Biology subjects

Dekker, C. L.

Publications and source records attributed to Dekker, C. L..

7 recordsLinked to original sources

bioRxiv2025

Cytokine Regulation of Human Antibody Responses to Influenza Vaccines

Studies show that human vaccine responses widely vary. Here, we analyzed data measuring 66 cytokines from 4 different inactivated influenza vaccine (IIV) cohorts over 5 seasons (N=581) and identified a significant correlation between baseline/day 0 serum IL-18 and IFN-{beta} concentrations and the vaccine-specific antibody response on day 28, suggesting these factors may have an adjuvant-like effect. To investigate this further, we tested the impact of 19 cytokines on the development of anti-influenza antibody response when administered together with the IIV vaccine in human tonsil and spleen organoids. We found that Type I IFNs (IFN-{beta} and others), IL-21, IL-12, IL-10, but not IL-18 or IFN-{gamma}, enhanced the antibody response. The live attenuated influenza vaccine (LAIV) induced a stronger antibody response than the inactivated one in organoids. Adding a single cytokine, IFN-{beta}, to IIV stimulation recapitulated most of the live vaccine-specific cytokine activation program. It increased the antibody response of the inactivated vaccine to that of the LAIV. Two other antibody-boosting cytokines, IL-12 and IL-21, were induced by LAIV but not by Type I IFNs, indicating different cytokines can affect different pathways leading to a robust antibody response. We then generated cytokine mRNA lipid nanoparticles (LNPs) to test the effect of cytokines on IIV response in a mouse model of immunization. We found that IL-21-LNPs augmented the quantity and breadth of the antibody responses, while IFN-{beta} LNPs enhanced durability. These findings identified parallel cytokine pathways regulating human vaccine responses and provide a rationale for using cytokines as adjuvants to mimic the effectiveness of live-attenuated vaccines without the risk of viral replication.

immunology↗

bioRxiv2019

An Inflammatory Clock Predicts Multi-morbidity, Immunosenescence and Cardiovascular Aging in Humans

While many diseases of aging have been linked to the immunological system, immune metrics with which to identify the most at-risk individuals are lacking. Here, we studied the blood immunome of 1001 individuals age 8-96 and derived an inflammatory clock of aging (iAge), which tracked with multi-morbidity and immunosenescence. In centenarians, iAge was on average, 40 years lower than their corresponding chronological age. The strongest contributor to this metric was the chemokine CXCL9, which was involved in cardiac aging, affected vascular function, and down-regulated Sirtuin-3, a longevity-associated molecule. Thus, our results identify an important link between inflammatory molecules and pathways known to govern lifespan.

immunology↗

bioRxiv2019

Transcriptional program of memory B cell activation, broadly binding anti-influenza antibodies, and bystander activation after vaccination revealed by single-cell transcriptomics

Antibody memory protects humans from many diseases. Protective antibody memory responses require activation of transcriptional programs, cell proliferation, and production of antigen-specific antibodies, but how these aspects of the response are coordinated is poorly understood. We profiled the molecular and cellular features of the antibody response to influenza vaccination by integrating single-cell transcriptomics, longitudinal antibody repertoire sequencing, and antibody binding measurements. Single-cell transcriptional profiling revealed a program of memory B cell activation characterized by CD11c and T-bet expression associated with clonal expansion and differentiation toward effector function. Vaccination elicited an antibody clone which rapidly acquired broad high-affinity hemagglutinin binding during affinity maturation. Unexpectedly, many antibody clones elicited by vaccination do not bind vaccine, demonstrating non-specific activation of bystander antibodies by influenza vaccination. These results offer insight into how molecular recognition, transcriptional programs, and clonal proliferation are coordinated in the human B cell repertoire during memory recall.

immunology↗

bioRxiv2019

The FluPRINT dataset: A multidimensional analysis of the influenza vaccine imprint on the immune system

Recent advances in machine learning have allowed identification of molecular and cellular factors that underly successful antibody responses to influenza vaccines. Results of these studies have revealed the high level of complexity necessary to establish influenza immunity, and many different cellular and molecular components involved. However, identified correlates of protection fail to account for the majority of vaccinated cases across ages, cohorts, and influenza seasons. Major challenges arise from small sample sizes and from analysis of only one aspect of the biology such by using transcriptome data. The objective of the current study is to create a unified database, entitled FluPRINT, to enable a large-scale study exploring novel cellular and molecular underpinnings of successful immunity to influenza vaccines. Over 3,000 parameters were considered, including serological responses to influenza strains, serum cytokines, cell subset phenotypes, and cytokine stimulations. FluPRINT, thus facilitates application of machine learning algorithms for data mining. The data are publicly available and represent a resource to uncover new markers and mechanisms that drive successful influenza vaccination.

