{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41081092", "kind": "science-record", "revision": 4, "content_hash": "sha256:8d5bb639a87375341810092d0a121693bb82b93d47c431cfff8f009a6a688384", "created_at": "2026-11-01T20:31:08Z", "updated_at": "2026-11-01T22:57:17Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatic analysis and experimental validation of hub autophagy-related genes as novel biomarkers for type 2 diabetes mellitus and Alzheimer's disease.", "doi": "10.7717/peerj.20143", "pmid": "41081092", "authors": ["Rui Zhang", "Ruowei Wang", "Shuna Zhai", "Chunhong Shen", "Yu An", "Quanri Liu"], "journal": "PeerJ", "year": 2025, "abstract": "Background & Objectives: Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) share considerable similarities in their proposed patho mechanisms. Autophagy, an intrinsic cellular process involved in the degradation of dysfunctional organelles and abnormal proteins, has been implicated in the pathogenesis of both AD and T2DM. This study aims to identify potential shared biomarkers related to autophagy in AD and T2DM by analyzing hub differentially expressed autophagy-related genes (DEARGs) and examining their potential functions.\nMethods: Gene expression profiles for AD and T2DM were acquired from the Gene Expression Omnibus (GEO) database (training sets: GSE109887 for AD and GSE104674 for T2DM; validation sets: GSE122063 for AD and GSE64998 for T2DM). Autophagy-related genes (ARGs) were extracted from multiple databases. DEARGs were identified and integrated with module genes derived from weighted gene co-expression network analysis (WGCNA) to determine key shared ARGs. Then, the STRING database was used to construct a protein-protein interaction (PPI) network, from which hub genes were identified. These hub genes were validated using independent microarray datasets through differential expression analysis, and ROC curves were generated to assess their diagnostic value. Moreover, the expression of the hub genes was validated in brain tissues of T2DM mouse models using qRT-PCR.\nResults: A total of 33 shared DEARGs were identified, among which 12 were designated as hub genes (ANXA5, CCND1, MAP2K1, HSPB1, BNIP3, BAG3, YAP1, MET, FBXW7, CCL2, PFKFB3, CDKN1A) in both AD and T2DM patients. Validation using other datasets confirmed that ANXA5, BAG3, and CDKN1A remained significantly upregulated, while MET remained downregulated in both AD and T2DM patients. Additionally, PFKFB3 showed an inverse expression pattern between the two diseases. The diagnostic performance of these five hub genes was assessed using ROC curves, with all five exhibiting values of area under the curve (AUC) exceeding 0.7 for T2DM in both training and validation sets. However, only MET and PFKFB3 demonstrated good diagnostic efficacy in AD patients. In animal models, qRT-PCR analysis revealed that the expression of ANXA5, BAG3, and MET was consistent with the bioinformatics results. In contrast, the expression of PFKFB3 and CDKN1A did not differ significantly between db/db model mice and db/m control mice.\nConclusions: Our integrated bioinformatics analyses, supported by preliminary experimental validations, identified several hub ARGs shared between AD and T2DM. Among these, ANXA5, BAG3, and MET exhibited consistent expression trends across datasets and experimental models, while CDKN1A and PFKFB3 showed inconsistent expression patterns. These findings underscore the complexity of autophagy-related crosstalk in AD-T2DM comorbidity and highlight the need for further research to clarify their diagnostic and therapeutic potential.", "claims": [{"id": "claim-data-access", "statement": "The following information was supplied regarding data availability:\nThe raw data is available at GEO: GSE109887, GSE104674, GSE122063, and GSE64998.\nThe custom R scripts for bioinformatic analyses are available at GitHub:\n- https://github.com/anyu900222/AD-T2DM-Autophagy,\n- An, Y. (2025). Bioinformatic analysis of hub autophagy-related genes for type 2 diabetes mellitus and Alzheimer’s disease. Zenodo. https://doi.org/10.5281/zenodo.16869519.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41081092", "locator": "sections[31] \"Data Availability\" paragraphs 1-6", "quote": "The following information was supplied regarding data availability:\nThe raw data is available at GEO: GSE109887, GSE104674, GSE122063, and GSE64998.\nThe custom R scripts for bioinformatic analyses are available at GitHub:\n- https://github.com/anyu900222/AD-T2DM-Autophagy,\n- An, Y. (2025). Bioinformatic analysis of hub autophagy-related genes for type 2 diabetes mellitus and Alzheimer’s disease. Zenodo. https://doi.org/10.5281/zenodo.16869519."