Ontology highlight
ABSTRACT:
PROVIDER: PRJNA839643 | ENA |
REPOSITORIES: ENA
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Project description:Mycoplasma pneumoniae clinical isolates WGS
| PRJDB18338 | ENA
Project description:Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.
2022-02-01 | E-MTAB-10129 | biostudies-arrayexpress
Project description:The clinical course of Coronavirus disease 2019 (COVID-19) displays a wide variability, ranging from completely asymptomatic forms to diseases associated with severe clinical outcomes. To reduce the incidence COVID-19 severe outcomes, innovative molecular biomarkers are needed to improve the stratification of patients at the highest risk of mortality and to better customize therapeutic strategies. MicroRNAs associated with COVID-19 outcomes could allow quantifying the risk of severe outcomes and developing models for predicting outcomes, thus helping to customize the most aggressive therapeutic strategies for each patient. Here, we analyzed the circulating miRNA profiles in a set of 12 hospitalized patients with severe COVID-19, with the aim to identify miRNAs associated with in-hospital mortality.
2021-11-24 | GSE189506 | GEO
Project description:The causative organism, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), exhibits a wide spectrum of clinical manifestations in disease-ridden patients. Differences in the severity of COVID-19 ranges from asymptomatic infections and mild cases to the severe form, leading to acute respiratory distress syndrome (ARDS) and multiorgan failure with poor survival. MiRNAs can regulate various cellular processes, including proliferation, apoptosis, and differentiation, by binding to the 3′UTR of target mRNAs inducing their degradation, thus serving a fundamental role in post-transcriptional repression. Alterations of miRNA levels in the blood have been described in multiple inflammatory and infectious diseases, including SARS-related coronaviruses. We used microarrays to delineate the miRNAs and snoRNAs signature in the peripheral blood of severe COVID-19 cases (n=9), as compared to mild (n=10) and asymptomatic (n=10) patients, and identified differentially expressed transcripts in severe versus asymptomatic, and others in severe versus mild COVID-19 cases. A cohort of 29 male age-matched patients were selected. All patients were previously diagnosed with COVID-19 using TaqPath COVID-19 Combo Kit (Thermo Fisher Scientific, Waltham, Massachusetts), or Cobas SARS-CoV-2 Test (Roche Diagnostics, Rotkreuz, Switzerland), with a CT value < 30. Additional criterion for selection was age between 35 and 75 years. Participants were grouped into severe, mild and asymptomatic. Classifying severe cases was based on requirement of high-flow oxygen support and ICU admission (n=9). Whereas mild patients were identified based on symptoms and positive radiographic findings with pulmonary involvement (n=10). Patients with no clinical presentation were labelled as asymptomatic cases (n=10).
2022-03-01 | E-MTAB-10970 | biostudies-arrayexpress
Project description:SARS-CoV-2 induces severe organ damage not only in the lung but also in the liver, heart, kidney, and intestine. It is known that COVID-19 severity correlates with liver dysfunction, but few studies have investigated the liver pathophysiology in COVID-19 patients. Here, we elucidated liver pathophysiology in COVID-19 patients using organs-on-a-chip technology and clinical analyses. First, we developed liver-on-a-chip (LoC) which recapitulating hepatic functions around the intrahepatic bile duct and blood vessel. We found that hepatic dysfunctions, but not hepatobiliary diseases, were strongly induced by SARS-CoV-2 infection. Next, we evaluated the therapeutic effects of COVID-19 drugs to inhibit viral replication and recover hepatic dysfunctions, and found that the combination of anti-viral and immunosuppressive drugs (Remdesivir and Baricitinib) is effective to treat hepatic dysfunctions caused by SARS-CoV-2 infection. Finally, we analyzed the sera obtained from COVID-19 patients, and revealed that COVID-19 patients, who were positive for serum viral RNA, are likely to become severe and develop hepatic dysfunctions, as compared with COVID-19 patients who were negative for serum viral RNA. We succeeded in modeling the liver pathophysiology of COVID-19 patients using LoC technology and clinical samples.
2023-03-07 | GSE193330 | GEO
Project description:To unravel distinct pattern of metagenomic surveillance and respiratory microbiota between Mycoplasma pneumoniae (M. pneumoniae) P1-1 and P1-2 and explore the impact of COVID-19 pandemic on epidemiological features
2024-08-07 | GSE274269 | GEO
Project description:To explore gene expression profiles that is predictive of COVID-19 deterioration, PBMC were collected from early stage non-severe COVID-19 patients and analyzed by grouping patients into 2 groups, deteriorated and non-deteriorated, based on the subsequent clinical courses.
2024-07-01 | GSE207625 | GEO
Project description:The objective of the study was to characterize the immunoreactivity profiles of IgG-reactive epitopes in COVID-19 patients with distinct disease trajectories as well as SARS-CoV-2-naïve sera, using a high-density SARS-CoV-2 whole proteome peptide microarray. The microarray comprised of a total of 5347 individual peptides, each consisting of 15 amino acids with an overlap of 13 amino acids printed in duplicate. The microarray also had a panel of the most relevant mutations from SARS-CoV-2 variants of concern like omicron, alpha, beta, gamma, delta, and others. This study consisted of 29 participants, including 10 naïve controls (5 pre-pandemic and 5 SARS-CoV-2 seronegative) and 19 RT-PCR-confirmed COVID-19 patients. The COVID-19 patients were stratified into two distinct cohorts based on their disease trajectories: the severe cohort (S), in which the patients presented moderate COVID-19 symptoms initially but eventually progressed toward severity; and the recovered cohort (R), in which severe COVID-19 patients progressed toward recovery. Our findings contribute to a deeper understanding of the immunopathogenesis of COVID-19 in patients with different disease trajectories, the effect of mutations on immunoreactivity, and potential cross-reactivity due to exposure to common cold viruses.
2025-03-31 | E-MTAB-14495 | biostudies-arrayexpress
Project description:The SARS-CoV-2 outbreak started on December 2019 in China and rapidly spread worldwide. Clinical manifestations of Coronavirus-disease 2019 (COVID-19) vary broadly, ranging from asymptomatic infection to acute respiratory failure and death, yet the underlying mechanisms and predictive biomarkers for this high variability are still unknown. Emerging evidence has shown that circulating extracellular vesicles (EVs) and extracellular RNAs (exRNAs) are functionally involved in a number of physiologic and pathologic processes. To test the hypothesis that these extracellular components are a key determinant of severity in COVID-19, we collected 31 serum samples from mild COVID-19 patients at admission in single center. After standard therapy without corticosteroids, 9 of 31 patients became severe COVID-19. We analyzed exRNA profiles from the 31 serums and 10 healthy controls for predicting COVID-19 severity value.
2022-03-31 | GSE158877 | GEO