{"doi":"10.3390/metabo14110617","title":"Metabolomic Insights into COVID-19 Severity: A Scoping Review","abstract":"<jats:p>Background: In 2019, SARS-CoV-2, the novel coronavirus, entered the world scene, presenting a global health crisis with a broad spectrum of clinical manifestations. Recognizing the significance of metabolomics as the omics closest to symptomatology, it has become a useful tool for predicting clinical outcomes. Several metabolomic studies have indicated variations in the metabolome corresponding to different disease severities, highlighting the potential of metabolomics to unravel crucial insights into the pathophysiology of SARS-CoV-2 infection. Methods: The PRISMA guidelines were followed for this scoping review. Three major scientific databases were searched: PubMed, the Directory of Open Access Journals (DOAJ), and BioMed Central, from 2020 to 2024. Initially, 2938 articles were identified and vetted with specific inclusion and exclusion criteria. Of these, 42 articles were retrieved for analysis and summary. Results: Metabolites were identified that were repeatedly noted to change with COVID-19 and its severity. Phenylalanine, glucose, and glutamic acid increased with severity, while tryptophan, proline, and glutamine decreased, highlighting their association with COVID-19 severity. Additionally, pathway analysis revealed that phenylalanine, tyrosine and tryptophan biosynthesis, and arginine biosynthesis were the most significantly impacted pathways in COVID-19 severity. Conclusions: COVID-19 severity is intricately linked to significant metabolic alterations that span amino acid metabolism, energy production, immune response modulation, and redox balance.</jats:p>","journal":"Metabolites","year":2024,"id":596604,"datarank":0.3453877639491069,"base_score":2.302585092994046,"endowment":2.302585092994046,"self_citation_contribution":0.3453877639491069,"citation_network_contribution":0.0,"self_endowment_contribution":0.3453877639491069,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1528014,"name":"Mohammad Mehdi Banoei","orcid":"0009-0009-2635-1574","position":1,"is_corresponding":false},{"id":1528016,"name":"Jasnoor Kaur","orcid":null,"position":2,"is_corresponding":false},{"id":1528019,"name":"Chel Hee Lee","orcid":"0000-0001-8209-8176","position":3,"is_corresponding":false},{"id":52065,"name":"Brent W. Winston","orcid":"0000-0003-2993-8871","position":4,"is_corresponding":false},{"id":1528013,"name":"Eric Pimentel","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Metabolomic Insights into COVID-19 Severity: A Scoping Review","abstract":"<jats:p>Background: In 2019, SARS-CoV-2, the novel coronavirus, entered the world scene, presenting a global health crisis with a broad spectrum of clinical manifestations. Recognizing the significance of metabolomics as the omics closest to symptomatology, it has become a useful tool for predicting clinical outcomes. Several metabolomic studies have indicated variations in the metabolome corresponding to different disease severities, highlighting the potential of metabolomics to unravel crucial insights into the pathophysiology of SARS-CoV-2 infection. Methods: The PRISMA guidelines were followed for this scoping review. Three major scientific databases were searched: PubMed, the Directory of Open Access Journals (DOAJ), and BioMed Central, from 2020 to 2024. Initially, 2938 articles were identified and vetted with specific inclusion and exclusion criteria. Of these, 42 articles were retrieved for analysis and summary. Results: Metabolites were identified that were repeatedly noted to change with COVID-19 and its severity. Phenylalanine, glucose, and glutamic acid increased with severity, while tryptophan, proline, and glutamine decreased, highlighting their association with COVID-19 severity. Additionally, pathway analysis revealed that phenylalanine, tyrosine and tryptophan biosynthesis, and arginine biosynthesis were the most significantly impacted pathways in COVID-19 severity. Conclusions: COVID-19 severity is intricately linked to significant metabolic alterations that span amino acid metabolism, energy production, immune response modulation, and redox balance.</jats:p>","is_dataset_classified":null,"base_score":2.1972245773362196,"endowment":2.1972245773362196,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"39590853","pmcid":"PMC11596841","openalex_id":"https://openalex.org/W4404263896","authors":[],"funders":[{"funder_name":"Lung Association, Alberta","grant_id":"n/a","title":null},{"funder_name":"Lung Association, Alberta","grant_id":"","title":null},{"funder_name":"NWT (National Grant Review program)","grant_id":"","title":null},{"funder_name":"University of Calgary","grant_id":"","title":null},{"funder_name":"Fluidome, Inc.","grant_id":"","title":null}],"total_grants":5,"fwci":1.3091,"citation_percentile":0.8005391,"influential_citations":0,"citation_trend":[{"year":2024,"count":1},{"year":2025,"count":3},{"year":2026,"count":4}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://www.mdpi.com/2218-1989/14/11/617/pdf?version=1731419949","host_type":"journal"},{"url":"https://www.mdpi.com/2218-1989/14/11/617/pdf?version=1731419949","host_type":"publisher"},{"url":"https://www.mdpi.com/2218-1989/14/11/617/pdf","host_type":"publisher"},{"url":"https://doi.org/10.3390/metabo14110617","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/39590853","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11596841","host_type":"repository"},{"url":"https://doaj.org/article/c7403d2d351b4ae988ce997662b2d667","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11596841/pdf/metabolites-14-00617.pdf","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC11596841","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC11596841?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Metabolomics and Mass Spectrometry Studies","COVID-19 Clinical Research Studies","Long-Term Effects of COVID-19"],"mesh_terms":[],"keywords":["Metabolomics","Metabolome","Coronavirus disease 2019 (COVID-19)","Glutamine","Medicine","Disease","Biology","Bioinformatics","Amino acid","Internal medicine","Biochemistry","Infectious disease (medical specialty)","Acute respiratory distress syndrome (ARDS)","Disease severity","Scoping Review","Covid-19","Sars-cov-2"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Reduced inequalities"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-28T10:44:58.928627Z","pmid":null,"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":[]}