{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34895312", "kind": "science-record", "revision": 4, "content_hash": "sha256:1409502d9623c650d631944acdaf5eaec8c6cd09752b812e27fad7e86f3c19a1", "created_at": "2026-11-01T17:36:36Z", "updated_at": "2026-11-01T22:05:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Risk-focused differences in molecular processes implicated in SARS-CoV-2 infection: corollaries in DNA methylation and gene expression.", "doi": "10.1186/s13072-021-00428-1", "pmid": "34895312", "authors": ["Chaini Konwar", "Rebecca Asiimwe", "Amy M Inkster", "Sarah M Merrill", "Gian L Negri", "Maria J Aristizabal", "Christopher F Rider", "Julie L MacIsaac", "Christopher Carlsten", "Michael S Kobor"], "journal": "Epigenetics & chromatin", "year": 2021, "abstract": "BACKGROUND: Understanding the molecular basis of susceptibility factors to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global health imperative. It is well-established that males are more likely to acquire SARS-CoV-2 infection and exhibit more severe outcomes. Similarly, exposure to air pollutants and pre-existing respiratory chronic conditions, such as asthma and chronic obstructive respiratory disease (COPD) confer an increased risk to coronavirus disease 2019 (COVID-19).\nMETHODS: We investigated molecular patterns associated with risk factors in 398 candidate genes relevant to COVID-19 biology. To accomplish this, we downloaded DNA methylation and gene expression data sets from publicly available repositories (GEO and GTEx Portal) and utilized data from an empirical controlled human exposure study conducted by our team.\nRESULTS: First, we observed sex-biased DNA methylation patterns in autosomal immune genes, such as NLRP2, TLE1, GPX1, and ARRB2 (FDR < 0.05, magnitude of DNA methylation difference Δβ > 0.05). Second, our analysis on the X-linked genes identified sex associated DNA methylation profiles in genes, such as ACE2, CA5B, and HS6ST2 (FDR < 0.05, Δβ > 0.05). These associations were observed across multiple respiratory tissues (lung, nasal epithelia, airway epithelia, and bronchoalveolar lavage) and in whole blood. Some of these genes, such as NLRP2 and CA5B, also exhibited sex-biased gene expression patterns. In addition, we found differential DNA methylation patterns by COVID-19 status for genes, such as NLRP2 and ACE2 in an exploratory analysis of an empirical data set reporting on human COVID-9 infections. Third, we identified modest DNA methylation changes in CpGs associated with PRIM2 and TATDN1 (FDR < 0.1, Δβ > 0.05) in response to particle-depleted diesel exhaust in bronchoalveolar lavage. Finally, we captured a DNA methylation signature associated with COPD diagnosis in a gene involved in nicotine dependence (COMT) (FDR < 0.1, Δβ > 0.05).\nCONCLUSION: Our findings on sex differences might be of clinical relevance given that they revealed molecular associations of sex-biased differences in COVID-19. Specifically, our results hinted at a potentially exaggerated immune response in males linked to autosomal genes, such as NLRP2. In contrast, our findings at X-linked loci such as ACE2 suggested a potentially distinct DNA methylation pattern in females that may interact with its mRNA expression and inactivation status. We also found tissue-specific DNA methylation differences in response to particulate exposure potentially capturing a nitrogen dioxide (NO2) effect-a contributor to COVID-19 susceptibility. While we identified a molecular signature associated with COPD, all COPD-affected individuals were smokers, which may either reflect an association with the disease, smoking, or may highlight a compounded effect of these two risk factors in COVID-19. Overall, our findings point towards a molecular basis of variation in susceptibility factors that may partly explain disparities in the risk for SARS-CoV-2 infection.", "claims": [{"id": "claim-method", "statement": "To investigate sex associated DNA methylation differences in our candidate genes, we first focused on the infection-relevant respiratory tissues (lung, nasal epithelia, and airway epithelia) and applied a linear model on M values for each CpG site using the R limma package. Sex was included as the main effect and age and disease status as the covariates. To account for multiple tests, p values were adjusted using the FDR method.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34895312", "locator": "sections[7] \"DNA methylation analysis: autosomal loci\" paragraph 2", "quote": "To investigate sex associated DNA methylation differences in our candidate genes, we first focused on the infection-relevant respiratory tissues (lung, nasal epithelia, and airway epithelia) and applied a linear model on M values for each CpG site using the R limma package. Sex was included as the main effect and age and disease status as the covariates. To account for multiple tests, p values were adjusted using the FDR method."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Accession numbers for the publicly available data sets utilized in the study are mentioned in the methods section. Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). Additional relevant data, if required is available on request. Data preprocessing R scripts are available on the KoborLab Github repository (https://github.com/kobor-lab/Public-Scripts/tree/master/COVID-19).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34895312", "locator": "sections[28] \"notes\" paragraph 1", "quote": "Accession numbers for the publicly available data sets utilized in the study are mentioned in the methods section. Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). Additional relevant data, if required is available on request. Data preprocessing R scripts are available on the KoborLab Github repository (https://github.com/kobor-lab/Public-Scripts/tree/master/COVID-19)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Overall, our findings point towards a molecular basis of variation in susceptibility factors that may partly explain disparities in the risk for SARS-CoV-2 infection.