The incidence of autoimmune diseases including multiple sclerosis is dramatically increasing. While there is a genetically defined “bedrock” susceptibility to develop T cell mediated autoimmunity, environmental cues likely determine the threshold for disease development. Yet, little is known on how environmental cues sensed at body/environment interfaces are translated into immunopathology in distant organs like the central nervous system (CNS). Here, we raise the hypothesis that immune cells must be activated at epithelial surfaces and then physically migrate to distant organs in order to induce autoimmunity. Furthermore, we propose that the “state of activation” of (either lymphoid or myeloid) immune cells can be interrogated by IL-6 production since IL-6 deficiency confers resistance to virtually any organ specific autoimmune disease and we have contributed fundamentally in defining the role of IL-6 for the generation of Th17 cells that are highly associated with autoimmune tissue inflammation. In EXODUS, we will develop ground-breaking next generation reporter tools in order to test these hypotheses. A split Cre recombinase protein, which dimerizes and is activated by blue light, will be used to genetically label cells (and their progeny) in a topologically defined manner (“compartment reporter”). Furthermore, we have developed a novel type of Cre-inducible in vivo IL-6 reporter (“activation reporter”). The combination of these tools will enable us to trace the anatomical compartment of activation of immune cells without limitations in lag time. Thus, site specific photogenetic co-induction of a fluorescence and IL-6 reporter will be used to probe peripheral sites for their potency to licence immune cells to travel to the CNS (Forward). Vice versa, labeling of cells in the CNS (through a thinned skull window) will allow for studying immune cell exodus from the CNS in homeostasis and during inflammation (Reverse).

Chronic back pain is a major burden and source of disability worldwide. It is primarily attributed to different biomechanical factors, but can also have inflammatory, neurological or psychological causes. Clinical findings and conventional imaging cannot reliably distinguish different causes of back pain. In contrast, individual biomechanical models can quantify diverse (pathologic) loading patterns and thus could be used to distinguish different aetiologies of back pain, to better understand individual pathophysiology and guide preventive strategies. During my recent ERC-StG “iBack”, I developed quantitative imaging methods and deep-learning based image processing to automatically generate a fully individualized biomechanical model of the thoracolumbar spine. Simultaneously, two large-scale epidemiologic studies collected clinical and high-resolution imaging data of the spine of more than 15,000 participants so far, aiming at more than 35,000 participants by mid 2022 The high-level objective of iBack-epic is to use such novel image analysis techniques to identify different biomechanical and inflammatory causes of back pain in study participants. I will adopt and extend my recently developed deep-learning based spine labelling and segmentation algorithms to fully automatically calculate individual biomechanical, functional and morphometric parameters of the spine. In this large-scale population data, I will identify different biomechanical loading patterns, use quantitative image-based parameters to discriminate normal ageing from pathologic degeneration and identify pathological conditions that are linked to back pain or subsequent development of chronic back pain. Such a differentiation – for the first time based on quantitative image data – will allow for a better understanding of the underlying pathophysiology of back pain, an improved risk stratification, a tailored investigation of genetic causes and thus will help to better guide preventive strategies.

An association between inflammation and carcinogenesis is well established, however, how they are related mechanistically in subtypes of sporadic intestinal tumours remains unclear. This study aims to decipher how oncogenes determine the inflammatory microenvironment (stroma) and how this affects tumour development and survival. Notably, intestinal epithelium-specific expression of oncogenic Kras(G12D), Braf(V637E) and Pik3ca(H1047R) in mice mimics serrated intestinal cancers in humans faithfully. Preliminary data suggest that the mutational make-up of the tumour may dictate the pro- and anti-tumourigenic immune response, which in turn determines tumour development and survival. This study therefore aims to characterise the tumour-infiltrating immune cells by systematic immunophenotyping and to decipher the involved inflammatory signalling mechanisms in a cell-type and mutation-specific manner. Moreover, we aim to reconstruct the formation of the oncogene-specific inflammatory microenvironment, which we will determine via endoscopic transplantation of intestinal organoids derived from Kras(G12D), Braf(V637E) and Pik3ca(H1047R) mice into the large intestine of wild-type mice. Importantly, detection of involved inflammatory mediators and immune cell-subtypes will allow us to genetically target them in vivo using novel in-house generated dual-recombinase systems (DRS). In order to investigate the consequences of inflammation on sporadic intestinal tumourigenesis, models with genetically or experimentally induced chronic inflammation will be applied. Conversely, immunodeficient Rag2;Il2rg–/– mice will be used to elucidate if sporadic intestinal carcinogenesis in Kras(G12D), Braf(V637E) and Pik3ca(H1047R) mice is dependent on inflammation and can be abrogated. This study will generate new mechanistic insights into the microenvironment of cancer subtypes, which could provide a basis for the development of new personalised immune therapies.

In 2015, four million people worldwide died because of the aftermaths of obesity (7% of total deaths), and in 2030, half of humankind is expected to be overweight. Lifestyle interventions in subjects with obesity can prevent the development of obesity-induced metabolic dysfunction but need personalization in order to become effective for diabetes and cardiovascular disease prevention. Visceral adiposity and adipocyte hypertrophy are phenotypes strongly linked to metabolic dysfunction in subjects with obesity. Visceral adiposity can be non-invasively measured using Magnetic Resonance Imaging (MRI). Adipocyte size measurements are however nowadays only feasible using highly invasive biopsy procedures that cause severe patient discomfort, hold a risk for complications and are therefore rarely performed in the personalization of lifestyle interventions. The ongoing ProFatMRI research program (ERC-StG 677661) focuses on the development of an MRI platform to non-invasively assess fat microstructure. In the present proof of concept (PoC) project, we will translate the lipid droplet size measurement approaches successfully developed within ProFatMRI into an effective and reproducible toolkit (FatVirtualBiopsy) for non-invasive in vivo human adipocyte size measurement. The present PoC project encompasses the evaluation and the technical adjustment of the adipocyte size measurement in the real-life scenario involving a lifestyle intervention in subjects with obesity, the development of a prototype and the adoption of an intellectual property strategy. The PoC project will result in a non-invasive imaging toolkit that can be integrated into clinical prevention, targeting a wide range of medical specialists involved in obesity treatment. FatVirtualBiopsy will therefore contribute to transform the personalization of lifestyle interventions and drastically improve their effectiveness in subjects with obesity towards diabetes and cardiovascular disease prevention.