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Contents:


  1. UAB Insight Endocrinology & Diabetes Volume 2
  2. Disease Mechanisms
  3. diabetesinsight volume 02 issue 02 research part ii Manual
  4. Internet Interventions for Long-Term Conditions: Patient and Caregiver Quality Criteria
  5. Genomics guided drug repositioning in asthma

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Since operations began in , donation partner Giant Eagle has Click the link to learn about Hunter's life. So far only sugar derived molecule have been described as heparanase inhibitors which proved to be challenging during development. We will use the currently available and our own crystal structures to build pharmacophore models.

Aim 3: Biophysical and in vitro characterization of the inhibitors. The resulting virtual compounds will be resynthesized and profiled biochemically and biophysically. If they exhibit a suitable profile they will be optimized for affinity and biochemical activity, while keeping a close eye on drug-like properties. This project deals with the synthesis of new drugs that inhibit heparanase I. Ultimately, these drugs would only be used in patients in whom heparanase is overexpressed. To this end, large data and sample repositories of patients with type 2 diabetes can be used which are managed by Lambers Heerspink and De Zeeuw.

This offers the opportunity that once a heparanase inhibitor is successfully synthesized in this project, the inhibitor can be targeted to the right patient population. This project links to disease mechanisms and in particular to the work carried out by Sabeth Verpoorte who will develop a disease on a chip model for dysfunction of the endothelial surface layer and albumin permeability. During the course of the project, the drugs synthesized in this program could potentially be tested on the chip developed by Verpoorte et.

Poelarends Name Co-Promotor: Prof. Dekker Other project members: P. Tepper technician , Haigen Fu PhD student. The immunocompromised state and diabetic complications lead to high risk for infections in diabetic patients. Also, higher antibiotic resistance rates in diabetic patients compared to those without diabetes have been reported, further complicating the treatment of the infectious disease. In fact, the first NDMproducing pathogen has been found in a diabetic patient. The fungal natural product aspergillomarasmine A AMA has recently been identified as a selective and potent NDM-1 inhibitor and a promising codrug candidate both in vitro and in vivo King et al.

We have recently developed a simple biocatalytic method to prepare AMA and related aminopolycarboxylic acids Poelarends et al. In this project, we will synthesize various aminopolycarboxylic acids, including novel analogues of AMA, as well as smart pro-drug versions of these compounds, and explore their bioactivity, target selectivity and therapeutic potential. As such, the proposed project will contribute to the development of new chemotherapeutic strategies to fight antibiotic-resistant pathogens, which are more prevalent in individuals with diabetes.

Please note that Prof. Poelarends is also participating in the Centre for Sustainable Antimicrobials CeSAM , which comprises advanced facilities for fundamental research to develop novel antibiotics and therapeutic concepts to fight resistant bacterial strains as well as high-throughput animal testing and adequate patient-screening facilities.

UAB Insight Endocrinology & Diabetes Volume 2

This existing network of collaborators will further support the proposed project. Indeed, infectious diseases are more prevelant and often more serious in diabetic patients, which potentially increases their morbimortality. Furthermore, higher antibiotic resistance rates in diabetic patients compared to those without diabetes have been reported, further complicating the treatment of the infectious disease. Due to common and recurrent infections, diabetic patients need more antibiotic treatments, which may further select for the presence and increase in antibiotic-resistant pathogens.

New chemotherapeutic strategies to fight antibiotic-resistant pathogens, particularly in patients with diabetes, are therefore urgently needed. In this way resistance can be overcome, allowing more efficient treatment of infectious diseases in diabetic as well as other patients. The proposed project fits in the Drug Development domain and will contribute to the development of new chemotherapeutic strategies to fight antibiotic-resistant pathogens, which are more prevalent in individuals with diabetes.

As such, it may also become linked to drug application. Additionally, it has become increasingly clear that particular DM medications might have beneficial effects in patients with HF. We will then investigate mechanistic implications of patient specific treatment targets in in-vitro and in-vivo models. Furthermore, by measuring novel targets in patients with HF, we will identify patients benefiting from a personalized medicine approach sub aim 4 using existing DM treatments.

