Identification of metabolic biomarkers associated with nonalcoholic fatty liver disease.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37697333", "kind": "science-record", "revision": 3, "content_hash": "sha256:4c27864b262e5ff1a6ca158e9a7d0b85a39cc53dca16fc79a97b8fa3d4159a35", "created_at": "2026-11-01T19:02:30Z", "updated_at": "2026-11-01T22:10:15Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of metabolic biomarkers associated with nonalcoholic fatty liver disease.", "doi": "10.1186/s12944-023-01911-2", "pmid": "37697333", "authors": ["Hua Jiang", "Yang Hu", "Zhibo Zhang", "Xujia Chen", "Jianpeng Gao"], "journal": "Lipids in health and disease", "year": 2023, "abstract": "BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease. Metabolism-related genes significantly influence the onset and progression of the disease. Hence, it is necessary to screen metabolism-related biomarkers for the diagnosis and treatment of NAFLD patients.\nMETHODS: GSE48452, GSE63067, and GSE89632 datasets including nonalcoholic steatohepatitis (NASH) and healthy controls (HC) analyzed in this study were retrieved from the Gene Expression Omnibus (GEO) database. First, differentially expressed genes (DEGs) between NASH and HC samples were obtained. Next, metabolism-related DEGs (MR-DEGs) were identified by overlapping DEGs and metabolism-related genes (MRG). Further, a protein-protein interaction (PPI) network was developed to show the interaction among MR-DEGs. Subsequently, the \"Least absolute shrinkage and selection operator regression\" and \"Random Forest\" algorithms were used to screen metabolism-related genes (MRGs) in patients with NAFLD. Next, immune cell infiltration and gene set enrichment analyses (GSEA) were performed on these metabolism-related genes. Finally, the expression of metabolism-related gene was determined at the transcription level.\nRESULTS: First, 129 DEGs related to NAFLD development were identified among patients with nonalcoholic steatohepatitis (NASH) and healthy control. Next, 18 MR-DEGs were identified using the Venn diagram. Subsequently, four genes, including AMDHD1, FMO1, LPL, and P4HA1, were identified using machine learning algorithms. Moreover, a regulatory network consisting of four genes, 25 microRNAs (miRNAs), and 41 transcription factors (TFs) was constructed. Finally, a significant increase in FMO1 and LPL expression levels and a decrease in AMDHD1 and P4HA1 expression levels were observed in patients in the NASH group compared to the HC group.\nCONCLUSION: Metabolism-related genes associated with NAFLD were identified, containing AMDHD1, FMO1, LPL, and P4HA1, which provide insights into diagnosing and treating patients with NAFLD.", "claims": [{"id": "claim-method", "statement": "The “Least absolute shrinkage and selection operator (LASSO)” regression analysis was performed, and the random forest (RF) algorithm was implemented using the “randomForest” package to screen important genes in the training cohort.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37697333", "locator": "sections[7] \"Machine learning methods\" paragraph 2", "quote": "The “Least absolute shrinkage and selection operator (LASSO)” regression analysis was performed, and the random forest (RF) algorithm was implemented using the “randomForest” package to screen important genes in the training cohort."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Availability of data and materialsThe raw data of this study are derived from the TCGA database (https://portal.gdc.cancer.gov/) and the GEO data portal (https://www.ncbi.nlm.nih.gov/geo/), which are publicly available databases.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37697333", "locator": "sections[27] \"notes\" paragraph 1", "quote": "Availability of data and materialsThe raw data of this study are derived from the TCGA database (https://portal.gdc.cancer.gov/) and the GEO data portal (https://www.ncbi.nlm.nih.gov/geo/), which are publicly available databases."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified four metabolism-related biomarkers—AMDHD1, FMO1, LPL, and P4HA1—as having potential value in diagnosing and treating patients with NAFLD.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37697333", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Metabolism-related genes associated with NAFLD were identified, containing AMDHD1, FMO1, LPL, and P4HA1, which provide insights into diagnosing and treating patients with NAFLD."