PERFECT-FIT

2020

Smoking tobacco and physical inactivity are key preventable risk factors of cardiovascular disease (CVD). Perfect Fit aims to prevent CVD, promote well-being, and reduce healthcare costs, particularly targeting disadvantaged populations where smoking and physical inactivity are prevalent.

The Research
The project develops tailored, evidence-based, near real-time computer coaching for quitting smoking and enhancing PA. For every individual, a personal model is designed which generates personalized recommendations based on high-quality existing and newly collected data, and adapts to changing circumstances/progress (similar to a TomTom navigation system), using machine learning techniques and incorporating domain-specific expert knowledge (e.g. health behaviour change strategies). Virtual coaches (VCs) communicate advice in a motivating way that fits individuals’ persuasive communication styles.

Perfect Fit integrates big-data science, sensor technology, and personalized real-time feedback to support smoking cessation and promote adequate physical activity (in both gym settings and daily life). The key questions of this study are:

  • Which adaptivity is needed to create a robust, safe, and effective interaction between individuals and machines?
  • How can we develop advanced data science methods and embed this in current smoking cessation and PA coaching practice?
  • How do measurement modalities, feedback and communication affect individuals’ smoking status and PA?

Origin
This project was funded within the Big Data & Health Program. The focus of this public-private research program is the use of big data for the early detection and prevention of cardiovascular diseases. The program has been developed by NWO, ZonMw, the Dutch Heart Foundation, the Top Sectors Life Sciences & Health (LSH), ICT and Creative Industry, the Ministry of Health, Welfare and Sport, and the Netherlands eScience Center. Within this research program, the ambitions of the Dutch Heart Foundation, the Ministry of Health, Welfare and Sport, and the Netherlands eScience Center were aligned with the ambitions of Commit2Data for the Top Sectors ICT, LSH, and Creative Industry, as described in the 2018-2019 Kennis- en Innovatiecontracts between NWO and the Top Sectors.

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Phaedra-impact

2018
Pulmonary Hypertension (PH), particularly Pulmonary Arterial Hypertension (PAH), presents a fatal complication in chronic diseases, affecting 1 in 50,000 individuals, predominantly at a young age and more often in females. The underlying genetic link involves mutations in the bone morphogenetic protein receptor type 2 (BMPR2) gene, disrupting BMP signaling. The PHAEDRA-IMPACT consortium aims to understand PH and PAH. The Research The research focuses on understanding PAH through the transforming growth factor-β (TGFβ) signaling pathway, particularly influenced by mutations in the bone morphogenetic protein receptor type 2 (BMPR2) gene, prevalent in heritable and some non-hereditary PAH cases. The PHAEDRA initiative identified compounds that modulate the TGFβ/BMP balance, showing efficacy in restoring endothelial function and reversing pulmonary vascular remodeling in preclinical models, though not curing PAH, making early detection crucial. PHAEDRA has identified biomarkers for timely diagnosis and personalized treatment. PHAEDRA-IMPACT will enhance early detection using non-invasive risk assessments, imaging, and biomarker profiling to detect pre-capillary PH. Precision medicine will guide tailored therapies based on advanced imaging and biomarker analyses, addressing disease progression variability among predisposed individuals. Additionally, patient-derived induced pluripotent stem (iPS) cells will be used in 3D culture models of lung and heart tissues to uncover PAH mechanisms and identify therapeutic targets. This comprehensive approach aims to advance our understanding of PAH pathogenesis, accelerate drug development, and enable personalized treatment and preventive strategies for individuals at risk or affected by PH. Origin This consortium was funded through the Impulse Grant program by the Dutch Heart Foundation.
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RECONNEXT

2021
Heart failure represents a significant healthcare challenge due to its high morbidity and mortality rates. Historically, the emphasis has been on heart failure with reduced ejection fraction characterized by left ventricular dilation. However, nearly half of heart failure patients involve diastolic dysfunction due to heart chamber stiffening, known as diastolic heart failure or HFpEF. The Focus Research conducted by our consortium indicates that impaired kidney function is an is a strong risk factor for HFpEF. Patients with chronic kidney disease are more prone to developing HFpEF and have higher mortality rates from associated complications. The specific mechanisms by which even slight declines in renal function worsen cardiovascular risk and impact the development and prognosis of HFpEF are not yet fully understood. Insights from RECONNECT highlight the pivotal role of systemic inflammation and microvasculature in this context. The Research RECONNEXT (Renal connection to microvascular disease and HFpEF: the next phase) is a multicenter consortium dedicated on advancing medical research on heart failure - particularly heart failure with preserved ejection fraction (HFpEF) - in relation to impaired kidney function. Specific pre-clinical and clinical research objectives have been defined: Identify renal drivers for HFpEF onset and progression in subgroups/clusters of HFpEF patients, taking patient-specific risk profiles into account. Deepen our understanding of the mechanistic pathways involved in the pathogenic cross-talk between renal drivers, systemic inflammation, microvasculature, and cardiac cells leading to HFpEF, using dedicated ex vivo bioassays to assess patient material and in vivo small and large animal models. Investigate the most promising therapeutic targets in newly developed and well-characterized state-of-the art rodent and porcine models of CKD-associated HFpEF, taking comorbidities into account. Investigate the most promising therapeutic, diagnostic and prognostic candidate(s) in well-defined patient-groups by taking a stratified approach. We expect that the results of this project will enhance our mechanistic insight in the renal drivers of HFpEF development and progression and will lead to the development of personalized diagnostic, prognostic and therapeutic solutions for HFpEF patients. The origin The RECONNECT consortium has provided fundamental knowledge on the connection between chronic kidney disease and HFpEF and established a translational pipeline for the discovery and evaluation of potential diagnostic, prognostic and therapeutic targets. RECONNEXT builds upon the success of RECONNECT, established in 2015 (see Figure 1 below), supported by CardioVasculair Onderzoek Nederland (CVON) and the Dutch Heart Foundation. The RECONNEXT consortium consists of nephrologists, cardiologists, general practitioners, and scientists from five leading academic centers in the Netherlands (UMC Utrecht, Erasmus MC, UMC Groningen, Amsterdam UMC, Leiden University) renowned for their expertise in heart failure, vascular biology, and chronic kidney disease.    
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