Current clinical guidelines allow already for some degree of personalized treatment for people with type 2 diabetes T2D. Factors such as age and comorbidity as well as patient preferences and goals should be taken into account when prescribing glucose-regulating and cardiovascular medication treatment.

This apparent lack of implementing personalized treatment needs further study in order to develop support strategies for both healthcare providers and patients to adopt more personalised treatment decision making. Since the majority of people with type 2 diabetes treatment are managed in primary care, this project will focus on the general practice setting where both general practitioners and practice support staff are responsible for routine diabetes care.

Develop patient-oriented strategies and tools to support personalized decision making for people with type 2 diabetes. This project includes the essential steps for developing a new practice-oriented intervention strategy before it can be implemented in practice: 1 describe the current situation and its determinants, 2 develop a toolbox to support healthcare professionals and patients in making personalized decisions, 3 evaluate the feasibility and potential effects of implementing the toolbox in general practice.

For part 3: pilot studies in general practice. This project will give insight in the current status and needs for implementing patient-oriented personalized treatment decision making in diabetes care, and provide a toolbox to support this implementation process in clinical practice. This may lead to expanding the patient-level factors that will be studied; developing tools together that can be used for assessing patient preferences; developing algorithms together that can be used to support healthcare professionals in making personalized decisions.

Treatments for type 2 diabetes T2D are approved based on clinical trial data. Favourable and unfavourable drug effects are weighed on a population level, and if the first outweigh the latter a positive ratio of benefit and risk can be assumed and the drug is approved. In diabetes, drugs are approved based on its effects on a validated surrogate endpoint, the biomarker glycosylated haemoglobin: HbA1c, and when there is sufficient reassurance the drugs are not harmful cardiovascular safety.

A thorough assessment of other, on- and off-target, effects, extensive subgroup analyses and available non clinical data further shapes the conditions — labeling and postmarketing surveillance — under which the drug is to be used in daily practice. HCPs then have to translate this population level information to an individual patient. Importantly, reimbursement authorities, HCPs and patients may take different views when compared to regulators and may value drug effects and the ratio of benefits and risks differently.

Various classes of antidiabetes drugs are currently available that have differential drug effects. Current clinical T2D guidelines favour drugs with demonstrated clinical benefit and well known safety profiles, but do allow some degree of personalized treatment. The main goal of antidiabetic treatment is to achieve normo-glycemia without serious high or low blood glucose levels to prevent or delay the onset and progression of diabetic complications. Factors to be considered include efficacy, age, potential side effects, weight gain, comorbidities, hypoglycemia risk, costs and patient preferences see also ProminenT Denig program.

Further, recent research shows that collecting evidence-based information based on individual patient preferences in the context of favourable and unfavourable effects is feasible and useful and could guide to a more patient-centered value judgement of pharmacological agents and thus contribute to a more transparent communication on how the patient views have been incorporated in the regulatory decision making.

However, these findings have not been systematically evaluated and translated back into the drug approval process. This project aims to study, from a regulatory perspective, how elicited patient preference information can be combined with clinical trial data to estimate the acceptability of various classes of antidiabetes drugs currently available that have differential drug effects.

Questions may include:. To improve regulatory decision-making for glucose-regulating medicines incorporating patient preferences and individual patient needs. This project will give insight in the current regulatory decision-making for diabetes medication and aims to more clearly display differential drug effects important to individual patients.

It will feedback to regulators and HTAs how information relevant for personalized treatment should be weighted and disclosed to a wider patient and HCP audience. This project aims at enlightening issues on health economics and precision medicine in diabetes treatment and prevention, with specific reference to reimbursement of new drugs. Notably, diabetes is involved with various risk factors for onset and complications, including genetics family history , life style and BMI. Additionally, situational issues come in concerning comorbidities, polypharmacy and adherence to therapies.

