Study predicts the future of antibody testing may move toward technologically advanced platforms that can test for multiple antibody types in a single blood sample.
Investigators have developed a new technique for accurately assessing the exposure of a population to a particular virus using influenza as a model, according to a study published in Nature Communications. The study authors believe this method overcomes common roadblocks to exposure assessment, including the possibility of multiple circulating strains and the fact that individuals can be vaccinated or naturally immune.
To conduct the study, investigators specifically examined the attack rate for human influenza A virus in a tropical setting. This virus is composed of 2 subtypes—H3N2 and H1N1—and multiple strains. The researchers define attack rate as an estimate of how many people have been infected with a particular disease, regardless of whether they had symptoms or whether they were tested or not.
“Accurately estimating the attack rate of a virus sounds like something epidemiologists should be able to do quite easily, but there are at least 4 major complications,” said Maciej Boni, PhD, in a press release. “First, you need to pre-plan collections of blood samples, otherwise there’s no way to get a snapshot of who in the population right now has antibodies and who doesn’t. Second, when testing for antibodies, you cannot always differentiate someone who was infected from someone who was vaccinated. Third, antibodies wane, so you may not be able to tell if someone was infected if their antibody levels are low now. Finally, many pathogens circulate as groups of strains or groups of variants, and there may be no laboratory assay to test for general exposure to any of these variants.”
The investigators used a dataset of 24,402 general-population serum samples collected in central and southern Vietnam between 2009 and 2015, and assayed the samples for antibodies to 11 different strains of human influenza A. These included the 1918 pandemic Spanish Flu strain and the 2009 swine flu pandemic virus strain, which are within the H1N1 subtype. They then used this dataset to derive a composite antibody measurement across both subtypes of influenza and across all the different strains.
“This composite measurement allowed us to more accurately estimate who had been infected by any strain and who hadn’t,” Boni said in the release. “This gives us a general picture of the disease burden of influenza in the tropical environment of southern and central Vietnam.”
The study results suggest an average of 26% of the Vietnamese population is exposed to subtype H3N2 influenza every year, and 16% is exposed to subtype H1N1. According to the investigators, these rates are slightly higher than the expected level of influenza exposure in temperate countries, which have winter flu seasons, but they have yet to analyze temperate country data with this approach.
“The future of antibody testing will be to move toward technologically advanced platforms that can test for multiple antibody types in a single blood sample,” said Marion Koopmans, PhD, and head of the Viroscience Department at the Erasmus Medical Centre 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 at a larger scale.”
New technique better assesses exposure of a population to a virus [news release]. EurekAlert; November 22, 2021. Accessed December 1, 2021. https://www.eurekalert.org/news-releases/935694