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Novel data-mining approach identifies biomarkers for diagnosis of Kawasaki disease
Adriana H Tremoulet1,2, Janusz Dutkowski3,4, Yuichiro Sato1,2
1Department of Pediatrics, University of California San Diego, La Jolla, California.
Insights
A new eight-biomarker panel can accurately diagnose Kawasaki disease (KD), a serious childhood illness. This diagnostic tool may help speed up treatment and prevent coronary artery damage in children with KD.
Area of Science:
- Pediatric Infectious Diseases
- Immunology
- Biomarker Discovery
Background:
- Kawasaki disease (KD) is a critical condition in children, often misdiagnosed due to overlapping symptoms with common febrile illnesses.
- Delayed diagnosis of KD increases the risk of severe coronary artery damage.
- There is an urgent need for a reliable diagnostic test for KD.
Purpose of the Study:
- To develop and validate a panel of biomarkers for the accurate diagnosis of acute Kawasaki disease.
- To differentiate KD patients from febrile controls (FC) with high clinical utility.
Main Methods:
- Plasma samples were collected from three independent cohorts of KD patients and FC.
- 88 inflammation-associated biomarkers were measured using Luminex bead technology.
- A Random Forest model was employed for biomarker panel selection.
Main Results:
- An eight-biomarker panel, including commonly available laboratory tests, demonstrated high diagnostic accuracy (81-96%) across three independent cohorts.
- The panel identified key biomarkers such as absolute neutrophil count, erythrocyte sedimentation rate, and C-reactive protein.
Conclusions:
- The developed eight-biomarker panel shows significant potential for improving the recognition of Kawasaki disease.
- Prospective validation is recommended before clinical implementation.
- This panel could aid in earlier and more accurate KD diagnosis, potentially reducing complications.
Background:
As Kawasaki disease (KD) shares many clinical features with other more common febrile illnesses and misdiagnosis, leading to a delay in treatment, increases the risk of coronary artery damage, a diagnostic test for KD is urgently needed. We sought to develop a panel of biomarkers that could distinguish between acute KD patients and febrile controls (FC) with sufficient accuracy to be clinically useful.
Methods:
Plasma samples were collected from three independent cohorts of FC and acute KD patients who met the American Heart Association definition for KD and presented within the first 10 d of fever. The levels of 88 biomarkers associated with inflammation were assessed by Luminex bead technology. Unsupervised clustering followed by supervised clustering using a Random Forest model was used to find a panel of candidate biomarkers.
Results:
A panel of biomarkers commonly available in the hospital laboratory (absolute neutrophil count, erythrocyte sedimentation rate, alanine aminotransferase, γ-glutamyl transferase, concentrations of α-1-antitrypsin, C-reactive protein, and fibrinogen, and platelet count) accurately diagnosed 81-96% of KD patients in a series of three independent cohorts.
Conclusion:
After prospective validation, this eight-biomarker panel may improve the recognition of KD.
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