Clinical Protocol for a Longitudinal Cohort Study Employing Systems Biology to Identify Markers of Vaccine Immunogenicity in Newborn Infants in The Gambia and Papua New Guinea

flowSim: Near duplicate detection for flow cytometry data

The analysis of large amounts of data is important for the development of machine learning (ML) models. flowSim is the first algorithm designed to visualize, detect and remove highly redundant information in flow cytometry (FCM) training sets to decrease the computational time for training and increase the performance of ML algorithms by reducing overfitting. flowSim performs near duplicate image detection by combining community detection algorithms with the density analysis of the marker expression values. flowSim clustering compared to consensus manual clustering on a dataset composed of 160 images of bivariate FCM data had a mean Adjusted Rand Index of 0.90, demonstrating its efficiency in identifying similar patterns. flowSim selectively discarded near duplicate files in datasets constructed with known redundancy, and removed 92.6% of FCM images in a dataset of over 500,000 drawn from public repositories.

A single birth dose of Hepatitis B vaccine induces polyfunctional CD4+ T helper cells

A single birth-dose of Hepatitis B vaccine (HepB) can protect newborns from acquiring Hepatitis B infection through vertical transmission, though several follow-up doses are required to induce long-lived protection. In addition to stimulating antibodies, a birth-dose of HepB might also induce polyfunctional CD4+ T-cells, which may contribute to initial protection. We investigated whether vaccination with HepB in the first week of life induced detectable antigen-specific CD4+ T-cells after only a single dose and following completion of the entire HepB vaccine schedule (3 doses). Using HBsAg- stimulated peripheral blood mononuclear cells from 344 infants, we detected increased populations of antigen-specific polyfunctional CD154+IL-2+TNFα+ CD4+ T-cells following a single birth-dose of HepB in a proportion of infants. Frequencies of polyfunctional T-cells increased following the completion of the HepB schedule but increases in the proportion of responders as compared to following only one dose was marginal. Polyfunctional T-cells correlated positively with serum antibody titres following the birth dose (day30) and completion of the 3-dose primary HepB vaccine series (day 128). These data indicate that a single birth dose of HepB provides immune priming for both antigen-specific B- and T cells.

Searching for a technology-driven acute rheumatic fever test: the START study protocol

INTRODUCTION

The absence of a diagnostic test for acute rheumatic fever (ARF) is a major impediment in managing this serious childhood condition. ARF is an autoimmune condition triggered by infection with group A Streptococcus. It is the precursor to rheumatic heart disease (RHD), a leading cause of health inequity and premature mortality for Indigenous peoples of Australia, New Zealand and internationally. METHODS AND ANALYSIS: 'Searching for a Technology-Driven Acute Rheumatic Fever Test' (START) is a biomarker discovery study that aims to detect and test a biomarker signature that distinguishes ARF cases from non-ARF, and use systems biology and serology to better understand ARF pathogenesis. Eligible participants with ARF diagnosed by an expert clinical panel according to the 2015 Revised Jones Criteria, aged 5-30 years, will be recruited from three hospitals in Australia and New Zealand. Age, sex and ethnicity-matched individuals who are healthy or have non-ARF acute diagnoses or RHD, will be recruited as controls. In the discovery cohort, blood samples collected at baseline, and during convalescence in a subset, will be interrogated by comprehensive profiling to generate possible diagnostic biomarker signatures. A biomarker validation cohort will subsequently be used to test promising combinations of biomarkers. By defining the first biomarker signatures able to discriminate between ARF and other clinical conditions, the START study has the potential to transform the approach to ARF diagnosis and RHD prevention.

ETHICS AND DISSEMINATION

The study has approval from the Northern Territory Department of Health and Menzies School of Health Research ethics committee and the New Zealand Health and Disability Ethics Committee. It will be conducted according to ethical standards for research involving Indigenous Australians and New Zealand Māori and Pacific Peoples. Indigenous investigators and governance groups will provide oversight of study processes and advise on cultural matters.

