Evaluation of aptima zika virus assay
Journal of Clinical Microbiology
Copyright © 2017 Ren et al. The Zika virus (ZIKV) epidemic in the Americas poses a public health emergency that requires a swift response. Accurate and reliable ZIKV diagnostic tests serve as an important tool for limiting the spread of ZIKV infections. The Aptima Zika virus assay (Hologic, Marlborough, MA) performed on the automated Panther system is a rapid and high-throughput method for detecting ZIKV RNA using transcriptionmediated amplification (TMA) technology. We evaluated the performance characteristics of the Aptima Zika virus assay on clinical serum and urine specimens (n=124) from two different patient populations and samples spiked with ZIKV from three different lineages (n=10). Compared to the real-time reverse transcription-PCR (rRTPCR) reference method, the Aptima ZIKV assay detected ZIKV RNA with a diagnostic accuracy of 94.8% (95% confidence interval [CI], 89.4 to 97.6), a sensitivity of 94.7% (95% CI, 73.5 to 99.9), and a specificity of 94.8% (95% CI, 88.9 to 97.8). Similar results were obtained regardless of whether a serum or urine source was used. The limits of detection of the assay at a 95% detection probability were 11.5 genome copy equivalents (GCE)/ml (95% fiducial limits, 7.9 to 20.2) in serum and 17.9 GCE/ml (95% fiducial limits, 13.1 to 27.5) in urine. The Aptima Zika virus assay results were highly reproducible (99%), and no cross-reactivity was seen during the testing of a panel of 95 specimens with potentially interfering substances, such as clinically relevant bacteria, fungi, and viruses, including other flaviviruses. The excellent performance characteristics and the convenience of a fully automated testing system make the Aptima ZIKV assay an attractive choice for clinical laboratories detecting ZIKV RNA from serum and urine.
Ren P, Ortiz DA, Terzian ACB, Colombo TE, Nogueira ML, Vasilakis N, Loeffelholz MJ. Evaluation of Aptima Zika Virus Assay. J Clin Microbiol. 2017 Jul;55(7):2198-2203. doi: 10.1128/JCM.00603-17. Epub 2017 May 3. PMID: 28468854; PMCID: PMC5483922.