BACKGROUND: Serodiagnosis of feline immunodeficiency virus (FIV) is complicated by the use of a formalin-inactivated whole-virus FIV vaccine. Cats respond to immunization with antibodies indistinguishable from those produced during natural infection by currently available diagnostic tests, which are unable to distinguish cats that are vaccinated against FIV, infected with FIV, or both. HYPOTHESIS: An enzyme-linked immunosorbent assay (ELISA) detecting antibodies against formalin-treated FIV whole virus and untreated transmembrane peptide will distinguish uninfected from infected cats, regardless of vaccination status. ANIMALS: Blood samples were evaluated from uninfected unvaccinated cats (n = 73 samples), uninfected FIV-vaccinated cats (n = 89), and FIV-infected cats (n = 102, including 3 from cats that were also vaccinated). METHODS: The true status of each sample was determined by virus isolation. Plasma samples were tested for FIV antibodies by a commercial FIV diagnostic assay and an experimental discriminant ELISA. RESULTS: All samples from uninfected cats were correctly identified by the discriminant ELISA (specificity 100%). Of the samples collected from FIV-infected cats, 99 were correctly identified as FIV-infected (sensitivity 97.1%). CONCLUSIONS AND CLINICAL IMPORTANCE: With the exception of viral isolation, the discriminant ELISA is the most reliable assay for diagnosis of FIV. A practical strategy for the diagnosis of FIV infection would be to use existing commercial FIV antibody assays as screening tests. Negative results with commercial assays are highly reliable predictors for lack of infection. Positive results can be confirmed with the discriminant ELISA. If the discriminant ELISA is negative, the cat is probably vaccinated against FIV but not infected. Positive results are likely to represent infection.
BACKGROUND: Serodiagnosis of feline immunodeficiency virus (FIV) is complicated by the use of a formalin-inactivated whole-virus FIV vaccine. Cats respond to immunization with antibodies indistinguishable from those produced during natural infection by currently available diagnostic tests, which are unable to distinguish cats that are vaccinated against FIV, infected with FIV, or both. HYPOTHESIS: An enzyme-linked immunosorbent assay (ELISA) detecting antibodies against formalin-treated FIV whole virus and untreated transmembrane peptide will distinguish uninfected from infected cats, regardless of vaccination status. ANIMALS: Blood samples were evaluated from uninfected unvaccinated cats (n = 73 samples), uninfected FIV-vaccinated cats (n = 89), and FIV-infectedcats (n = 102, including 3 from cats that were also vaccinated). METHODS: The true status of each sample was determined by virus isolation. Plasma samples were tested for FIV antibodies by a commercial FIV diagnostic assay and an experimental discriminant ELISA. RESULTS: All samples from uninfected cats were correctly identified by the discriminant ELISA (specificity 100%). Of the samples collected from FIV-infectedcats, 99 were correctly identified as FIV-infected (sensitivity 97.1%). CONCLUSIONS AND CLINICAL IMPORTANCE: With the exception of viral isolation, the discriminant ELISA is the most reliable assay for diagnosis of FIV. A practical strategy for the diagnosis of FIV infection would be to use existing commercial FIV antibody assays as screening tests. Negative results with commercial assays are highly reliable predictors for lack of infection. Positive results can be confirmed with the discriminant ELISA. If the discriminant ELISA is negative, the cat is probably vaccinated against FIV but not infected. Positive results are likely to represent infection.
Authors: Susan Little; Dorothee Bienzle; Lisa Carioto; Hugh Chisholm; Elizabeth O'Brien; Margie Scherk Journal: Can Vet J Date: 2011-08 Impact factor: 1.008
Authors: Isabella Oliveira Almeida; Mariana Arnoni Alves da Silva; Bruna Voltolin de Sena; Jeanne Saraiva da Paz; Tamara de Almeida Jaretta; Priscila Camargo Granadeiro Faria; Rodrigo Dos Santos Horta Journal: Rev Bras Med Vet Date: 2021-04-09
Authors: Mark Westman; Dennis Yang; Jennifer Green; Jacqueline Norris; Richard Malik; Yasmin A Parr; Mike McDonald; Margaret J Hosie; Sue VandeWoude; Craig Miller Journal: Viruses Date: 2021-03-12 Impact factor: 5.048