8. Prognostic Value of SMIM1 and SEZ6L2 in Pan-Cancer\" paragraph 2", "quote": "Significant prognostic differences (P = 1.8e − 9) were observed in the results of the survival analysis (Figure 9(f))."}, {"asset": "source:pmid:35578687", "locator": "sections[21] \"3.8. Prognostic Value of SMIM1 and SEZ6L2 in Pan-Cancer\" paragraph 2", "quote": "SMIM1 and SEZ6L2 have an important prognostic value in the pan-cancer analysis."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "SMIM1 and SEZ6L2 showed significant prognostic value in the pan-cancer analysis, with survival-analysis P values of 4.3e − 6 and 1.8e − 9, respectively.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35578687"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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