Known biomarkers concern blood sugar levels and Hb1Ac, but also nephropathic complication-related biomarkers such as albumin. Associations of biomarkers, risk factors and situational issues with hard outcomes such as hospitalizations that can be economically valued will be investigated using secondary analysis on clinical trials and analysis of real-world data to identify patient subgroups most benefiting or being minimally harmed with targeted therapies.

This project includes the essential steps for developing a new health economic diabetes model that is able to assess personalized medicine 1 describe the currently available models and their fitness to assess personalized medicine, 2 assess associations of real-life patient characteristics non-adherence, comorbidities, biomarkers with morbidity and mortality, 3 incorporate these personalized patient profiles and develop and validate a new health economic model. This project will give insight in the current status of the health economic assessments of personalized diabetes treatment, and provide an optimized model taking into account patient heterogeneity.

This may lead to expanding the patient-level factors that will be assessed in reimbursement decision making; as well as support healthcare professionals in making personalized decisions. Current guidelines of type 2 diabetes management advocate targeting multiple renal and cardiovascular risk markers, including HbA1c, blood pressure, albuminuria and lipid levels, in order to mitigate long-term health risks. Despite targeting these risk markers with drug treatment, patients with type 2 diabetes remain at high residual risk for CV and renal disease.

Part of this high residual risk is due to the fact that not all patients beneficially respond to the drugs that target the abovementioned cardiovascular risk factors. Indeed, previous studies from our group have shown that some patients benefit from a given treatment, but many others do not. In addition to this between individual variability in drug response in a single risk factor, we have shown that a single drug affects many more risk markers than the one intended.

For example, the antihypertensive angiotensin receptor blocker ARB losartan decreases uric acid, hemoglobin, albuminuria and increases serum potassium. Some of these effects may be beneficial for renal and cardiovascular outcomes, such as a reduction in blood pressure, albuminuria, or uric acid. Yet, other effects, such as an increase in potassium may increase renal and cardiovascular risk. We have shown that the multiple effects of a drug on multiple renal and cardiovascular risk factors vary within individuals indicating that some patients show a reduction in blood pressure in response to ARB treatment but no change in albuminuria or vice versa.

Given the large variation in drug response in multiple cardiovascular risk factors one should combine the short term effects of a single drug in each individual to obtain a more accurate estimate of the ultimate drug effect per patient. We therefore developed an algorithm, a so-called multiple risk Parameter Response Efficacy PRE score, to predict the potential long renal effect of a drug based on the composite of short term drug effects in individual patients.


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In previous work we showed that integrating the short-term changes in all measured cardiovascular risk markers following ARB treatment gave a much better prediction who would benefit from the ARB losartan compared to when based on blood pressure alone the on-target risk factor.

Clinical practice currently lacks an holistic and patient-centered treatment approach, which can be attributed to several reasons:. Thus, a novel tool that is both accurate in predicting long-term outcomes and feasible to use in clinical practice to optimize pharmacotherapy remains urgently needed in order to maximize renal and cardiovascular prognosis of patients with type 2 diabetes. The aim of this project is to design and test a decision support system based on a personalized multiple parameter efficacy PRE score that translates the short term response in multiple renal and cardiovascular risk markers into a predicted long term drug effect in type 2 diabetes care.

Ultimately this should lead to a more personalized treatment approach and improved outcomes. In this project a prospective study will be conducted to determine if the PRE score website web app can improve risk marker management for individual patients with type 2 diabetes. The presentation of the PRE score will be tailored to be informative for both primary care physicians as well as patients, and will include the following:.

Firstly, we will develop a version of the PRE score that is suitable for use in primary care, with the ability to predict long-term renal and cardiovascular outcomes for a diverse type 2 diabetes population. Secondly, we will determine the feasibility of using the score in practice by performing qualitative and semi-quantitative studies.

Thirdly, the PRE score will be pilot tested in primary care practice in a pragmatic trial design comparing PRE score decision support guided therapy vs. The database contains individualized patient data on demographics, drug treatment, risk marker responses and clinical outcomes during long-term follow-up. Data from the following risk markers will be included in the PRE score: systolic blood pressure, albuminuria, potassium, cholesterol, body weight, HbA1c. We will measure change in the markers and assess if we are more accurate in predicting outcomes than single marker changes.

