Pulmonary hypertension (PH) is a rare but progressive fatal disease characterized by accumulation of persistently activated cell types in the pulmonary vascular wall exhibiting abnormal expression of genes driving proliferation, inflammation, and metabolism. The currently used vasodilatory therapies have little or no impact on this activated phenotype and therefore offer no cure or even substantial survival benefit. PH has a high female predominance (3:1 to 9:1). This proposal aims to understand the mechanism behind the high female predominance to identify novel therapeutic targets to attenuate disease progression in male and female PH patients. Female predominance can be linked to sex hormones and/or incomplete X chromosome inactivation (XCI) leading to biallelic expression of immunoinflammatory and metabolic genes. To understand the impact of oestrogen and androgen signalling on abnormal vascular remodelling in PH, I will develop a unique opposite-sex lung transplantation rat model, identify oestrogen metabolites in a large set of patient serum samples and explore their biological relevance using pulmonary vascular cells from male and female PH patients in cell-based assays. Preliminary experiments suggest there is incomplete XCI in PH. I propose to combine sequencing and molecular studies to extensively characterize the impact of incomplete XCI on the physiology of male and female PAH cells and identify genes and druggable targets regulating incomplete XCI in PH. Finally, I will explore a novel pulmonary endothelium-specific drug delivery method to deliver identified promising genes/compounds to selectively inhibit the activated pulmonary vasculature thereby minimalizing side effects compared to current delivery methods. Together, this high risk-high gain study will dissect the molecular mechanisms underlying the unresolved female predominance in PH and offer novel pulmonary endothelium-specific therapies for both male and female PH patients.

The advances in medical sciences and biopharmaceutical development during the last decennia have been overwhelming. While the scientific and clinical insight in numerous diseases have significantly increased, the curative treatment to most diseases is still not in reach. The most common diseases such as cancer and chronic diseases are still challenging scientists. Therefore, during our ERC Advanced project the main goal was to develop a vaccine to cure cancer using targeted immunotherapy. We used dendritic cells (DCs) as potentiator to improve anti-tumor T cell activity. However, we discovered that many tumors display a high content of sialic acids which actively suppress DCs function and induce tolerance to tumor associated antigens. This unexpected serendipity finding that sialylation of tumor associated antigens induced tolerance to the body’s immune response opens a window of opportunity to use sialylation (modification with sialic acid) to induce tolerance in allergies, such as house dust mite allergy (HDM). In the ERC PoC project (MATCH) I will couple HDM major allergens to specific sialic acid using a linker molecule to induce immune tolerance towards effector T cells in inflammation processes during HDM allergy. The results will lead to validation of the technology developed during the ERC Advanced project and PoC that sialylation induces tolerance when used with HDM allergens. When PoC is reached, the MATCH technology will represent a new allergen immunotherapy in a vaccine technology for HDM allergy with shorter treatment protocols, better efficacy and reduced side effects can be developed. The future potential of this technology may be extended to other allergies and/or autoimmune diseases.

Brain disorders present a staggering health-care burden, costing around 800 billion euros per year in the EU and affecting almost 180 million people. Currently, development of treatments for these disorders is very unsuccessful. Of all currently prescribed drugs, >30% target G-protein coupled receptors, that are typically activated by neuromodulators. Neuromodulators are signaling molecules secreted by most neurons, which regulate many processes in our brain and body. Dysregulation of neuromodulator secretion is firmly associated with many neuropsychiatric disorders, but no screening assay for neuromodulator secretion is currently available to test drug candidates. We have developed a human-based neuromodulator screening assay for preclinical testing of compounds for neuropsychiatric disorders. This assay, the HumanNeuronScreen, uses human neurons derived from somatic patient cells (e.g. skin), to maximally approach the situation in the patients’ CNS and thereby greatly enhancing target validation and lead optimization in preclinical research. It delivers in depth knowledge on the mechanism, potency and selectivity of drug candidates, supporting a higher success rate for clinical trials. Therefore, the value proposition of our product consists of a drastic reduction of costs in drug-development for pharmaceutical and biotech companies, and potentially impacts on 180 million patients in Europe. This proof-of-concept project aims to prove the commercial potential for the HumanNeuronScreen by measuring a reference library of compounds that establishes the resolution, reproducibility and dynamic range of the screen. An IP strategy will be developed to ensure a market position and business strategy will be created and validated. Together, this maximizes the value of the research conducted in the ERC Advanced grant DCV fusion.

Causal conclusions are at the center of research, yet notoriously difficult to obtain. Many research studies report correlations only, which, in line with the maxim, do not imply causation. With correlations, one can make predictions. With causation, one can intervene. Paradoxically, causal inference can become harder when more data becomes available. In the by now increasingly common high-dimensional settings which are the focus of this proposal, including all variables is impossible while including too few can severely bias results. Variable selection becomes necessary, yet available methods are in short supply. My aim is to develop Bayesian nonparametric methods and theory for high-dimensional causal inference. Bayesian nonparametrics is eminently suited for variable selection in causal inference, because it excels at both incorporating and describing uncertainty. Recent theoretical advances, in particular in Bernstein-von Mises theory and high-dimensional nonparametric regression, have now finally opened up causal inference to Bayesian nonparametric approaches. I will investigate high-dimensional versions of the two most important causal frameworks, based on unconfoundedness and directed acyclic graphs. I will focus on novel aspects scarcely available in the literature, including uncertainty quantification, a broad range of data types, and nonlinear relationships. My expertise in causal inference, Bayesian nonparametrics, variable selection and survival analysis puts me in a unique position to work on this multifaceted challenge. My dual track in theoretical and applied statistics enables me to identify the problems which have highest priority in practice and are mathematically interesting. The novel methods with solid mathematical statistical foundation resulting from this proposal will tremendously expand the now limited settings in which trustworthy high-dimensional causal inference is possible, with applications in medicine, economics and many other fields.

Traditionally, AD is regarded as a neurodegenerative disease and as such, the major focus has been on investigating and treating neurodegeneration and neuronal functioning. Only the last decade, it became apparent that AD pathogenesis strongly interferes with immunological processes and vice versa. Indeed, my novel findings show that the immune system in patients with early AD is already severely derailed and highlight a specific role for CD8+ T-cells. My exciting data also suggest the importance of bio-active lipids like sphingolipids and specialized pro-resolving mediators in early AD pathogenesis, possibly by controlling the immune system. The identification of how the altered lipid landscape underlies AD and affects immune homeostasis is essential to come to new insights into disease pathogenesis and to discover novel intervention strategies, the ultimate goal of the BRAIN project. I therefore here hypothesize that a misbalance in bioactive lipids plays a key role in the induction and propagation of the impaired immune homeostasis associated with AD progression, thereby forming a novel target for treatment. My key objectives are: i) Unravel bioactive lipid signatures and define correlations with disease progression, sex, biomarkers and an unbalanced immune response in early AD, ii) Elucidate the underlying mechanisms of uncontrolled lipid mediator balance and how this relates to the altered immune landscape, iii) Identify key players in this process and perform proof of concept studies to define if restoring the lipid balance reinstates immune homeostasis and consequently cognition and disease pathogenesis in AD. Together this study will provide in-depth understanding of how bio-active lipids affect immune mediated processes that underlie disease progression, investigate interaction thereof and decode underlying mechanisms to pave the way towards the development of improved prognostic/diagnostic tools and identification of novel therapeutic targets.