Epigenetic Clock for Multi-Tissue Age Prediction
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Solution Overview
Problem
Current methods fail to accurately predict age across various human tissues using DNA methylation levels, with previous studies focusing on specific tissues and not providing a universal predictor that can estimate age irrespective of tissue type.
Innovation Solution
A method involving the measurement of specific CpG methylation markers, forming a linear combination of these markers to estimate chronological or biological age, using a calibration function to transform methylation levels into an epigenetic clock, allowing for age prediction in multiple tissues without requiring adjustments or offsets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If age prediction methods are developed for specific tissues (blood, saliva, brain), then measurement precision for that tissue is improved, but adaptability across different tissue types deteriorates
Solution Approach 1:
The patent develops a universal age prediction method that works across multiple tissue types (blood, saliva, brain, and other human tissues) using a common set of DNA methylation markers and prediction algorithm. This resolves the contradiction by making the measurement method adaptable to different tissues while maintaining prediction accuracy through the use of tissue-agnostic epigenetic markers.
2Measurement precision
If tissue-specific CpG markers are used for age prediction, then measurement precision is improved, but device complexity increases due to needing different markers for different tissues
Solution Approach 1:
The patent employs a single universal set of CpG markers that can be used across all tissue types for age prediction, eliminating the need for tissue-specific marker panels. This reduces device complexity by standardizing the marker set while maintaining prediction precision through the selection of epigenetically stable and tissue-invariant CpG sites.
3Measurement precision
If comprehensive DNA methylation profiling is performed across the genome, then measurement precision is improved, but loss of substance increases due to extensive DNA consumption
Solution Approach 1:
The patent extracts and focuses on a specific subset of highly informative CpG markers that are most predictive of age, rather than performing comprehensive genome-wide methylation profiling. This extraction of key markers reduces DNA consumption and material loss while maintaining high prediction accuracy by concentrating on the most relevant epigenetic signals.
Solution Approach 2:
The patent uses a limited number of selected CpG markers (partial action) rather than analyzing the entire genome, achieving sufficient prediction accuracy with minimal DNA input. This partial approach to methylation profiling reduces substance consumption while maintaining the essential predictive power needed for age estimation.
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 accurate age prediction across different tissues, including inaccessible ones, using accessible tissues like blood or saliva, with high correlation and minimal error, facilitating the assessment of biological age and its implications for health and disease.
Implementation Method 1
measuring the methylation of specific DNA Cytosine-phosphate-Guanine (CpG) methylation markers attached to the individual's DNA
Data Source
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AI summary
A method for determining the age of a biological sample comprising measuring a methylation level of a set of methylation markers in genomic DNA of the biological sample. An age of the biological sample is determined with a statistical prediction algorithm, comprising (a) obtaining a linear combination of the methylation marker levels, and (b) applying a transformation to the linear combination to determine the age of the biological sample.