Newswise – New research from UNC Charlotte Center for Computational Intelligence for Predicting Health and Environmental Risks (CIPHER) has found that the two most common strains of the virus that cause COVID-19, SARS-CoV-2 variants BA.2.86 and JN.1, are not significantly better at evading immune responses and causing infection, than its predecessor Omicron has a high number of mutations compared to previous variants.

When the Omicron offshoot BA.2.86 and its close relative JN.1 were first identified, they raised significant public health concerns. These concerns were related to the fact that the original Omicron variant was heavily mutated, leading to both immune evasion and breakthrough infection, and was more contagious and highly mutated compared to previous variants.

There has been some speculation that large numbers of new mutations in BA.2.86 and JN.1 give these variants a greater ability to evade the human immune system and be more transmissible. Extensive computer analysis conducted by a team of scientists and students at UNC Charlotte found that these variants had only small, statistically insignificant changes in immune evasion and infection transmission capacity compared to previous variants, including Omicron.

“These results really surprised me. The fact that Omicron, with its large number of mutations, led to greater immune evasion and an increase in cases and hospitalizations was predictable. However, BA.2.86 and JN.1 have another large set of mutations, and while we have seen some evidence of increased prevalence of these two variants in wastewater and genomic surveillance, there has not been an associated large increase in cases or hospital burden ” said Daniel Janiesthe co-director of CIPHER and Carol Grotnes Belk Distinguished Professor of Bioinformatics and Genomics in the College of Computing and Informatics.

To assess the immune evasion of BA.2.86 and JN.1, the UNC Charlotte research team conducted an extensive study in silico Analysis of the receptor binding domain (RBD; the region of the viral genome against which vaccines are developed) of SARS-CoV-2, comparing the two newer variants with earlier variants, to calculate the relative binding affinity of neutralizing antibodies against the RBD of vaccinated patients , infected patients and therapeutic sources. In addition to antibody analysis, the researchers calculated the relative binding affinity of BA.2.86 and JN.1 to Angiotensin Converting Enzyme-2 (ACE2) compared to previous variants.

The team found minor changes in binding affinity for neutralizing antibodies and ACE2 for BA.2.86 and JN.1 compared to previous SARS-CoV-2 variants. However, these changes were not statistically significant. Therefore, they concluded that BA.2.86 and JN.1 do not show a significant increase in immune evasion or infectious capacity compared to previous variants. In explaining their findings, the researchers note that genomic surveillance, which counts mutations or the relative prevalence of a variant, does not necessarily reveal the functional and health effects of the variant.

In a study due for publication outlining their research, the team discusses the benefits of their approach to understanding the function of variants and the need for future studies to assess variation outside the RBD for future analysis. Future studies in this area will benefit from an increased focus on antibodies derived from memory B cells, which produce antibodies in response to SARS-CoV-2.

“In patients whose immune systems have been exposed to an earlier Omicron variant, memory B cells can provide significant protection against the newer Omicron variants BA.2.86 and JN.1,” said Shirish Yasa, a current graduate student in bioinformatics and computer science Charlotte helped conduct this research. “This protection conferred by memory B cell-derived antibodies is a process that is not yet well studied. An increase in Omicron attacks on memory B cells via vaccination and prior infection may be a significant factor in the overall reduction in hospitalizations and deaths among patients exposed to the offspring of the original Omicron variant.”

This research contributes to the functional understanding of the SARS-CoV-2 variants BA.2.86 and JN.1 and builds on genomic surveillance studies. Additionally, these efforts at UNC Charlotte have introduced new methods for functional computational immunology that will aid in ongoing efforts to mitigate the consequences of the COVID-19 pandemic.

Preprint available at

Authors include:

Shirish Yasa

Sayal Guirales-Medrano

Denis Jacob Machado

Colby T Ford

Daniel Janies

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