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Immunological processes play pivotal role in a variety of neurological diseases, including neoplastic conditions. Gliomas are highly malignant brain tumors which actively suppress anti-tumor immune responses. Current clinical imaging is mainly restricted to assess morphological information (e.g. tumor size, extent of edema and gliosis) but does not provide “functional” information on immune cell influx, cellular distributions and perturbations that occur after therapy induction.

By 2035, obesity could affect half the global population, increasing cardiometabolic diseases considerably, particularly among women. One-size-fits-all treatments for obesity and associated diseases are proving insufficient due to the diverse ways these conditions develop, manifest, and respond. Dr. Chakaroun's research uses multi-omics technologies to investigate how the microbiome—our largest endocrine organ—contributes to cardiometabolic disease heterogeneity and sex-specific differences.

Gliomas are the most common brain tumors in children and adolescents, ranging from benign forms to life-threatening tumors despite intensive treatment. Currently, treatment decisions are often based on symptoms and imaging, although genetic alterations in tumor cells can provide valuable insights into tumor biology. This project aims to explore how genetic features of gliomas can be used to better predict disease progression and tailor treatments to the individual tumor.

The present highly personnel (and technology) intensive research project is intended to use the gold standard for diaphragmatic strength determination for the first time by means of gold standard techniques established in only a few laboratories in the world based on our established laboratory infrastructure in Aachen, in order to determine the extent of the development of VIDD by repeated measurements throughout invasive mechanical ventilation for the first time and to make its weakness determinable as a biomarker after the project.

The project aims to better understand the development of pediatric low-grade gliomas, the most common brain tumors in children. Despite their generally lower aggressiveness, these tumors are highly variable and difficult to treat, often leading to relapses and long-term complications. Using innovative single-cell sequencing technology, the project will investigate how these tumors evolve over time, particularly in response to treatments. It will explore biological changes and mechanisms that contribute to tumor progression and drug resistance.

Diffuse midline gliomas are among the most aggressive brain tumors with unfavourable prognosis and poor response towards standard therapy. As diffuse midline gliomas can in principle be recognized and combated by the human immune system, deciphering the specific immune cell receptors might enable to manufacture engineered T cells which can then be transferred to patients with diffuse midline gliomas. The aim of this project is to develop such an adoptive T-cell therapy for patients with diffuse midline gliomas.

Immune checkpoints are receptors that modulate immunological self-tolerance. This new class of therapeutics has already revolutionized immuno-oncology. However, it is now known that immune checkpoint therapy also shows promising results in cardiovascular diseases. This is consistent with the “inflammatory hypothesis of atherosclerosis”. This project investigates the translational potential of immune checkpoint modulation in cardiovascular diseases.

Further information here. 

Clonal hematopoiesis of indeterminate potential (CHIP) is a significant age-related phenomenon and a risk factor for both hematological and non-hematological diseases. Despite established risk stratification systems, many factors contributing to the development and progression of CHIP remain unclear, which is why the CHIP Clinic TUM and the "Deutsche CHIP Register e.V." were founded. The aim of this project is to gain new insights into clonal dynamics and risk factors through substantial expansion of the CHIP cohort and prospective nationwide data collection in Germany.

This project uses Artificial Intelligence (AI) to analyze muscle MRI scans. It aims to explore the link between muscle health and the risk of cardiovascular disease, metabolic disorders, and chronic back pain. By assessing muscle mass and quality, particularly fat content, the project seeks to discover new biomarkers. These could enable better prevention and early detection in the future. The project combines data from large studies with innovative AI image analysis methods.