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pmid:39994392
Atrial fibrillation risk model based on LASSO and SVM algorithms and immune infiltration of key mitochondrial energy metabolism genes.
Xunjie Yang · Weng Lan · Chunyi Lin · Chunyu Zhu · Zicong Ye · Zhishi Chen · Guian Zheng
Scientific reports · 2025 doi:10.1038/s41598-025-91047-3
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Experiment
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Data
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Analysis
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Execution
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Complete file
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This study used bioinformatics and machine learning to explore the relationship between mitochondrial energy metabolism-related genes (MEMRGs) and immune infiltration in AF. The datasets GSE31821, GSE41177, and GSE79768 were retrieved from the Gene Expression Omnibus (GEO) database, and differential expression analysis identified 59 mitochondrial energy metabolism-related differentially expressed genes (MEMRDEGs) associated with AF. Key MEMRDEGs were selected using the least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) methods, and a diagnostic model was developed. Immune infiltration was assessed using single-sample gene set enrichment analysis (ssGSEA) and the microenvironment cell population counter (MCPcounter). The diagnostic model, based on the key genes ACAT1, ALDH1L2, HTT, OGDH, and SLC25A3, achieved an area under the curve (AUC) of 0.903. Significant differences in immune cell composition were observed between the AF and control groups. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE31821", "GSE41177", "GSE79768"], "resolved_accessions": ["GSE31821", "GSE41177", "GSE79768"], "statements": ["The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp."], "basis": "The paper names GSE31821, GSE41177, GSE79768 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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:39994392", "data:geo:GSE31821"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE31821"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:46:45Z", "independence": "single_reader"}, "evidence_check": {"method": "reordered", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 17320, "completion_tokens": 2486, "cached_tokens": 256}}, "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:39994392", "type": "paper", "label": "pmid:39994392"}, {"id": "source:pmid:39994392", "type": "manuscript", "label": "PMID 39994392 full text"}, {"id": "data:geo:GSE31821", "type": "dataset", "label": "GEO GSE31821"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:39994392", "type": "paper", "label": "pmid:39994392"}, {"id": "source:pmid:39994392", "type": "manuscript", "label": "PMID 39994392 full text"}, {"id": "data:geo:GSE31821", "type": "dataset", "label": "GEO GSE31821"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-39994392", "type": "extraction", "used": ["source:pmid:39994392"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE31821", "type": "accession_resolution", "used": ["data:geo:GSE31821"], "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:39994392", "parent_hash": "sha256:172b6d70e50fa632ee185d27d4cbbe34d234fbaaf04e0bd0ee49b8618e885287", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE31821 licence not read", "asset:data:geo:GSE31821 not downloaded", "asset:data:geo:GSE41177 licence not read", "asset:data:geo:GSE41177 not downloaded", "asset:data:geo:GSE79768 licence not read", "asset:data:geo:GSE79768 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The differential analysis of the integrated GEO datasets was executed with the limma R package, which compared the gene expression levels of the AF and normal groups to identify DEGs between the two groups. The LASSO regression method was subsequently executed with glmnet (R package)39, with the settings specified as set. seed (500) and family=\"binomial.” Finally, we built an SVM model using the 52 MEMRDEGs and the SVM technique."], "order_basis": "analysis_only", "id": "assay:1"}]}