Work Package 5: Multi-omics platforms 

The omics platforms provide WPs 1 to 4 with infrastructure and expertise for the analysis and integrative evaluation and interpretation of molecular high-throughput data. In addition to a service function, the experts of WP5 have their own scientific aspects and a strong involvement in the goals of WPs 1 to 4.

WP5.1 Genomics and Transcriptomics

The concept of a "personalized medicine" is based, among other factors, on the ability to stratify individuals using genetic variants. The evolution of sequencing techniques offers the possibility of a comprehensive determination of DNA and RNA variants. A state-of-the-art sequencing platform is available with the Munich Sequencing Alliance, a joint institution of the two Munich universities, the Max Planck Institute for Psychiatry and the HMGU.

  • Contribution to WP1 (coronary heart disease):

Some variant information is already available for the patient samples in the DigiMed Bayern project. These will be enriched and standardized using current array and sequencing methods. The aim is a uniform data set for the core samples, in which metabolomic and proteomic data sets are obtained, in addition to the genomic and transcriptomic variants.

  • Contribution to WP2 (carotid stenosis and stroke):

The scope and selection of existing vascular preparations should be validated in preliminary examinations. Sequencing is then carried out in parallel with the proteomics examinations in 1,250 patients, as a target. Standard protocols are initially used for sequencing with a coverage of approx. 50 million sequencing reads per sample. In a parallel approach, transcriptome examinations in individual cells are to be carried out specifically for the carotid samples. In this context, the working group develops tools and routines for the project participants. The sequence data is stored in the DigiMed Bayern database at the LRZ. Sequences, both from publicly available resources and from cooperation partners, should also be made available to the project partners on this database.

  • Contribution to WP3 (Familial Hypercholesterolaemia):

For the screening examinations of pathogenic variants in FH genes, the working group has access to extensive preliminary work using SNP arrays. This includes array records from more than 20,000 samples. Due to the appropriate specification, the same arrays are planned to be used for DigiMed Bayern cohort. In order to determine the sensitivity of the array, random synthetic samples should be used as controls. A capture procedure is being established for the panel examinations, which enables the exons of 4 FH genes (LDLR, WPOB, PCSK9, HCHOLA3) to be subjected to a comprehensive variant analysis. For the genome tests in diagnostically unclear FH families, transcriptomics tests for splice variants in blood samples are carried out in parallel.

  • Contribution to WP4 (The General Population of Bavaria):

For the project, the KORA population serves as a representative data set with extensive omics data for the Bavarian population. The aim of WP4 is to complete the genomic and transcriptomic data of all KORA sample data sets that are available for DigiMed Bayern.

(updated: Dec. 2019)

WP5.2 Proteomics and Metabolomics

Proteins are the biological function carriers of the cell. Many pathophysiologically relevant proteins are secreted by cells and accumulated in the extracellular space or circulate in the blood plasma. At the same time, the enzymatic function of proteins creates an enormous variety of metabolic products (metabolites). Both proteins and metabolites are of great clinical importance, because in many cases they can be used as so-called biomarkers to predict or determine health status. Classic methods for protein or metabolite determination - as they are already used extensively in the clinical routine - normally allow the quantification of only one protein or metabolite at a time. In contrast, mass spectrometry-based methods enable the measurement of a large number of different molecules simultaneously. Within DigiMed Bayern, this potential is now to be used to identify new biomarkers for coronary heart disease (CHD, WP1), stroke (WP2) and heart attack (WP4). These biomarkers can be used in the future for improved diagnosis, prevention and treatment in the context of P4 medicine.

  • Contribution to WP1 (coronary artery disease):

As part of the multi-omics approach carried out at the German Heart Center Munich (DHM) to better understand CAD, tissue proteomes from selected patient groups are to be measured and associated with further global genomic and transcriptomic data. The types of tissue to be examined are blood, adipose tissue, internal mammary artery and other types of tissue, which will be determined in the further process of the project depending on sample availability. The tissue samples from about 100 patients are already available and can be measured immediately after the start of the project. Within the DigiMed Bayern project, samples are continuously collected during operative interventions, and added to the data set after measurement.

