Title Promoter Affiliations Abstract "The beta-cell and the immune system in type 1 diabetes: partners in crime - developing new therapies in type 1 diabetes through better understanding of beta-cell behaviour and use of novel immunomodulators." "Chantal Mathieu" "Clinical and Experimental Endocrinology" "Type 1 diabetes (T1D) is a lifelong autoimmune disease where the immune system selectively destroys the pancreatic insulin-producing beta-cells leading to absolute insulin deficiency. Although our understanding of the (immune) mechanisms involved in T1D is growing, it still remains incomplete but the beta-cell has been positively identified as both driver and target of the disease. The steep increase in incidence and the younger age at onset suggest that environmental beta-cell stress triggers, against the background of genetic risk, are implicated both as triggers and potentiators of beta-cell destruction. To develop effective therapies, we need to expand our knowledge on the interaction between an autoimmune-prone immune system and the beta-cells, especially since none of the current approaches have succeeded in stably preserving or restoring beta-cell mass/function in T1D patients. Here, we aim to better understand the lethal dialogue between immune system and islet beta-cell to come to novel intervention strategies." "The beta-cell and the immune system in type 1 diabetes: partners in crime - developing new therapies in type 1 diabetes through better understanding of beta-cell behaviour and use of novel immunomodulators." "Chantal Mathieu" "Clinical and Experimental Endocrinology, Gene Expression Unit" "Prevention of type 1 diabetes (T1D), the most common metabolic disease in childhood and adolescence, remains an elusive goal, with therapy after therapy failing to demonstrate long-term efficacy in arresting the autoimmune attack against the pancreatic insulin-producing beta-cell in people at risk for or with recent T1D. We propose to pursue an integrated approach, recognizing the crucial role of both the immune system and the beta-cell in the pathophysiology and natural history of the disease. Our hypothesis is that besides the (auto)-immune system the beta-cell itself is a dynamic partner in the T1D disease process. We believe that this partner should not be neglected when considering new strategies for intervention and disease prevention. The beta-cell is the key as a renewable source of new beta-cells, a provider of beta-cell antigens, a potential source of chemokine production and as a target not only for cell death, but also for dysfunction in the presence of inflammation and immune attack. We recognize moreover the role of the environment, in particular nutrition, in determining immunogenicity, function, and survival of the beta-cell under immune attack. In the present project we want to exploit our expertise in transcriptomics, proteomics, preclinical animal models of T1D and clinical immune interventions to gain further insight into the destructive interaction between the beta-cell and the immune system in T1D. Exchanges of findings between different work packages is maximized, as is cross-fertilization between techniques and expertise in our diverse consortium, consisting of beta-cell physiologists, nutritionists, immunologists, hormone (vitamin D) specialists, T1D animal model specialists, and clinicians, with experience in immune interventions in T1D patients. We have brought together this diverse consortium to realize our objective: To develop novel therapies to stop T1D through a better understanding of beta-cell behavior and the use of novel immunomodulators." "Translational approaches to disease modifying therapy of type 1 diabetes: An innovative approach towards understanding and arresting Type 1 diabetes – time to harvest." "Chantal Mathieu" "Clinical and Experimental Endocrinology" "In the previous 4 years, the INNODIA project has built a landmark sample collection network in Europe and has established the go-to platform for clinical trials in T1D intervention, aimed at achieving protection of functional beta-cell mass.In a close collaboration between basic, translational and clinical researchers, industry partners, foundations and also people living with T1D we have built a platform of biomarker analysis using standardized sample collections, sample analysis and bioinformatics assisted integration of data. Our approach allows integrated analysis of multiple biomarkers and robust modeling of disease. Sample collection in people with newly diagnosed T1D and at-risk family members is ongoing in an unprecedented manner in Europe and has established a unique living biobank.In a similar way, we have built a clinical trials network in EU, that is now the unique network for clinical trials for interventions for at risk individuals or newly diagnosed people with T1D. Now we are at a point where we can move INNODIA to the next level and harvest the seedings of the original project:-We want to consolidate the INNODIA clinical network into the network of reference for conducting intervention studies targeted at preventing or arresting T1D. This step harvests on the establishment of our clinical sample collection network. We introduce next to the one study in the original INNODIA project, at least 2 large phase 2 trials, as well as several small mechanistic trials. -We want to continuously introduce novel biomarkers into the evolving cloud of biomarkers used in the natural history study, in particular biomarkers coming from the basic research laboratories, biomarkers identified at the time of INNODIA writing, that could not be integrated due to lack of funding.