<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Gutmann C</submitter><funding>Cancer Research UK</funding><funding>Francis Crick Institute</funding><funding>Versus Arthritis</funding><funding>NHS Foundation Trust</funding><funding>Innovative Medicines Initiative 2 Joint Undertaking</funding><funding>National Institute of Academic Anaesthesia</funding><funding>National Institute for Health Research Clinician Scientist Award</funding><funding>Austrian Ministry for Digital and Economic Affairs</funding><funding>European Union’s Horizon 2020</funding><funding>National Institute for Health Research (NIHR)</funding><funding>Leducq Foundation</funding><funding>UK Medical Research Council Clinical Research Training Fellowship</funding><funding>NIHR Academic Clinical Fellowship in Combined Infection Training</funding><funding>Austrian Research Promotion Agency FFG</funding><funding>Centre for Promoting Vascular Health in the Ageing Community</funding><funding>British Heart Foundation</funding><funding>John Black Charitable Foundation</funding><funding>The NIHR Collaboration for Leadership in Applied Health Research and Care South London at King’s College Hospital NHS Foundation Trust</funding><funding>Rosetrees Trust</funding><funding>Lower Green Foundation</funding><funding>Biomedical Research Centre</funding><funding>Biomedical Research Centre at Guy’s and St Thomas</funding><funding>Medical Research Council</funding><funding>Medizinisch-Wissenschaftlicher Fonds des Buergermeisters der Bundeshauptstadt Wien</funding><funding>Austrian Ministry for Transport, Innovation and Technology</funding><funding>Wellcome Trust</funding><funding>BHF Centre for Vascular Regeneration with Edinburgh</funding><pagination>461-474</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8689968</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>118(2)</volume><pubmed_abstract>&lt;h4>Aims&lt;/h4>Coronavirus disease 2019 (COVID-19) can lead to multiorgan damage. MicroRNAs (miRNAs) in blood reflect cell activation and tissue injury. We aimed to determine the association of circulating miRNAs with COVID-19 severity and 28 day intensive care unit (ICU) mortality.&lt;h4>Methods and results&lt;/h4>We performed RNA-Seq in plasma of healthy controls (n = 11), non-severe (n = 18), and severe (n = 18) COVID-19 patients and selected 14 miRNAs according to cell- and tissue origin for measurement by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in a separate cohort of mild (n = 6), moderate (n = 39), and severe (n = 16) patients. Candidates were then measured by RT-qPCR in longitudinal samples of ICU COVID-19 patients (n = 240 samples from n = 65 patients). A total of 60 miRNAs, including platelet-, endothelial-, hepatocyte-, and cardiomyocyte-derived miRNAs, were differentially expressed depending on severity, with increased miR-133a and reduced miR-122 also being associated with 28 day mortality. We leveraged mass spectrometry-based proteomics data for corresponding protein trajectories. Myocyte-derived (myomiR) miR-133a was inversely associated with neutrophil counts and positively with proteins related to neutrophil degranulation, such as myeloperoxidase. In contrast, levels of hepatocyte-derived miR-122 correlated to liver parameters and to liver-derived positive (inverse association) and negative acute phase proteins (positive association). Finally, we compared miRNAs to established markers of COVID-19 severity and outcome, i.e. SARS-CoV-2 RNAemia, age, BMI, D-dimer, and troponin. Whilst RNAemia, age and troponin were better predictors of mortality, miR-133a and miR-122 showed superior classification performance for severity. In binary and triplet combinations, miRNAs improved classification performance of established markers for severity and mortality.&lt;h4>Conclusion&lt;/h4>Circulating miRNAs of different tissue origin, including several known cardiometabolic biomarkers, rise with COVID-19 severity. MyomiR miR-133a and liver-derived miR-122 also relate to 28 day mortality. MiR-133a reflects inflammation-induced myocyte damage, whilst miR-122 reflects the hepatic acute phase response.</pubmed_abstract><journal>Cardiovascular research</journal><pubmed_title>Association of cardiometabolic microRNAs with COVID-19 severity and mortality.