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.
Although PGTs have been commercialized for more than 10 years, adoption continues to remain low. This is primarily due to the unclear clinical benefits of these genetic tests and the lack of involvement of health authorities and regulatory body oversight. The most widely used PGT for clinical purposes is hereditary cancer testing (HCT), where a multitude of genes are analyzed for inheritable cancer prediction. While BRCA1 and BRAC2 mutation testing has been used for breast cancer and ovarian cancer risk prediction, the discovery of new gene markers, variant interpretation tools, and the development of multiplexed assays of multigene panels will make this testing type more clinically relevant. The widespread utilization of PGTs can also foster an era of personalized medicine based on individual disease risk profiles.
PGTs are also being increasingly developed for nonclinical purposes, and they are widely available in the direct-to-consumer (DTC) format where individual genomes are assessed to predict innate traits and improve overall health and wellness.
This Frost & Sullivan research service discusses the importance of predictive genetic testing in disease susceptibility prediction, the discovery of novel disease biomarkers for drug discovery, pharmacogenomics, metabolism, nutrigenomic profiling, and well-being, among other topics.
Several new companies have entered this market, and they are focused on reducing test costs and improving test sensitivity and accuracy. Collaborations are also on the rise, with pharmaceutical companies partnering with PGT developers and public healthcare systems engaging with multiple entities to work on genomic analysis to accelerate preventive health strategies at a national level. The deployment of advanced data analysis tools and data storage and management systems is also fostering the growth of PGTs.