Conducting clinical research in a resource-constrained setting: lessons from a longitudinal cohort study in The Gambia

Clinical research conducted to Good Clinical Practice (GCP) standards is increasingly being undertaken in resource-constrained low-income and middle-income countries (LMICs) settings. This presents unique challenges that differ from those faced in high-income country (HIC) contexts, due to a dearth of infrastructure and unique socio-cultural contexts. Field experiences by research teams working in these LMIC contexts are thus critical to advancing knowledge on successful research conduct in these settings. The Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine has operated in The Gambia, a resource-constrained LMIC for over 70 years and has developed numerous research support platforms and systems. The unit was the lead clinical collaborator in a recently completed Expanded Program on Immunization Consortium (EPIC) study, involving a multicountry collaboration across five countries including the USA, Canada, Belgium, Papua New Guinea and The Gambia. The EPIC study recruited and completed follow-up of 720 newborn infants over 2 years. In this paper, we provide in-depth field experience covering challenges faced by the Gambian EPIC team in the conduct of this study. We also detail some reflections on these challenges. Our findings are relevant to the international research community as they highlight practical day-to-day challenges in conducting GCP standard clinical research in resource-constrained LMIC contexts. They also provide insights on how study processes can be adapted early during research planning to mitigate challenges.

Predictive Markers of Immunogenicity and Efficacy for Human Vaccines

Vaccines represent one of the major advances of modern medicine. Despite the many successes of vaccination, continuous efforts to design new vaccines are needed to fight "old" pandemics, such as tuberculosis and malaria, as well as emerging pathogens, such as Zika virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Vaccination aims at reaching sterilizing immunity, however assessing vaccine efficacy is still challenging and underscores the need for a better understanding of immune protective responses. Identifying reliable predictive markers of immunogenicity can help to select and develop promising vaccine candidates during early preclinical studies and can lead to improved, personalized, vaccination strategies. A systems biology approach is increasingly being adopted to address these major challenges using multiple high-dimensional technologies combined with in silico models. Although the goal is to develop predictive models of vaccine efficacy in humans, applying this approach to animal models empowers basic and translational vaccine research. In this review, we provide an overview of vaccine immune signatures in preclinical models, as well as in target human populations. We also discuss high-throughput technologies used to probe vaccine-induced responses, along with data analysis and computational methodologies applied to the predictive modeling of vaccine efficacy.

Plasma Adenosine Deaminase (ADA)-1 and -2 Demonstrate Robust Ontogeny Across the First Four Months of Human Life

Background

Human adenosine deaminases (ADAs) modulate the immune response: ADA1 via metabolizing adenosine, a purine metabolite that inhibits pro-inflammatory and Th1 cytokine production, and the multi-functional ADA2, by enhancing T-cell proliferation and monocyte differentiation. Newborns are relatively deficient in ADA1 resulting in elevated plasma adenosine concentrations and a Th2/anti-inflammatory bias compared to adults. Despite the growing recognition of the role of ADAs in immune regulation, little is known about the ontogeny of ADA concentrations.

Methods

In a subgroup of the EPIC002-study, clinical data and plasma samples were collected from 540 Gambian infants at four time-points: day of birth; first week of life; one month of age; and four months of age. Concentrations of total extracellular ADA, ADA1, and ADA2 were measured by chromogenic assay and evaluated in relation to clinical data. Plasma cytokines/chemokine were measured across the first week of life and correlated to ADA concentrations.

Results

ADA2 demonstrated a steady rise across the first months of life, while ADA1 concentration significantly decreased 0.79-fold across the first week then increased 1.4-fold by four months of life. Males demonstrated significantly higher concentrations of ADA2 (1.1-fold) than females at four months; newborns with early-term (37 to <39 weeks) and late-term (≥41 weeks) gestational age demonstrated significantly higher ADA1 at birth (1.1-fold), and those born to mothers with advanced maternal age (≥35 years) had lower plasma concentrations of ADA2 at one month (0.93-fold). Plasma ADA1 concentrations were positively correlated with plasma CXCL8 during the first week of life, while ADA2 concentrations correlated positively with TNFα, IFNγ and CXCL10, and negatively with IL-6 and CXCL8.

Conclusions

The ratio of plasma ADA2/ADA1 concentration increased during the first week of life, after which both ADA1 and ADA2 increased across the first four months of life suggesting a gradual development of Th1/Th2 balanced immunity. Furthermore, ADA1 and ADA2 were positively correlated with cytokines/chemokines during the first week of life. Overall, ADA isoforms demonstrate robust ontogeny in newborns and infants but further mechanistic studies are needed to clarify their roles in early life immune development and the correlations with sex, gestational age, and maternal age that were observed.