Ad 2: In this study we will determine the acceptability and usefulness of the validated PRE score in combination with treatment decision support for primary care.

Disease Mechanisms

This will be done by performing a mixed method approach of semi-qualitative and quantitative methods in small groups of primary care physicians and practice assistants. Ad 3: A pragmatic controlled pilot study will be performed comparing the PRE score with care as usual. The population consists of primary care practices in the northern part of the Netherlands, with possible extension to other parts of the Netherlands.

Outcomes are tailoring of treatment and risk factor control. This project addresses Precision Medicine in its purest form. The project thus addresses the 4-Ps Prevention, Prediction, Personalized and Patient of precision medicine:. This project links to the research program intended by Prof.

P Denig focusing on how to involve patient and physician in implementing personalized therapy approaches. In addition, it also links to the project of Prof. Hillege and Mol which is focused on how to interpret drug efficacy for regulatory approaches based on multiple effects of single drugs. Bakker Name Co-Promotor: Prof. Navis Other project members: To be determined. Diabetes is a devastating disease, with numerous complications, due to its adverse effects on the micro- and macrovascular system. This is not only true in the general population, but particularly so in patient populations, where diabetes is often not only more frequent, but — likely due to impaired homeostatic capacity — often also gives rise to more severe complications.

Omic-technologies, like NMR-metabolimics provide large amounts of data of which the predictive value for development of diabetes and for complications of diabetes is still in the beginning of its evaluation. We are currently generating such data in large cohorts of the general population, patient cohorts and in intervention studies in patients with diabetes. Collectively these studies should foster individualization of treatment in patients with diabetes.

To assess biomarkers in general population and patients cohorts and to compare predictive capacity for development of diabetes, complications of diabetes, and drug response. Assessments of single biomarkers Assessments of omic profiles metabolomics, proteomic, peptidomic. The omic profiles in general population and patients with diabetes will be compared to assess if there are disease specific profiles associated with diease progression or whether common omic profiles exists independent of background population, type of disease, or severity of the disease.

The population will be divided in test and validation cohorts to ensure external validation of the discovered profiles. The omic profiles will be assessed in alreadly collected samples. Different matrices are available and will be used plasma, serum, urine. We will identify biomarkers that allow for early detection of diabetes, its complications and response to treatment. This will allow for better personalization of treatment.

This project links with various other ProminenT projects on biomarkers and response to treatment in diabetes within ProminenT Heerspink. Lifestyle is a main driving force of diabetes and its complications, with a main role for diet and physical in- activity. Accordingly, diabetes management includes both lifestyle management and pharmacotherapy, as stated in inter- national guidelines. Better prevention and treatment of diabetes requires improvement of both lifestyle management and pharmacotherapy, preferably in an integrated way.

Considering the overall quality of management of diabetes, the efficacy of lifestyle management is lagging behind considerably relative to pharmacological treatment as the large majority of patient fails to achieve any lifestyle treatment aim, despite substantial efforts and costs for lifestyle management. Hence, there is a large unmet need for better lifestyle management. Recent studies on determinants of effective lifestyle management underline the importance of considering personal preferences and habits, and environmental factors as success factors for sustained efficacy.

In diabetes however, little attention has been given to identifying habits and preferences, assessment of environmental factors, or assessing their associations with morbidity and their consequences for better management. Assessment of robust lifestyle patterns provides a relevant strategy to map habits and preferences at the aggregate level, and analyze for relevant environmental determinants that can guide better intervention strategies. These patterns strongly associate with multi- morbidity, demonstrating their clinical relevance.

Moreover, their marked regional distribution supports the role of socio-cultural environmental factors. This provides an excellent starting point to analyze the role of lifestyle patterns as determinants of morbidity in diabetes, their consequences for current management, and design of new strategies that effectively account for preferences, habits and environmental factors. As such it is uniquely fitted to provide an empirical basis for new approaches towards better personalization of diabetes management that are within reach with currently available technology at affordable costs.

