{"doi":"10.1016/j.ebiom.2023.104719","title":"Machine learning identifies signatures of macrophage reactivity and tolerance that predict disease outcomes","abstract":"BACKGROUND: Single-cell transcriptomic studies have greatly improved organ-specific insights into macrophage polarization states are essential for the initiation and resolution of inflammation in all tissues; however, such insights are yet to translate into therapies that can predictably alter macrophage fate. METHOD: Using machine learning algorithms on human macrophages, here we reveal the continuum of polarization states that is shared across diverse contexts. A path, comprised of 338 genes accurately identified both physiologic and pathologic spectra of \"reactivity\" and \"tolerance\", and remained relevant across tissues, organs, species, and immune cells (>12,500 diverse datasets). FINDINGS: This 338-gene signature identified macrophage polarization states at single-cell resolution, in physiology and across diverse human diseases, and in murine pre-clinical disease models. The signature consistently outperformed conventional signatures in the degree of transcriptome-proteome overlap, and in detecting disease states; it also prognosticated outcomes across diverse acute and chronic diseases, e.g., sepsis, liver fibrosis, aging, and cancers. Crowd-sourced genetic and pharmacologic studies confirmed that model-rationalized interventions trigger predictable macrophage fates. INTERPRETATION: These findings provide a formal and universally relevant definition of macrophage states and a predictive framework (http://hegemon.ucsd.edu/SMaRT) for the scientific community to develop macrophage-targeted precision diagnostics and therapeutics. FUNDING: This work was supported by the National Institutes for Health (NIH) grant R01-AI155696 (to P.G, D.S and S.D). Other sources of support include: R01-GM138385 (to D.S), R01-AI141630 (to P.G), R01-DK107585 (to S.D), and UG3TR003355 (to D.S, S.D, and P.G). D.S was also supported by two Padres Pedal the Cause awards (Padres Pedal the Cause/RADY #PTC2017 and San Diego NCI Cancer Centers Council (C3) #PTC2017). S.S, G.D.K, and D.D were supported through The American Association of Immunologists (AAI) Intersect Fellowship Program for Computational Scientists and Immunologists. We also acknowledge support from the Padres Pedal the Cause #PTC2021 and the Torey Coast Foundation, La Jolla (P.G and D.S). D.S, P.G, and S.D were also supported by the Leona M. and Harry B. Helmsley Charitable Trust.","journal":"EBioMedicine","year":2023,"id":323427,"datarank":0.5456379239589579,"base_score":3.6375861597263857,"endowment":3.6375861597263857,"self_citation_contribution":0.5456379239589579,"citation_network_contribution":0.0,"self_endowment_contribution":0.5456379239589579,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":37,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9519,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":807708,"name":"Saptarshi Sinha","orcid":"0000-0002-4100-5727","position":1,"is_corresponding":false},{"id":552315,"name":"Gajanan D. Katkar","orcid":"0000-0002-9982-8582","position":2,"is_corresponding":false},{"id":588906,"name":"Daniella Vo","orcid":"0000-0003-3432-2326","position":3,"is_corresponding":false},{"id":356455,"name":"Sahar Taheri","orcid":"0000-0001-6716-7356","position":4,"is_corresponding":false},{"id":356454,"name":"Dharanidhar Dang","orcid":"0000-0002-3802-381X","position":5,"is_corresponding":false},{"id":348404,"name":"Soumita Das","orcid":"0000-0003-3895-3643","position":6,"is_corresponding":false},{"id":294966,"name":"Debashis Sahoo","orcid":"0000-0003-2329-8228","position":7,"is_corresponding":false},{"id":294967,"name":"Pradipta Ghosh","orcid":"0000-0002-8917-3201","position":0,"is_corresponding":true}],"reference_count":89,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:07:52.377944Z","pmid":"37516087","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}