IgG 3 + B cells are associated with the development of multiple sclerosis

Objectives Disease‐modifying therapies (DMTs) targeting B cells are amongst the most effective for preventing multiple sclerosis (MS) progression. IgG3 antibodies and their uncharacterised B‐cell clones are predicted to play a pathogenic role in MS. Identifying subsets of IgG3+ B cells involved in MS progression could improve diagnosis, could inform timely disease intervention and may lead to new DMTs that target B cells more specifically. Methods We designed a 31‐parameter B‐cell‐focused mass cytometry panel to interrogate the role of peripheral blood IgG3+ B cells in MS progression of two different patient cohorts: one to investigate the B‐cell subsets involved in conversion from clinically isolated syndrome (CIS) to MS; and another to compare MS patients with inactive or active stages of disease. Each independent cohort included a group of non‐MS controls. Results Nine distinct CD20+IgD−IgG3+ B‐cell subsets were identified. Significant changes in the proportion of CD21+CD24+CD27−CD38− and CD27+CD38hiCD71hi memory B‐cell subsets correlated with changes in serum IgG3 levels and time to conversion from CIS to MS. The same CD38− double‐negative B‐cell subset was significantly elevated in MS patients with active forms of the disease. A third CD21+CD24+CD27+CD38− subset was elevated in patients with active MS, whilst narrowband UVB significantly reduced the proportion of this switched‐memory B‐cell subset. Conclusion We have identified previously uncharacterised subsets of IgG3+ B cells and shown them to correlate with autoimmune attacks on the central nervous system (CNS). These results highlight the potential for therapies that specifically target IgG3+ B cells to impact MS progression

Inverse relationship between oligoclonal expanded CD69- TTE and CD69+ TTE cells in bone marrow of multiple myeloma patients.

CD8+CD57+ terminal effector T (TTE) cells are a component of marrow-infiltrating lymphocytes and may contribute to the altered immune responses in multiple myeloma (MM) patients. We analyzed TTE cells in the bone marrow (BM) and peripheral blood (PB) of age-matched controls and patients with monoclonal gammopathy of undetermined significance (MGUS), smoldering MM (SMM), and newly diagnosed (ND) MM using flow cytometry, mass cytometry, and FlowSOM clustering. TTE cells are heterogeneous in all subjects, with BM containing both CD69- and CD69+ subsets, while only CD69- cells are found in PB. Within the BM-TTE compartment, CD69- and CD69+ cells are found in comparable proportions in controls, while CD69- cells are dominant in MGUS and SMM and predominantly either CD69- or CD69+ cells in NDMM. A positive relationship between CD69+TTE and CD69-TTE cells is observed in the BM of controls, lost in MGUS, and converted to an inverse relationship in NDMM. CD69-TTE cells include multiple oligoclonal expansions of T-cell receptor/Vβ families shared between BM and PB of NDMM. Oligoclonal expanded CD69-TTE cells from the PB include myeloma-reactive cells capable of killing autologous CD38hi plasma cells in vitro, involving degranulation and high expression of perforin and granzyme. In contrast to CD69-TTE cells, oligoclonal expansions are not evident within CD69+TTE cells, which possess low perforin and granzyme expression and high inhibitory checkpoint expression and resemble T resident memory cells. Both CD69-TTE and CD69+TTE cells from the BM of NDMM produce large amounts of the inflammatory cytokines interferon-γ and tumor necrosis factor α. The balance between CD69- and CD69+ cells within the BM-TTE compartment may regulate immune responses in NDMM and contribute to the clinical heterogeneity of the disease

“Beyond words”: a researcher’s guide to using photo elicitation in psychology

The use of photo elicitation is limited within the field of psychology despite its theoretical and practical potential. It offers significant benefits as a qualitative method that could present a new and interesting way of exploring previously understood topics within the discipline. Within our discussions, we present a Step-by-Step guide in which we outline the key practical stages, as well as ethical assurances involved in photo elicitation research, using our ongoing research as an illustrative example. It is intended that this could be used as a model of good practice for developing research paradigms beyond those typically used within the psychology discipline

Relationship between the Clinical Frailty Scale and short-term mortality in patients ≥ 80 years old acutely admitted to the ICU: a prospective cohort study.

