29 research outputs found
Drivers of quasispecies development in SARS-CoV-2 and implications for emergent variants and COVID-19
No full text: Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, significant research has focused on SARS-CoV-2 evolution and transmission. Most transmission studies rely on RT-qPCR and consensus sequencing for SARS-CoV-2 characterization, often overlooking the collection of viable genetically linked genomes characterized by one or more intra-host single nucleotide variants (iSNVs) within the same sample, defined as "quasispecies" (QS), which could influence disease outcomes. QS are highly variable in genomic position and frequency and have been proven to impact viral evolution substantially. Several de novo mutations were detected in QS before becoming lineage defining in variants of concern (VOCs). These mutations can also result from errors during replication and transcription leading to the development of defective viral genomes (DVGs) that are incapable of replicating, but important for propagating viral diversity during infection. In a continuously changing landscape of dominating VOCs and anti-SARS-CoV-2 therapy and vaccination strategies, this scoping review aims to summarize the current state-of-the-art and identify knowledge gaps in understanding QS development and their impact on intra-host SARS-CoV-2 evolution, virulence, and intra-host immunity. Finally, we explore the potential of studying inter-host transmission in households as a mirror for community transmission and evolution
Mining the human intestinal microbiota and the Clostridioides difficile genome to develop predictive biomarkers of C. difficile infection
No full textAbstract: Clostridioides difficile infection (CDI) is the most common form of infectious antibiotic-associated diarrhea (AAD) causing considerable morbidity and mortality in acute-care facilities. Hospitalized patients receiving broad-spectrum antibiotic treatment are particularly susceptible to CDI as a result of antibiotic-induced perturbations in the intestinal microbiota. Thanks to the evolution and increasing accessibility to next-generation sequencing (NGS) technologies, substantial advances have been made toward understanding C. difficile transmission, virulence, and phylogeny. However, much still remains unknown about this opportunistic pathogen. In this thesis, we aimed to identify early microbial biomarkers predictive of AAD in patients undergoing broad-spectrum antibiotic treatment, with a particular emphasis on CDI. We further aimed at understanding the phylogeny of toxigenic C. difficile strains by assigning a genomic context to their infection potential. Here, we present a high-resolution, genome-wide characterization of the Leeds-Leiden/ECDC strain collection of primarily toxigenic C. difficile strains (n = 73). This effort constitutes, to our knowledge, the largest chromosome-wide comparative genomics study to date that investigates C. difficile phylogeny. The human intestinal microbiota was mined for predictive microbiota-based biomarkers of CDI in a large, elderly, hospitalized population. This resulted in the development of a predictive algorithm enabling enrichment of patients at high-risk of CDI, which ultimately resulted in the filing of a patent. Longitudinally collected fecal samples from the same study population were further assessed for structural microbial alterations following broad-spectrum antibiotic treatment, which showed antibiotic-specific alterations in microbial composition with a resulting alteration in metabolism. In conclusion, this thesis provides a comprehensive investigation into genomic and microbiota-based facilitators of CDI by investigating C. difficile phylogeny and genomic features of C. difficile expressed as virulence and transmission traits as well as a thorough investigation into structural changes in the human intestinal microbiota pre and post antibiotic treatment
COVID-19 and SARS-CoV-2 vaccination related T-cell immune response in diverse populations
No full textAbstract: Immune dysregulation has been established as a key feature of COVID-19. Both vaccination against COVID-19 and infection by SARS-CoV-2 induce adaptive immune responses. However, much of the focus in vaccine development and immunity surveillance has been on the role of serology and neutralizing antibodies, with less emphasis on understanding the role of T cells, especially in immunocompromised hosts. Mounting evidence suggests T cell contributions to the host immune response are required for early, broad, and durable protection from the SARS-CoV-2 virus, especially in the setting of new variants of concern (VOCs). The main objective of this thesis was to expand our understanding of cellular immune responses against SARS-CoV-2 and COVID-19 vaccinations with a focus on CD4+ and CD8+ compartments in diverse populations. In the