Computational Analysis of the Immune Infiltration Pattern and Candidate Diagnostic Biomarkers in Lumbar Disc Herniation.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35531067", "kind": "science-record", "revision": 5, "content_hash": "sha256:fd1e4f41f7bf236a35f01e049d433dc08f5112270a8ca9a785576a6a9301f57d", "created_at": "2026-11-01T18:14:25Z", "updated_at": "2026-11-01T22:49:01Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Computational Analysis of the Immune Infiltration Pattern and Candidate Diagnostic Biomarkers in Lumbar Disc Herniation.", "doi": "10.3389/fnmol.2022.846554", "pmid": "35531067", "authors": ["Kai Li", "Shijue Li", "Haojie Zhang", "Di Lei", "Wai Leung Ambrose Lo", "Minghui Ding"], "journal": "Frontiers in molecular neuroscience", "year": 2022, "abstract": "Objectives: Lumbar disc herniation (LDH) is a musculoskeletal disease that contributes to low back pain, sciatica, and movement disorder. Existing studies have suggested that the immune environment factors are the primary contributions to LDH. However, its etiology remains unknown. We sought to identify the potential diagnostic biomarkers and analyze the immune infiltration pattern in LDH.\nMethods: The whole-blood gene expression level profiles of GSE124272 and GSE150408 were downloaded from the Gene Expression Omnibus (GEO) database, including that of 25 patients with LDH and 25 healthy volunteers. After merging the two microarray datasets, Differentially Expressed Genes (DEGs) were screened, and a functional correlation analysis was performed. The Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithm and support vector machine recursive feature elimination (SVM-RFE) were applied to identify diagnostic biomarkers by a cross-validation method. Then, the GSE42611 dataset was used as a validation dataset to detect the expression level of these diagnostic biomarkers in the nucleus pulposus and evaluate their accuracy. The hub genes in the network were identified by the CIBERSORT tool and the Weighted Gene Coexpression Network Analysis (WGCNA). A Spearman correlation analysis between diagnostic markers and infiltrating immune cells was conducted to further illustrate the molecular immune mechanism of LDH.\nResults: The azurophil granule and the systemic lupus erythematosus pathway were significantly different between the healthy group and the LDH group after gene enrichment analysis. The XLOC_l2_012836, lnc-FGD3-1, and scavenger receptor class A member 5 were correlated with the immune cell infiltration in various degrees. In addition, five hub genes that correlated with LDH were identified, including AQP9, SIRPB2, SLC16A3, LILRB3, and HSPA6.\nConclusion: The XLOC_l2_012836, lnc-FGD3-1, and SCARA5 might be adopted for the early diagnosis of LDH. The five identified hub genes might have similar pathological mechanisms that contribute to the degeneration of the lumbar disc. The identified hub genes and immune infiltrating pattern extend the knowledge on the potential functioning mechanisms, which offer guidance for the development of therapeutic targets of LDH.", "claims": [{"id": "claim-method", "statement": "The Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithm and support vector machine recursive feature elimination (SVM-RFE) were applied to identify diagnostic biomarkers by a cross-validation method.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35531067", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithm and support vector machine recursive feature elimination (SVM-RFE) were applied to identify diagnostic biomarkers by a cross-validation method."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124272; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150408; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35531067", "locator": "sections[17] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124272; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150408; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The XLOC_l2_012836, lnc-FGD3-1, and SCARA5 might be adopted for the early diagnosis of LDH.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35531067", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "The XLOC_l2_012836, lnc-FGD3-1, and SCARA5 might be adopted for the early diagnosis of LDH."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The XLOC_l2_012836, lnc-FGD3-1, and SCARA5 might be adopted for the early diagnosis of LDH.", "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:35531067"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE124272"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE124272"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35531067", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fnmol.2022.846554", "sha256": "sha256:f977dc3efac9dec3d09fd63c83f223dd0052d247750572b0833c3719ab02924a", "bytes": 35590, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fnmol.2022.846554", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9069112", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE124272", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124272", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE124272", "version": null, "note": "Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124272; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150408; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124272; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150408; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3526782", "GSM3526783", "GSM3526784", "GSM3526785", "GSM3526786", "GSM3526787", "GSM3526788", "GSM3526789", "GSM3526790", "GSM3526791", "GSM3526792", "GSM3526793", "GSM3526794", "GSM3526795", "GSM3526796", "GSM3526797"], "sample_count": 16, "group_sizes": null, "group_sizes_basis": null, "platform": "21185", "taxon": "Homo sapiens", "title": "Transcriptome signatures reveal candidate key genes in the whole blood of patients with lumbar disc