Breaking research appearing online today in Clinical Chemistry, the journal of AACC, demonstrates that a recently developed diagnostic test can detect the new strain of influenza (H7N9) currently causing an outbreak in China.
Since the end of March, 31 people have died from H7N9 infection, and the number of confirmed cases has climbed to 129. Evidence suggests that most H7N9 infections have arisen from poultry-to-human transmission, and that passage of the virus between humans is limited. However, researchers have also found mutations in the virus that are known to help avian viruses adapt to mammalian hosts. If these mutations lead to sustained human-to-human transmission, a serious pandemic could occur.
In this study, Wong et al. designed a diagnostic test with high specificity for the H7N9 virus that does not cross react with distantly related viruses, including all previously known avian and mammalian H7 viruses. They also show that this one-step quantitative real-time PCR assay enables specimen processing in about 3 hours.
According to the authors, this new test should also detect viruses closely related to the H7N9 virus. If confirmed, this capability could prove vital; it's likely that the H7N9 virus is evolving rapidly, and there could be multiple introductions of avian H7N9 viruses from animals to humans. The test also demonstrates a detection limit of ~0.04 median tissue culture infective dose (TCID50) per reaction. This means that it should be sensitive enough to identify patients with active virus replications.
"These results suggest that the established assay should be suitable for screening H7N9 viruses in human samples," said lead investigator Leo Poon, PhD, of the University of Hong Kong, though additional evaluation using clinical specimens from H7N9 patients is needed.
If validated, this diagnostic test could help health officials avert a potential pandemic by allowing them to monitor the spread of the virus. The test could also identify H7N9 patients in the early stages of infection, improving their chances of responding to clinical treatments.