first chapters, I describe the current literature on key immunocompromised groups \u2013 concentrating on people living with human immunodeficiency virus (PLWH), solid organ transplant (SOT) recipients, and patients with solid and haematological malignancies \u2013 and the unique T cell phenotypes observed in different fragile hosts in response to SARS-CoV-2 antigens. After describing the framework of the T cell analysis in Chapter 2, I focus on investigating longitudinal T cell responses among PLWH after BNT162b2 vaccination in Chapter 3. Our results suggest that the durable serological and CD4+ T-cell responses developing in vaccinated PLWH are associated with IL-2-mediated CD4+ T-cell activation that likely compensates for CD4+ T-cell depletion in PLWH. In Chapter 4 I assess monoclonal antibody (mAb) therapy for the treatment of COVID-19 and the effect of host immune factors on Spike mutation development. We hypothesise that the de novo mutations identified in the SARS-CoV-2 spike protein are escape mutants that evade mAb neutralisation and facilitate a more natural progression of disease, thereby resulting in a more robust T cell immune response. We further demonstrate that host-driven immune and non-immune responses are essential for the development of mutant SARS-CoV-2 and support informed decision-making in reducing the risk of mAb treatment failure. Finally, in Chapter 5, I discuss the overall results with a focus on future considerations for our workgroup and the direction towards which this research can be expanded. This thesis forms the basis for future research in the development of effective vaccination strategies and provides advice for developing best practice policies in terms of COVID-19 therapeutics
Immunological biomarkers of COVID-19 : response to vaccination and monoclonal antibody treatments in immunocompromised patients
No full textAbstract: COVID-19 has caused almost 7 million deaths worldwide with 768 million documented cases of SARS-CoV-2 infections. However, the burden of the pandemic could have been even higher without the development of effective COVID-19 treatments and vaccines in record time. The overarching goal of this thesis was to expend the knowledge about immune responses to COVID-19 and COVID-19 vaccination with the focus on understanding how host immune responses, especially the ones driven by cytokines, chemokines, and growth factors, pre-determine or affect the course of the disease and vaccination. As part of my doctoral thesis, I studied multiple cohorts of immunocompromised patients with COVID-19, or at high risk of developing COVID-19, with the overall aim to build immune-related signatures to predict either development of vaccination responses or responses to treatments, such as those with anti-SARS-CoV-2 monoclonal antibodies (mAb). Specifically, I explored post-vaccine immune responses in solid organ transplant (SOT) recipients and patients with solid and haematological malignancies and identified clinical and molecular signatures predictive of insufficient immune responses. Given the inability of some of these patients to develop sufficient antibody responses to COVID-19 vaccines, I assessed currently available treatment and prophylaxis options. Specifically, I evaluated the effect of mAb treatments and of host immune factors on Spike mutation development. Additionally, I studied neutralizing capacity of bamlanivimab, bamlanivimab/etesevimab, casirivimab/imdevimab, sotrovimab or tixagevimab/cilgavimab against SARS-CoV-2-CoV-2 variants of concern (VOCs). In conclusion, much like an orchestra, where the contributions of each instrument may seem minimal and indistinguishable among others, the influence of cytokines, chemokines and growth factors on COVID-19 is also subtle and may not be overtly noticeable, however, they play a crucial role in co-ordinating and orchestrating various immune responses important in COVID-19 disease and its prevention and treatment. Research findings described in this thesis utilise these variables to understand the molecular pathology of COVID-19 and hopefully would provide a lasting impact on ongoing efforts to combat this global health crisis and its aftermath
Interleukin-2-mediated CD4 T-cell activation correlates highly with effective serological and T-cell responses to SARS-CoV-2 vaccination in people living with HIV
