Methylation Marker Detection for Respiratory Virus Severity Prediction
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Solution Overview
Problem
Current methods lack effective solutions for detecting and predicting the severity of SARS-CoV-2 infection and treatment response, particularly in identifying subphenotypes that may benefit from specific interventions based on molecular and epigenetic markers.
Innovation Solution
The technology involves analyzing differentially methylated regions (DMRs) and positions (DMPs) in DNA to identify specific methylation markers that can distinguish COVID-19 severity and treatment response, using methods such as bisulfite treatment, methylation-specific PCR, and next-generation sequencing to assess methylation states in biological samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current detection methods are used, then general diagnostic capability is maintained, but ability to predict disease severity and treatment response is insufficient
Solution Approach 1:
The patent segments the detection approach by focusing on specific differentially methylated regions (DMRs) and positions (DMPs) rather than analyzing the entire genome. This targeted segmentation of methylation markers enables precise prediction of disease severity and treatment response while reducing the complexity of the detection system compared to comprehensive genomic analysis.
Solution Approach 2:
The patent transitions from traditional single-omic approaches to a multi-omic integration that combines transcriptomic data with epigenetic methylation markers. This dimensional expansion allows the system to capture both gene expression states and epigenetic regulatory patterns, significantly improving prediction accuracy for disease severity and treatment response.
2Loss of information
If comprehensive multi-omic analysis is performed, then molecular-level understanding of individual responses is improved, but cost and complexity of testing increases
Solution Approach 1:
The patent extracts and isolates specific differentially methylated regions (DMRs) and positions (DMPs) that are most informative for predicting COVID-19 outcomes. By extracting only these critical epigenetic markers rather than analyzing all possible molecular features, the system maintains comprehensive molecular-level insight while reducing analytical complexity and testing costs.
Solution Approach 2:
The patent performs preliminary identification of differentially methylated regions through bioinformatic analysis of multi-omic data, then uses these pre-identified markers for clinical prediction. This preliminary action of selecting the most informative markers beforehand reduces the complexity of subsequent clinical testing while preserving the molecular-level detail needed for accurate individual response prediction.
3Adaptability or versatility
If epigenetic markers are analyzed, then ability to distinguish subphenotypes is improved, but difficulty of detection and measurement increases
Solution Approach 1:
The patent applies local quality by focusing measurement efforts on specific differentially methylated regions (DMRs) and positions (DMPs) that are locally informative for subphenotype classification. Rather than attempting to measure methylation patterns genome-wide, the system targets specific genomic locations with known associations with COVID-19 outcomes, reducing measurement difficulty while maintaining the ability to distinguish subphenotypes.
Solution Approach 2:
The patent changes the measurement parameter from global methylation levels to specific differential methylation at defined DMRs and DMPs. This parameter change enables the use of targeted bisulfite sequencing and methylation-specific PCR assays, which are more feasible for clinical implementation while still providing the epigenetic resolution needed to identify distinct subphenotypes with different treatment responses.
Data Source
AI summary
Methods of detecting, predicting severity of, and/or predicting treatment response to respiratory virus infection in a sample obtained from a subject. The methods include assaying a methylation state of a marker in a sample obtained from a subject and identifying the subject as having respiratory virus infection, a likelihood of severe outcomes of respiratory infection, and/or a likelihood of treatment response depending on the methylation state of the marker. The markers can include bases (DMP) in differentially methylated regions (DMR) as provided herein.