Our underlying assumption is that better lifestyle management will facilitate overall management of diabetes, lead to lower requirements for pharmacotherapy, better outcomes and lower costs. Identify the role of differences in dietary and lifestyle habits as a determinant of multi- morbidity and treatment quality in diabetes, as a basis for better personalized prevention and management strategies. The main approach of the project is epidemiological. The strategy is to translate advanced big data analysis into practical guidelines for better personalization of diabetes management.

Data from available cohorts general population including diabetes, and diabetes-only, respectively are available for analysis of dietary patterns, their association with multi- morbidity, with patient management i. Dietary patterns will be analyzed from Food Frequency Questionnaires by Principal component analysis, and related to multi-morbidity by multivariate modeling. Data on physical activity SQUASH and on smoking, alcohol and substance use will be integrated into an overall lifestyle score.

diabetesinsight volume 02 issue 02 research part ii Manual

Combination with data on pharmacotherapy will reveal interaction between lifestyle pattern and need for pharmacotherapy, and modification of efficacy of pharmacotherapy by lifestyle pattern. Health economic aspects will be analyzed to assess the costs of inadequate lifestyle management on overall health care costs in diabetes i.

Subsequent adjustment for relevant factors age, gender, income, education etc will serve to identify confounders and modifiable environmental factors are new targets for more effective lifestyle intervention. As such it is uniquely fitted to provide an empirical basis for readily feasible approaches towards better personalization of diabetes management that are within reach with currently available technology, at affordable costs. Implementation and success of such approaches will greatly contribute to the credibility of personalized medicine as a new paradigm.

Rienstra and Prof. Atrial fibrillation AF is a vascular disease being associated with cardiovascular diseases and risk factors like hypertension, diabetes, obesity, and heart failure with a preserved ejection fraction HFpEF. AF is not benign. It is progressive due to atrial structural remodelling caused by AF risk factors, cardiovascular diseases, and AF itself, i.

AF progression is associated with impaired prognosis. Patients with AF and HFpEF are heterogeneous and share clinical risk factors, like hypertension, diabetes and obesity. These factors are linked, both to each other and to adverse cardiovascular outcomes. It is questioned whether it is AF itself that contributes to worse prognosis, or, instead, whether AF is just a bystander being a marker of more severe atrial and ventricular diseases.

There are many unanswered questions about the pathophysiology, risk factors, symptomatology, diagnosis, and prognosis of AF and HFpEF. Additionally, treatment is cumbersome. Although it is generally assumed that eliminating AF is associated with improved outcome, so far, however, the trials did not show any benefit of attempts to abolish AF. Recent data, though, demonstrated that in patients with AF and HFpEF a strategy focusing on risk factor management, i. Therefore, more systematic research is needed to answer these issues and to provide treatments that improve quality of life and reduce adverse outcomes.

For that, extensive phenotyping to assess the presence of risk factors using new imaging techniques, measures of atrial myopathy, and of diastolic dysfunction, are essential. It is our hypothesis that 1 the pathophysiology and prognostic significance of AF depends on severity of risk factors; 2 atrial myopathy develops in association with and as marker of ventricular myopathy; 3 diabetes, hypertension and obesity play a pivotal role as risk factors for atrial and ventricular myopathy; and finally 4 personalized risk factor reduction reduces AF progression, atrial myopathy and severity of HFpEF.

AF, thus, is just a bystander being a marker of severity of disease. An implantable loop recorder is implanted to monitor AF burden and extensive phenotyping at baseline is performed as depicted in the Table. Blood samples for analysis of biomarkers will be collected at inclusion and at 2. During the course of the study, additional biomarkers of interest can be added to the list of biomarkers including now haemodynamic parameters, inflammation, fibrosis, adipose tissue, hypercoagulability, ischemia, metabolic stress.

