MS Diagnosis via Immune-Microbiome Integration
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Solution Overview
Problem
Current methods for identifying multiple sclerosis (MS) and predicting treatment-seeking behavior in patients are limited by their focus on single systems rather than simultaneous, multi-system evaluations of immune, metabolome, gut microbiome profiles, and diet, failing to account for confounding factors like demographics and diet.
Innovation Solution
A method involving the analysis of blood and fecal samples to determine immune profiles, gut microbiome profiles, and the strength of immune-microbial homeostatic relationships, with specific thresholds for identifying MS patients and predicting treatment-seeking behavior based on the relative abundance of Barnesiella spp.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single-system evaluation methods are used for identifying MS patients, then the diagnostic process is simple, but the identification accuracy and predictive capability are insufficient
Solution Approach 1:
The patent combines multiple evaluation systems (immune profile analysis, metabolome profiling, gut microbiome characterization, and dietary assessment) into an integrated diagnostic approach. This merging of previously separate single-system evaluations creates a multi-system framework that simultaneously assesses multiple biological and environmental factors, thereby improving identification accuracy while managing complexity through systematic integration
Solution Approach 2:
The diagnostic method uses a composite evaluation framework that integrates data from diverse sources (immune markers, metabolites, microbial taxa, dietary components) analogous to composite materials. This composite approach combines the strengths of each individual system to create a more robust and accurate diagnostic tool than any single system could provide alone
2Loss of information
If multi-system evaluations are implemented simultaneously, then comprehensive understanding of immune-microbial interactions is achieved, but the complexity of data analysis and processing increases
Solution Approach 1:
The patent segments the complex multi-system evaluation into distinct analytical modules: immune profile determination, metabolome profiling, gut microbiome characterization, and dietary assessment. Each module processes specific types of data independently, allowing for systematic analysis of complex interactions while managing data processing complexity through structured segmentation of the evaluation framework
Solution Approach 2:
The patent introduces computational algorithms and statistical models as intermediary tools that facilitate the integration and analysis of multi-system data. These intermediaries process and synthesize information from immune, metabolome, microbiome, and dietary assessments, transforming complex raw data into meaningful insights about immune-microbial interactions and treatment predictions
3Measurement precision
If confounding factors like demographics and diet are not addressed, then the study design is simpler, but the predictive accuracy for treatment-seeking behavior is reduced
Solution Approach 1:
The patent applies local quality control by specifically addressing confounding factors (demographics, dietary habits) within the broader multi-system evaluation framework. Rather than treating all factors uniformly, the methodology selectively incorporates and adjusts for specific confounders that may influence treatment-seeking behavior predictions, thereby improving predictive accuracy while managing study design complexity through targeted adjustment
Data Source
AI summary
Methods for identifying MS in a subject based on an analysis of the strength of the immune-microbial homeostatic relationship based on the immune profile and the gut microbiome profile are described. In addition, methods of identifying MS patients likely to seek disease-modifying treatment within six months based on an analysis of the relative abundance of Barnesiella spp. based on the gut microbiome profile are described.