Research Overview

Predictive genetic testing refers to the testing of genetic mutations and variations in an individual to predict the risk of disease susceptibility and the inheritance of Mendelian diseases and other complex diseases. Genomic analysis studies such as genome-wide association studies (GWAS), SNP arrays, and the WGS of select populations have helped to understand the impact of mutations and variants on health and disease risk; rising awareness and public/private initiatives for preventive healthcare are also driving market growth. Massively parallel NGS-based methods and advanced genomic and cytogenomic analysis tools are used in predictive genetic tests (PGTs) to analyze gene mutations, variants, and chromosomal aberrations, which can increase the susceptibility of a disease; PGTs are also being used to predict disease severity.

The use of large-scale genomics data to develop population-based genomic studies for predictive and preventive health is also gaining traction, and several countries, including the United States and the United Kingdom, have carried out large-scale genomic studies to develop DNA repositories that can be used in preventative healthcare strategies. The key technologies used in genomic analysis include whole genome sequencing (WGS), whole exome sequencing (WES), targeted sequencing (gene panels), and genotyping (SNP arrays, optical genome mapping), and each technology has its own advantages and disadvantages. Combining DNA analysis with microbiome DNA assessment and RNA analysis can improve the clinical utility of PGTs, and many research organizations and start-ups are focusing on combination-based tests to improve clinical utility for disease risk prediction.