ABSTRACT
Background: Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) could aid the diagnosis of acute respiratory infections (ARI) owing to its affordability and high-throughput capacity. MALDI-MS has been proposed for use on commonly available respiratory samples, without specialized sample preparation, making this technology especially attractive for implementation in low-resource regions. Here, we assessed the utility of MALDI-MS in differentiating SARS-CoV-2 versus non-COVID acute respiratory infections (NCARI) in a clinical lab setting of Kazakhstan. Methods: Nasopharyngeal swabs were collected from in- and outpatients with respiratory symptoms and from asymptomatic controls (AC) in 2020-2022. PCR was used to differentiate SARS-CoV-2+ and NCARI cases. MALDI-MS spectra were obtained for a total of 252 samples (115 SARS-CoV-2+, 98 NCARI and 39 AC) without specialized sample preparation. In our first sub-analysis, we followed a published protocol for peak preprocessing and Machine Learning (ML), trained on publicly available spectra from South American SARS-CoV-2+ and NCARI samples. In our second sub-analysis, we trained ML models on a peak intensity matrix representative of both South American (SA) and Kazakhstan (Kaz) samples. Results: Applying the established MALDI-MS pipeline "as is" resulted in a high detection rate for SARS-CoV-2+ samples (91.0%), but low accuracy for NCARI (48.0%) and AC (67.0%) by the top-performing random forest model. After re-training of the ML algorithms on the SA-Kaz peak intensity matrix, the accuracy of detection by the top-performing Support Vector Machine with radial basis function kernel model was at 88.0, 95.0 and 78% for the Kazakhstan SARS-CoV-2+, NCARI, and AC subjects, respectively with a SARS-CoV-2 vs. rest ROC AUC of 0.983 [0.958, 0.987]; a high differentiation accuracy was maintained for the South American SARS-CoV-2 and NCARI. Conclusions: MALDI-MS/ML is a feasible approach for the differentiation of ARI without a specialized sample preparation. The implementation of MALDI-MS/ML in a real clinical lab setting will necessitate continuous optimization to keep up with the rapidly evolving landscape of ARI.
Subject(s)
Respiratory Tract InfectionsABSTRACT
BackgroundCOVID-19 vaccines have played a critical role in controlling the COVID-19 pandemic. Although overall considered safe, COVID-19 vaccination has been associated with rare but severe thrombotic events, occurring mainly in the context of adenoviral vectored vaccines. A better understanding of mechanisms underlying vaccine-induced hypercoagulability and prothrombotic state is needed to improve vaccine safety profile. MethodsWe assessed changes to the biomarkers of endothelial function (endothelin, ET-1), coagulation (thrombomodulin, THBD and plasminogen activator inhibitor, PAI) and platelet activation (platelet activating factor, PAF, and platelet factor 4 IgG antibody, PF4 IgG) within a three-week period after the first (prime) and second (boost) doses of Gam-Covid-Vac, an AdV5/AdV26-vectored COVID-19 vaccine. Blood plasma collected from vaccinees (n=58) was assayed using ELISA assays. Participants were stratified by prior COVID-19 exposure based on their baseline SARS-CoV-2-specific serology results. ResultsWe observed a significant post-prime increase in circulating ET-1, with levels sustained after the boost dose compared to baseline. ET-1 elevation following dose 2 was most pronounced in vaccinees without prior COVID-19 exposure. Prior COVID-19 was also associated with a mild increase in post-dose 1 PAI. ConclusionsVaccination was associated with elevated ET-1 up to day 21 after the second vaccine dose, while no marked alterations to other biomarkers, including PF4 IgG, were seen. A role of persistent endothelial activation followingCOVID-19 vaccination warrants further investigation.
Subject(s)
Thrombophilia , Thrombosis , Blood Coagulation Disorders, Inherited , COVID-19ABSTRACT
Background Sputnik-V (Gam-COVID-Vac) is a heterologous, recombinant adenoviral (rAdv) vector-based, COVID-19 vaccine now used in >70 countries. Yet there is a shortage of data on this vaccine’s performance in diverse populations. Here, we performed a prospective cohort study to assess the reactogenicity and immunologic outcomes of Sputnik-V vaccination in a multiethnic cohort from Kazakhstan. Methods COVID-19-free participants (n=82 at baseline) were followed at day 21 after Sputnik-V dose 1 (rAd5) and dose 2 (rAd26). Self-reported local and systemic adverse events were captured using questionnaires. Blood and nasopharyngeal swabs were collected to perform SARS-CoV-2 diagnostic and immunologic assays. Findings Of the 73 and 70 participants retained post-dose 1 and 2, respectively, most (>50%) reported mild-to-moderate injection site or systemic reactions to vaccination; no severe or potentially life-threatening conditions were reported. dose 1 appeared to be more reactogenic than dose 2, with fatigue and headache more frequent in participants with prior COVID-19 exposure. After dose 2 nausea was more common in subjects without prior COVID-19. The combined S-IgG and S-IgA seroconversion rate was 97% post-dose 1, remaining the same post-dose 2. The proportion of participants with detectable virus neutralization titers was 83% post-dose 1’, and increased to 98% post-dose 2’, with the largest relative increase observed in participants without prior COVID-19 exposure. Nasal S-IgG and S-IgA increased post-dose 1, while the boosting effect of dose 2 on mucosal S-IgG, but not S-IgA, was only observed in subjects without prior COVID-19. Systemically, vaccination reduced serum levels of growth regulated oncogene (GRO), which correlated with an elevation in blood platelet count. Interpretation Sputnik-V dose 1 elicited both blood and mucosal SARS-CoV-2 immunity, while the immune boosting effect of dose 2 was minimal, suggesting that adjustments to the current vaccine dosing regimen may be necessary to optimize immunization efficacy and cost-effectiveness. Although Sputnik-V appears to have a reactogenicity profile similar to that of other COVID-19 vaccines, the observed alterations to the GRO/platelet axis call for further investigation of Sputnik V effects on systemic immunology. Funding Ministry of Education and Science of the Republic of Kazakhstan.
