Foxp3 molecular dynamics in Treg in juvenile idiopathic arthritis

Since the identification of the regulatory T-cell (Treg)-associated transcription factor Foxp3, there have been intensive research efforts to understand its biology and roles in maintaining immune homeostasis. It is well established that thymic selection of a repertoire of self-reactive Foxp3+ T-cells provides an essential mechanism to minimize reactions to self-antigens in the periphery, and thus aid in the prevention of autoimmunity. It is clear from both genetic and immunological analyses of juvenile idiopathic arthritis (JIA) patients that T-cells have a strong role to play in both the initiation and propagation of disease. The current paradigm is to view autoimmunity as a consequence of an imbalance between inflammatory and immunoregulatory mechanisms. This view has led to the assigning of cells and inflammatory mediators to different classes based on their assumed pro- or anti-inflammatory roles. This is typically reported as ratios of effector T-cells to Treg cells. Problematically, many analyses are based on static “snapshots-in-time,” even though both mouse models and human patient studies have highlighted the dynamic nature of Foxp3+ T-cells in vivo, which can exhibit plasticity and time-dependent functional states. In this review, we discuss the role of Foxp3 dynamics in the control of T-cell responses in childhood arthritis, by reviewing evidence in humans and relevant mouse models of inflammatory disease. Whilst the cellular dynamics of Treg have been well evaluated—leading to standard data outputs such as frequency, quantity and quality (often assessed by in vitro suppressive capacity)—we discuss how recent insights into the molecular dynamics of Foxp3 transcription and its post-translational control may open up tantalizing new avenues for immunotherapies to treat autoimmune arthritis

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Antigen and checkpoint receptor engagement recalibrates T cell receptor signal strength

How T cell receptor (TCR) signal strength modulates T cell function and to what extent this is modified by immune checkpoint blockade (ICB) are key questions in immunology. Using Nr4a3-Tocky mice, we characterized early quantitative and qualitative changes that occur in CD4(+) T cells in relation to TCR signaling strength. We captured how dose- and time-dependent programming of distinct co-inhibitory receptors rapidly recalibrates T cell activation thresholds and visualized the immediate effects of ICB on T cell re-activation. Our findings reveal that anti-PD1 immunotherapy leads to an increased TCR signal strength. We defined a strong TCR signal metric of five genes upregulated by anti-PD1 in T cells (TCR.strong), which was superior to a canonical T cell activation gene signature in stratifying melanoma patient outcomes to anti-PD1 therapy. Our study therefore reveals how analysis of TCR signal strength—and its manipulation—can provide powerful metrics for monitoring outcomes to immunotherapy

Pseudaminic acid on Campylobacter jejuni flagella modulates dendritic cell IL-10 expression via Siglec-10 receptor: a novel flagellin-host interaction.

INTRODUCTION: Campylobacter jejuni is a leading cause of bacterial gastroenteritis worldwide. At present the identity of host-pathogen interactions that promote successful bacterial colonisation remain ill defined. Herein, we aimed to investigate C. jejuni-mediated effects on dendritic cell (DC) immunity. RESULTS: We found C. jejuni to be a potent inducer of human and murine DC interleukin 10 (IL-10) in vitro, a cellular event that was MyD88- and p38 MAPK-signalling dependent. Utilizing a series of C. jejuni isogenic mutants we found the major flagellin protein, FlaA, modulated IL-10 expression, an intriguing observation as C. jejuni FlaA is not a TLR5 agonist. Further analysis revealed pseudaminic acid residues on the flagella contributed to DC IL-10 expression. We identified the ability of both viable C. jejuni and purified flagellum to bind to Siglec-10, an immune-modulatory receptor. In vitro infection of Siglec-10 overexpressing cells resulted in increased IL-10 expression in a p38-dependent manner. Detection of Siglec-10 on intestinal CD11c(+) CD103(+) DCs added further credence to the notion that this novel interaction may contribute to immune outcome during human infection. CONCLUSIONS: We propose that unlike the Salmonella Typhimurium flagella-TLR5 driven pro-inflammatory axis, C. jejuni flagella instead promote an anti-inflammatory axis via glycan-Siglec-10 engagement

Bacterial cancer therapy in autochthonous colorectal cancer affects tumor growth and metabolic landscape

Bacterial cancer therapy (BCT) shows great promise for treatment of solid tumors, yet basic mechanisms of bacterial-induced tumor suppression remain undefined. Attenuated strains of Salmonella enterica serovar Typhimurium (STm) have commonly been used in mouse models of BCT in xenograft and orthotopic transplant cancer models. We aimed to better understand the tumor epithelium–targeted mechanisms of BCT by using autochthonous mouse models of intestinal cancer and tumor organoid cultures to assess the effectiveness and consequences of oral treatment with aromatase A–deficient STm (STm(Δ)aroA). STm(Δ)aroA delivered by oral gavage significantly reduced tumor burden and tumor load in both a colitis-associated colorectal cancer (CAC) model and in a spontaneous Apc(min/+) intestinal cancer model. STm(Δ)aroA colonization of tumors caused alterations in transcription of mRNAs associated with tumor stemness, epithelial-mesenchymal transition, and cell cycle. Metabolomic analysis of tumors demonstrated alteration in the metabolic environment of STm(Δ)aroA-treated tumors, suggesting that STm(Δ)aroA imposes metabolic competition on the tumor. Use of tumor organoid cultures in vitro recapitulated effects seen on tumor stemness, mesenchymal markers, and altered metabolome. Furthermore, live STm(Δ)aroA was required, demonstrating active mechanisms including metabolite usage. We have demonstrated that oral BCT is efficacious in autochthonous intestinal cancer models, that BCT imposes metabolic competition, and that BCT has direct effects on the tumor epithelium affecting tumor stem cells

Exploring the sequence determinants of amyloid structure using position-specific scoring matrices

Protein aggregation results in beta-sheet-like assemblies that adopt either a variety of amorphous morphologies or ordered amyloid-like structures. These differences in structure also reflect biological differences; amyloid and amorphous beta-sheet aggregates have different chaperone affinities, accumulate in different cellular locations and are degraded by different mechanisms. Further, amyloid function depends entirely on a high intrinsic degree of order. Here we experimentally explored the sequence space of amyloid hexapeptides and used the derived data to build Waltz, a web-based tool that uses a position-specific scoring matrix to determine amyloid-forming sequences. Waltz allows users to identify and better distinguish between amyloid sequences and amorphous beta-sheet aggregates and allowed us to identify amyloid-forming regions in functional amyloids