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Clinical Course of Infection and Cross-Species Detection of Equine Parvovirus-Hepatitis.

Jan Felix DrexlerMara KlöhnYannick BrüggemannVolker KinastDaniel TodtAlexander StangMarcha BadenhorstKatja KoeppelAlan GuthrieUrsula GronerChristina PuffMadeleine de le RoiWolfgang BaumgärtnerJessika-Maximiliane V CavalleriEike Steinmann
Published in: Viruses (2021)
Since its first discovery by Arnold Theiler in 1918, serum hepatitis also known as Theiler's disease has been reported worldwide, causing idiopathic acute hepatitis and liver failure in horses. Recent studies have suggested a novel parvovirus, named equine parvovirus hepatitis (EqPV-H), to be associated with Theiler's disease. Despite the severity and potential fatality of EqPV-H infection, little is known about the possibility of developing chronic infections and putative cross-species infection of equine sister species. In the present longitudinal study, we employed qPCR analysis, serology, and biochemical testing as well as pathology examination of liver biopsies and sequence analysis to investigate potential chronic EqPV-H infection in an isolated study cohort of in total 124 horses from Germany over five years (2013-2018). Importantly, our data suggest that EqPV-H viremia can become chronic in infected horses that do not show biochemical and pathological signs of liver disease. Phylogenetic analysis by maximum likelihood model also confirms high sequence similarity and nucleotide conservation of the multidomain nuclear phosphoprotein NS1 sequences from equine serum samples collected between 2013-2018. Moreover, by examining human, zebra, and donkey sera for the presence of EqPV-H DNA and VP1 capsid protein antibodies, we found evidence for cross-species infection in donkey, but not to human and zebra. In conclusion, this study provides proof for the occurrence of persistent EqPV-H infection in asymptomatic horses and cross-species EqPV-H detection in donkeys.
Keyphrases
  • liver failure
  • small molecule
  • risk assessment
  • machine learning
  • drug induced
  • intensive care unit
  • high throughput
  • deep learning
  • big data
  • circulating tumor cells
  • sensitive detection
  • respiratory failure
  • case control