Biomarkers Found for COVID-19 Condition in Children May Help Predict Disease Severity and Develop MIS-C Therapies
|
By HospiMedica International staff writers Posted on 01 Sep 2021 |

Illustration
Researchers have found biomarkers that could help predict the severity of a rare but serious complication in children with COVID-19.
The findings of the study led by Cedars-Sinai (Los Angeles, CA, USA) may help predict disease severity and develop therapies for Multisystem Inflammatory Syndrome in Children (MIS-C). This rare but serious inflammatory condition that affects children who contract COVID-19 produces a distinctive pattern of biomarkers that may help physicians predict disease severity and also aid researchers in developing new treatments, according to findings of the study.
The Cedars-Sinai study focused on MIS-C, an inflammatory response involving multiple organs that can occur weeks after infection with SARS-CoV-2, the virus that causes COVID-19. The investigators examined a small group of patients to identify an array of pathogenic pathways culminating in MIS-C, along with proteins in the blood with potential to act as biomarkers to forecast the severity of the syndrome and help drive treatment decisions. A picture is emerging of MIS-C as an autoimmune disease in which the immune system becomes overactive and mistakenly attacks the body's own organs, according to the researchers. This process may be triggered by widespread tissue damage caused by the SARS-CoV-2 infection.
Children with MIS-C often present symptoms similar to those observed in the so-called cytokine storm, an inflammatory response that can be fatal in COVID-19 patients. These symptoms may include persistent fever and gastrointestinal, respiratory, neurological and cardiovascular problems, such as shock and heart muscle inflammation. Previous research had uncovered similar biological processes involved in MIS-C, the cytokine storm and toxic shock syndrome - a rare, life-threatening complication of bacterial infections. For the new study, the research team adopted an interdisciplinary approach in which they examined 69 children, including those with and without MIS-C and seven with another pediatric inflammatory disorder - Kawasaki disease. Future investigations are needed to validate the findings in a larger patient group, according to the researchers.
"We deployed an array of advanced techniques, including proteomics, RNA sequencing and analyses of antibodies and immune system signaling," said Jennifer Van Eyk, PhD, director of the Advanced Clinical Biosystems Research Institute in the Smidt Heart Institute at Cedars-Sinai, and an expert on proteomics - the study of proteins at the molecular and genetic levels. "By combining forces, we are better able to accelerate scientific discoveries to keep pace with the rapidly evolving pandemic and to inform clinical decisions."
Related Links:
Cedars-Sinai
The findings of the study led by Cedars-Sinai (Los Angeles, CA, USA) may help predict disease severity and develop therapies for Multisystem Inflammatory Syndrome in Children (MIS-C). This rare but serious inflammatory condition that affects children who contract COVID-19 produces a distinctive pattern of biomarkers that may help physicians predict disease severity and also aid researchers in developing new treatments, according to findings of the study.
The Cedars-Sinai study focused on MIS-C, an inflammatory response involving multiple organs that can occur weeks after infection with SARS-CoV-2, the virus that causes COVID-19. The investigators examined a small group of patients to identify an array of pathogenic pathways culminating in MIS-C, along with proteins in the blood with potential to act as biomarkers to forecast the severity of the syndrome and help drive treatment decisions. A picture is emerging of MIS-C as an autoimmune disease in which the immune system becomes overactive and mistakenly attacks the body's own organs, according to the researchers. This process may be triggered by widespread tissue damage caused by the SARS-CoV-2 infection.
Children with MIS-C often present symptoms similar to those observed in the so-called cytokine storm, an inflammatory response that can be fatal in COVID-19 patients. These symptoms may include persistent fever and gastrointestinal, respiratory, neurological and cardiovascular problems, such as shock and heart muscle inflammation. Previous research had uncovered similar biological processes involved in MIS-C, the cytokine storm and toxic shock syndrome - a rare, life-threatening complication of bacterial infections. For the new study, the research team adopted an interdisciplinary approach in which they examined 69 children, including those with and without MIS-C and seven with another pediatric inflammatory disorder - Kawasaki disease. Future investigations are needed to validate the findings in a larger patient group, according to the researchers.
"We deployed an array of advanced techniques, including proteomics, RNA sequencing and analyses of antibodies and immune system signaling," said Jennifer Van Eyk, PhD, director of the Advanced Clinical Biosystems Research Institute in the Smidt Heart Institute at Cedars-Sinai, and an expert on proteomics - the study of proteins at the molecular and genetic levels. "By combining forces, we are better able to accelerate scientific discoveries to keep pace with the rapidly evolving pandemic and to inform clinical decisions."
