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1.
J Am Heart Assoc ; 12(6): e027801, 2023 03 21.
Article in English | MEDLINE | ID: covidwho-2264637

ABSTRACT

Background Meta-analysis can identify biological factors that moderate cardiac magnetic resonance myocardial tissue markers such as native T1 (longitudinal magnetization relaxation time constant) and T2 (transverse magnetization relaxation time constant) in cohorts recovering from COVID-19 infection. Methods and Results Cardiac magnetic resonance studies of patients with COVID-19 using myocardial T1, T2 mapping, extracellular volume, and late gadolinium enhancement were identified by database searches. Pooled effect sizes and interstudy heterogeneity (I2) were estimated with random effects models. Moderators of interstudy heterogeneity were analyzed by meta-regression of the percent difference of native T1 and T2 between COVID-19 and control groups (%ΔT1 [percent difference of the study-level means of myocardial T1 in patients with COVID-19 and controls] and %ΔT2 [percent difference of the study-level means of myocardial T2 in patients with COVID-19 and controls]), extracellular volume, and the proportion of late gadolinium enhancement. Interstudy heterogeneities of %ΔT1 (I2=76%) and %ΔT2 (I2=88%) were significantly lower than for native T1 and T2, respectively, independent of field strength, with pooled effect sizes of %ΔT1=1.24% (95% CI, 0.54%-1.9%) and %ΔT2=3.77% (95% CI, 1.79%-5.79%). %ΔT1 was lower for studies in children (median age: 12.7 years) and athletes (median age: 21 years), compared with older adults (median age: 48 years). Duration of recovery from COVID-19, cardiac troponins, C-reactive protein, and age were significant moderators for %ΔT1 and/or %ΔT2. Extracellular volume, adjusted by age, was moderated by recovery duration. Age, diabetes, and hypertension were significant moderators of the proportion of late gadolinium enhancement in adults. Conclusions T1 and T2 are dynamic markers of cardiac involvement in COVID-19 that reflect the regression of cardiomyocyte injury and myocardial inflammation during recovery. Late gadolinium enhancement and to a lesser extent extracellular volume, are more static biomarkers moderated by preexisting risk factors linked to adverse myocardial tissue remodeling.


Subject(s)
COVID-19 , Contrast Media , Child , Humans , Aged , Young Adult , Adult , Middle Aged , Gadolinium , Magnetic Resonance Imaging, Cine/methods , Myocardium/pathology , Magnetic Resonance Imaging/methods , Magnetic Resonance Spectroscopy , Predictive Value of Tests
2.
Viruses ; 14(7)2022 06 23.
Article in English | MEDLINE | ID: covidwho-1911647

ABSTRACT

Coronavirus disease 2019 (COVID-19) is caused by the SARS-CoV-2 virus, responsible for an atypical pneumonia that can progress to acute lung injury. MicroRNAs are small non-coding RNAs that control specific genes and pathways. This study evaluated the association between circulating miRNAs and lung injury associated with COVID-19. Methods: We evaluated lung injury by computed tomography at hospital admission and discharge and the serum expression of 754 miRNAs using the TaqMan OpenArray after hospital discharge in 27 patients with COVID-19. In addition, miR-150-3p was validated by qRT-PCR on serum samples collected at admission and after hospital discharge. Results: OpenArray analysis revealed that seven miRNAs were differentially expressed between groups of patients without radiological lung improvement compared to those with lung improvement at hospital discharge, with three miRNAs being upregulated (miR-548c-3p, miR-212-3p, and miR-548a-3p) and four downregulated (miR-191-5p, miR-151a-3p, miR-92a-3p, and miR-150-3p). Bioinformatics analysis revealed that five of these miRNAs had binding sites in the SARS-CoV-2 genome. Validation of miR-150-3p by qRT-PCR confirmed the OpenArray results. Conclusions: The present study shows the potential association between the serum expression of seven miRNAs and lung injury in patients with COVID-19. Furthermore, increased expression of miR-150 was associated with pulmonary improvement at hospital discharge.


Subject(s)
COVID-19 , Lung Injury , MicroRNAs , COVID-19/genetics , Computational Biology/methods , Humans , MicroRNAs/metabolism , SARS-CoV-2
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