Echocardiographic image acquisition will be performed to assess atrial and ventricular sizes and function in accordance to the recommendations of the American Society of Echocardiography and European Association of Cardiovascular Imaging. Cardiac catheterization will be done to asses pulmonary wedge pressure as a surrogate measure of the left ventricular end diastolic pressure LVEDP. Left heart catheterization will be performed to assess the presence of significant coronary artery disease or left-sided valve disease, and LVEDP will be assessed.

Extensive phenotyping of patients with AF and HFpEF will more than before reveal which risk factors need attention and therapy. These will differ among patients and contribute to precision medicine In this way, medical decisions and therapies are tailored to the individual patient.

In this way interventions are concentrated on those who will benefit, sparing expense and side effects for those who will not. Read out. Research Projects. Research Projects Print. Please find below a description of the Research Projects. Project 1. Loes Kistemaker Background Asthma is a chronic respiratory disease that affects approximately million people worldwide [1]. Overall aim In this project, we aim to identify the relevant targets for repositioned drugs for asthma intervention, validate these in in vitro model systems for preclinical studies assessing the suitability of selected candidate compounds and validate their efficacy in relevant in vivo disease models.

Methods We will accomplish this by taking the following stepwise approach. Tentative thesis Chapter outline Identification of the relevant targets for repositioned drugs for asthma Validation of targets in in vitro model systems for preclinical studies Detection methods and investigation of the suitability of candidate compounds Validation of the selected compounds and detection methods in relevant in vitro and vivo models. How does this project contribute to Precision Medicine Asthma genetics has been a key strength of GRIAC since the mids, when the chromosome 5q locus was first identified as harbouring asthma and hyperresponsiveness genes.

Possible links to other ProminenT domains Obesity, diabetes, and asthma have attained global epidemic proportions. Overall aim Evaluation of novel FXR modulators in mice for potential application in humans is hampered by the presence of mouse-specific pathways in bile acid metabolism. Aim 1 To silence Cyp2c70 in liver, young and adult mice expressing Cas9 specifically in hepatocytes will be injected with adenovirus containing sgRNA targeting the Cyp2c70 gene.

Tentative thesis Chapter outline Introduction Cholesterol and bile acid metabolism and bile formation in a mouse model with a humanized bile acid pool Development of diet-induced NAFLD in a mouse model with a humanized bile acid pool-role of FXR — controlled pathways in lipid and cholesterol metabolism Does a humanized bile acid pool impact on the development of insulin resistance and disturbed glucose metabolism in diet-induced NAFLD in mice?

Does a humanized bile acid pool contribute to the development of inflammation in diet-induced NAFLD in mice? Effects of pharmacological FXR activation on cholesterol and bile acid metabolism in a mouse model with a humanized bile acid pool Effects of pharmacological FXR activation on diet-induced NAFLD pathologies in a mouse model with a humanized bile acid pool Combination therapies? How does this project contribute to Precision Medicine Obesity, metabolic syndrome, and non-alcoholic fatty liver disease NAFLD are increasing worldwide.

Overall aim The aim of this research project is to identify molecular mechanisms linking changes in energy metabolism to pro-inflammatory gene expression in DMT-II. Methods Experiments will be carried out in microfluidic perfusion tissue slice culture in collaboration with the group of Sabeth Verpoorte. Tentative thesis Chapter outline Current knowledge about the link between energy metabolism and chronic inflammation New methodology to study histone acetylation dynamics in microfluidic perfusion tissue slice culture New methodology to study protein acetylation dynamics in microfluidic perfusion tissue slice culture Effects of nutrient supply, stimulation insulin and KDAC inhibitors on histone acetylation dynamics and regulation of pro- and anti-inflammatory gene expression in diabetes Effects of nutrient supply, stimulation insulin and KDAC inhibitors on protein acetylation dynamics and regulation of pro- and anti-inflammatory gene expression in diabetes How dows this project contribute to Precision Medicine The proposed research project will make a significant contribution to our understanding of how changes in energy metabolism are linked to chronic inflammation in DMT-II.