-We want to harvest on our potential to introduce disruptors of the pathogenic process in T1D, targeting different players and link these disruptors to biomarker changes, thus providing the potential to arrive to earlier read-out of intervention studies and faster drug development.-We want to feed back findings from our intervention studies and biomarker signature changes to the basic laboratories, to study the impact of heterogeneity on therapeutic success and move to personalized medicine." "Prediction of pregnancy outcomes in women with gestational diabetes and their risk to develop diabetes postpartum." "Chantal Mathieu" "Clinical and Experimental Endocrinology" "Recently a one-step screening strategy with more stringent criteria to diagnose gestational diabetes (GDM) has been proposed by ‘The International Association of Diabetes and Pregnancy Study Groups’ (IADPSG). The use of this new screening strategy for GDM remains controversial, mainly because of paucity of data on the cost effectiveness of such strategy, the uncertainty on the clinical relevance of treatment of mild GDM based on the IADPSG criteria and the uncertainty on the risk of women who have had mild GDM to develop type 2 diabetes postpartum. We therefore plan to start a large multi-centric cohort study to search for the best screening strategy for pregestational diabetes early in pregnancy and to investigate the most cost effective screening strategy for GDM as well as the best follow up strategy after pregnancy in women with previous GDM in the Belgian setting. After excluding pregestational diabetes in the first trimester, women will receive universal screening for GDM comparing different methods of screening (two-step vs. one-step) and different diagnostic criteria. In women with previous GDM, the degree of carbohydrate intolerance will be evaluated 3 and 12 months postpartum. Here we wish to gain insight in biomarkers present in women with GDM that will allow prediction of pregnancy outcomes and the risk to develop diabetes after the delivery. Biomarkers for inflammation, insulin resistance, beta-cell dysfunction and ongoing autoimmune disease will be investigated. These insights will help to better tailor the follow up strategy for both mother and offspring." "Early detection of Diabetes trough advanced data mining techniques." "Bart De Moor" "ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics" "Diabetes mellitus is a metabolic disorder characterized by chronic hyperglycemia, which may cause serious harm to many of the body's systems. Diabetes is a deadly pandemic which presents a significant burden on healthcare systems worldwide, and will continue to do so as its global prevalence rises rapidly (particularly type 2 diabetes). In developed countries, the rising prevalence is primarily driven by population aging, lifestyle changes and greater longevity of diabetes patients. Diabetes can be managed effectively when detected early. Unfortunately, early detection proves difficult as the time between onset and clinical diagnosis may span several years. Furthermore, estimates indicate that over one third of diabetes patients in developed countries are undiagnosed.We investigated the potential of Belgian health expenditure data as a basis to build a cost-effective population-wide screening approach for (type 2) diabetes mellitus, aspiring to improve secondary prevention by speeding up the diagnosis of patients in order to initiate treatment before the disease has caused irrevocable damage. We used health expenditure data collected by the National Alliance of Christian Mutualities - the largest social health insurer in Belgium. This data comprises basic biographic information and records of all refunded medical interventions and drug purchases, thus providing a long-term longitudinal overview of over 4 million individuals' medical expenditure histories.Screening was formulated as a binary classification task, in which diabetes patients represent the positive class. Due to the nature of the problem and limitations of health expenditure data, we were unable to identify a set of known negatives (patients without diabetes). Hence, we had to learn classifiers from positive and unlabeled data. During this project we made two contributions to this subdomain of semi-supervised learning: (i) a novel learning method which is robust to false positives and (ii) an approach to evaluate classifiers using traditional metrics without known negatives in the test set. Additionally, we mapped the survival of patients starting various antidiabetic pharmacotherapies and developed two open-source machine learning