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified 33 shared differentially expressed autophagy-related genes between Alzheimer’s disease and type 2 diabetes mellitus and selected 12 as hub genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41081092", "locator": "sections[19] \"PPI network construction and identification of hub genes\" paragraph 2", "quote": "The 33 shared genes between AD and T2DM were used to construct a PPI network via the STRING database. As indicated in Fig. 6A, the resulting network was visualized using Cytoscape. Based on node degree ranking, 12 genes (ANXA5, CCND1, MAP2K1, BAG3, BNIP3, HSPB1, CCL2, FBXW7, MET, YAP1, CDKN1A and PFKFB3) were identified as hub genes for further analysis (Fig. 6B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified 33 shared differentially expressed autophagy-related genes between Alzheimer’s disease and type 2 diabetes mellitus and selected 12 as hub genes.", "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:41081092"], "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:GSE104674"], "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:GSE104674"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41081092", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7717/peerj.20143", "sha256": "sha256:a3b43c03145c481d196869a422b3cf525c9bcd45b067b7e5dd9939c3a0f6b5cd", "bytes": 62716, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.7717/peerj.20143", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12510248", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE104674", "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=GSE104674", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE104674", "version": null, "note": "The following information was supplied regarding data availability:\nThe raw data is available at GEO: GSE109887, GSE104674, GSE122063, and GSE64998.\nThe custom R scripts for bioinformatic analyses are available at GitHub:\n- https://github.com/anyu900222/AD-T2DM-Autophagy,\n- An, Y. 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"The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: edger."}, "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": ["GSE109887", "GSE104674", "GSE122063", "GSE64998"], "resolved_accessions": ["GSE109887", "GSE104674", "GSE122063", "GSE64998"], "statements": ["The following information was supplied regarding data availability:\nThe raw data is available at GEO: GSE109887, GSE104674, GSE122063, and GSE64998.\nThe custom R scripts for bioinformatic analyses are available at GitHub:\n- https://github.com/anyu900222/AD-T2DM-Autophagy,\n- An, Y. (2025). Bioinformatic analysis of hub autophagy-related genes for type 2 diabetes mellitus and Alzheimer’s disease. Zenodo. https://doi.org/10.5281/zenodo.16869519."], "basis": "The paper names GSE109887, GSE104674, GSE122063, GSE64998 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:41081092", "data:geo:GSE104674"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE104674"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T20:02:56Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 17390, "completion_tokens": 1859, "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:41081092", "type": "paper", "label": "pmid:41081092"}, {"id": "source:pmid:41081092", "type": "manuscript", "label": "PMID 41081092 full text"}, {"id": "data:geo:GSE104674", "type": "dataset", "label": "GEO GSE104674"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:41081092", "type": "paper", "label": "pmid:41081092"}, {"id": "source:pmid:41081092", "type": "manuscript", "label": "PMID 41081092 full text"}, {"id": "data:geo:GSE104674", "type": "dataset", "label": "GEO GSE104674"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-41081092", "type": "extraction", "used": ["source:pmid:41081092"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE104674", "type": "accession_resolution", "used": ["data:geo:GSE104674"], "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:41081092", "parent_hash": "sha256:1ed7e34ee10b6cdb48b14a43944643b73bb847c9b536d89e424f7948dea75413", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE104674 licence not read", "asset:data:geo:GSE104674 not downloaded", "asset:data:geo:GSE109887 licence not read", "asset:data:geo:GSE109887 not downloaded", "asset:data:geo:GSE122063 licence not read", "asset:data:geo:GSE122063 not downloaded", "asset:data:geo:GSE64998 licence not read", "asset:data:geo:GSE64998 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "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": ["e hub genes were validated using independent microarray datasets through differential expression ana"], "order_basis": "paper_text_order:1284", "id": "assay:1"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["genes was validated in brain tissues of T2DM mouse models using qRT-PCR. Results: A total of 33", "l age of 11 weeks at the study endpoint. The mice were housed under specific-pathogen-free (SPF) co", "were routinely cleaned and disinfected. Four mice were housed in each cage to meet social needs, wi", "e of the procedure. At the end of the study, mice were euthanized by intraperitoneal injection of e"], "order_basis": "paper_text_order:1491", "id": "assay:2"}, {"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": ["Differential expression analysis of autophagy-related genes (DEARGs) was performed using the “limma” R package for the AD and control groups in the GSE109887 dataset, and the “edgeR” package for the T2DM and control groups in the GSE104674 dataset."