CAMBRIDGE, Mass.--(BUSINESS WIRE)--nference, an AI-driven health technology company, today announced the publication of a preprint study in medRxiv, validating the company’s methodology for characterizing SARS-CoV-2 evolution. The study provides the first compelling genomic signal showing how highly transmissive and immuno-evasive variants, such as Omicron and Delta, emerge as dominant variants of concern. The study, titled “Continuous genomic diversification of long polynucleotide fragments drives the emergence of new SARS-CoV-2 variants of concern,” has been submitted for peer review.
Using methodology developed by nference, the study examined 100,000 repetitions of an iterative sampling experiment and compared the number of distinctive 9-unit strings of molecules called nucleotides (9-mers) in the most common strains of SARS-CoV-2. Results showed that each new variant (except for Beta, which did not circulate rapidly worldwide) had more unique strings than the variant that immediately preceded it. The original strain of the virus had 45 unique 9-mers, while Alpha had 109, Beta 69, Gamma 122, Delta 181, and Omicron 295.
While it is generally expected that a virus will accumulate more mutations over time, the unique characteristics of variants of concern at the polynucleotide level provide additional context beyond the number of mutations acquired. This is further demonstrated by the new IHU variant but has not spread rapidly across the globe. Despite having a higher mutational load than Delta, these variants have similar characteristics at the polynucleotide level, demonstrating that an increased mutational load does not imply an increase in distinctiveness. This newly identified pattern may help predict which strains will become variants of concern and inform future vaccine design.
“As the COVID-19 pandemic continues to evolve, it is extremely important for our scientific community to begin to understand how a virus like SARS-CoV-2 manages to adapt its genome over time,” said Venky Soundararajan, Ph.D., Co-Founder and Chief Scientific Officer at nference. “With this level of insight, we can begin to predict which dominant variants are likely to emerge in the future. This methodology can also be applied to retrospectively study the genomic history of human pathogens to give us a clearer picture of infectious viruses. This latest breakthrough is a testament to our commitment to moving this promising era of data science into meaningful cures for patients.”
To facilitate similar real-time assessments on the competitive fitness of potential future variants, nference has launched a publicly available software application called GENI, a pandemic preparedness software tool with genomic inference. The application will help decode how SARS-CoV-2 has evolved over time and is freely accessible to the academic and scientific communities, providing researchers with structured datasets to aid in important decision-making for public health during the COVID pandemic.
About nference
Through its powerful augmented intelligence software nferX®, nference is transforming health care by making biomedical knowledge computable. The nference platform partnership with Mayo Clinic has given an opportunity to synthesize more than 100 years of institutional knowledge, producing real-world evidence in real time by converting large amounts of data into deep insights to advance discovery and development of diagnostics and therapeutics. nference is headquartered in Cambridge, Massachusetts. Follow nference on LinkedIn and Twitter. Visit us at nference.com.