No full text: People living with HIV (PLWH) despite having an appreciable depletion of CD4+ T-cells show a good severe acute respiratory syndrome coronavirus 2 vaccination response. The underlying mechanism(s) are currently not understood. We studied serological and polyfunctional T-cell responses in PLWH receiving anti-retroviral therapy stratified on CD4+ counts as PLWH-high (CD4 ≥ 500 cells/mm3) and PLWH-low (<500 cells/mm3). Responses were assessed longitudinally before the first vaccination (T0), 1-month after the first dose (T1), 3-months (T2), and 6-months (T3) after the second dose. Expectedly, both PLWH-high and -low groups developed similar serological responses after T2, which were also non-significantly different from age and vaccination-matched HIV-negative controls at T3. The immunoglobulin G titers were also protective showing a good correlation with angiotensin-converting enzyme 2-neutralizations (R = 0.628, p = 0.005). While surface and intracellular activation analysis showed no significant difference at T3 between PLWH and controls in activated CD4+CD154+ and CD4+ memory T-cells, spike-specific CD4+ polyfunctional cytokine expression analysis showed that PLWH preferentially express interleukin (IL)-2 (p < 0.001) and controls, interferon-γ (p = 0.017). CD4+ T-cell counts negatively correlated with IL-2-expressing CD4+ T-cells including CD4+ memory T-cells (Spearman ρ: -0.85 and -0.80, respectively; p < 0.001). Our results suggest that the durable serological and CD4+ T-cell responses developing in vaccinated PLWH are associated with IL-2-mediated CD4+ T-cell activation that likely compensates for CD4+ T-cell depletion in PLWH
Clinical efficacy of different monoclonal antibody regimens among non-hospitalised patients with mild to moderate COVID-19 at high risk for disease progression: a prospective cohort study
No full textThis study aimed to compare the clinical progression of COVID-19 in high-risk outpatients treated with the monoclonal antibodies (mAb) bamlanivimab, bamlanivimab-etesevimab and casirivimab-imdevimab. This is an observational, multi-centre, prospective study conducted from 18 March to 15 July 2021 in eight Italian tertiary-care hospitals including mild-to-moderate COVID-19 outpatients receiving bamlanivimab (700 mg), bamlanivimab-etesevimab (700–1400 mg) or casirivimab-imdevimab (1200–1200 mg). All patients were at high risk of COVID-19 progression according to Italian Medicines Agency definitions. In a patient subgroup, SARS-CoV-2 variant and anti-SARS-CoV-2 serology were analysed at baseline. Factors associated with 28-day all-cause hospitalisation were identified using multivariable multilevel logistic regression (MMLR) and summarised with adjusted odds ratio (aOR) and 95% confidence interval (CI). A total of 635 outpatients received mAb: 161 (25.4%) bamlanivimab, 396 (62.4%) bamlanivimab-etesevimab and 78 (12.2%) casirivimab-imdevimab. Ninety-five (15%) patients received full or partial SARS-CoV-2 vaccination. The B.1.1.7 (Alpha) variant was detected in 99% of patients. Baseline serology showed no significant differences among the three mAb regimen groups. Twenty-eight-day all-cause hospitalisation was 11.3%, with a significantly higher proportion (p 0.001) in the bamlanivimab group (18.6%), compared to the bamlanivimab-etesevimab (10.1%) and casirivimab-imdevimab (2.6%) groups. On MMLR, aORs for 28-day all-cause hospitalisation were significantly lower in patients receiving bamlanivimab-etesevimab (aOR 0.51, 95% CI 0.30–0.88 p 0.015) and casirivimab-imdevimab (aOR 0.14, 95% CI 0.03–0.61, p 0.009) compared to those receiving bamlanivimab. No patients with a history of vaccination were hospitalised. The study suggests differences in clinical outcomes among the first available mAb regimens for treating high-risk COVID-19 outpatients. Randomised trials are needed to compare efficacy of mAb combination regimens in high-risk populations and according to circulating variants
Host immunological responses facilitate development of SARS-CoV-2 mutations in patients receiving monoclonal antibody treatments
No full textAbstract: The role of host immunity in emergence of evasive SARS-CoV-2 Spike mutations under therapeutic monoclonal antibody (mAb) pressure remains to be explored. Here, we show that patients treated with various anti-SARS-CoV-2 mAb regimens develop evasive Spike mutations with remarkable speed and high specificity to the targeted mAb-binding sites. Mutations develop more frequently in immunocompromised patients and strongly correlate not only with neutralizing capacity of the therapeutic mAbs, but also with an anti-inflammatory and healing-promoting host milieu. We further built and deploy machine-learning models on host-derived biomarkers that identify patients at high risk of developing escape mutations against therapeutic mAbs with high accuracy. While our data suggest that host-driven responses are essential for development of mutant SARS-CoV-2, the mechanisms and models described here could also be utilized to reduce risk of treatment failure in high-risk populations receiving anti-SARS-CoV-2 mAb treatments and improve mitigation strategies for possible dissemination of escape SARS-CoV-2 mutants
Clinical Impact of Monoclonal Antibodies in the Treatment of High-Risk Patients with SARS-CoV-2 Breakthrough Infections:The ORCHESTRA Prospective Cohort Study