Subject(s)
COVID-19 , IgG Deficiency , Immune System DiseasesABSTRACT
Background COVID-19 exposure in Central Asia appears underestimated and SARS-CoV-2 seroprevalence data are urgently needed to inform ongoing vaccination efforts and other strategies to mitigate the regional pandemic. Here, we assessed the prevalence of anti-SARS-CoV-2 antibody-mediated immunity in a heterogeneous cohort of public university employees in Karaganda, Kazakhstan. Methods Asymptomatic subjects (n=100) were recruited prior to their first COVID-19 vaccination. Questionnaires were administered to capture a range of demographic and clinical characteristics. Nasopharyngeal swabs were collected for SARS-CoV-2 RT-qPCR testing. Serological assays were performed to detect spike (S)-reactive IgG and IgA and to assess virus neutralization. Pre-pandemic samples were used to validate the assay positivity thresholds. Results Anti-S IgG and IgA seropositivity rates among SARS-CoV-2 PCR-negative participants (n=100) were 42% (95% CI [32.2-52.3]) and 59% (95% CI [48.8-69.0]), respectively, and 64% (95% CI [53.4-73.1]) of the cohort tested positive for at least one of the antibodies. Anti-S IgG titres correlated with virus neutralization activity, detectable in 49% of the tested subset with prior COVID-19 history. Serologically confirmed history of COVID-19 was associated with Kazakh ethnicity and self-reported history of respiratory illness since March 2020. Conclusions SARS-CoV-2 exposure in this cohort is ∼15-fold higher compared to the reported all-time national and regional COVID-19 prevalence. Continuous serological surveillance is critical for understanding the COVID-19 transmission dynamics and should be nationally implemented to better inform the public health response in Central Asia.
Subject(s)
COVID-19ABSTRACT
Background: The earliest coronavirus disease-2019 (COVID-19) cases in Central Asia were announced in March 2020 by Kazakhstan. Despite the implementation of aggressive measures to curb infection spread, gaps remain in the understanding of the clinical and epidemiologic features of the regional pandemic. Methods: We did a retrospective, observational cohort study of patients with laboratory-confirmed COVID-19 in Kazakhstan between February and April 2020. We compared demographic, clinical, laboratory and radiological data of patients with different COVID-19 severities on admission. Univariable and multivariable logistic regression was used to assess factors associated with disease severity and death. Whole-genome SARS-CoV-2 analysis was performed in 53 patients without a recent history of international travel. Findings: Of the 1072 patients with laboratory-confirmed COVID-19 in March-April 2020, the median age was 36 years (IQR 24-50) and 484 (45%) were male. On admission, 683 (64%) participants had mild, 341 (32%) moderate, and 47 (4%) severe-to-critical COVID-19 manifestation; 20 deaths (1.87%) were reported at study exit. Multivariable regression indicated increasing odds of severe disease associated with older age (odds ratio 1.05, 95% CI 1.03-1.07, per year increase; p<0.001), the presence of comorbidities (2.13, 95% CI 1.07-4.23; p<0.031) and elevated white blood cell count (WBC, 1.14, 95% CI 1.01-1.28; p<0.032) on admission, while older age (1.09, 95% CI 1.06-1.12, per year increase; p<0.001) and male sex (5.97, 95% CI 1.95-18.32; p<0.002) were associated with increased odds of death. The Kazakhstan SARS-CoV-2 isolates grouped into seven distinct lineages O/B.4.1, S/A.2, S/B.1.1, G/B.1, GH/B.1.255, GH/B.1.3 and GR/B.1.1.10. Interpretation: Older age, comorbidities, increased WBC count, and male sex were risk factors for COVID-19 disease severity and mortality in Kazakhstan. The broad SARS-CoV-2 diversity suggests multiple importations and community-level amplification, likely predating the declaration of state emergency. Continuous epidemiologic and genomic surveillance may be critical for a better understanding of the regional COVID-19 dynamics.