Computational Biology and Immune Response Trajectories of Type 1 Diabetes Development

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We seek to explore the complex diversity of immunologic and molecular characteristics in the development of autoimmunity and type 1 diabetes.

Website Institute

Lead Scientist

We seek to explore the complex diversity of immunologic and molecular characteristics in the development of autoimmunity and type 1 diabetes.

Website Institute

Lead Scientist

To investigate the underlying factors and processes of type 1 diabetes development in childhood, we use modern cutting-edge technologies and computational methods to discover novel markers of autoimmunity development in our large longitudinal cohort studies.

Together with our partners at Helmholtz Munich, particularly the Institute of Translational Genomics and the Computational Health Center, we combine multi-‘omics’ data (such as genomics, epigenomics, transcriptomics and proteomics) and modern (AI-powered) analytic tools to identify new patterns and markers associated with autoimmunity and progression to clinical type 1 diabetes. This will enable us to improve our knowledge in autoimmune mechanisms that drive the development of type 1 diabetes in childhood.

Epigenomics

DNA methylation plays a crucial role in genomic stability and gene regulation. Various environmental factors have been shown to be associated with or even affect DNA methylation. Within this project we explore whether environmental factors can influence DNA methylation profiles of children at-risk for type 1 diabetes development.

Immunology

Type 1 diabetes is caused by the autoimmune response against pancreatic beta-cells. Understanding the immunological processes before the onset of type 1 diabetes is crucial to improve risk prediction and prevention strategies. Within this project we primarily want to decipher immunological patterns that contribute to different progression types from early autoimmunity onset to clinical type 1 diabetes.

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Genomics

The risk for the development of type 1 diabetes is strongly driven by multiple genetic variants. Within this project our aim is to identify novel genetic markers and develop improved polygenic risk scores (PRS) with a higher precision to predict the progression to type 1 diabetes.

Computational Biology and Immune Response Trajectories of Type 1 Diabetes Development

Projects

Epigenomics

Immunology

Genomics

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