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]},"meta":{"api_version":"v1","automation_ladder_snapshot":"ba34b49490d9bfaf","automation_ladder_caveats":["Method extraction is rule-based and has no hand-judged accuracy sample. Evidence bands order textual support; method agreement intervals are null (n=0), never probabilities. Work-type validation does not validate methods.","Operation coverage describes only explicitly named methods. It does not prove a complete protocol, compatible parameters, successful compilation or re-execution. Unrecognised or ambiguous methods require review.","Data reachability is a textual accession or public-data statement. No dataset was downloaded or checked for access, completeness or licence.","Capabilities are planning states seeded from the dated equipment register. No bench ownership, completed quote or partner booking is inferred. Procurement counts are dependencies, not guaranteed replications or financial returns.","Tier and blocker counts are deterministic assessments of this corpus, not measured agreement. R3 is reserved for procurement; unresolved methods and data require human work (R4). The most restrictive axis wins, with capability, method, data as tie-breaks. Resolving one blocker can leave another at the same tier."],"engine":"corpus_engine","engine_provider":"rule_based_v1+lex99e1195c7d6f","run_id":"run-20261023T122449232913","source":"esearch","source_detail":"PubMed mirror biomed_pubmed (read-only)","run_status":"complete","imported_at":"2026-11-03T20:16:52+00:00","generated_at":"2026-11-04T02:46:40+00:00","total_papers":5529,"total_assays_tracked":29,"automatable_assay_families":6,"validated":true,"caveat_count":9,"blocking_caveats":5,"caveats":[{"code":"low_evidence_dominates","basis":["4,152 of 5,529 classifications (75.1%) matched no cue evidence and sit at the 0.05 floor.","34 of 230 data_only calls (14.8%) are in that group."],"claim":"Work type and confidence bands","gloss":"Most records were classified from their title and framing alone, with assay-cue coverage at zero.","detail":"Most classifications in this run rest on no matched evidence at all. At the evidence floor the work type comes from title framing and a fixed prior, not from anything in the paper, so the published work-type split should be read as a rough triage signal rather than a measured distribution. The impact is bounded but not removed: since 2026-10-23 the engine excludes floor-confidence records from the shortlist entirely and publishes them separately as held out, so the recommendation is unaffected even though the census is.","status":"unverified","severity":"high"},{"code":"runtime_is_modelled","basis":["Runtime is summed from published per-assay hour figures. Timing awaits the first executed replication.","4,407 of 5,529 records (79.7%) model to 0.00 hours because no assay was matched, which the ranking then reads as \"cheapest\".","0 of 10 shortlisted records carry a 0.00-hour estimate."],"claim":"Estimated replication runtime","gloss":"The hour figures are estimates built from assay mentions; timing awaits the first executed replication.","detail":"The hour figures are a cost model derived from the bench steps implied by each matched assay family. The first executed replication will supply measured timing. Records without an assay match currently receive a zero-hour model value.","status":"unverified","severity":"high"},{"code":"signal_score_without_citations","basis":["5,529 of 5,529 records (100.0%) have no citation count from the source metadata."],"claim":"Signal score","gloss":"The signal score uses publication-type weight because the mirror supplied zero citation counts.","detail":"The source supplied no citation counts for any record in this run, so the signal score is publication-type weight only. The citation term of the ranking is inert here, and the shortlist is ordered by publication type alone.","status":"unverified","severity":"high"},{"code":"abstract_absent","basis":["1,667 of 5,529 records (30.2%) carry no abstract at all."],"claim":"Evidence base for classification","gloss":"Some records contain a title and publication type only, defining the available classification evidence.","detail":"Where the mirror contains a title and publication types only, those fields define the classifier evidence. A methods section is required for fuller automated and human review.","status":"unverified","severity":"medium"},{"code":"classifier_agreement_measured","basis":["Published two-way decision agreement 77.7% (310 of 399 decidable records) from a stratified hand-check of 438 real records.","Three-way diagnostic agreement 73.9% (288 of 390 decidable records).","data_only agreement 75.2% (100 of 133 decidable).","48 record(s) could not be decided from title and abstract and were excluded from the denominator.","56 analysis-only records were published under another work type, so the data_only share is not an upper bound."],"claim":"Published automatable decision","gloss":"This figure has been checked against a human reading the same papers, so we know how often it is right.","detail":"The published automatable / not-automatable distribution comes from a rule-based classifier that was hand-checked against a fixed ground-truth definition. The agreement rates below are measured, not estimated. The three-way work type remains a diagnostic and is reported separately.","status":"measured","severity":"high"},{"code":"llm_comparison_not_measured","basis":["rule_based_v1+lex99e1195c7d6f produced 5,529 of 5,529 classifications.","Measured on 438 labelled records; these are RULE-BASED figures, not model results."],"claim":"Rule-based versus LLM agreement","gloss":"Every number here is the rule engine’s own. Model comparison begins when a working API credential is connected and measured.","detail":"The published two-way decision agreed with a human reading