In addition to this systems medicine approach, a biomarker-oriented approach is also to be pursued. A biobank with blood plasma and clinical data from ~ 1,200 patients is already established in the DHM. Blood plasma contains a large number of known biomarkers, of which more than 100 can already be measured on the proteomics level. In addition to the quantitative determination of already approved markers, the correlation of proteomic and clinical data should be used to identify new proteins that are related to CHD. In addition to the proteomic measurements, the blood metabolome will also be examined from the same samples. The metabolites contained in the blood reflect the metabolic status of the patient, and are related to the progression of the disease. There is also great potential here to identify new biomarkers for CHD, and to characterize causal signal pathways that are initiated, for example, by genetic variants.

The proteomic and metabolomic measurements of the blood plasma should also be used to determine the effects of individual medication on the hemogram in a systematic manner. In many cases, the direct effect of individual medications and the associated medical benefits are not obvious. By creating a defined comparison cohort, the proteomic and metabolomic measurements of the blood plasma can provide direct conclusions about their effectiveness in everyday clinical practice and make a direct contribution to treatment schemes for CHD.

  • Contribution to WP 2 (carotid stenosis)

The plaques consist mostly of extracellular (lipo-) protein components. In the mouse model, the group of Prof. Mann and Dr. Wierer recently showed that these components differ significantly from the extracellular proteins of the normal vascular wall. DigiMed Bayern aims to determine the human plaque proteome and, by correlating it with clinical data, to contribute to better categorization of plaques. This could enable a better prediction of postoperative clinical progression.

From the vascular preparations of the carotid artery of approximately 1,000 patients, targeted areas are to be removed using laser microdissection, and then used for proteome analysis. Although the sample quantity is extremely small with this approach, over 5,000 quantified proteins can be expected with the methods developed by the research group.

The vascular preparations to be analyzed are already available. In order to achieve increased reproducibility, an automated high-throughput process will first be established, which is based on image analysis with neural networks and subsequent laser microdissection and efficient collection in reaction vials. This procedure is then applied to all samples.

In addition to the plaque samples, the plasma proteome and metabolome of the same patient group are also measured in order to identify biomarkers that are associated with different plaque stability.

  • Contribution to WP4 (The General Population of Bavaria):

The KORA cohort has been studied in a variety of ways. As part of DigiMed Bayern, the assigned blood samples are to be used for the to date most extensive plasma proteome study of the general population. For this purpose, blood samples from 500 patients taken at different times in their lives are examined in the first project period. By integrating with clinical data, as well as existing and in DigiMed Bayern created omics data, predictive patterns for myocardial infarction and other clinical pictures are to be identified. In the further course of the project, the measurements will be expanded to a total of approximately 2,500 patients.

The analysis of the plasma proteome to determine the health status could be established as a generally applicable method in the future. DigiMed Bayern makes it possible to test this approach on an appropriate scale, and to apply it directly. In addition to the large number of marker proteins determined at the same time, another advantage is the small amount of sample that is required for the analysis. Already 5µl of blood are sufficient, which is why the blood sampling is associated with minimal patient stress.

(updated: Dec. 2019)

Prof. Dr. Thomas Meitinger
Prof. Dr. Thomas Meitinger

Leitung Institut für Humangenetik, Klinikum rechts der Isar, Technische Universität München

+49 (0) 89 / 4140-6381

Dr. Holger Prokisch
Dr. Holger Prokisch

AG Leiter, Institut für für Neurogenomik, Helmholtz Zentrum München; AG Leiter, Institut für Humangenetik, Klinikum rechts der Isar, Technische Universität München

+49 (0) 89 / 3187-2890
Prof. Dr. Matthias Mann
Prof. Dr. Matthias Mann

Director Department of Proteomics and Signal Transduction, Max-Planck-Institute of Biochemistry

+49 (0) 89 / 8578-2557

Prof. Dr. Dieter Kranzlmüller
Prof. Dr. Dieter Kranzlmüller

Vorsitzender des Direktoriums des LRZ

+49 (0) 89 / 35831-8700