Digital Medicine
Computational Medicine
Claudia Langenberg
Common metabolic disorders such as obesity, insulin resistance and type 2 diabetes have both environmental and genetic causes. We now know that many sections of the genome influence the risk of weight gain or adverse fat distribution, in addition to the important roles played by lack of physical activity and excessive intake of high-calorie foods. However, it is unclear how the identified genes exert their influence or which mechanisms provide the best targets for intervention. Hundreds and thousands of molecules (such as the human metabolome or proteome) can now be detected and measured in concentration on a large scale in blood and other tissues. Our team is integrating genetic, biological, and "omics" data from large-scale population and clinical studies to characterize the genetic architecture of human metabolism and its influence on health and disease.
Data-Science for Metabolic and Population Health
Common metabolic conditions such as obesity, insulin resistance and type 2 diabetes have both environmental and genetic causes. For example, we now understand that many genetic regions increase the risk of putting on weight or distributing fat unfavorably, in addition to the important roles played by a lack of physical activity and excessive intake of high-calorie foods. Little is known about how identified genes influence disease or which mechanisms are the best targets for intervention. Hundreds and thousands of molecules (such as the human metabolome or proteome) can now be detected and measured on a massive scale in blood and other tissues. Our team integrates genomic and other biological and ‘omic’ data in large-scale population and clinical studies to characterize the genetic architecture of human metabolism and its influence on health and disease.
For recent results and studies please visit www.omicscience.org
Address:
BIH - Digital Health Center
Charité – Universitätsmedizin Berlin
Campus Mitte
Kapelle-Ufer 2
10117 Berlin