Bram van Cranenbroek

Vedolizumab, a gut-selective integrin antagonist, is an effective therapy for inflammatory bowel disease (IBD), but immune correlates of treatment response remain poorly understood. We performed longitudinal immune profiling of blood and serum from 20 vedolizumab-treated IBD patients (15 Crohn’s disease, 5 ulcerative colitis) to characterize treatment-associated immune changes and identify baseline features associated with clinical response. Samples were collected at baseline and week 14. Immune cell phenotyping was performed using five 10-color flow cytometry panels, while serum proteomics was assessed with the Olink^® 96 Inflammation panel. Age- and sex-matched healthy controls (HCs) were included for comparison. IBD patients could be distinguished from HCs based primarily on immune cell profiles, whereas serum proteomic differences were less pronounced. Vedolizumab treatment induced modest changes in immune cell composition and serum proteins. Clinical responders exhibited shifts in three immune populations and a reduction in CXCL8 and IL-6 levels by week 14. Unsupervised hierarchical clustering of five baseline immune cell populations stratified patients into two groups that broadly corresponded with treatment outcome. Furthermore, non-responders exhibited increased IFNγ and CXCL9 levels. However, these immune cell populations and proteins did not remain significant upon correcting for multiple testing. Taken together, we identified exploratory immune and cytokine patterns associated with vedolizumab response that may support the development of precision medicine approaches in IBD.

Pregnancy after renal transplantation is associated with an increased risk of complications. While a delicately balanced uterine immune system is essential for a successful pregnancy, little is known about the uterine immune environment of pregnant kidney transplant recipients. Moreover, children born to kidney transplant recipients are exposed in utero to immunosuppressive drugs, with possible consequences for neonatal outcomes. Here, we defined the effects of kidney transplantation on the immune cell composition during pregnancy with a cohort of kidney transplant recipients as well as healthy controls with uncomplicated pregnancies. Maternal immune cells from peripheral blood were collected during pregnancy as well as from decidua and cord blood obtained after delivery. Multiparameter flow cytometry was used to identify and characterize populations of cells. While systemic immune cell frequencies were altered in kidney transplant patients, immune cell dynamics over the course of pregnancy were largely similar to healthy women. In the decidua of women with a kidney transplant, we observed a decreased frequency of HLA-DR⁺ Treg, particularly in those treated with tacrolimus versus those that were treated with azathioprine next to tacrolimus, or with azathioprine alone. In addition, both the innate and adaptive neonatal immune system of children born to kidney transplant recipients was significantly altered compared to neonates born from uncomplicated pregnancies. Overall, our findings indicate a significant and distinct impact on the maternal systemic, uterine, and neonatal immune cell composition in pregnant kidney transplant recipients, which could have important consequences for the incidence of pregnancy complications, treatment decisions, and the offspring’s health.

Psoriasis (Pso) is a chronic inflammatory skin disease, and up to 30% of Pso patients develop psoriatic arthritis (PsA), which can lead to irreversible joint damage. Early detection of PsA in Pso patients is crucial for timely treatment but difficult for dermatologists to implement. We, therefore, aimed to find disease-specific immune profiles, discriminating Pso from PsA patients, possibly facilitating the correct identification of Pso patients in need of referral to a rheumatology clinic. The phenotypes of peripheral blood immune cells of consecutive Pso and PsA patients were analyzed, and disease-specific immune profiles were identified via a machine learning approach. This approach resulted in a random forest classification model capable of distinguishing PsA from Pso (mean AUC = 0.95). Key PsA-classifying cell subsets selected included increased proportions of differentiated CD4+CD196+CD183-CD194+ and CD4+CD196-CD183-CD194+ T-cells and reduced proportions of CD196+ and CD197+ monocytes, memory CD4+ and CD8+ T-cell subsets and CD4+ regulatory T-cells. Within PsA, joint scores showed an association with memory CD8+CD45RA-CD197- effector T-cells and CD197+ monocytes. To conclude, through the integration of in-depth flow cytometry and machine learning, we identified an immune cell profile discriminating PsA from Pso. This immune profile may aid in timely diagnosing PsA in Pso.

Different components of the immune response show large variability between individuals, but they also vary within the same individual because of host and environmental factors. In this study, we report an extensive analysis of the immune characteristics of 56 individuals over four timepoints in 1 single year as part of the Human Functional Genomics Project. We characterized 102 cell subsets using flow cytometry; quantified production of eight cytokines and two chemokines in response to 20 metabolic, bacterial, fungal, and viral stimuli; and measured circulating markers of inflammation. Taking advantage of the longitudinal sampling, both seasonal and nonseasonal sources of variability were studied. The circulating markers of inflammation IL-18, IL-18 binding protein, and resistin displayed clear seasonal variability, whereas the strongest effect was observed for α-1 antitrypsin. Cytokine production capacity also showed strong seasonal changes, especially after stimulation with the influenza virus, Borrelia burgdorferi, and Escherichia coli. Furthermore, we observed moderate seasonality effects on immune cell counts, especially in several CD4+/CD8+ T cell subpopulations. Age of the volunteers was an important factor influencing IFN-γ and IL-22 production, which matched the strong impact of age on several T cell subsets. Finally, on average, genetics accounted for almost 50% of the interindividual variance not already explained by age, sex, and body mass index, although this varies strongly for different parameters. In conclusion, seasonality is an important environmental factor that influences immune responses, in addition to specific genetic and nongenetic host factors, and this may well explain the seasonal variation in the incidence and severity of immune-mediated diseases.