Sleep Apnea Metabolite Profiling for Diagnosis and Treatment Selection
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Solution Overview
Problem
Current diagnosis of sleep apnea relies heavily on costly and inaccessible Polysomnography, lacking reliable biomarkers for accurate diagnosis and treatment prediction.
Innovation Solution
Identify specific metabolites (PC-O-(38:3), SM (43:1), LPC (24:1), and TG (44:1) through mass spectrometry in biological samples to determine the presence of sleep apnea and guide appropriate treatments like ENT surgery, CPAP therapy, or bariatric surgery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Polysomnography is used for diagnosis of sleep apnea, then diagnostic accuracy is improved, but cost and accessibility worsen
Solution Approach 1:
The patent creates a biochemical copy or signature of sleep apnea through metabolite profiling. Instead of requiring direct polysomnographic measurement, the invention detects metabolic biomarkers (such as specific lipid profiles, amino acid concentrations, or metabolic ratios) that serve as indirect copies of the underlying sleep apnea condition, enabling diagnosis through accessible blood or urine tests
Solution Approach 2:
The patent replaces the mechanical/electrical polysomnography system with a biochemical detection system. Rather than using sensors to measure brain waves, eye movements, and respiratory efforts during sleep, the invention substitutes this with mass spectrometry or other biochemical assays to detect metabolic byproducts that indicate sleep apnea, thereby reducing cost and increasing accessibility
2Ease of operation
If no reliable biomarkers are used, then diagnostic simplicity is maintained, but diagnostic capability and treatment prediction worsen
Solution Approach 1:
The patent identifies and utilizes specific changes in metabolic parameters as biomarkers for sleep apnea. By measuring alterations in metabolite concentrations (such as changes in lipid ratios, amino acid levels, or metabolic flux) that occur during sleep apnea episodes, the invention transforms these biochemical parameter changes into reliable diagnostic indicators that maintain simplicity while enhancing diagnostic capability and treatment prediction
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables non-invasive, accessible diagnosis and treatment prediction, facilitating mass screening and monitoring treatment efficacy, thereby improving identification and management of sleep apnea.
Implementation Method 1
performing mass spectrometry (MS) for metabolomics analyses on the biological sample
Data Source
AI summary
The present subject matter relates to a method of diagnosing and treating sleep apnea (SA) in a subject. The method may include determining whether the subject needs a Polysomnography by obtaining a biological sample from the subject to determine if the subject has a metabolite selected from the group consisting of PC-O-(38:3), SM (43:1), LPC (24:1), PC (46:1), and TG (44:1). Expression of one of the metabolites may be associated with the presence of SA in a subject. If the subject has a metabolite associated with the presence of SA, then the method includes conducting a Polysomnography on the subject to further determine if the subject has SA. If the subject is further determined to have SA, the method may then include treating the subject with a treatment of SA selected from the group consisting of ENT multilevel surgery, continuous positive airway pressure therapy, and bariatric surgery.