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The Oxford Vaccine Group is an independent multi-disciplinary clinical trials and epidemiology group based at the Centre for Clinical Vaccinology and Tropical Medicine, University of Oxford. OVG works towards the goal of developing new and improved vaccines for the prevention of infection in adults and children.
Dysregulated humoral immunity to nontyphoidal Salmonella in HIV-infected African adults.
Nontyphoidal Salmonellae are a major cause of life-threatening bacteremia among HIV-infected individuals. Although cell-mediated immunity controls intracellular infection, antibodies protect against Salmonella bacteremia. We report that high-titer antibodies specific for Salmonella lipopolysaccharide (LPS) are associated with a lack of Salmonella-killing in HIV-infected African adults. Killing was restored by genetically shortening LPS from the target Salmonella or removing LPS-specific antibodies from serum. Complement-mediated killing of Salmonella by healthy serum is shown to be induced specifically by antibodies against outer membrane proteins. This killing is lost when excess antibody against Salmonella LPS is added. Thus, our study indicates that impaired immunity against nontyphoidal Salmonella bacteremia in HIV infection results from excess inhibitory antibodies against Salmonella LPS, whereas serum killing of Salmonella is induced by antibodies against outer membrane proteins.
Host genetic variants near the PAX5 gene locus associate with susceptibility to invasive group A streptococcal disease
AbstractWe undertook a genome-wide association study of susceptibility to invasive group A streptococcal (GAS) disease combining data from distinct clinical manifestations and ancestral populations. Amongst other signals, we identified a susceptibility locus located 18kb from PAX5, an essential B-cell gene, which conferred a nearly two-fold increased risk of disease (rs1176842, odds ratio 1.8, 95% confidence intervals 1.5-2.3, P=3.2×10−7). While further studies are needed, this locus could plausibly explain some inter-individual differences in antibody-mediated immunity to GAS, perhaps providing insight into the effects of intravenous immunoglobulin in streptococcal toxic shock.
A common NFKB1 variant detected through antibody analysis in UK Biobank predicts risk of infection and allergy.
Infectious agents contribute significantly to the global burden of diseases through both acute infection and their chronic sequelae. We leveraged the UK Biobank to identify genetic loci that influence humoral immune response to multiple infections. From 45 genome-wide association studies in 9,611 participants from UK Biobank, we identified NFKB1 as a locus associated with quantitative antibody responses to multiple pathogens, including those from the herpes, retro-, and polyoma-virus families. An insertion-deletion variant thought to affect NFKB1 expression (rs28362491), was mapped as the likely causal variant and could play a key role in regulation of the immune response. Using 121 infection- and inflammation-related traits in 487,297 UK Biobank participants, we show that the deletion allele was associated with an increased risk of infection from diverse pathogens but had a protective effect against allergic disease. We propose that altered expression of NFKB1, as a result of the deletion, modulates hematopoietic pathways and likely impacts cell survival, antibody production, and inflammation. Taken together, we show that disruptions to the tightly regulated immune processes may tip the balance between exacerbated immune responses and allergy, or increased risk of infection and impaired resolution of inflammation.
Effective altruism, technoscience and the making of philanthropic value
A recent philanthropic movement with advocates among high-profile tech entrepreneurs and philosophers, effective altruism (EA) has been widely disparaged for its flawed moral philosophy and conservative political implications. As philanthropic practice, however, it has been seldom studied. In this paper, we argue that claims to technoscientific expertise are central to how EA actors understand, legitimize, and take part in the production of philanthropic value. We analyze their practices of categorization, ranking and measurement as well as underlying technoscientific imaginaries and moral views through comparing three areas of EA intervention: neglected tropical diseases, cultured meat, and AI safety. We show how EA involves various and contested ambitions to direct knowledge production and redraw the boundaries of expert communities, shedding light on the centrality of technoscience in philanthropists’ worldmaking ambitions.
Homologous & heterologous COVID-19 vaccine priming schedules: an analysis of systemic & mucosal immunity
Most two dose vaccination schedules, including UK-licensed SARS-CoV2 vaccinations, are licensed as homologous schedules. At the point of UK emergency licensure of the first two SARS-CoV2 vaccines, global demand for vaccine outstripped supply. National immunisation programmes faced logistical challenges to ensure sufficient doses of the same vaccine could be distributed to each person in the manufacturer-recommended timeframe. Two randomised control trials (Com-COV1 and Com-COV2) assessed safety, tolerability and non-inferiority of humoral immunogenicity of heterologous priming schedules using vaccines available to the UK immunisation program – AstraZeneca, Pfizer, Moderna and Novavax. Heterologous schedules are more reactogenic than their equivalent homologous schedules, however, all schedules are tolerable and without safety concern. Not all heterologous schedules are non-inferior to their relevant homologous schedule in terms of serum anti-SARS-CoV2 spike binding IgG, but they do always achieve a robust immunological response at least as large as the least immunogenic schedule studied (homologous AstraZeneca), which has proven efficacy against both severe disease and symptomatic infection. Differences between vaccine platforms are also qualitative with clear differences in the capability of each schedule to produce neutralising responses. T-cell responses differ markedly with the greatest responses seen in those receiving heterologous schedules with AstraZeneca as the first dose. Increasing priming interval from one to three months resulted in a modest increase in antibody response and a decrease in cellular response. Mucosal responses were evaluated as an exploratory endpoint. There was no evidence that mucosal anti-SARS-CoV2 spike IgA was induced by intramuscular vaccination. There is evidence that nasal mucosal responses can occur in the absence of systemic responses, possibly due to asymptomatic mucosal SARS-CoV2 exposure. Existing mucosal IgA responses against seasonal coronaviruses may confer some degree of protection against SARS-CoV2 infection. These results support the use of heterologous schedules as viable alternatives to homologous schedules and support flexibility in priming interval. They have informed UK and global immunisation policy. There is a need for alternative vaccination strategies, such as mucosally delivered vaccines, which induce mucosal responses that may reduce transmission.
