Vitamin D deficiency after allogeneic hematopoietic cell transplantation promotes T-cell activation and is inversely associated with an EZH2-ID3 signature.

Vitamin D promotes a shift from a proinflammatory to a more tolerogenic immune state in allogeneic hematopoietic cell transplant (HCT) recipients. The dominant mechanism responsible for this shift has not been elucidated. We took a multifaceted approach to evaluating the clinical and immunologic impact of low vitamin D levels in 53 HCT recipients. We used 28-plex flow cytometry for immunophenotyping, serum cytokine levels, T-cell cytokine production, and T-cell whole genome transcription. The median day-30 vitamin D level was 20 ng/mL, and deficiency was common in younger patients undergoing myeloablative transplantation. Low vitamin D levels were associated with a high CD8/Treg ratio, increased serum levels and T-cell production of proinflammatory cytokines, and a gene expression signature of unrestrained T-cell proliferation and epigenetic modulation through the PRC2/EZH2 complex. Immunophenotyping confirmed a strong association between high levels of vitamin D and an activated EZH2 signature, characterized by overexpression of ID3, which has a role in effector T-cell differentiation. Our findings demonstrate the critical role of vitamin D in modulating T-cell function in human GVHD and identify a previously undescribed interaction with EZH2 and ID3, which may impact effector differentiation and has implications to cell therapies and other forms of cancer immunotherapy. © 20XX American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.

Longitudinal profiling of respiratory and systemic immune responses reveals myeloid cell-driven lung inflammation in severe COVID-19.

Immune response dynamics in coronavirus disease 2019 (COVID-19) and their severe manifestations have largely been studied in circulation. Here, we examined the relationship between immune processes in the respiratory tract and circulation through longitudinal phenotypic, transcriptomic, and cytokine profiling of paired airway and blood samples from patients with severe COVID-19 relative to heathy controls. In COVID-19 airways, T cells exhibited activated, tissue-resident, and protective profiles; higher T cell frequencies correlated with survival and younger age. Myeloid cells in COVID-19 airways featured hyperinflammatory signatures, and higher frequencies of these cells correlated with mortality and older age. In COVID-19 blood, aberrant CD163+ monocytes predominated over conventional monocytes, and were found in corresponding airway samples and in damaged alveoli. High levels of myeloid chemoattractants in airways suggest recruitment of these cells through a CCL2-CCR2 chemokine axis. Our findings provide insights into immune processes driving COVID-19 lung pathology with therapeutic implications for targeting inflammation in the respiratory tract.

Variable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation.

Allogeneic hematopoietic cell transplantation (allo-HCT) is a potentially curative procedure for a large number of diseases. However, the greatest barriers to the success of allo-HCT are relapse and graft-versus-host-disease (GVHD). Many studies have examined the reconstitution of the immune system after allo-HCT and searched for factors associated with clinical outcome. Serum biomarkers have also been studied to predict the incidence and prognosis of GVHD. However, the use of multiparametric immunophenotyping has been less extensively explored: studies usually focus on preselected and predefined cell phenotypes and so do not fully exploit the richness of flow cytometry data. Here we aimed to identify cell phenotypes present 30 days after allo-HCT that are associated with clinical outcomes in 37 patients participating in a trial relating to the prevention of GVHD, derived from 82 flow cytometry markers and 13 clinical variables. To do this we applied variable selection methods in a competing risks modeling framework, and identified specific subsets of T, B, and NK cells associated with relapse. Our study demonstrates the value of variable selection methods for mining rich, high dimensional clinical data and identifying potentially unexplored cell subpopulations of interest.

ushr: Understanding suppression of HIV in R.

BACKGROUND: HIV/AIDS is responsible for the deaths of one million people every year. Although mathematical modeling has provided many insights into the dynamics of HIV infection, there is still a lack of accessible tools for researchers unfamiliar with modeling techniques to apply them to their own clinical data. RESULTS: Here we present ushr, a free and open-source R package that models the decline of HIV during antiretroviral treatment (ART) using a popular mathematical framework. ushr can be applied to longitudinal data of viral load measurements, and provides processing tools to prepare it for computational analysis. By mathematically fitting the data, important biological parameters can then be estimated, including the lifespans of short and long-lived infected cells, and the time to reach viral suppression below a defined detection threshold. The package also provides visualization and summary tools for fast assessment of model results. CONCLUSIONS: ushr enables researchers without a strong mathematical or computational background to model the dynamics of HIV using longitudinal clinical data. Increasing accessibility to such methods may facilitate quantitative analysis across a broader range of independent studies, so that greater insights on HIV infection and treatment dynamics may be gained.

A wave of monocytes is recruited to replenish the long-term Langerhans cell network after immune injury.

A dense population of embryo-derived Langerhans cells (eLCs) is maintained within the sealed epidermis without contribution from circulating cells. When this network is perturbed by transient exposure to ultraviolet light, short-term LCs are temporarily reconstituted from an initial wave of monocytes but thought to be superseded by more permanent repopulation with undefined LC precursors. However, the extent to which this process is relevant to immunopathological processes that damage LC population integrity is not known. Using a model of allogeneic hematopoietic stem cell transplantation, where alloreactive T cells directly target eLCs, we have asked whether and how the original LC network is ultimately restored. We find that donor monocytes, but not dendritic cells, are the precursors of long-term LCs in this context. Destruction of eLCs leads to recruitment of a wave of monocytes that engraft in the epidermis and undergo a sequential pathway of differentiation via transcriptionally distinct EpCAM+ precursors. Monocyte-derived LCs acquire the capacity of self-renewal, and proliferation in the epidermis matched that of steady-state eLCs. However, we identified a bottleneck in the differentiation and survival of epidermal monocytes, which, together with the slow rate of renewal of mature LCs, limits repair of the network. Furthermore, replenishment of the LC network leads to constitutive entry of cells into the epidermal compartment. Thus, immune injury triggers functional adaptation of mechanisms used to maintain tissue-resident macrophages at other sites, but this process is highly inefficient in the skin.

Identifying T Cell Receptors from High-Throughput Sequencing: Dealing with Promiscuity in TCRα and TCRß Pairing.

Characterisation of the T cell receptors (TCR) involved in immune responses is important for the design of vaccines and immunotherapies for cancer and autoimmune disease. The specificity of the interaction between the TCR heterodimer and its peptide-MHC ligand derives largely from the juxtaposed hypervariable CDR3 regions on the TCRα and TCRß chains, and obtaining the paired sequences of these regions is a standard for functionally defining the TCR. A brute force approach to identifying the TCRs in a population of T cells is to use high-throughput single-cell sequencing, but currently this process remains costly and risks missing small clones. Alternatively, CDR3α and CDR3ß sequences can be associated using their frequency of co-occurrence in independent samples, but this approach can be confounded by the sharing of CDR3α and CDR3ß across clones, commonly observed within epitope-specific T cell populations. The accurate, exhaustive, and economical recovery of TCR sequences from such populations therefore remains a challenging problem. Here we describe an algorithm for performing frequency-based pairing (alphabetr) that accommodates CDR3α- and CDR3ß-sharing, cells expressing two TCRα chains, and multiple forms of sequencing error. The algorithm also yields accurate estimates of clonal frequencies.