Decoding the mitochondrial connection: development and validation of biomarkers for classifying and treating systemic lupus erythematosus through bioinformatics and machine learning.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38044432", "kind": "science-record", "revision": 4, "content_hash": "sha256:313a573d301d3e5ef05056c68f2dc75f2715287967d0bfff5ca6778ff410bfc4", "created_at": "2026-11-01T19:02:59Z", "updated_at": "2026-11-01T22:53:14Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Decoding the mitochondrial connection: development and validation of biomarkers for classifying and treating systemic lupus erythematosus through bioinformatics and machine learning.", "doi": "10.1186/s41927-023-00369-0", "pmid": "38044432", "authors": ["Haoguang Li", "Lu Zhou", "Wei Zhou", "Xiuling Zhang", "Jingjing Shang", "Xueqin Feng", "Le Yu", "Jie Fan", "Jie Ren", "Rongwei Zhang", "Xinwang Duan"], "journal": "BMC rheumatology", "year": 2023, "abstract": "BACKGROUND: Systemic lupus erythematosus (SLE) is a multifaceted autoimmune disease characterized by clinical and pathological diversity. Mitochondrial dysfunction has been identified as a critical pathogenetic factor in SLE. However, the specific molecular aspects and regulatory roles of this dysfunction in SLE are not fully understood. Our study aims to explore the molecular characteristics of mitochondria-related genes (MRGs) in SLE, with a focus on identifying reliable biomarkers for classification and therapeutic purposes.\nMETHODS: We sourced six SLE-related microarray datasets (GSE61635, GSE50772, GSE30153, GSE99967, GSE81622, and GSE49454) from the Gene Expression Omnibus (GEO) database. Three of these datasets (GSE61635, GSE50772, GSE30153) were integrated into a training set for differential analysis. The intersection of differentially expressed genes with MRGs yielded a set of differentially expressed MRGs (DE-MRGs). We employed machine learning algorithms-random forest (RF), support vector machine (SVM), and least absolute shrinkage and selection operator (LASSO) logistic regression-to select key hub genes. These genes' classifying potential was validated in the training set and three other validation sets (GSE99967, GSE81622, and GSE49454). Further analyses included differential expression, co-expression, protein-protein interaction (PPI), gene set enrichment analysis (GSEA), and immune infiltration, centered on these hub genes. We also constructed TF-mRNA, miRNA-mRNA, and drug-target networks based on these hub genes using the ChEA3, miRcode, and PubChem databases.\nRESULTS: Our investigation identified 761 differentially expressed genes (DEGs), mainly related to viral infection, inflammatory, and immune-related signaling pathways. The interaction between these DEGs and MRGs led to the identification of 27 distinct DE-MRGs. Key among these were FAM210B, MSRB2, LYRM7, IFI27, and SCO2, designated as hub genes through machine learning analysis. Their significant role in SLE classification was confirmed in both the training and validation sets. Additional analyses included differential expression, co-expression, PPI, GSEA, immune infiltration, and the construction of TF-mRNA, miRNA-mRNA, and drug-target networks.\nCONCLUSIONS: This research represents a novel exploration into the MRGs of SLE, identifying FAM210B, MSRB2, LYRM7, IFI27, and SCO2 as significant candidates for classifying and therapeutic targeting.", "claims": [{"id": "claim-method", "statement": "The limma package in R program [19] was used to evaluate differentially expressed genes (DEGs) between SLE and healthy controls, using cutoffs for adjustment: p-value < 0.05 and FC (fold changes) > 1.5.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38044432", "locator": "sections[4] \"Identification of differentially expressed genes (DEGs)\" paragraph 2", "quote": "The limma package in R program [19] was used to evaluate differentially expressed genes (DEGs) between SLE and healthy controls, using cutoffs for adjustment: p-value < 0.05 and FC (fold changes) > 1.5."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/supplementary material. We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). Further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38044432", "locator": "sections[27] \"Data Availability\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/supplementary material. We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). Further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "An ANN model based on five hub genes achieved an AUC of 0.967 (95% CI 0.945–0.984) for classifying SLE in the training set.", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "Next, an ANN model for classifying SLE was developed utilizing five hub genes, achieving an AUC of 0.967 (95% CI 0.945–0.984) on the training set, as shown in Fig. 5A and B."