</pubmed_title><pmcid>PMC8689968</pmcid><funding_grant_id>FC001093</funding_grant_id><funding_grant_id>ACF-2019-17-014</funding_grant_id><funding_grant_id>M943</funding_grant_id><funding_grant_id>COVID041</funding_grant_id><funding_grant_id>FS/18/60/34181B</funding_grant_id><funding_grant_id>RE/18/2/34213</funding_grant_id><funding_grant_id>RM/17/3/33381</funding_grant_id><funding_grant_id>FS/18/60/34181</funding_grant_id><funding_grant_id>821283</funding_grant_id><funding_grant_id>871562</funding_grant_id><funding_grant_id>18CVD02</funding_grant_id><funding_grant_id>PG/17/48/32956</funding_grant_id><funding_grant_id>CH/16/3/32406</funding_grant_id><funding_grant_id>SP/17/10/33219</funding_grant_id><funding_grant_id>CH/1999001/11735</funding_grant_id><funding_grant_id>CS-2016-16-011</funding_grant_id><funding_grant_id>MR/R017751/1</funding_grant_id><funding_grant_id>RG/16/14/32397</funding_grant_id><pubmed_authors>Khamina K</pubmed_authors><pubmed_authors>Burnap SA</pubmed_authors><pubmed_authors>Cassel C</pubmed_authors><pubmed_authors>Napoli S</pubmed_authors><pubmed_authors>McPhail MJW</pubmed_authors><pubmed_authors>Merrick B</pubmed_authors><pubmed_authors>Eichinger S</pubmed_authors><pubmed_authors>Mayr M</pubmed_authors><pubmed_authors>Shankar-Hari M</pubmed_authors><pubmed_authors>Mujib SF</pubmed_authors><pubmed_authors>Shah AM</pubmed_authors><pubmed_authors>Theofilatos K</pubmed_authors><pubmed_authors>Hackl M</pubmed_authors><pubmed_authors>Fish M</pubmed_authors><pubmed_authors>Roy R</pubmed_authors><pubmed_authors>Gutmann C</pubmed_authors><pubmed_authors>Schmidt LE</pubmed_authors><pubmed_authors>Traby L</pubmed_authors><pubmed_authors>Nabeebaccus A</pubmed_authors><pubmed_authors>Auzinger G</pubmed_authors><pubmed_authors>Trovato F</pubmed_authors><pubmed_authors>Diendorfer AB</pubmed_authors><pubmed_authors>O'Gallagher K</pubmed_authors><pubmed_authors>Hayday AC</pubmed_authors><pubmed_authors>Edgeworth JD</pubmed_authors><pubmed_authors>Sanderson B</pubmed_authors></additional><is_claimable>false</is_claimable><name>Association of cardiometabolic microRNAs with COVID-19 severity and mortality.</name><description>&lt;h4>Aims&lt;/h4>Coronavirus disease 2019 (COVID-19) can lead to multiorgan damage. MicroRNAs (miRNAs) in blood reflect cell activation and tissue injury. We aimed to determine the association of circulating miRNAs with COVID-19 severity and 28 day intensive care unit (ICU) mortality.&lt;h4>Methods and results&lt;/h4>We performed RNA-Seq in plasma of healthy controls (n = 11), non-severe (n = 18), and severe (n = 18) COVID-19 patients and selected 14 miRNAs according to cell- and tissue origin for measurement by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in a separate cohort of mild (n = 6), moderate (n = 39), and severe (n = 16) patients. Candidates were then measured by RT-qPCR in longitudinal samples of ICU COVID-19 patients (n = 240 samples from n = 65 patients). A total of 60 miRNAs, including platelet-, endothelial-, hepatocyte-, and cardiomyocyte-derived miRNAs, were differentially expressed depending on severity, with increased miR-133a and reduced miR-122 also being associated with 28 day mortality. We leveraged mass spectrometry-based proteomics data for corresponding protein trajectories. Myocyte-derived (myomiR) miR-133a was inversely associated with neutrophil counts and positively with proteins related to neutrophil degranulation, such as myeloperoxidase. In contrast, levels of hepatocyte-derived miR-122 correlated to liver parameters and to liver-derived positive (inverse association) and negative acute phase proteins (positive association). Finally, we compared miRNAs to established markers of COVID-19 severity and outcome, i.e. SARS-CoV-2 RNAemia, age, BMI, D-dimer, and troponin. Whilst RNAemia, age and troponin were better predictors of mortality, miR-133a and miR-122 showed superior classification performance for severity. In binary and triplet combinations, miRNAs improved classification performance of established markers for severity and mortality.&lt;h4>Conclusion&lt;/h4>Circulating miRNAs of different tissue origin, including several known cardiometabolic biomarkers, rise with COVID-19 severity. MyomiR miR-133a and liver-derived miR-122 also relate to 28 day mortality. MiR-133a reflects inflammation-induced myocyte damage, whilst miR-122 reflects the hepatic acute phase response.</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Jan</publication><modification>2024-10-16T05:24:17.567Z</modification><creation>2022-02-11T15:41:50.412Z</creation></dates><accession>S-EPMC8689968</accession><cross_references><pubmed>34755842</pubmed><doi>10.1093/cvr/cvab338</doi></cross_references></HashMap>