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Plasma multi-omics identify early pathogenesis and biomarkers of SCD post-AMI

ABSTRACT: Plasma multi-omics identify early pathogenesis and biomarkers of SCD post-AMI

PROVIDER: PRJNA915943 | ENA |

REPOSITORIES: ENA

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Plasma multi-omics identify early pathogenesis and biomarkers of SCD post-AMI

Project description:Early identification and treatment of Sudden Cardiac Death (SCD) post-myocardial infarction (MI) are currently limited by unclear warning indicators and elusive pathogenesis. Here, we constructed a comprehensive multi-omics blood atlas in the acute phase of AMI from 55 pairs of SCD patients and matched survivors, confirmed immune dysregulation and metabolic disorders as the biological hubs leading to post-MI SCD. Targeted proteome quantification identified a TOP4 protein-based biomarker panel, which were validated by internal and external cohorts, and confirmed a superior early prediction power of SCD to traditional clinical risk models. Further interventions targeting complement factor D (CFD) suggested a potential therapeutic strategy for high-risk MI. Our study provided valuable knowledge about the molecular changes and pathogenesis of SCD, shed light on accurate risk stratification and potential therapeutic targets in high SCD-risk MI.

2024-12-31 | GSE221740 | GEO

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Project description:miRNAs expression profiles were screened by microarray between the Health, Highrisk, Stable Angia, and AMI patients.

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Human Plasma: Health vs. High risk vs. Stable Angina vs. AMI

Project description:miRNAs expression profiles were screened by microarray between the Health, Highrisk, Stable Angia, and AMI patients. Biological replicates: 8 replicates in each group.

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Plasma Proteomics Identify Biomarkers and Pathogenesis of COVID-19.

Project description:The coronavirus disease 2019 (COVID-19) pandemic is a global public health crisis. However, little is known about the pathogenesis and biomarkers of COVID-19. Here, we profiled host responses to COVID-19 by performing plasma proteomics of a cohort of COVID-19 patients, including non-survivors and survivors recovered from mild or severe symptoms, and uncovered numerous COVID-19-associated alterations of plasma proteins. We developed a machine-learning-based pipeline to identify 11 proteins as biomarkers and a set of biomarker combinations, which were validated by an independent cohort and accurately distinguished and predicted COVID-19 outcomes. Some of the biomarkers were further validated by enzyme-linked immunosorbent assay (ELISA) using a larger cohort. These markedly altered proteins, including the biomarkers, mediate pathophysiological pathways, such as immune or inflammatory responses, platelet degranulation and coagulation, and metabolism, that likely contribute to the pathogenesis. Our findings provide valuable knowledge about COVID-19 biomarkers and shed light on the pathogenesis and potential therapeutic targets of COVID-19.

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NHLBI TOPMed: Outcome Modifying Gene in SCD (OMG-SCD)

Project description:NHLBI TOPMed: Outcome Modifying Gene in SCD (OMG-SCD)

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NHLBI TOPMed: Outcome Modifying Gene in SCD (OMG-SCD)

Project description:NHLBI TOPMed: Outcome Modifying Gene in SCD (OMG-SCD)

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miRNA profiling in the plasma of patients with acute myocardial infarction (AMI)

Project description:Studies of miRNA profiling in the plasma of AMI patients with Left ventricular end diastolic volume (LVEDV) increase or LVEDV decrease between discharge and follow-up Venous blood was collected in citrated tubes prior discharge. Plasma was harvested by centrifugation and stored at -80Â°C until assayed. Identical volumes of plasma from the 30 patients of a group (LVEDV increase or LVEDV decrease) were pooled to reach a final volume of 400ÂµL for each group. The two pools were processed conjointly. Total RNA was extracted using miRVana isolation kit (Applied Biosystems), dephosphorylated and labeled using miRNA Complete Labeling and hybridization kit (Agilent). Hybridization was performed on miRNA Human Microarray Release 12.0 slides (Agilent). 4 arrays per pool were hybridized. Scanning was achieved with the Genepix 4000B Scanner (Molecular Devices, Sunnyvale, USA). Raw data were acquired with the Genepix Pro software (Molecular Devices).

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Effect of AMI-5 on mouse pancreas differentiation

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