packages: one for ensemble learning and another to automate hyperparameter search.We built a screening method with competitive performance to existing state-of-the-art approaches. This exceeded our expectations, since health expenditure data omits most info about the typical risk factors used by other screening methods (BMI, lifestyle, genetic predisposition, ...). As such, the combination of health expenditure data and additional information about risk factors is a promising avenue for future research in screening for diabetes mellitus. Finally, our approach has a very low operational cost since we only used readily-available data, which effectively removes one of the key barriers of population-wide screening for diabetes." "Promotion of a healthy lifestyle in women with a history of gestational diabetes" "Katrien Fouzia Benhalima" "Woman and Child, Clinical and Experimental Endocrinology" "The prevalence of gestational diabetes (GDM) increases worldwide with rates between 9-35%, posing challenges to maintain high-quality care in the management of GDM. A valuable solution to cope with this increasing burden could be the organization of group education. In this research project, we will analyze the collected data of a prospective observational cohort study with the aim to evaluate women’s satisfaction about (group) education, their knowledge about GDM and their emotional status (the ELENA study).Moreover, GDM might be the best well-known predictor for subsequent development of type 2 diabetes mellitus (T2DM), as it is estimated that approximately one-third of women with T2DM may have had previous GDM. Recent research conducted at UZ Leuven has shown that 42% of women with GDM, diagnosed on the basis of the 2013 WHO criteria, experienced glucose intolerance in early postpartum. The goal of this research is to further investigate the prevalence of and risk factors for glucose intolerance and T2DM in early postpartum.Literature has established that lifestyle modifications are effective in the prevention of diabetes when offered to high risk middle-age individuals, but there is limited evidence regarding the effectiveness of lifestyle interventions in women with recent GDM. We will therefore conduct a randomized controlled trial with 1 year of follow-up to evaluate the efficacy and feasibility of a telephone and mobile-based lifestyle intervention in women with glucose intolerance after a recent history of GDM to promote a healthy lifestyle (the MELINDA study)." "Neutrophils and post-translationally modified beta-cell proteins: a driving force behind type 1 diabetes?" "Chantal Mathieu" "Clinical and Experimental Endocrinology" "Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by the selective destruction of the pancreatic insulin-producing beta cells by infiltrating immune cells, leading to an absolute insulin deficiency. The prevalence of T1D is increasing worldwide and the concern regarding the number of new T1D cases relates in part to the development of chronic complications, either microvascular (i.e., retinopathy, neuropathy, and nephropathy) or macrovascular (i.e., cardiovascular disease, cerebrovascular accidents, and peripheral vascular disease). Although innate immune cells like dendritic cells and macrophages are well known to be involved in distinct aspects of T1D development, less is known about the role of neutrophils in the different developmental stages and clinical disease features. Once thought to be relatively short-lived homogenous innate immune cells, restricted to their role of ‘first responders’, neutrophils are now believed to possess phenotypic and functional heterogeneity and plasticity that has set them at the center of the stage in autoimmune disease research. Neutrophils are capable of multiple functions such as phagocytosis, degranulation and most notably, neutrophil extracellular trap (NET) formation (NETosis), which involves the extrusion of chromatin entangled with anti-microbial proteins. The later has been shown to be implicated in not only direct cell damage through the release of inflammatory proteins such as myeloperoxidase (MPO) and neutrophil elastase (ELANE), but also in the generation of autoantigens. Neutrophils undergoing NETosis have been detected within the pancreas of both pre-symptomatic autoantibody positive and newly-diagnosed T1D individuals. Increased levels of NET markers such as MPO and ELANE have been observed in the periphery of T1D patients. Also, increased NETosis has been linked to vascular complications of the disease. Yet, the exact role of neutrophils and their functional characteristics in T1D pathophysiology remains to be elucidated. While neutrophils have displayed multidimensional functions and phenotypes in many autoimmune disorders, research is scarce on the various neutrophil subsets in these diseases. Recent evidence suggests however that neutrophils may be composed of specific subpopulations that are phenotypically, functionally, and transcriptionally distinct. Some of these neutrophil populations, described as low-density neutrophils (LDNs) with a ‘lower buoyant density’, were found to settle within