"The whole is greater than the sum of the parts"
Human physiology is governed by a complex and dynamic molecular interplay. High-throughput technologies enable studies interrogating thousands of molecules with similar biochemical properties (e.g. transcriptomics for RNA transcripts, proteomics for proteins). However, a single layer of -omics can only provide limited insights into (patho-)physiological mechanisms.
RNA, proteins, and metabolites exert orchestrated and complementary functions within discrete molecular pathways regulating specific biological processes. Thus, multi-omics studies provide a combined view of multiple functional layers at a system level. The depth and sensitivity of this multi-dimensional information will enable Systems Medicine to predict changes in physiology based on perturbations of specific biological networks.
The potential of Systems Medicine is already flourishing on pioneering multi-omic studies. Examples include investigations of the molecular programs governing human pregnancy, the early prediction of diseases, and perturbations of human physiology during space missions.
In our laboratory we develop technologies to overcome current methodological limitations related to compliance, reproducibility, accuracy, sensitivity, data security, and anonymity. Our goal is to provide personalized, accurate, and sensitive multi-dimensional molecular fingerprints of human physiology :
Using medical engineering we have developed, tested and patented a small blood sampling device (see figure below) collecting four blood drops after a minimally invasive fingerpick. On one hand, this device standardizes the isolation of blood plasma and blood cells, thus minimizing variability. On the other hand, several strategies enable us to correct for those changes in the concentration of the measured molecules that inevitably occur during transport and storage of this device. Hence, reliable measurements of the "real" concentration of these molecules in blood can be obtained - this accuracy is key for the success of any downstream data analysis workflow.
Using biochemistry and state-of-the-art instrumentation setup in our laboratory (i.e. QExactive HFX Mass Spectrometer, see below), we have developed workflows enabling the reproducible quantification of >15,000 mRNA, >1,000 microRNA, >500 proteins and >400 metabolites from the cell-free plasma and immune cells preserved inside our capillary blood sampling device at room temperature for several days.
We are using data integration and machine learning strategies for the analysis of these multi-dimensional datasets. Our strategies to standardized sampling and preservation as well as to correct for the changes in concentration of the measured molecules will have a significant benefit on the performance of our algorithms (by reducing the Garbage In - Garbage Out problem).
Thus, we expect to go beyond classical biomarkers and to observe longitudinal changes in
activation of multi-omic pathways that will define more specific and sensitive tracking tools of
particular physiological alterations.
By implementing Blockchain technology we are creating a technological enviroment for the anonymous and secure upload, storage, analysis and sharing of multi-dimensional data.
We apply the translational potential of our multidisciplinary pipeline across biomedical research questions, e.g. in collaboration with our sister-laboratory on human skin biopsies in the setting of pain research.