on 310 of 399 decidable records (77.7%). The diagnostic three-way label agreed on 288 of 390 decidable records (73.9%). Every percentage in this run belongs to the rule engine. Model comparison begins when a working API credential is connected and measured.","status":"not_measured","severity":"high"},{"code":"confidence_is_a_band","basis":["low band: 135 of 210 hand-judged records were correct, 64.3% [57.6, 70.5] (95% CI).","medium band: 80 of 104 hand-judged records were correct, 76.9% [68.0, 84.0] (95% CI).","high band: 73 of 76 hand-judged records were correct, 96.0% [89.0, 98.7] (95% CI).","A fitted calibrated probability was built, measured and withdrawn: it overstated held-out accuracy and reorders nothing."],"claim":"Confidence band and evidence score","gloss":"The confidence band carries a measured accuracy interval; 0.85 represents relative rank strength.","detail":"Confidence on this run is a BAND plus its measured accuracy interval. The number stored alongside each record is a monotone evidence score that orders records; 0.85 represents relative rank strength. A fitted probability was withdrawn after it overstated held-out accuracy. Threshold on the band.","status":"measured","severity":"medium"},{"code":"three_way_split_is_diagnostic","basis":["The corpus is published at the two-way decision: automatable or not-automatable. The three-way split (data_only / physical / mixed) is published as a diagnostic with its measured reliability attached, not as a claim, because the rule engine's `mixed` call cannot be defended.","The engine called 22 record(s) mixed; 10 matched the human judgement (45.5%, 95% CI 26.9-65.3).","The engine's `mixed` call is right on 10/22 hand-judged records (45.5%, 95% CI 26.9%-65.3%); a constant `physical` guess scores 36.4%.","The engine's `mixed` call does not reliably beat a constant `physical` guess on the hand-judged records it labels mixed.","The sign of that difference flips between two independent samples, so the three-way refinement is not demonstrably informative.","The mixed stratum contributes a disproportionate share of errors relative to its size.","At title-only depth the physical/mixed split collapses: a title says that work was done, not whether it was also analysed."],"claim":"The published decision is two-way","gloss":"The three-way split is shown for diagnosis only. The published split is two ways.","detail":"Count and filter the corpus on automatable versus not-automatable. The data_only / physical / mixed split remains an internal engine diagnostic because the mixed call has lower measured reliability.","status":"measured","severity":"medium"},{"code":"automatable_flag_unproven","basis":["6 of 29 assay families are marked automatable now: meta_analysis, machine_learning, survival_analysis, pca, molecular_docking, differential_expression.","The flag is a rule over assay family and work type; validation begins with the first executed replication.","It inherits the 75.2% data_only agreement rate, because the flag requires the record to be analysis-only."],"claim":"Automatable now","gloss":"This flag marks assay families the rules classify as data-only. The first executed replication will validate it.","detail":"This flag marks families the rules consider replicable from data alone. Its validity depends on the analysis-only classification and will be measured through an executed replication.","status":"unverified","severity":"medium"}],"confidence_policy":"band_with_measured_interval","confidence_contract":{"policy":"band_with_measured_interval","summary":"Confidence is reported as a BAND with a measured accuracy interval. The raw evidence score supplies monotone ordering. A fitted point estimate was withdrawn after it overstated held-out accuracy.","evidence_score":"A monotone evidence score in [0,1] built from cue mass, axis separation and text coverage. Use it to order records. Interpret 0.85 as relative rank strength.","confidence_band":"low | medium | high. Consumers threshold on this value.","band_accuracy":"Wilson 95% interval on the measured agreement of the hand-judged records in this band.","calibrated_confidence":"WITHDRAWN. Reintroduction requires held-out evidence demonstrating reliable estimates across every bin."},"band_accuracy":{"low":{"n":210,"low":0.576,"band":"low","high":0.7046,"agree":135,"accuracy":0.6429},"high":{"n":76,"low":0.8903,"band":"high","high":0.9865,"agree":73,"accuracy":0.9605},"medium":{"n":104,"low":0.6795,"band":"medium","high":0.8397,"agree":80,"accuracy":0.7692}},"provider":"rule_based_v1+lex99e1195c7d6f","lexicon_id":"99e1195c7d6f","contract_published_at":"2026-10-23T12:25:29.022232+00:00","confidence_is_band":true,"confidence_is_probability":false,"decision_taxonomy":"two_way","decidable_fraction_two_way":0.8854,"decidable_fraction_two_way_low":0.8565,"decidable_fraction_two_way_high":0.9143,"decidable_fraction_three_way":0.8586,"decidable_fraction_three_way_low":0.8287,"decidable_fraction_three_way_high":0.8884,"decidable_population":5529,"validation_sample_size":438,"three_way_cost_fraction":0.0268,"three_way_cost_records":148,"decision_counts":{"automatable":230,"not_automatable":5299},"decision_split":{"automatable":{"count":230,"share":0.04159884246699222},"not_automatable":{"count":5299,"share":0.9584011575330078}},"diagnostic_work_type_counts":{"mixed":24,"physical":5275,"data_only":230}}}