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The study identified four metabolism-related biomarkers—AMDHD1, FMO1, LPL, and P4HA1—as having potential value in diagnosing and treating patients with NAFLD.", "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:37697333"], "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:GSE48452"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:machine_learning_random_forest", "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:GSE48452"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:machine_learning_random_forest"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37697333", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12944-023-01911-2", "sha256": "sha256:4bbfb8bd8d401cb56d3445e3eec73be90a2d5742d595027aa55ace513d82600c", "bytes": 32020, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12944-023-01911-2", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10494330", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE48452", "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=GSE48452", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE48452", "version": null, "note": "Availability of data and materialsThe raw data of this study are derived from the TCGA database (https://portal.gdc.cancer.gov/) and the GEO data portal (https://www.ncbi.nlm.nih.gov/geo/), which are publicly available databases.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Availability of data and materialsThe raw data of this study are derived from the TCGA database (https://portal.gdc.cancer.gov/) and the GEO data portal (https://www.ncbi.nlm.nih.gov/geo/), which are publicly available databases.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1178970", "GSM1178971", "GSM1178972", "GSM1178973", "GSM1178974", "GSM1178975", "GSM1178976", "GSM1178977", "GSM1178978", "GSM1178979", "GSM1178980", "GSM1178981", "GSM1178982", "GSM1178983", "GSM1178984", "GSM1178985", "GSM1178986", "GSM1178987", "GSM1178988", "GSM1178989", "GSM1178990", "GSM1178991", "GSM1178992", "GSM1178993", "GSM1178994", "GSM1178995", "GSM1178996", "GSM1178997", "GSM1178998", "GSM1178999", "GSM1179000", "GSM1179001", "GSM1179002", "GSM1179003", "GSM1179004", "GSM1179005", "GSM1179006", "GSM1179007", "GSM1179008", "GSM1179009", "GSM1179010", "GSM1179011", "GSM1179012", "GSM1179013", "GSM1179014", "GSM1179015", "GSM1179016", "GSM1179017", "GSM1179018", "GSM1179019", "GSM1179020", "GSM1179021", "GSM1179022", "GSM1179023", "GSM1179024", "GSM1179025", "GSM1179026", "GSM1179027", "GSM1179028", "GSM1179029", "GSM1179030", "GSM1179031", "GSM1179032", "GSM1179033", "GSM1179034", "GSM1179035", "GSM1179036", "GSM1179037", "GSM1179038", "GSM1179039", "GSM1179040", "GSM1179041", "GSM1179042"], "sample_count": 73, "group_sizes": null, "group_sizes_basis": null, "platform": "11532", "taxon": "Homo sapiens", "title": "Human liver biopsy of different phases from control to NASH", "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:GSE63067", "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=GSE63067", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE63067", "version": null, "note": "Availability of data and materialsThe raw data of this study are derived from the TCGA database (https://portal.gdc.cancer.gov/) and the GEO data portal (https://www.ncbi.nlm.nih.gov/geo/), which are publicly available databases.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Availability of data and materialsThe raw data of this study are derived from the TCGA database (https://portal.gdc.cancer.gov/) and the GEO data portal (https://www.ncbi.nlm.nih.gov/geo/), which are publicly available databases.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1539877", "GSM1539878", "GSM1539879", "GSM1539880", "GSM1539881", "GSM1539882", "GSM1539883", "GSM1539884", "GSM1539885", "GSM1539886", "GSM1539887", "GSM1539888", "GSM1539889", "GSM1539890", "GSM1539891", "GSM1539892", "GSM1539893", "GSM1539894"], "sample_count": 18, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Expression data from human non-alcoholic fatty liver disease stages", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE89632", "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=GSE89632", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE89632", "version": null, "note": "Availability of data and materialsThe raw data of this study are derived from the TCGA database (https://portal.gdc.cancer.gov/) and the GEO data portal (https://www.ncbi.nlm.nih.gov/geo/), which are publicly available databases.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Availability of data and materialsThe raw data of this study are derived from the TCGA database (https://portal.gdc.cancer.gov/) and the GEO data portal (https://www.ncbi.nlm.nih.gov/geo/), which are publicly available databases.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2385720", "GSM2385721", "GSM2385722", "GSM2385723", "GSM2385724", "GSM2385725", "GSM2385726", "GSM2385727", "GSM2385728", "GSM2385729", "GSM2385730", "GSM2385731", "GSM2385732", "GSM2385733", "GSM2385734", "GSM2385735", "GSM2385736", "GSM2385737", "GSM2385738", "GSM2385739", "GSM2385740", "GSM2385741", "GSM2385742", "GSM2385743", "GSM2385744", "GSM2385745", "GSM2385746", "GSM2385747", "GSM2385748", "GSM2385749", "GSM2385750", "GSM2385751", "GSM2385752", "GSM2385753", "GSM2385754", "GSM2385755", "GSM2385756", "GSM2385757", "GSM2385758", "GSM2385759", "GSM2385760", "GSM2385761", "GSM2385762", "GSM2385763", "GSM2385764", "GSM2385765", "GSM2385766", "GSM2385767", "GSM2385768", "GSM2385769", "GSM2385770", "GSM2385771", "GSM2385772", "GSM2385773", "GSM2385774", "GSM2385775", "GSM2385776", "GSM2385777", "GSM2385778", "GSM2385779", "GSM2385780", "GSM2385781", "GSM2385782"], "sample_count": 