}, "evidence": [{"asset": "source:pmid:38044432", "locator": "sections[18] \"Performance of hub genes to classify SLE\" paragraph 2", "quote": "Next, an ANN model for classifying SLE was developed utilizing five hub genes, achieving an AUC of 0.967 (95% CI 0.945–0.984) on the training set, as shown in Fig. 5A and B."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "An ANN model based on five hub genes achieved an AUC of 0.967 (95% CI 0.945–0.984) for classifying SLE in the training set.", "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:38044432"], "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:GSE30153"], "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:GSE30153"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38044432", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s41927-023-00369-0", "sha256": "sha256:69bf8fbaf935e031633cccbfc6694e11efb0def12c629a84078c0fef691dab2d", "bytes": 52842, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s41927-023-00369-0", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10694981", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE30153", "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=GSE30153", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE30153", "version": null, "note": "The original contributions presented in the study are included in the article/supplementary material. We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). Further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/supplementary material. We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). Further inquiries can be directed to the corresponding author.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM746726", "GSM746727", "GSM746728", "GSM746729", "GSM746730", "GSM746731", "GSM746732", "GSM746733", "GSM746734", "GSM746735", "GSM746736", "GSM746737", "GSM746738", "GSM746739", "GSM746740", "GSM746741", "GSM746742", "GSM746743", "GSM746744", "GSM746745", "GSM746746", "GSM746747", "GSM746748", "GSM746750", "GSM746751", "GSM746752"], "sample_count": 26, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "B cell signature during inactive systemic lupus", "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:GSE49454", "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=GSE49454", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE49454", "version": null, "note": "The original contributions presented in the study are included in the article/supplementary material. We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). Further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/supplementary material. We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). Further inquiries can be directed to the corresponding author.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1199352", "GSM1199353", "GSM1199354", "GSM1199355", "GSM1199356", "GSM1199357", "GSM1199358", "GSM1199359", "GSM1199360", "GSM1199361", "GSM1199362", "GSM1199363", "GSM1199364", "GSM1199365", "GSM1199367", "GSM1199369", "GSM1199373", "GSM1199376", "GSM1199379", "GSM1199381", "GSM1199384", "GSM1199386", "GSM1199388", "GSM1199391", "GSM1199394", "GSM1199396", "GSM1199398", "GSM1199399", "GSM1199400", "GSM1199401", "GSM1199402", "GSM1199403", "GSM1199404", "GSM1199405", "GSM1199406", "GSM1199407", "GSM1199408", "GSM1199409", "GSM1199410", "GSM1199411", "GSM1199412", "GSM1199413", "GSM1199414", "GSM1199415", "GSM1199416", "GSM1199417", "GSM1199418", "GSM1199419", "GSM1199420", "GSM1199421", "GSM1199422", "GSM1199423", "GSM1199424", "GSM1199425", "GSM1199426", "GSM1199427", "GSM1199428", "GSM1199429", "GSM1199430", "GSM1199431", "GSM1199432", "GSM1199433", "GSM1199434", "GSM1199435", "GSM1199436", "GSM1199437", "GSM1199438", "GSM1199439", "GSM1199440", "GSM1199441", "GSM1199442", "GSM1199443", "GSM1199444", "GSM1199445", "GSM1199446", "GSM1199447", "GSM1199448", "GSM1199449", "GSM1199450", "GSM1199451", "GSM1199452", "GSM1199453", "GSM1199454", "GSM1199455", "GSM1199456", "GSM1199457", "GSM1199458", "GSM1199459", "GSM1199460", "GSM1199461", "GSM1199462", "GSM1199463", "GSM1199464", "GSM1199465", "GSM1199466", "GSM1199467", "GSM1199468", "GSM1199469", "GSM1199470", "GSM1199471", "GSM1199472", "GSM1199473", "GSM1199474", "GSM1199475", "GSM1199476", "GSM1199477", "GSM1199478", "GSM1199479", "GSM1199480", "GSM1199481", "GSM1199482", "GSM1199483", "GSM1199484", "GSM1199485", "GSM1199486", "GSM1199487", "GSM1199488", "GSM1199489", "GSM1199490", "GSM1199491", "GSM1199492", "GSM1199493", "GSM1199494", "GSM1199495", "GSM1199496", "GSM1199497", "GSM1199498", "GSM1199499", "GSM1199500", "GSM1199501", "GSM1199502", "GSM1199503", "GSM1199504", "GSM1199505", "GSM1199506", "GSM1199507", "GSM1199508", "GSM1199509", "GSM1199510", "GSM1199511", "GSM1199512", "GSM1199513", "GSM1199514", "GSM1199515", "GSM1199516", "GSM1199517", "GSM1199518", "GSM1199519", "GSM1199520", "GSM1199521", "GSM1199522", "GSM1199523", "GSM1199524", "GSM1199525", "GSM1199526", "GSM1199527", "GSM1199528", "GSM1199529", "GSM1199530", "GSM1199531", "GSM1199532", "GSM1199533", "GSM1199534", "GSM1199535", "GSM1199536", "GSM1199537", "GSM1199538", "GSM1199539", "GSM1199540", "GSM1199541", "GSM1199542", "GSM1199543", "GSM1199544", "GSM1199545", "GSM1199546", "GSM1199547", "GSM1199548"], "sample_count": 