Schneider C. Lab: Pioneering Big Data to Revolutionize Digital prevention
Towards sustainable, innovation-driven data science for prevention and therapy of gastrointestinal and metabolic diseases
The research group "Schneider C. Lab" at Uniklinik Aachen is a young, diverse, and interdisciplinary group of scientists from Medicine over Data Science to Astrophysics. We extract insights with direct clinical value from large databases such as the UKBiobank (A large cohort of over 500.000 people and a follow-up of ~ 15 years, with access to electronic health records, lifestyle data, serum parameters, metabolomics, genetic sequencing, imaging, and much more available to us) . Our main focus is the prevention of diseases in the gastrointestinal tract and the liver, ranging from analyzing nutritional supplements to genetic alterations, with the aim of predicting the risk of disease using Multi-Omic-methods. To learn more about our research, take a look at our featured publications.
Our Research and expertise
Note: The primary focus of our goal is to use sustainable data science approaches to advance our understanding of the prevention and treatment of gastrointestinal and metabolic diseases. At Schneider Lab, we specialize in conducting cutting-edge research on the complex interactions between environmental, genetic, and lifestyle factors that contribute to the development and progression of these diseases. We use state-of-the-art data science techniques to analyze large and diverse datasets, including genomics, metabolomics, and microbiome data, to identify novel biomarkers, therapeutic targets, and personalized interventions that can improve health outcomes for patients. Our ultimate goal is to develop sustainable and effective strategies for preventing and treating gastrointestinal (GI) and metabolic diseases that can be applied at the population level.
Our Mission
Our mission in the Schneider Lab is to use population-based genetic studies, lifestyle-related data and lipidomic data to advance our understanding of the underlying mechanisms that contribute to gastrointestinal and metabolic diseases, with a particular focus on liver-associated diseases. We aim to identify key risk factors and biomarkers that can be used to develop effective prevention and treatment strategies for these diseases. By integrating cutting-edge data science techniques with epidemiological research, we aim to generate actionable insights that can be applied at a population level to promote better health outcomes. Ultimately, our goal is to contribute to the development of sustainable and effective approaches to the prevention and treatment of gastrointestinal and metabolic diseases, and to improve the overall health and well-being of individuals and communities.
Projects
The global obesity epidemic is accompanied by a massive increase in diabetes mellitus (T2DM), metabolic-dysfunction associated steatotic liver disease (MASLD) and cardiovascular disease (CVD). We will integrate and analyze unrelated population-based cohorts and leverage the growing wealth of multi-omics data. We are an interdisciplinary international team of researchers striving to prevent GI diseases by integrating existing data sources. Using metabolomic analyses, analyses of large patient cohorts (UK Biobank, Penn Medicine Biobank), and artificial intelligence.
An example disease that illustrates methods of our lab is MASLD:
MASLD, the most common liver disease, already affects 30-40% of the Western population and is expected to become the leading cause of liver failure in Western countries. The pathophysiological hallmark of MASLD is excessive lipid accumulation in the liver (i.e. hepatic steatosis). Steatosis is strongly influenced by genetics, and the best established MASLD-related genetic risk variants TM6SF2 rs58542926 (E167K) and PNPLA3 rs738409 (I148M) both result in increased hepatocellular lipid accumulation. Because hepatic lipid metabolism and plasma lipoprotein metabolism are so closely linked, pharmacological treatment of steatosis may have an impact on plasma lipids and vice versa. Overexpression of TM6SF2, for example, reduces steatosis by increasing VLDL (Very Low-Density Lipoprotein) secretion and, consequently, plasma lipid levels; Conversely, approved drugs that lower low-density lipoprotein (LDL) cholesterol by reducing hepatic VLDL secretion exacerbate hepatic steatosis. This requires the development of novel system-level approaches to uncover new therapeutic targets for hepatic steatosis without increasing plasma lipids and thus CVD risk. Our ideal target for MASLD therapy would reduce liver lipid accumulation and thus the risk of MASLD without affecting (or even reducing) serum lipid levels. In a systematic, population-based approach, we will deeply phenotype the metabolic effects of MASLD-protective single nucleotide polymorphisms (SNPs) and lifestyle changes with a particular focus on changes in serum lipid metabolism and CVD risk.
Furthermore, we are exploring how lifestyle changes (nutrition, exercise) may influence metabolic liver disease development. Lastly, we are focused on drug repurposing to find already existing drugs that can be used to combat metabolic liver diseases.
Following this mission, our lab fosters close collaboration with various research groups within the University Hospital RWTH Aachen and with our national and international collaborators.
Sustainability
Planetary health is a prerequisite for individual health. For us as scientists and clinicians, it is imperative to spread awareness: We need to limit global temperature increase and restore biodiversity to protect health.