Performance Evaluation of VIDAS® Diagnostic Assays Detecting Anti-Chikungunya Virus IgM and IgG Antibodies: An International Study.

Chikungunya (CHIK) is a debilitating mosquito-borne disease with an epidemiology and early clinical symptoms similar to those of other arboviruses-triggered diseases such as dengue or Zika. Accurate and rapid diagnosis of CHIK virus (CHIKV) infection is therefore challenging. This international study evaluated the performance of the automated VIDAS® anti-CHIKV IgM and IgG assays compared to that of manual competitor IgM and IgG ELISA for the detection of anti-CHIKV IgM and IgG antibodies in 660 patients with suspected CHIKV infection. Positive and negative agreements of the VIDAS® CHIKV assays with ELISA ranged from 97.5% to 100.0%. The sensitivity of the VIDAS® CHIKV assays evaluated in patients with a proven CHIKV infection confirmed reported kinetics of anti-CHIKV IgM and IgG response, with a positive detection of 88.2-100.0% for IgM ≥ 5 days post symptom onset and of 100.0% for IgG ≥ 11 days post symptom onset. Our study also demonstrated the superiority of ELISA and VIDAS® assays over rapid diagnostic IgM/IgG tests. The analytical performance of VIDAS® anti-CHIKV IgM and IgG assays was excellent, with a high precision (coefficients of variation ≤ 7.4%) and high specificity (cross-reactivity rate ≤ 2.9%). This study demonstrates the suitability of the automated VIDAS® anti-CHIKV IgM and IgG assays to diagnose CHIKV infections and supports its applicability for epidemiological surveillance and differential diagnosis in regions endemic for CHIKV.

Performance characteristics of the VIDAS® ANTI-HEV IgM and IgG assays.

BACKGROUND: Several unautomated anti-HEV diagnostic tests are presently available. OBJECTIVE: We have evaluated the performance of the new automated VIDAS® ANTI-HEV IgM and IgG assays. STUDY DESIGN: We assessed the reproducibility and cross-reactivity of both VIDAS assays and the analytical sensitivity and linearity of the VIDAS IgG assay. We also tested the VIDAS and comparator assays Wantai IgG and IgM on immunocompetent and immunocompromised patients. Data were analysed according to the infectious profile, with samples from viremic phase (HEV RNA/IgM positive) and post-viremic phase (HEV RNA negative, IgM positive) infections, and uninfected patients (HEV RNA/IgM negative). RESULTS: Within-run reproducibility was <10% and between-run reproducibility was <12% for both assays. We found no cross-reactivity, except for the VIDAS IgG assay in some patients with HBV (1/10) or malaria (3/23) infections and for the VIDAS IgM assay in some HIV-infected patients (1/10). The VIDAS IgG assay was linear over 0.10-10.0 U/mL. Analytical sensitivity of the IgG assay was 0.71 IU/ml (probit analysis). The clinical sensitivity of the VIDAS IgM assay was 97.65% for viremic samples (83/85) and 59.15% (42/71) for post-viremic samples from immunocompetent patients. It was 78.95% (45/57) for acute phase samples and 77.78% (28/36) for post-viremic samples from immunocompromised patients. Specificity was excellent (>99%) in both populations. CONCLUSION: The analytical and clinical performance of the new VIDAS® ANTI-HEV assays was excellent. These rapid, automated assays for detecting HEV antibodies will strengthen the arsenal for diagnosing HEV infections.

Impact of Serum and Plasma Matrices on the Titration of Human Inflammatory Biomarkers Using Analytically Validated SRM Assays.

Protein biomarker discovery has inherent challenges linked to the validation of the analytical method used or to the impact of biological matrices. Matrix influences must be mastered to guarantee the reliability of the identified biomarkers to monitor human diseases. In this study, multiplexed mass spectrometry assays in selected reaction monitoring (SRM) mode have been developed to measure 107 inflammatory putative proteins in matched serum and plasma from 36 ICU trauma patients. The assays' validation directly in clinical samples was shown to be valuable to manage intersample variability. Using the validation process developed here, assays were validated for 58 biomarkers in serum, 57 in plasma, and 55 in both matrices. Correlation analyses demonstrated that the quantitation using SRM of most of the validated biomarkers (45/55) was impacted by the biological matrix and that the matrix impact was biomarker-dependent. Among the 45 impacted biomarkers, 23 were nevertheless correlated between serum and plasma, whereas the quantitation was shown to be equivalent in both for the 10 last proteins. Matrix selection using SRM is therefore suggested to be suitable prior to clinical evaluation of biomarkers in a large cohort of patients.