No full textThe clinical impact of anti-spike monoclonal antibodies (mAb) in Coronavirus Disease 2019 (COVID-19) breakthrough infections is unclear. We present the results of an observational prospective cohort study assessing and comparing COVID-19 progression in high-risk outpatients receiving mAb according to primary or breakthrough infection. Clinical, serological and virological predictors associated with 28-day COVID-19-related hospitalization were identified using multivariate logistic regression and summarized with odds ratio (aOR) and 95% confidence interval (CI). A total of 847 COVID-19 outpatients were included: 414 with primary and 433 with breakthrough infection. Hospitalization was observed in 42/414 (10.1%) patients with primary and 8/433 (1.8%) patients with breakthrough infection (p < 0.001). aOR for hospitalization was significantly lower for breakthrough infection (aOR 0.12, 95%CI: 0.05–0.27, p < 0.001) and higher for immunocompromised status (aOR:2.35, 95%CI:1.08–5.08, p = 0.003), advanced age (aOR:1.06, 95%CI: 1.03–1.08, p < 0.001), and male gender (aOR:1.97, 95%CI: 1.04–3.73, p = 0.037). Among the breakthrough infection group, the median SARS-CoV-2 anti-spike IgGs was lower (p < 0.001) in immunocompromised and elderly patients >75 years compared with that in the immunocompetent patients. Our findings suggest that, among mAb patients, those with breakthrough infection have significantly lower hospitalization risk compared with patients with primary infection. Prognostic algorithms combining clinical and immune-virological characteristics are needed to ensure appropriate and up-to-date clinical protocols targeting high-risk categories.</p
Using machine learning to predict antibody response to SARS-CoV-2 vaccination in solid organ transplant recipients: the multicentre ORCHESTRA cohort
No full textObjectives: Study aim is to assess predictors of negative antibody response (AbR) in solid organ transplant (SOT) recipients after the first booster of SARS-CoV-2 vaccination. Methods: SOT recipients receiving SARS-CoV-2 vaccination were prospectively enrolled (March 2021-January 2022) at six hospitals in Italy and Spain. AbR was assessed at first dose (t0), second dose (t1), 3±1 month (t2), and 1 month after third dose (t3). Negative AbR at t3 was defined as anti-receptor binding domain titre <45 BAU/mL. Machine Learning models were developed to predict the individual risk of negative (vs. positive) AbR using as covariates age, type of transplant, time between transplant and vaccination, immunosuppressive drugs, type of vaccine, and graft function, and subsequently assessed using a validation cohort. Results: Overall, 1615 SOT recipients (1072 [66.3%] males, mean±standard deviation (SD) age 57.85±13.77) were enrolled and 1211 received three vaccination doses. Negative AbR rate decreased from (886/946) 93.66% to (202/923) 21.90% from t0 to t3. Univariate analysis showed that older patients (mean age 60.21±11.51 vs. 58.11±13.08), anti-metabolites (57.9% vs. 35.1%) steroids (52.9% vs. 38.5%), recent transplantation (<3 years) (17.8% vs. 2.3%), and kidney, heart, or lung compared to liver transplantation (25%, 31.8%, 30.4% vs. 5.5%) had a higher likelihood of negative AbR. Machine learning algorithms showing best prediction performance were logistic regression (precision recall curve-PRAUC mean 0.37 [95%CI 0.36-0.39]) and k-Nearest Neighbors (PRAUC 0.36 [0.35-0.37]). Conclusions: Almost a quarter of SOT recipients showed negative AbR after first booster dosage. Unfortunately, clinical information cannot efficiently predict negative AbR even with ML algorithms
Microbiota-based markers predictive of development of Clostridioides difficile infection
No full textAntibiotic-induced modulation of the intestinal microbiota can lead to Clostridioides difficile
infection (CDI), which is associated with considerable morbidity, mortality, and healthcare costs globally. Therefore, identification of markers predictive of CDI could substantially
contribute to guiding therapy and decreasing the infection burden. Here, we analyze the
intestinal microbiota of hospitalized patients at increased CDI risk in a prospective, 90-day
cohort-study before and after antibiotic treatment and at diarrhea onset. We show that
patients developing CDI already exhibit significantly lower diversity before antibiotic treat ment and a distinct microbiota enriched in Enterococcus and depleted of Ruminococcus, Blautia,
Prevotella and Bifidobacterium compared to non-CDI patients. We find that antibiotic
treatment-induced dysbiosis is class-specific with beta-lactams further increasing enter ococcal abundance. Our findings, validated in an independent prospective patient cohort
developing CDI, can be exploited to enrich for high-risk patients in prospective clinical trials,
and to develop predictive microbiota-based diagnostics for management of patients at
risk for CDI