BACKGROUND: The Clinical Frailty Scale (CFS) is frequently used to measure frailty in critically ill adults. There is wide variation in the approach to analysing the relationship between the CFS score and mortality after admission to the ICU. This study aimed to evaluate the influence of modelling approach on the association between the CFS score and short-term mortality and quantify the prognostic value of frailty in this context. METHODS: We analysed data from two multicentre prospective cohort studies which enrolled intensive care unit patients ≥ 80 years old in 26 countries. The primary outcome was mortality within 30-days from admission to the ICU. Logistic regression models for both ICU and 30-day mortality included the CFS score as either a categorical, continuous or dichotomous variable and were adjusted for patient's age, sex, reason for admission to the ICU, and admission Sequential Organ Failure Assessment score. RESULTS: The median age in the sample of 7487 consecutive patients was 84 years (IQR 81-87). The highest fraction of new prognostic information from frailty in the context of 30-day mortality was observed when the CFS score was treated as either a categorical variable using all original levels of frailty or a nonlinear continuous variable and was equal to 9% using these modelling approaches (p < 0.001). The relationship between the CFS score and mortality was nonlinear (p < 0.01). CONCLUSION: Knowledge about a patient's frailty status adds a substantial amount of new prognostic information at the moment of admission to the ICU. Arbitrary simplification of the CFS score into fewer groups than originally intended leads to a loss of information and should be avoided. Trial registration NCT03134807 (VIP1), NCT03370692 (VIP2)

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

B cells are required for sunlight protection of mice from a CNS-targeted autoimmune attack.

The ultraviolet (UV) radiation contained in sunlight is a powerful immune suppressant. While exposure to UV is associated with protection from the development of autoimmune diseases, particularly multiple sclerosis, the precise mechanism by which UV achieves this protection is not currently well understood. Regulatory B cells play an important role in preventing autoimmunity and activation of B cells is a major way in which UV suppresses adaptive immune responses. Whether UV-protection from autoimmunity is mediated by the activation of regulatory B cells has never been considered before. When C57BL/6 mice were exposed to low, physiologically relevant doses of UV, a unique population of B cells was activated in the skin draining lymph nodes. As determined by flow cytometry, CD1d(low)CD5(-)MHC-II(hi)B220(hi) UV-activated B cells expressed significantly higher levels of CD19, CD21/35, CD25, CD210 and CD268 as well as the co-stimulatory molecules CD80, CD86, CD274 and CD275. Experimental autoimmune encephalomyelitis (EAE) in mice immunized with MOG/CFA was reduced by exposure to UV. UV significantly inhibited demyelination and infiltration of inflammatory cells into the spinal cord. Consequently, UV-exposed groups showed elevated IL-10 levels in secondary lymphoid organs, delayed EAE onset, reduced peak EAE score and significantly suppressed overall disease incidence and burden. Importantly, protection from EAE could be adoptively transferred using B cells isolated from UV-exposed, but not unirradiated hosts. Indeed, UV-protection from EAE was dependent on UV activation of lymph node B cells because UV could not protect mice from EAE who were pharmacologically depleted of B cells using antibodies. Thus, UV maintenance of a pool of unique regulatory B cells in peripheral lymph nodes appears to be essential to prevent an autoimmune attack on the central nervous system

Mass cytometry discovers two discrete subsets of CD39⁻ treg which discriminate MGUS from multiple myeloma

© 2019 Marsh-Wakefield, Kruzins, McGuire, Yang, Bryant, Fazekas de St. Groth, Nassif, Byrne, Gibson, Brown, Larsen, McCulloch, Boyle, Clark, Joshua, Ho and Vuckovic. Multiple Myeloma (MM) is preceded by the clinically stable condition monoclonal gammopathy of undetermined significance (MGUS). Critical immune events that discriminate MGUS from newly diagnosed MM (ND)MM patients remain unknown, but may involve changes in the regulatory T cell (Treg) compartment that favor myeloma growth. To address this possibility, we used mass cytometry and the unsupervised clustering algorithm Flow self-organizing map (FlowSOM) to interrogate the distribution of multiple subsets within CD25+ CD127low/neg Treg in matched bone marrow (BM) and peripheral blood (PB) of MGUS and NDMM patients. Both mass cytometry and flow cytometry confirmed a trend toward prevalence of CD39− Treg within the Treg compartment in BM and PB of NDMM patients compared to CD39− Treg in MGUS patients. FlowSOM clustering displayed a phenotypic organization of Treg into 25 metaclusters that confirmed Treg heterogeneity. It identified two subsets which emerged within CD39− Treg of NDMM patients that were negligible or absent in CD39− Treg of MGUS patients. One subset was found in both BM and PB which phenotypically resembled activated Treg based on CD45RO, CD49d, and CD62L expression; another subset resembled BM-resident Treg based on its tissue-resident CD69+ CD62L− CD49d− phenotype and restricted location within the BM. Both subsets co-expressed PD-1 and TIGIT, but PD-1 was expressed at higher levels on BM-resident Treg than on activated Treg. Within BM, both subsets had limited Perforin and Granzyme B production, whilst activated Treg in PB acquired high Perforin and Granzyme B production. In conclusion, the use of mass cytometry and FlowSOM clustering discovered two discrete subsets of CD39− Treg which are discordant in MGUS and NDMM patients and may be permissive of myeloma growth which warrants further study. Understanding the regulatory properties of these subsets may also advance MGUS and MM diagnosis, prognosis, and therapeutic implications for MM patients