systems biology↗

bioRxiv2019

SIMON, an automated machine learning system reveals immune signatures of influenza vaccine responses

Machine learning holds considerable promise for understanding complex biological processes such as vaccine responses. Capturing interindividual variability is essential to increase the statistical power necessary for building more accurate predictive models. However, available approaches have difficulty coping with incomplete datasets which is often the case when combining studies. Additionally, there are hundreds of algorithms available and no simple way to find the optimal one. Here, we developed Sequential Iterative Modelling "OverNight" or SIMON, an automated machine learning system that compares results from 128 different algorithms and is particularly suitable for datasets containing many missing values. We applied SIMON to data from five clinical studies of seasonal influenza vaccination. The results reveal previously unrecognized CD4+ and CD8+ T cell subsets strongly associated with a robust antibody response to influenza antigens. These results demonstrate that SIMON can greatly speed up the choice of analysis modalities. Hence, it is a highly useful approach for data-driven hypothesis generation from disparate clinical datasets. Our strategy could be used to gain biological insight from ever-expanding heterogeneous datasets that are publicly available.

immunology↗

bioRxiv2017

Signatures of Selection in the Human Antibody Repertoire: Selective Sweeps, Competing Subclones, and Neutral Drift

Antibodies are created and refined by somatic evolution in B cell populations, which endows the human immune system with the ability to recognize and eliminate diverse pathogens. However, the evolutionary processes that sculpt antibody repertoires remain poorly understood. Here, using an unbiased repertoire-scale approach, we show that the molecular signatures of evolution are evident in human B cell lineages and reveal how antibodies evolve somatically. We measured the dynamics and genetic diversity of B cell responses of five adults longitudinally before and after influenza vaccination using high-throughput antibody repertoire sequencing. We identified vaccine-responsive B cell lineages that carry signatures of selective sweeps driven by positive selection, and discovered that they often display evidence for selective sweeps favoring multiple subclones. We also found persistent B cell lineages that exhibit stable population dynamics and carry signatures of neutral drift. By exploiting the linkage between B cell fitness and antibody binding affinity, we demonstrated the potential for using signatures of selection to identify antibodies with high binding affinity. This quantitative characterization reveals that antibody repertoires are shaped by an unexpectedly broad spectrum of evolutionary processes and shows how signatures of evolutionary history can be harnessed for antibody discovery and engineering.\n\nOne Sentence SummaryMolecular signatures of somatic evolution reveal that diverse evolutionary processes ranging from strong positive selection to neutral drift sculpt human antibodies.

immunology↗

bioRxiv2017

Dynamics Of The Human Antibody Repertoire Following B-cell Depletion In Systemic Sclerosis

Systemic sclerosis with pulmonary arterial hypertension (SSc-PAH) is a debilitating and frequently lethal disease of unknown cause lacking effective treatment options. Lymphocyte anomalies and autoantibodies observed in systemic sclerosis have suggested an autoimmune character. Here we study the clonal structure of the B-cell repertoire in SSc-PAH using immunoglobulin heavy-chain sequencing before and after B-cell depletion. We found SSc-PAH to be associated with anomalies in B-cell development, namely altered VDJ rearrangement frequencies (reduced IGHV2-5 segment usage) and an increased somatic mutation-fixation probability in expanded B-cell lineages. SSc-PAH was also characterized by anomalies in B-cell homeostasis, namely an expanded IgD+ proportion with reduced mutation loads and an expanded proportion of highly antibody-secreting cells. Disease signatures pertaining to IGHV2-5 segment usage, IgD proportions and mutation loads were temporarily reversed after B-cell depletion. Analyzing the time course of B-cell depletion, we find that the kinetics of naive replenishment are predictable from baseline measurements alone, that release of plasma cells into the periphery can precede naive replenishment and that modes of B-cell receptor diversity are highly elastic. Our findings shed light on the humoral immune basis of SSc-PAH and provide insights into the effect of B-cell depletion on the antibody repertoire.\n\nAbbreviations

immunology↗