Related Links:
Cedars-Sinai
Latest COVID-19 News
- Low-Cost System Detects SARS-CoV-2 Virus in Hospital Air Using High-Tech Bubbles
- World's First Inhalable COVID-19 Vaccine Approved in China
- COVID-19 Vaccine Patch Fights SARS-CoV-2 Variants Better than Needles
- Blood Viscosity Testing Can Predict Risk of Death in Hospitalized COVID-19 Patients
- ‘Covid Computer’ Uses AI to Detect COVID-19 from Chest CT Scans
- MRI Lung-Imaging Technique Shows Cause of Long-COVID Symptoms
- Chest CT Scans of COVID-19 Patients Could Help Distinguish Between SARS-CoV-2 Variants
- Specialized MRI Detects Lung Abnormalities in Non-Hospitalized Long COVID Patients
- AI Algorithm Identifies Hospitalized Patients at Highest Risk of Dying From COVID-19
- Sweat Sensor Detects Key Biomarkers That Provide Early Warning of COVID-19 and Flu
- Study Assesses Impact of COVID-19 on Ventilation/Perfusion Scintigraphy
- CT Imaging Study Finds Vaccination Reduces Risk of COVID-19 Associated Pulmonary Embolism
- Third Day in Hospital a ‘Tipping Point’ in Severity of COVID-19 Pneumonia
- Longer Interval Between COVID-19 Vaccines Generates Up to Nine Times as Many Antibodies
- AI Model for Monitoring COVID-19 Predicts Mortality Within First 30 Days of Admission
- AI Predicts COVID Prognosis at Near-Expert Level Based Off CT Scans
Channels
Artificial Intelligence
view channel
AI Platform Interprets Real-Time Wearable Data for Parkinson’s Management
Parkinson’s disease presents fluctuating motor and non-motor symptoms that complicate day-to-day self-management and clinical decision-making. Care teams require timely, longitudinal insight into medication... Read more
Algorithm Identifies Cardiac Arrest Hotspots to Guide AED Placement
Out-of-hospital sudden cardiac arrest is common and usually fatal, and survival depends on rapid defibrillation. Many communities deploy automated external defibrillators without precise guidance, which... Read moreCritical Care
view channel
Synthetic Biology Approach Enables On-Demand Liver Tissue Growth
End-stage liver disease occurs when hepatic injury exceeds the organ’s normal regenerative capacity, leaving transplantation as the only option. Access to donor livers remains limited, with thousands on... Read more
Bioinspired Imaging System Identifies Cancerous Lymph Nodes Intraoperatively
Accurate identification of cancer-involved lymph nodes during surgery remains difficult, forcing trade-offs between complete tumor clearance and the risk of complications such as lymphedema.... Read moreSurgical Techniques
view channel
Fish-Skin Graft Shortens Hospital Stay in Severe Burns
Severely burned patients who require skin grafting face intensive inpatient management, where length of stay and complications such as sepsis, graft loss, venous thromboembolism, and hospital-acquired... Read more
Transcatheter Valve Replacement Demonstrates High Success in Real-World Study
Severe tricuspid regurgitation occurs when the tricuspid valve fails to close, causing backward blood flow that drives right‑sided heart failure symptoms and repeat hospitalizations in older adults.... Read morePatient Care
view channel
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read more
Revolutionary Automatic IV-Line Flushing Device to Enhance Infusion Care
More than 80% of in-hospital patients receive intravenous (IV) therapy. Every dose of IV medicine delivered in a small volume (<250 mL) infusion bag should be followed by subsequent flushing to ensure... Read moreHealth IT
view channel
Automated System Classifies and Tracks Cardiogenic Shock Across Hospital Settings
Cardiogenic shock remains a difficult, time-sensitive emergency, with delayed identification driving poor outcomes and persistently high mortality. Many cases go undocumented even at advanced stages, hindering... Read more
Voice-Driven AI System Enables Structured GI Procedure Documentation
Documentation during gastrointestinal (GI) procedures often competes with real-time clinical decision-making and imposes a significant cognitive burden on physicians. Manual data entry and post-procedure... Read more
EMR-Based Tool Predicts Graft Failure After Kidney Transplant
Kidney transplantation offers patients with end-stage kidney disease longer survival and better quality of life than dialysis, yet graft failure remains a major challenge. Although a successful transplant... Read more
Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
The future of medicine is likely to focus on the personalization of healthcare—understanding exactly what an individual requires and delivering the appropriate combination of nutrients, metabolites, and... Read morePoint of Care
view channelBusiness
view channel
Sinocare Presents AI-Driven Integrated Digital Health Solutions at CMEF
At the 93rd China International Medical Equipment Fair (CMEF), Sinocare presented a comprehensive portfolio of digital health technologies designed to support integrated chronic disease management across... Read more