Possible links to other ProminenT domains The proposed research will elucidate disease mechanisms linking aberrant energy metabolism to chronic inflammation in DMT-II by assessing the balance between protein acetylation and deacetylation protein. Common immune signatures in chronic inflammatory diseases for prediction of disease progression. M van der Geest, Y van Sleen Background Chronic inflammation is a hallmark of systemic autoimmune diseases like Giant cell arteritis GCA and rheumatoid arthritis RA and systemic inflammatory diseases like type 2 diabetes. Overall aim The overarching hypothesis of the current proposal is that dysregulation of interleukin 6 IL-6 axis is a common mechanism responsible for the individual variety in disease course and treatment response in GCA, RA and type 2 diabetes.

What is the effect of chronic IL-6 stimulation on Treg functionality? Is there a differential treatment response between GCA patients with high IL-6 levels versus those with low levels? How dows this project contribute to Precision Medicine A better understanding of the factors governing CD4 T cell driven autoimmune diseases is highly awaited as it is likely to provide a rational for novel targets of treatment.

Possible links to other ProminenT domains Biologicals targeting immune subsets and chemical drugs targeting signaling pathways can be designed based on insights into common immune signatures in chronic inflammatory diseases for prediction of disease progression. Also especially in RA there is a wealth of drugs targeting specific pathways which can be used and translated to GCA and type 2 diabetes Lastly most drugs still come at a price of immune suppression and subsequent vulnerability to infectious diseases. Creating an urgent need for precision medicine.

The project links to various other research projects within ProminenT. Bischoff investigates chronic inflammatory phenotypes in obese and diabetic individuals and aims to develop new methodologies to measure inflammatory metabolites. We will discuss with Bischoff if we can use his methodology in our cohorts as well. Overall aim In this project, we propose to develop microfluidic models for the glycocalyx with or without endothelial cells present to investigate the effects of glycocalyx degradation on the development of albuminuria and subsequent progression of renal and cardiovascular disease.

Methods Microfluidic devices will first be implemented for the development of a robust glyocalyx layer. Technical objectives: 1 a robust, microperfusion glycocalyx model in-chip b combined endothelial cell-glycocalyx model 2 investigate effect of various parameters on induction of inflammation in combined model to gain more insight into pathophysiology of albuminuria in diabetic patients 3 test potential drugs targeting the glycocalyx 4 identify the circumstances under which these drugs offer the most benefit Tentative thesis Chapter outline Establishment and characterization of a microfluidic, cell-free glycocalyx model Establishment of a glycocalyx-endthelium organ-on-a-chip GEOoaC model Design of an albumin leakage assay in the GEOoaC Characteristics of endogenous stimulation of albumin leakage effects.

Consideration of glucose concentrations and profiles; inflammation by LPS; influence of cholesterol; etc. Investigation of the pharmacological inhibition of albumin leakage inhibition of heparinase, restoration of glycocalyx layer, etc. How dows this project contribute to Precision Medicine Though in vitro drug screening is well established, it is often difficult to accurately extrapolate test results back to possible therapeutic or pathological effects in the human being.

Possible links to other ProminenT domains This project in Disease Mechanisms links well to collaborators working in Drug Development, as the model, once developed, can be used for testing potential pharmaceutical compounds. Warmerdam iPSC facility Background Type 1 diabetes T1D is characterized by elevated glucose levels as a consequence of loss of insulin secretion by endocrine beta cells in the islets of Langerhans in the pancreas.

Overall aim The overall aim of the project is to investigate the interactions between exocrine acinar cells and endocrine beta cells in the early pathogenesis of type 1 diabetes and the potential role in triggering T1D. Methods Advanced electron microscopy EM , color EM that will allow high throughput analysis of Islet morphology up to the ultrastructural level and that allows discrimination of cellular hormones versus enzymes will be applied as described before Scotuzzi, ; Ravelli Tentative thesis Chapter outline Introduction to thesis Introduction to type 1 diabetes and potential triggers Mechanisms of exocrine-endocrine cell mixing in type 1 diabetes Development of a patient-specific 3D pancreatic cell culture system for the study of exocrine-endocrine interactions The interaction between exocrine and endocrine cells in the pathogenesis of type 1 diabetes The role of type 1 diabetes patient-specific HLA haplotypes in exocrine-endocrine cell interactions.