177, "group_sizes": null, "group_sizes_basis": null, "platform": "10558", "taxon": "Homo sapiens", "title": "Modular repertoire analyses identify dynamic type I and type II interferon transcriptional signatures in adult SLE patients", "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:GSE50772", "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=GSE50772", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE50772", "version": null, "note": "The original contributions presented in the study are included in the article/supplementary material. We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). Further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/supplementary material. We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). 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We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). Further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/supplementary material. We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). 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We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). Further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/supplementary material. We have uploaded all my source code and experimental data to a cloud disk (https://www.jianguoyun.com/p/DTnH9WsQ9djyCxjnmJYFIAA). Further inquiries can be directed to the corresponding author.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2666720", "GSM2666721", "GSM2666722", "GSM2666723", "GSM2666724", "GSM2666725", "GSM2666726", "GSM2666727", "GSM2666728", "GSM2666729", "GSM2666730", "GSM2666731", "GSM2666732", "GSM2666733", "GSM2666734", "GSM2666735", "GSM2666736", "GSM2666737", "GSM2666738", "GSM2666739", "GSM2666740", "GSM2666741", "GSM2666742", "GSM2666743", "GSM2666744", "GSM2666745", "GSM2666746", "GSM2666747", "GSM2666748", "GSM2666749", "GSM2666750", "GSM2666751", "GSM2666752", "GSM2666753", "GSM2666754", "GSM2666755", "GSM2666756", "GSM2666757", "GSM2666758", "GSM2666759", "GSM2666760", "GSM2666761", "GSM2666762", "GSM2666763", "GSM2666764", "GSM2666765", "GSM2666766", "GSM2666767", "GSM2666768", "GSM2666769", "GSM2666770", "GSM2666771", "GSM2666772", "GSM2666773", "GSM2666774", "GSM2666775", "GSM2666776", "GSM2666777", "GSM2666778"], "sample_count": 59, "group_sizes": null, "group_sizes_basis": null, "platform": "21970", "taxon": "Homo sapiens", "title": "Identification of a neutrophil-related gene expression signature that distinguishes between adult patients with and without nephritis in active systemic lupus erythematosus", "resolution_checked_at": "2026-11-01T17:30:42Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE30153 not downloaded", "asset:data:geo:GSE30153 licence not read", "asset:data:geo:GSE49454 not downloaded", "asset:data:geo:GSE49454 licence not read", "asset:data:geo:GSE50772 not downloaded", "asset:data:geo:GSE50772 licence not read", "asset:data:geo:GSE61635 not downloaded", "asset:data:geo:GSE61635 licence not read", "asset:data:geo:GSE81622 not downloaded", "asset:data:geo:GSE81622 licence not read", "asset:data:geo:GSE99967 not downloaded", "asset:data:geo:GSE99967 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The limma package in R program [19] was used to evaluate differentially expressed genes (DEGs) between SLE and healthy controls, using cutoffs for adjustment: p-value < 0.05 and FC (fold changes) > 1.5."}}, {"id": "method-2", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-3", "family": "machine_learning", 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reader quoted it from the paper. No tolerance is published because the paper states none."}, {"id": "target-published-estimate-auc", "claim_id": "claim-target-result", "operation": "build_graph", "expected_value": 0.967, "unit": "auc", "tolerance": null, "state": "complete", "note": "The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none."}], "gaps": ["method.reader_differs_from_extractor"]}, "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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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