Study predicts that the future of antibody testing may evolve into technologically advanced platforms capable of testing multiple types of antibodies in a single blood sample.
Investigators have developed a new technique to accurately assess a population’s exposure to a particular virus using influenza as a model, according to a study published in Natural communications. The study authors believe this method overcomes common barriers to exposure assessment, including the possibility of multiple strains circulating and the fact that individuals can be vaccinated or naturally immunized.
To conduct the study, investigators specifically looked at the attack rate of human influenza A virus in a tropical environment. This virus is made up of 2 subtypes – H3N2 and H1N1 – and several strains. Researchers define attack rate as an estimate of the number of people infected with a particular disease, whether or not they show symptoms or have been tested or not.
“Accurately estimating the attack rate of a virus sounds like something epidemiologists should be able to do fairly easily, but there are at least 4 major complications,” Maciej Boni, PhD, said in a press release. “First of all, you need to plan blood sample collections in advance, otherwise there is no way to get a snapshot of who in the population currently has antibodies and who does not. . Second, when testing for antibodies, you cannot always tell the difference between an infected person and a vaccinated person. Third, the antibodies go down, so you might not be able to tell if a person has been infected if their antibody levels are low now. Finally, many pathogens circulate as strain clusters or variant clusters, and there may be no laboratory tests to test systemic exposure to any of these variants.
Investigators used a data set of 24,402 serum samples from the general population collected in central and southern Vietnam between 2009 and 2015, and analyzed the samples for antibodies to 11 different strains of human influenza A. These included the pandemic strain of Spanish influenza of 1918 and the pig of 2009 pandemic influenza virus strain, which belong to the H1N1 subtype. They then used this dataset to derive a composite measure of antibodies for the two influenza subtypes and for all of the different strains.
“This composite measure allowed us to more accurately estimate who had been infected with a strain and who had not,” Boni said in the statement. “This gives us a general picture of the disease burden of influenza in the tropical environment of southern and central Vietnam.”
The results of the study suggest that an average of 26% of the Vietnamese population is exposed to the H3N2 subtype each year, and 16% are exposed to the H1N1 subtype. These rates are slightly above the expected level of influenza exposure in temperate countries, which have winter influenza seasons, researchers said, but they have yet to analyze data from temperate countries with this approach.
“The future of antibody testing will be to evolve into technologically advanced platforms that can test multiple types of antibodies in a single blood sample,” said Marion Koopmans, PhD, and head of the Viroscience department at the Center. medical Erasmus in the Netherlands, in a press release. “With a small team, we were able to generate 270,000 antibody measurements in just 2 years. This is proof that this approach could work on a larger scale.
A new technique better assesses a population’s exposure to a virus [news release]. EurekAlert; November 22, 2021. Accessed December 1, 2021. https://www.eurekalert.org/news-releases/935694