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34895312", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Overall, our findings point towards a molecular basis of variation in susceptibility factors that may partly explain disparities in the risk for SARS-CoV-2 infection."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Overall, our findings point towards a molecular basis of variation in susceptibility factors that may partly explain disparities in the risk for SARS-CoV-2 infection.", "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:34895312"], "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:GSE101641"], "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:GSE101641"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34895312", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s13072-021-00428-1", "sha256": "sha256:e21cc5d0ed798fef93638f2d07346ec61d197cb4463623b77ada6fce38b6210d", "bytes": 65700, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s13072-021-00428-1", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8665859", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE101641", "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=GSE101641", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE101641", "version": null, "note": "Accession numbers for the publicly available data sets utilized in the study are mentioned in the methods section. Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). Additional relevant data, if required is available on request. Data preprocessing R scripts are available on the KoborLab Github repository (https://github.com/kobor-lab/Public-Scripts/tree/master/COVID-19).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Accession numbers for the publicly available data sets utilized in the study are mentioned in the methods section. Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). Additional relevant data, if required is available on request. 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Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). Additional relevant data, if required is available on request. Data preprocessing R scripts are available on the KoborLab Github repository (https://github.com/kobor-lab/Public-Scripts/tree/master/COVID-19).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Accession numbers for the publicly available data sets utilized in the study are mentioned in the methods section. Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). Additional relevant data, if required is available on request. 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Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). Additional relevant data, if required is available on request. Data preprocessing R scripts are available on the KoborLab Github repository (https://github.com/kobor-lab/Public-Scripts/tree/master/COVID-19).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Accession numbers for the publicly available data sets utilized in the study are mentioned in the methods section. Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). 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Data preprocessing R scripts are available on the KoborLab Github repository (https://github.com/kobor-lab/Public-Scripts/tree/master/COVID-19)."], "basis": "The paper names GSE101641, GSE104471, GSE65163, GSE85568, GSE137716, GSE111629, GSE174818, GSE111396, GSE52401, GSE65205 in 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:34895312", "data:geo:GSE101641"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE101641"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:10:53Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 15661, "completion_tokens": 3078, "cached_tokens": 264}}, "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:34895312", "type": "paper", "label": "pmid:34895312"}, {"id": "source:pmid:34895312", "type": "manuscript", "label": "PMID 34895312 full text"}, {"id": "data:geo:GSE101641", "type": "dataset", "label": "GEO GSE101641"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:34895312", "type": "paper", "label": "pmid:34895312"}, {"id": "source:pmid:34895312", "type": "manuscript", "label": "PMID 34895312 full text"}, {"id": "data:geo:GSE101641", "type": "dataset", "label": "GEO GSE101641"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-34895312", "type": "extraction", "used": ["source:pmid:34895312"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE101641", "type": "accession_resolution", "used": ["data:geo:GSE101641"], "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:34895312", "parent_hash": "sha256:8b3ca5b61e521b2805325d4bfc7a5a259a286bb08c8828e74132a95828d40084", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE101641 licence not read", "asset:data:geo:GSE101641 not downloaded", "asset:data:geo:GSE104471 licence not read", "asset:data:geo:GSE104471 not downloaded", "asset:data:geo:GSE111396 licence not read", "asset:data:geo:GSE111396 not downloaded", "asset:data:geo:GSE111629 licence not read", "asset:data:geo:GSE111629 not downloaded", "asset:data:geo:GSE137716 licence not read", "asset:data:geo:GSE137716 not downloaded", "asset:data:geo:GSE174818 licence not read", "asset:data:geo:GSE174818 not downloaded", "asset:data:geo:GSE52401 licence not read", "asset:data:geo:GSE52401 not downloaded", "asset:data:geo:GSE65163 licence not read", "asset:data:geo:GSE65163 not downloaded", "asset:data:geo:GSE65205 licence not read", "asset:data:geo:GSE65205 not downloaded", "asset:data:geo:GSE85568 licence not read", "asset:data:geo:GSE85568 not downloaded", "execution.not_run", "method.reader_named_unmapped", "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": 0.8, "evidence": ["limma"], "order_basis": "analysis_only", "id": "assay:1"}]},"meta":{"api_version":"v1","automation_ladder_snapshot":"ba34b49490d9bfaf","automation_ladder_caveats":["Method extraction is rule-based and has no hand-judged accuracy sample. 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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}}}