the peripheral blood mononuclear cell layer after density gradient centrifugation of whole blood. Immunosuppressive subsets were also found within the normal-density neutrophil layer (normal-density neutrophils, NDN). Some of these subtypes have been linked to the pathophysiology of various autoimmune diseases and cancers. While all these neutrophil populations are characterized by a neutrophil-like morphology and the expression of granulocyte lineage markers, their phenotype, maturation/activation status, and function are different depending on the disease type. Here we studied the characteristics of neutrophils from individuals in different developmental stages of T1D, compared to those of age-, sex-, race-matched healthy controls (HC). We focused primarily on NET formation, in terms of levels and peripheral markers indicative of the process, and neutrophil subtypes such as LDNs that could play a role in the pathophysiology of the disease." "Link between residual beta cell function and glycemic variability in (pre)type 1 diabetes" "Frans Gorus" "Experimental Pharmacology, KU Leuven, Ghent University, University of Antwerp, Pathologic Biochemistry and Physiology" "Type 1 diabetes develops when 60 to 90% of insulin-producing beta cells have been destroyed. This cell loss leads to greater variability of blood glucose levels both before and after diagnosis. This variability is predictive of progression to clinical onset of diabetes in risk groups and of frequence of hypoglycemic events in patients. Novel beta cell therapy trials aim to prevent or cure diabetes by trying to preserve or restore functional beta cell mass. In preparation of future trials the collaborating teams of the present application have validated dynamic tests to measure functional beta cell mass in vivo through prolonged stimulation of beta cells by elevated glucose levels (hyperglycemic clamp tests). The present application proposes to measure glycemic variability by continuous glucose monitoring (CGM) and frequent self-monitoring of blood glucose (SBMG) in 40 recent-onset type 1 diabetic patients and in 40 high-risk relatives (>50% 5-year risk of diabetes) (age 12-39 years)" "Relation between residual beta cell function and glycemic variability in (pre)type 1 diabetes." "Pieter Gillard" "Clinical and Experimental Endocrinology" "Type 1 diabetes develops when 60 to 90% of insulin-producing beta cells ahve been destroyed. This cell loss leads to greater variability of blood glucose levels both before and after diagnosis. This variability is predictive of progression to clinical onset of diabetes in risk groups and of frequenc of hypoglycemic events in patients. Novel beta cell therapy trials aim to prevent or cure diabetes by trying to preserve or restore functional beta cell mass. In preparation of future trials the collaborating teams of the present application have validated dynamic tests to measure functional beta cell mass in vivo through prolonged stimulation of beta cells by elevated glucose levels (hyperglycemic clamp tests). The present application proposes to measure glycemic variability by continuous glucose monitoring (CGM) and frequent self-monitoring of blood glucose (SBMG) in 40 recent-onset type 1 diabetic patients and in 40 high-risk relatives (>50% 5-year risk of diabetes) (age 12-39 years) as a funtion of their residual functional beta cell mass as determined by hyperglicemic clamp. The participant will undergo 5 clamp tests and 5 periods of glycemic monitoring during a 2-year follow-up. Various parameters of glycemic variability will be derived from CGM and SMBG measurements and correlated with corresponding values of residual beta cell function (anticipated to vary between 10 and 100% of healthy controls in the proposed study groups) and parameters of metabolic control. This should allow to identify treatment goals for functional beta cell mass to be reached in therapy trials in order to avoid frequent hypoglycemia in patients and dysglycemia in risk groups." "Relation between residual beta cell function and glycemic variability in (pre) type 1 diabetes" "Guy T'Sjoen" "Department of Internal medicine" "Type 1 diabetes develops when 60 to 90% of insulin-producing beta cellsahve been destroyed. This cell loss leads to greater variability ofblood glucose levels both before and after diagnosis. This variability is predictive of progression to clinical onset of diabetes in risk groups and offrequenc of hypoglycemic events in patients. Novel beta cell therapy trials aim to prevent or cure diabetes by trying to preserve or restore functionalbeta cell mass. In preparation of future trials the collaborating teams of the present application have validated dynamic tests to measure functionalbeta cell mass in vivo through prolonged stimulation of beta cells by elevated glucose levels (hyperglycemic clamp tests). The present applicationproposes to measure glycemic variability by continuous glucose monitoring (CGM) and frequent self-monitoring of blood glucose (SBMG) in 40recent-onset type 1 diabetic patients and in 40 high-risk relatives (>50% 5-year risk of diabetes) (age 12-39 years) as a"