Embryo Genetic Screening Using ROH-Based Risk Assessment
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Solution Overview
Problem
Current preimplantation genetic testing (PGT) techniques fail to comprehensively address the unique genetic risks associated with consanguineous unions, particularly neglecting the cumulative impact of multiple recessive variants and localized homozygosity, leading to an unmet need for more sophisticated methods to quantify and mitigate the risks of autosomal recessive disorders and complex diseases in offspring.
Innovation Solution
A novel PGT-C method integrating global and localized runs of homozygosity (ROH) analysis with polygenic scores and other genetic data to generate a comprehensive risk assessment, using machine learning models to predict embryo selection based on quantifiable differences in homozygosity burden, incorporating factors like clinical significance, pathogenic variant frequency, and familial history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current PGT techniques (PGT-A, PGT-M, PGT-SR, PGT-P) are used for embryo screening, then specific genetic abnormalities can be detected, but they fail to comprehensively assess the cumulative impact of multiple recessive variants and localized homozygosity in consanguineous unions
Solution Approach 1:
The patent combines multiple existing PGT techniques (PGT-A, PGT-M, PGT-SR, PGT-P) into a unified comprehensive screening approach that simultaneously evaluates autosomal aneuploidy, segmental aneuploidy, specific monogenic disorders, and polygenic disease risks, thereby achieving comprehensive risk assessment that none of the individual techniques could provide alone
Solution Approach 2:
The patent creates a universal screening system that can detect multiple types of genetic abnormalities across different inheritance patterns and disease mechanisms within a single testing framework, making the system adaptable to various clinical scenarios in consanguineous unions
2Productivity
If standard PGT methods are applied to consanguineous couples, then common genetic disorders can be screened, but rare variants, novel variants, and cryptic variants remain undetected
Solution Approach 1:
The patent adds a new dimension to variant detection by incorporating whole genome sequencing data that captures rare, novel, and cryptic variants across the entire genome, rather than relying solely on targeted panels or common variant databases, thereby detecting variants that previously remained invisible to standard screening methods
3Device complexity
If existing PGT techniques are used, then individual genetic risks can be assessed, but the cumulative impact of multiple variants with small individual effects is neglected
Solution Approach 1:
The patent merges individual variant risk assessments with polygenic risk scores and runs of homozygosity analysis to calculate an overall cumulative risk score that integrates the effects of multiple variants, including those with small individual effects, thereby preventing loss of cumulative risk information
4Reliability
If comprehensive genetic screening is performed on all embryos, then accurate risk assessment is achieved, but the complexity and cost of the testing increases significantly
Solution Approach 1:
The patent segments the comprehensive screening into distinct analytical components (aneuploidy detection, monogenic disorder screening, polygenic risk assessment, runs of homozygosity analysis) that can be processed separately and integrated, making the complex system more manageable and interpretable while maintaining overall accuracy
Data Source
AI summary
Described herein are systems and methods and systems for preimplantation genetic testing of an embryo derived from consanguineous parents (PGT-C). The methods involve receiving embryonic genetic data and determining a proportion of the genome in long runs of homozygosity for the entire genome (global F value) as well as for one or more regions of interest within the genome (localized F values). The localized F values are weighted based on one or more factors relating to genetic viability and genetic disorders of the embryo. The global F value and weighted localized F values may be integrated with other genetic data to predict relevant risk scores.