Object-Oriented Variant Database for Genetic Mutation Analysis
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Solution Overview
Problem
Current genetic testing databases are limited by their flat file structures, making it laborious for doctors to interpret genetic test results, especially when multiple mutations need to be considered together, as they lack mechanisms to store information about combinations of mutations that may indicate specific diseases.
Innovation Solution
A system and method using object-oriented concepts to store and describe genetic variants and their relationships, allowing for the creation of variant objects and relation objects that can contain other objects, enabling the representation of complex mutation combinations without requiring new flat file entries, and providing a rich patient report with medical information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If flat file database structures are used to store genetic mutations, then the database is simple to implement and query, but it cannot store information about combinations of mutations and requires laborious manual interpretation
Solution Approach 1:
The patent implements a nested object structure where Variant objects contain Mutation objects, and Relation objects contain Variant objects. This hierarchical nesting allows the database to represent complex relationships between multiple mutations while maintaining a unified, manageable structure. Each level of nesting encapsulates specific information, enabling the system to store combination data without requiring flat, cumbersome file structures.
Solution Approach 2:
The patent transitions from a two-dimensional flat file structure to a multi-dimensional object-oriented structure. By introducing hierarchical levels (Relation → Variant → Mutation) and semantic dimensions (pathogenicity, inheritance patterns, clinical significance), the system gains the ability to represent complex genetic interactions that cannot be captured in traditional flat databases, while still maintaining query efficiency through indexed object relationships.
2Loss of information
If separate database entries are created for each mutation combination, then complete genetic information is stored, but the database becomes extremely large and difficult to maintain
Solution Approach 1:
The Relation object serves multiple functions: it stores combination information, defines pathogenicity relationships, specifies inheritance patterns, and links to clinical significance data. This multi-functionality allows a single Relation object to replace what would otherwise require multiple separate database entries for the same genetic combination, significantly reducing database size while maintaining information completeness.
Solution Approach 2:
The patent merges related genetic information into unified objects. Multiple mutations that form a pathological combination are merged into a single Relation object, which consolidates their individual Variant objects and Mutation objects. This merging eliminates redundant storage of combination data and simplifies maintenance by providing a single point of update for combination-related information.
3Productivity
If traditional database lookup methods are used, then individual mutations can be found, but combination mutations require manual research in literature
Solution Approach 1:
The system implements feedback mechanisms where the database automatically queries for Relation objects based on detected mutation combinations in patient samples. When multiple mutations are identified, the system feeds this combination information back into the database query process, which then returns pre-analyzed pathogenicity and clinical significance data. This automated feedback loop eliminates the need for manual literature research while maintaining high lookup speed.
Solution Approach 2:
The patent performs preliminary analysis of mutation combinations during database population and updates. Relation objects are pre-configured with pathogenicity assessments, inheritance patterns, and clinical significance information before being queried. This preliminary action allows the system to immediately retrieve combination significance data during patient testing without requiring real-time literature searches, significantly improving productivity.
Data Source
AI summary
The invention provides a system and method for describing polymorphisms or genetic variants based on information about mutations and relationships among them. The invention uses object-oriented concepts to describe variants as variant objects and relations among those variants as variant relation object, each object being an instance of an abstract class of genomic feature and able to contain any number of other objects. Information about genetic disorders is stored in association with the object that represents the pathogenic variant. Genetic test results are used to access corresponding objects to provide a report based on variants or polymorphisms in a patient's genetic material.