Metabolite Panel for Coronary Artery Disease Risk Stratification
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Solution Overview
Problem
Current methods for assessing and managing coronary artery disease (CAD) are incomplete in understanding the genetic and metabolic factors, leading to inadequate risk stratification and identification of individuals at high risk for cardiovascular events.
Innovation Solution
The use of metabolomics to detect and analyze specific metabolites such as acylcarnitines, amino acids, ketones, and free fatty acids in blood samples to predict the likelihood of CAD and cardiovascular events, allowing for personalized treatment plans including dietary, exercise, and pharmaceutical interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional risk factors are used for CAD assessment, then the assessment is simple and widely applicable, but the understanding of genetic and metabolic factors is incomplete leading to inadequate risk stratification
Solution Approach 1:
The patent segments the CAD risk assessment into multiple independent components: traditional risk factors (age, sex, smoking, hypertension, diabetes, dyslipidemia) and metabolite risk factors (acylcarnitines, amino acids, ketones, free fatty acids). Each component can be assessed separately and then integrated to provide comprehensive risk stratification, thereby improving measurement precision without overwhelming complexity
Solution Approach 2:
The metabolite panel serves multiple functions: it provides diagnostic information about current metabolic state, predictive information about future CAD risk, and stratification information for treatment planning. This multi-functionality allows a single set of measurements to address multiple clinical needs, improving risk stratification accuracy while maintaining practical applicability
2Loss of information
If comprehensive metabolite detection is performed, then the understanding of disease process and risk prediction is enhanced, but the complexity of detection and analysis increases
Solution Approach 1:
The metabolite detection is segmented into distinct categories (acylcarnitines, amino acids, ketones, free fatty acids) that can be measured using standardized techniques. This segmentation allows the complex task of comprehensive metabolite profiling to be broken down into manageable, routine laboratory procedures, reducing the perceived difficulty of detection
Solution Approach 2:
The patent uses metabolites as intermediary biomarkers that reflect underlying genetic and metabolic processes. Rather than directly measuring complex genetic architectures or metabolic pathways, the metabolites serve as accessible, measurable proxies that provide comprehensive information about CAD risk while simplifying the detection process
Data Source
AI summary
Methods of assessing the risk of cardiovascular disease in a subject by detecting the level of at least one metabolite in a sample from the subject are disclosed herein. The level of the metabolite is indicative of the risk of cardiovascular disease in the subject. The metabolites may be acylcarnitines, amino acids, ketones, free fatty acids or hydroxybutyrate. The cardiovascular disease may be risk of a cardiovascular event, presence of coronary artery disease or risk of development of coronary artery disease.