prolapse", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE150408", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150408", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE150408", "version": null, "note": "Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124272; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150408; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124272; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150408; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4548691", "GSM4548692", "GSM4548693", "GSM4548694", "GSM4548695", "GSM4548696", "GSM4548697", "GSM4548698", "GSM4548699", "GSM4548700", "GSM4548701", "GSM4548702", "GSM4548703", "GSM4548704", "GSM4548705", "GSM4548706", "GSM4548707", "GSM4548708", "GSM4548709", "GSM4548710", "GSM4548711", "GSM4548712", "GSM4548713", "GSM4548714", "GSM4548715", "GSM4548716", "GSM4548717", "GSM4548718", "GSM4548719", "GSM4548720", "GSM4548721", "GSM4548722", "GSM4548723", "GSM4548724", "GSM4548725", "GSM4548726", "GSM4548727", "GSM4548728", "GSM4548729", "GSM4548730", "GSM4548731", "GSM4548732", "GSM4548733", "GSM4548734", "GSM4548735", "GSM4548736", "GSM4548737", "GSM4548738", "GSM4548739", "GSM4548740", "GSM4548741", "GSM4548742", "GSM4548743", "GSM4548744", "GSM4548745", "GSM4548746", "GSM4548747", "GSM4548748", "GSM4548749"], "sample_count": 59, "group_sizes": null, "group_sizes_basis": null, "platform": "21185", "taxon": "Homo sapiens", "title": "Identification of key genes potentially related to intervertebral disc degeneration by microarray analysis", "resolution_checked_at": "2026-11-01T17:30:42Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE42611", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE42611", "version": null, "note": "Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124272; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150408; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124272; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150408; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1045788", "GSM1045789", "GSM1045790", "GSM1045791", "GSM1045792", "GSM1045793", "GSM1045794", "GSM1045795"], "sample_count": 8, "group_sizes": null, "group_sizes_basis": null, "platform": "6247", "taxon": "Rattus norvegicus", "title": "An Organ Culture System to Model Early Degenerative Changes of the Intervertebral Disc: II Profiling Global Gene Expression Changes", "resolution_checked_at": "2026-11-01T18:06:44Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE124272 not downloaded", "asset:data:geo:GSE124272 licence not read", "asset:data:geo:GSE150408 not downloaded", "asset:data:geo:GSE150408 licence not read", "asset:data:geo:GSE42611 not downloaded", "asset:data:geo:GSE42611 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "machine_learning", "specific": "support_vector_machine", "label": "Machine learning", "dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithm and support vector machine recursive feature elimination (SVM-RFE) were applied to identify diagnostic biomarkers by a cross-validation method."}}, {"id": "method-2", "family": "regression_modelling", "specific": "logistic", "label": "Regression modelling", "dsl_operations": ["glm_logit_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictors_and_outcome"], "evidence": {"score": 0.7, "band": "medium", "quote": "logistic regression"}}, {"id": "method-3", "family": "correlation_analysis", "specific": "spearman", "label": "Correlation analysis", "dsl_operations": ["spearman_rho"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.7, "band": "medium", "quote": "Spearman correlation"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: support_vector_machine."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE124272", "GSE150408", "GSE42611"], "resolved_accessions": ["GSE124272", "GSE150408", "GSE42611"], "statements": ["Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124272; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150408; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611."], "basis": "The paper names GSE124272, GSE150408, GSE42611 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "assets": ["source:pmid:35531067", "data:geo:GSE124272"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE124272"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:45:07Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 10037, "completion_tokens": 1611, "cached_tokens": 128}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:35531067", "type": "paper", "label": "pmid:35531067"}, {"id": "source:pmid:35531067", "type": "manuscript", "label": "PMID 35531067 full text"}, {"id": "data:geo:GSE124272", "type": "dataset", "label": "GEO GSE124272"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35531067", "type": "paper", "label": "pmid:35531067"}, {"id": "source:pmid:35531067", "type": "manuscript", "label": "PMID 35531067 full text"}, {"id": "data:geo:GSE124272", "type": "dataset", "label": "GEO GSE124272"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35531067", "type": "extraction", "used": ["source:pmid:35531067"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE124272", "type": "accession_resolution", "used": ["data:geo:GSE124272"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:35531067", "parent_hash": "sha256:f5d9f85eeeaa7f349618e6278067c7750e637877d2eac89b5a78538ec3e54d57", "fork_of": null, "generation": 4}, "gaps": ["asset:data:geo:GSE124272 licence not read", "asset:data:geo:GSE124272 not downloaded", "asset:data:geo:GSE150408 licence not read", "asset:data:geo:GSE150408 not downloaded", "asset:data:geo:GSE42611 licence not read", "asset:data:geo:GSE42611 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["25 healthy volunteers. After merging the two microarray datasets, Differentially Expressed Genes (DE"], "order_basis": "paper_text_order:705", "id": "assay:1"}, {"role": "analysis", "definition_id": "machine_learning", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["train_classifier", "cross_validate", "roc_auc"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithm and support vector machine recursive feature elimination (SVM-RFE) were applied to identify diagnostic biomarkers by a cross-validation method."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}