A novel blood-free analytical framework for the quantification of neuroinflammatory load from TSPO PET Imaging.
Positron Emission Tomography (PET) of the 18 kDa translocator protein (TSPO) is critical for neuroinflammation studies but faces substantial methodological challenges. These include issues with arterial blood sampling for kinetic modeling, the absence of suitable reference regions, genetic polymorphisms affecting tracer affinity, altered blood-to-brain tracer delivery in inflammatory conditions, and high signal variability. This study presents a novel blood-free reference-free method for TSPO PET quantification, leveraging a logistic regression model to estimate the probability of TSPO overexpression across brain regions. Validation was performed on 323 human brain scans from five datasets and three radiotracers. The quantified TSPO topology in healthy controls showed strong concordance with the constitutive TSPO gene expression for all tracers. When using [ 11 C]PBR28 PET data, the method replicated previous findings in schizophrenia, Alzheimer's disease, chronic pain, and XBD173 blocking. However, model extension to [ 18 F]DPA-714 and [ 11 C]-(R)-PK11195 revealed small effect sizes and high variability, suggesting the need for tracer-specific model optimization. Finally, validation in a rat model of lipopolysaccharide-induced neuroinflammation confirmed previous evidence of increased brain TSPO uptake after a systemic challenge. This novel non-invasive method provides individualized TSPO PET quantification, demonstrating broad applicability across TSPO PET tracers and imaging sites, assuming sufficient training data for model development.
Evaluation of naturally occurring IgG anti-Vi antibody titers as predictors and correlates of typhoid fever in Dhaka, Bangladesh.
BACKGROUND: When delivered through vaccination Vi-polysaccharide antigen of Salmonella enterica serotype Typhi protects against typhoid by inducing IgG anti-Vi antibodies. We aimed to determine whether the presence of antibodies following natural infection is associated with a lower incidence of typhoid fever in endemic regions. METHODS: We analyzed data from a cohort study of typhoid fever conducted in Dhaka, Bangladesh. Plasma IgG anti-Vi antibodies were measured using a standard enzyme-linked immunosorbent assay in random serosurveys of a population that had not previously received typhoid vaccination. Participants were followed for up to 20 months for culture-confirmed typhoid fever. The receiver operating characteristic (ROC) curve and Cox proportional hazard models were used to evaluate the associations between antibody levels and typhoid risk. RESULTS: The ROC analysis revealed that IgG anti-Vi antibody titers were predictive of typhoid risk among the 8,261 serosurvey participants (area under the curve: 0·63; 95% confidence interval (CI): 0·58─0·67). Detection of any antibodies was associated with a lower risk of typhoid in crude analyses (hazard ratio (HR): 0·13; 95% CI: 0·03─0·52), though this association declined after adjustment (HR: 0·32; 95% CI: 0·07─1·40). A positive correlation was observed between IgG anti-Vi titers and age (correlation coefficient 0·35; p
Artificial intelligence for modelling infectious disease epidemics.
Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI.
A computational method for immune repertoire mining that identifies novel binders from different clonotypes, demonstrated by identifying anti-Pertussis toxoid antibodies
AbstractDue to their shared genetic history, antibodies from the same clonotype often bind to the same epitope. This knowledge is used in immune repertoire mining, where known binders are used to search bulk sequencing repertoires to identify new binders. However current computational methods cannot identify epitope convergence between antibodies from different clonotypes, limiting the sequence diversity of antigen-specific antibodies which can be identified. We describe how the antibody binding site, the paratope, can be used to cluster antibodies with common antigen reactivity from different clonotypes. Our method, paratyping, uses the predicted paratope to identify these novel cross clonotype matches. We experimentally validated our predictions on a Pertussis toxoid dataset. Our results show that even the simplest abstraction of the antibody binding site, using only the length of the loops involved and predicted binding residues, is sufficient to group antigen-specific antibodies and provide additional information to conventional clonotype analysis.