{"doi":"10.3389/fimmu.2022.945583","title":"Prophylactic treatment of Glycyrrhiza glabra mitigates COVID-19 pathology through inhibition of pro-inflammatory cytokines in the hamster model and NETosis","abstract":"Severe coronavirus disease (COVID-19) is accompanied by acute respiratory distress syndrome and pulmonary pathology, and is presented mostly with an inflammatory cytokine release, a dysregulated immune response, a skewed neutrophil/lymphocyte ratio, and a hypercoagulable state. Though vaccinations have proved effective in reducing the COVID-19-related mortality, the limitation of the use of vaccine against immunocompromised individuals, those with comorbidity, and emerging variants remains a concern. In the current study, we investigate for the first time the efficacy of the Glycyrrhiza glabra (GG) extract, a potent immunomodulator, against SARS-CoV-2 infection in hamsters. Prophylactic treatment with GG showed protection against loss in body weight and a 35%–40% decrease in lung viral load along with reduced lung pathology in the hamster model. Remarkably, GG reduced the mRNA expression of pro-inflammatory cytokines and plasminogen activator inhibitor-1 (PAI-1). In vitro , GG acted as a potent immunomodulator by reducing Th2 and Th17 differentiation and IL-4 and IL-17A cytokine production. In addition, GG also showed robust potential to suppress ROS, mtROS, and NET generation in a concentration-dependent manner in both human polymorphonuclear neutrophils (PMNs) and murine bone marrow-derived neutrophils (BMDNs). Taken together, we provide evidence for the protective efficacy of GG against COVID-19 and its putative mechanistic insight through its immunomodulatory properties. Our study provides the proof of concept for GG efficacy against SARS-CoV-2 using a hamster model and opens the path for further studies aimed at identifying the active ingredients of GG and its efficacy in COVID-19 clinical cases.","journal":"Frontiers in Immunology","year":2022,"id":252895,"datarank":0.47670807455219194,"base_score":3.1780538303479458,"endowment":3.1780538303479458,"self_citation_contribution":0.47670807455219194,"citation_network_contribution":0.0,"self_endowment_contribution":0.47670807455219194,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":23,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9583,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":898126,"name":"Prabhakar Babele","orcid":null,"position":1,"is_corresponding":false},{"id":863961,"name":"Srikanth Sadhu","orcid":null,"position":2,"is_corresponding":false},{"id":898127,"name":"Upasna Madan","orcid":null,"position":3,"is_corresponding":false},{"id":707487,"name":"Manas Ranjan Tripathy","orcid":"0000-0003-2683-7872","position":4,"is_corresponding":false},{"id":172034,"name":"Sandeep Goswami","orcid":null,"position":5,"is_corresponding":false},{"id":323260,"name":"Shailendra Mani","orcid":"0000-0001-8541-8315","position":6,"is_corresponding":false},{"id":781825,"name":"Sachin Kumar","orcid":"0000-0002-3835-8935","position":7,"is_corresponding":false},{"id":51566,"name":"Amit Awasthi","orcid":"0000-0002-2563-1971","position":8,"is_corresponding":false},{"id":707490,"name":"Madhu Dikshit","orcid":"0000-0002-2777-0940","position":9,"is_corresponding":false},{"id":702087,"name":"Zaigham Abbas Rizvi","orcid":"0000-0001-7850-5672","position":0,"is_corresponding":true}],"reference_count":80,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:24:50.819822Z","pmid":"36238303","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":[]}