Gut Microbiota Risk Modeling for Mild Cognitive Impairment
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Solution Overview
Problem
Existing methods for evaluating the risk of mild cognitive impairment require blood samples to measure L-Ergothioneine concentration, which is inconvenient and not directly related to intestinal microbiota data.
Innovation Solution
A system and method for calculating the risk of mild cognitive impairment using intestinal microbiota data from stool samples, including extraction and analysis of intestinal microorganisms, and a model to predict the probability of impairment based on differences between healthy and impaired microbiota.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If blood samples are collected to measure L-Ergothioneine concentration for evaluating cognitive function, then measurement accuracy is improved, but ease of operation deteriorates due to invasive procedure
Solution Approach 1:
The patent uses intestinal microbiota as an intermediary indicator to indirectly assess cognitive function risk. Instead of directly measuring L-Ergothioneine in blood, the system analyzes microbiota composition from stool samples, which serves as a mediator reflecting cognitive health status. This resolves the contradiction by maintaining measurement reliability through the intermediary while eliminating the invasive blood collection procedure.
2Ease of operation
If intestinal microbiota data is used to calculate mild cognitive impairment risk, then ease of operation is improved through non-invasive stool sample collection, but measurement precision deteriorates compared to direct blood measurement
Solution Approach 1:
The patent establishes intestinal microbiota characteristics as an intermediary biomarker that correlates with cognitive function. The system measures microbiota composition (e.g., ratios of specific bacterial genera) from stool samples, which indirectly reflects L-Ergothioneine-related cognitive health pathways. This intermediary approach maintains ease of operation while achieving sufficient measurement precision for risk assessment.
Solution Approach 2:
The patent replaces the mechanical/biological system of blood sampling and direct L-Ergothioneine measurement with an alternative biological system—microbiota analysis from stool samples. This substitution uses a different biological pathway (gut-brain axis) to achieve the same diagnostic goal, improving ease of operation while maintaining acceptable precision through validated microbiota-cognition correlations.
3Reliability
If a model using intestinal microorganisms representing differences between healthy and impaired microbiota is constructed, then reliability is improved for predicting cognitive impairment, but device complexity increases
Solution Approach 1:
The patent extracts specific, clinically relevant microbiota characteristics from complex microbiota data—such as the ratio of specific bacterial genera (e.g., Prevotella/Firmicutes ratio) or presence of particular taxa. By focusing on these extracted key indicators rather than analyzing the entire microbiota profile, the system improves reliability for cognitive impairment prediction while reducing computational and analytical complexity.
Solution Approach 2:
The patent applies local quality by focusing analysis on specific microbiota components most strongly associated with cognitive function, rather than uniformly analyzing all microbiota. The model weights and prioritizes particular bacterial taxa or functional markers that have demonstrated local (specific) associations with cognitive health, improving predictive reliability while simplifying the overall assessment framework.
Data Source
AI summary
A technique for calculating a risk of mild cognitive impairment for a subject who submitted a stool sample and a questionnaire, and a system for calculating a risk indicator for mild cognitive impairment is presented. The system includes an extraction unit configured to extract, from a first data related to intestinal microbiota data of a user, a second data related to a factor or intestinal microorganisms that is indicated to relate to the mild cognitive impairment; and a calculation unit configured to input the second data into a model for calculating a probability of the user having the mild cognitive impairment, the model having a third data as a variable, the third data being related to one or more intestinal microorganisms that represents a difference between intestinal microbiota of healthy participants and intestinal microbiota of patients with the mild cognitive impairment, and to calculate the risk of the user for the mild cognitive impairment, wherein the risk for the mild cognitive impairment is a probability of developing or having already developed the mild cognitive impairment.