Kawasaki Disease Gene Expression Diagnostic Method
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Solution Overview
Problem
Current diagnostic methods for Kawasaki disease (KD) are inadequate as they struggle to accurately distinguish KD from other febrile illnesses, leading to delayed diagnosis and increased risk of coronary artery aneurysm formation.
Innovation Solution
A method utilizing whole blood gene expression patterns to identify KD by detecting modulation in gene expression levels of a specific gene signature comprising at least 5 of the 13 genes: CACNA1E, DDIAS, KLHL2, PYROXD2, SMOX, ZNF185, LINC02035, CLIC3, S100P, IFI27, HS.553068, CD163, and RTN1.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If clinical diagnosis based on signs and symptoms is used, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent replaces the mechanical/visual clinical assessment system with a molecular biology-based gene expression analysis system. Instead of relying on physicians visually assessing clinical signs and symptoms, the invention uses RNA sequencing and bioinformatics to detect specific gene expression patterns characteristic of KD, thereby substituting subjective clinical judgment with objective molecular measurements.
Solution Approach 2:
The invention changes the diagnostic parameter from macroscopic clinical signs (fever, rash, lymphadenopathy) to microscopic molecular parameters (gene expression levels of specific genes such as CD163, CCL3, CCL4, and other inflammatory markers). This parameter transformation enables more precise differentiation between KD and other febrile illnesses by measuring the actual molecular response in the patient's blood cells.
2Measurement precision
If gene expression analysis is used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex gene expression analysis into distinct, manageable components: (1) RNA extraction from whole blood, (2) RNA sequencing or microarray analysis, (3) Bioinformatics processing to quantify gene expression levels, and (4) Interpretation of specific gene signatures. This segmentation allows each step to be optimized and performed by different specialists or automated systems, reducing the perceived complexity for end users.
Solution Approach 2:
The invention introduces bioinformatics algorithms and computational tools as intermediaries between the raw gene expression data and the clinical diagnosis. These computational mediaries automatically process the complex data, identify characteristic KD gene signatures, and provide interpretable results, thereby shielding clinicians from the complexity of molecular analysis while maintaining high diagnostic precision.
3Measurement precision
If RNA extraction from exosomes is used, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent extracts only the essential diagnostic information (gene expression levels of specific genes) from the complex biological sample, eliminating the need for complicated exosome isolation steps. By focusing on measuring gene expression directly in whole blood or easily processed samples, the invention takes out the problematic exosome extraction step while retaining the diagnostic precision through alternative molecular markers.
Data Source
AI summary
A method of identifying a subject having Kawasaki disease (KD), which includes discriminating the subject from a subject having another condition, for example other infectious and inflammatory conditions, such as those that present similar symptoms to KD. Also provided is a minimal gene signature employed in the method, as well as primers, probes and gene chips for use in the method.