Integrative Metabolomics to Identify Molecular Signatures of Responses to Vaccines and Infections

Approaches to the identification of metabolites have progressed from early biochemical pathway evaluation to modern high-dimensional metabolomics, a powerful tool to identify and characterize biomarkers of health and disease. In addition to its relevance to classic metabolic diseases, metabolomics has been key to the emergence of immunometabolism, an important area of study, as leukocytes generate and are impacted by key metabolites important to innate and adaptive immunity. Herein, we discuss the metabolomic signatures and pathways perturbed by the activation of the human immune system during infection and vaccination. For example, infection induces changes in lipid (e.g., free fatty acids, sphingolipids, and lysophosphatidylcholines) and amino acid pathways (e.g., tryptophan, serine, and threonine), while vaccination can trigger changes in carbohydrate and bile acid pathways. Amino acid, carbohydrate, lipid, and nucleotide metabolism is relevant to immunity and is perturbed by both infections and vaccinations. Metabolomics holds substantial promise to provide fresh insight into the molecular mechanisms underlying the host immune response. Its integration with other systems biology platforms will enhance studies of human health and disease.

Preparing for Life: Plasma Proteome Changes and Immune System Development During the First Week of Human Life

Neonates have heightened susceptibility to infections. The biological mechanisms are incompletely understood but thought to be related to age-specific adaptations in immunity due to resource constraints during immune system development and growth. We present here an extended analysis of our proteomics study of peripheral blood-plasma from a study of healthy full-term newborns delivered vaginally, collected at the day of birth and on day of life (DOL) 1, 3, or 7, to cover the first week of life. The plasma proteome was characterized by LC-MS using our established 96-well plate format plasma proteomics platform. We found increasing acute phase proteins and a reduction of respective inhibitors on DOL1. Focusing on the complement system, we found increased plasma concentrations of all major components of the classical complement pathway and the membrane attack complex (MAC) from birth onward, except C7 which seems to have near adult levels at birth. In contrast, components of the lectin and alternative complement pathways mainly decreased. A comparison to whole blood messenger RNA (mRNA) levels enabled characterization of mRNA and protein levels in parallel, and for 23 of the 30 monitored complement proteins, the whole blood transcript information by itself was not reflective of the plasma protein levels or dynamics during the first week of life. Analysis of immunoglobulin (Ig) mRNA and protein levels revealed that IgM levels and synthesis increased, while the plasma concentrations of maternally transferred IgG1-4 decreased in accordance with their in vivo half-lives. The neonatal plasma ratio of IgG1 to IgG2-4 was increased compared to adult values, demonstrating a highly efficient IgG1 transplacental transfer process. Partial compensation for maternal IgG degradation was achieved by endogenous synthesis of the IgG1 subtype which increased with DOL. The findings were validated in a geographically distinct cohort, demonstrating a consistent developmental trajectory of the newborn's immune system over the first week of human life across continents. Our findings indicate that the classical complement pathway is central for newborn immunity and our approach to characterize the plasma proteome in parallel with the transcriptome will provide crucial insight in immune ontogeny and inform new approaches to prevent and treat diseases.

A cloud-based bioinformatic analytic infrastructure and Data Management Core for the Expanded Program on Immunization Consortium

The Expanded Program for Immunization Consortium - Human Immunology Project Consortium study aims to employ systems biology to identify and characterize vaccine-induced biomarkers that predict immunogenicity in newborns. Key to this effort is the establishment of the Data Management Core (DMC) to provide reliable data and bioinformatic infrastructure for centralized curation, storage, and analysis of multiple de-identified "omic" datasets. The DMC established a cloud-based architecture using Amazon Web Services to track, store, and share data according to National Institutes of Health standards. The DMC tracks biological samples during collection, shipping, and processing while capturing sample metadata and associated clinical data. Multi-omic datasets are stored in access-controlled Amazon Simple Storage Service (S3) for data security and file version control. All data undergo quality control processes at the generating site followed by DMC validation for quality assurance. The DMC maintains a controlled computing environment for data analysis and integration. Upon publication, the DMC deposits finalized datasets to public repositories. The DMC architecture provides resources and scientific expertise to accelerate translational discovery. Robust operations allow rapid sharing of results across the project team. Maintenance of data quality standards and public data deposition will further benefit the scientific community.