Discussion and future perspectives How dows this project contribute to Precision Medicine Patient-derived induced pluripotent stem cells and thereof derived exocrine and endocrine pancreatic cells allow the investigation of patient-specific disease pathogenesis and responsiveness to therapeutic interventions.

Possible links to other ProminenT domains Patient-derived induced pluripotent stem cells and thereof derived exocrine and endocrine pancreatic cells allow: The investigation of patient-specific disease pathogenesis pilar Disease Mechanisms The investigation of responsiveness to potential therapeutic interventions pillars Drug development and Drug application. Project 2. Zeeuw Background To retain albumin, one of the main circulating blood proteins, in the vasculature the vessel is aligned with a polysaccharide layer called the glycocalyx that repels albumin.

Overall aim The hypothesis is that heparanase inhibitors will have profound effects on the course of the diabetes disease. Therefore, we propose three aims: Expression, purification, crystallization, crystal structure analysis and screening method establishment of human heparanase; Design, synthesis and optimization of novel heparanase inhibitors; Biophysical and in vitro characterization of the inhibitors. Methods Aim 1: Expression, purification, crystallization, crystal structure analysis and screening method establishment of human heparanase: For the envisioned drug discovery program recombinant heparanase is needed.

Internet Interventions for Long-Term Conditions: Patient and Caregiver Quality Criteria

Tentative thesis Chapter outline Review on disease and structural biology of heparanase Discovery of heparanase inhibitors Biophysical and structural characterization of heparanase inhibitors Optimisation of heparanase inhibitors: form HL Biological evaluation of heparanase inhibitors Summary and outlook How does this project contribute to Precision Medicine This project deals with the synthesis of new drugs that inhibit heparanase I. Possible links to other ProminenT domains This project links to disease mechanisms and in particular to the work carried out by Sabeth Verpoorte who will develop a disease on a chip model for dysfunction of the endothelial surface layer and albumin permeability.

Tepper technician , Haigen Fu PhD student Background The immunocompromised state and diabetic complications lead to high risk for infections in diabetic patients. Possible links to other ProminenT domains The proposed project fits in the Drug Development domain and will contribute to the development of new chemotherapeutic strategies to fight antibiotic-resistant pathogens, which are more prevalent in individuals with diabetes.

Nutrition Insights for People with Diabetes

Using the top targets found in 1 , we will examine the effect of patient specific targets on cardiomyocyte phenotype and function using an in-vitro approach. High glucose; cardiac stretch; oxidative stress; hypoxia on both RNA RT-qPCR and Protein Western Blot level using a panel of genes and proteins known to be associated in eccentric and concentric hypertrophy, and extracellular matrix and sarcomere structure.

Genomics guided drug repositioning in asthma

Here, we will produce total knock-out and overexpression mouse models and phenotype mice using echocardiography and study of cardiac tissue. In case of a less-severe phenotype, we will investigate the role of said targets in a pathological setting using a trans-aortic constriction TAC model to produce LV dysfunction. Possible links to other ProminenT domains This proposal is linked to the following ProminenT domains: Disease mechanisms sub aim [1], [2] and [3] Drug development sub aim [1], [2] and [3] Drug application sub aim [1] and [4].

Project 3. Questions may include: What was the impact of the guideline recommendations regarding personalized treatment on potential under- and overtreatment in specific subgroups of T2D patients? What are individual trends in risk factor control over time for T2D patients in relation to treatment changes e.

Which patients do or do not receive intensification of treatment when indicated? How can patient preferences be assessed? Which tools are needed to support the process of personalized treatment in T2D from the healthcare provider and the patient perspective? What is the feasibility and impact of implementing these tools in practice? Overall aim Develop patient-oriented strategies and tools to support personalized decision making for people with type 2 diabetes.