63, "group_sizes": null, "group_sizes_basis": null, "platform": "14951", "taxon": "Homo sapiens", "title": "Genome-wide analysis of hepatic gene expression in patients with non-alcoholic fatty liver disease  and in healthy donors in relation to hepatic fatty acid composition and other nutritional factors", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE48452 not downloaded", "asset:data:geo:GSE48452 licence not read", "asset:data:geo:GSE63067 not downloaded", "asset:data:geo:GSE63067 licence not read", "asset:data:geo:GSE89632 not downloaded", "asset:data:geo:GSE89632 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The “Least absolute shrinkage and selection operator (LASSO)” regression analysis was performed, and the random forest (RF) algorithm was implemented using the “randomForest” package to screen important genes in the training cohort."}}, {"id": "method-2", "family": "principal_component_analysis", "specific": "pca", "label": "Principal component analysis", "dsl_operations": ["pca_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["wide_numeric_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "Principal component analysis"}}, {"id": "method-3", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor", "method.machine_learning_random_forest"]}, "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": false, "required_operations": [], "missing_operations": ["machine_learning_random_forest"], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: random_forest."}, "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": ["GSE48452", "GSE63067", "GSE89632"], "resolved_accessions": ["GSE48452", "GSE63067", "GSE89632"], "statements": ["Availability of data and materialsThe raw data of this study are derived from the TCGA database (https://portal.gdc.cancer.gov/) and the GEO data portal (https://www.ncbi.nlm.nih.gov/geo/), which are publicly available databases."], "basis": "The paper names GSE48452, GSE63067, GSE89632 in Gene Expression Omnibus (GEO) database and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:37697333", "data:geo:GSE48452"], "steps": []}, "must_build": {"dsl_operations": [{"operation": "machine_learning_random_forest", "unlocks_papers": null, "priority": null}], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE48452"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:53:09Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 9228, "completion_tokens": 1677, "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:37697333", "type": "paper", "label": "pmid:37697333"}, {"id": "source:pmid:37697333", "type": "manuscript", "label": "PMID 37697333 full text"}, {"id": "data:geo:GSE48452", "type": "dataset", "label": "GEO GSE48452"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37697333", "type": "paper", "label": "pmid:37697333"}, {"id": "source:pmid:37697333", "type": "manuscript", "label": "PMID 37697333 full text"}, {"id": "data:geo:GSE48452", "type": "dataset", "label": "GEO GSE48452"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37697333", "type": "extraction", "used": ["source:pmid:37697333"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE48452", "type": "accession_resolution", "used": ["data:geo:GSE48452"], "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:37697333", "parent_hash": "sha256:b47d8df98a13797fc95702b9a35fa2c6c587b975d21948ee0ef17afcbb807e6a", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE48452 licence not read", "asset:data:geo:GSE48452 not downloaded", "asset:data:geo:GSE63067 licence not read", "asset:data:geo:GSE63067 not downloaded", "asset:data:geo:GSE89632 licence not read", "asset:data:geo:GSE89632 not downloaded", "execution.not_run", "method.machine_learning_random_forest", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:run_analysis blocked on method:machine_learning_random_forest"], "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": ["erential genes First, the “linear models for microarray data” R package [14] were used to identify d"], "order_basis": "paper_text_order:2168", "id": "assay:1"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["sion Quantitative reverse transcriptase PCR (RT-qPCR) was performed to determine MRG expression p", "n Quantitative reverse transcriptase PCR (RT-qPCR) was performed to determine MRG expression p", "formed using the 2xUniversal Blue SYBR Green qPCR Master Mix (Servicebio, Wuhan, China). All t"], "order_basis": "paper_text_order:3742", "id": "assay:2"}, {"role": "analysis", "definition_id": "machine_learning", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The “Least absolute shrinkage and selection operator (LASSO)” regression analysis was performed, and the random forest (RF) algorithm was implemented using the “randomForest” package to screen important genes in the training cohort."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}