BioSignATure - Systems-oriented, multi-omics identification of biomarker signatures for atherothrombosis detection, quantification and treatment

2 PhD positions in the curATime clusters4future initiative offered in IPP winter call 2022

Scientific Background

Atherothrombotic disease (e.g., myocardial infarction, stroke) is the leading cause of death and disability worldwide, accounting for nearly one third of all deaths. The current generation of therapeutics (e.g., lipid lowering agents, antiplatelet agents, anticoagulants) insufficiently addresses the wide spectrum of pathomechanisms implicated in atherothrombosis. Hence, new and innovative drugs are needed. The largest efficiency bottleneck in traditional drug development is identifying the appropriate therapeutic target. Approximately 95% of drugs tested in human trials fail due to a lack of translatability of preclinical models to the human setting in a traditional drug development pipeline, resulting in a lack of efficacy or safety issues. Incorporating human data at an early stage could significantly reduce the preclinical target screening space. In the bioSignATure project, human multi-omics data from independent cohort studies will be used to discover new targets and assess their likely efficacy and safety. The primary discovery data level will be proteomics, specifically enabled through the use of the Olink Explore 3072 immuno-NGS assay, allowing the sensitive and specific relative quantification of nearly 3,000 proteins, and a DIA mass spectrometry approach to provide complementary coverage of the proteome. Different omics levels are used for orthogonal validation and more detailed assessment of target efficacy and safety. The availability of detailed clinical and subclinical information is instrumental in establishing evidence for target-disease linkage from several complementary angles. 

PhD project: 

This project is one of the lighthouse projects in “CurATime – Cluster for Atherothrombosis and Individualized Medicine” (, a research cluster recently funded by the German Federal Ministry of Education and Research (BMBF) for €15 million for the first 3-year funding period. The goal of the PhD project is to help implement and to interpret the results of an analytical pipeline that prioritizes molecular signatures and specific targets for therapeutics, diagnostic and prognostic tools in the setting of atherothrombosis, by evaluating candidate targets along several relevant dimensions. This pipeline includes, among other things:

  • The identification and ranking of targets by innovative machine learning methods
  • Embedding targets in signaling pathways and studying their potential interaction with other pathways
  • Surveying candidate molecules’ on-target and off-target effects by assessing their relationship with different subclinical markers of atherosclerosis as well as organ damage markers and the broader clinical phenotype
  • Corroborating the validity of targets by external (cross-cohort) and orthogonal validation (e.g., by assessing the effect of SNPs or CpG site methylation in corresponding genes) 

Initiative and creativity are highly valued traits in the prospective candidate, and new ideas to further optimize the pipeline for its purpose are strongly encouraged. 

The human biodatabases used in this project are high-dimensional, spanning clinical and subclinical data (including detailed medical-technical information such as echocardiographic and coronary angiographic imaging), DNA (genotyping array with ~2.2M variants), proteomic and lipidomic data (targeted immuno-NGS-based multiplex assays, DIA mass spectrometry) as well as DNA methylation data (Illumina 850K MethylationEPIC array) and miRNA sequencing data (Next Generation Sequencing). In context of the larger curATime project, additional data will be generated and integrated as well, such as on autoantibodies and the microbiome. 

The candidate will be integrated in a friendly, professional and highly multidisciplinary team, comprising clinicians, epidemiologists, bioinformaticians, biostatisticians, as well as biologists and biochemists. Specific competences and supervisors are present to support the PhD candidate. Within the bioSignATure project, the candidate will additionally interact with experts in the fields of artificial intellligence (DFKI, German Research Center for Artificial Intelligence), bioinformatics with focus on interspecies ortholog mapping and pathway analysis (Computational Biology and Data Mining, Johannes Gutenberg University Mainz), drug/mRNA vaccine development (TRON gGmbH, Translational Oncology; BioNTech SE) as well as basic research in thrombosis (CTH, Center for Thrombosis and Hemostasis). The latter group will simultaneously perform multi-omics analyses in the context of mouse models, allowing bidirectional translation of results between species. 

Publications relevant to the project

Ten Cate V, Prochaska JH, Schulz A, Koeck T, Pallares Robles A, Lenz M, et al. Protein expression profiling suggests relevance of noncanonical pathways in isolated pulmonary embolism. Blood. 2021;137(19):2681-93.

Pallares Robles A, Ten Cate V, Schulz A, Prochaska JH, Rapp S, Koeck T, et al. Association of FXI activity with thrombo-inflammation, extracellular matrix, lipid metabolism and apoptosis in venous thrombosis. Sci Rep. 2022;12(1):9761.

Keller T, Zeller T, Peetz D, Tzikas S, Roth A, Czyz E, et al. Sensitive troponin I assay in early diagnosis of acute myocardial infarction. N Engl J Med. 2009;361(9):868-77.

Neumann JT, Twerenbold R, Ojeda F, Sörensen NA, Chapman AR, Shah ASV, et al. Application of High-Sensitivity Troponin in Suspected Myocardial Infarction. N Engl J Med. 2019;380(26):2529-40.

Wild PS, Zeller T, Beutel M, Blettner M, Dugi KA, Lackner KJ, et al. [The Gutenberg Health Study]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2012;55(6-7):824-9.

Göbel S, Prochaska JH, Tröbs SO, Panova-Noeva M, Espinola-Klein C, Michal M, et al. Rationale, design and baseline characteristics of the MyoVasc study: A prospective cohort study investigating development and progression of heart failure. Eur J Prev Cardiol. 2021;28(9):1009-18.

More P, Bindila L, Wild P, Andrade-Navarro M, Fontaine JF. LipiDisease: associate lipids to diseases using literature mining. Bioinformatics. 2021;37(21):3981-2.

Alanis-Lobato G, Andrade-Navarro MA, Schaefer MH. HIPPIE v2.0: enhancing meaningfulness and reliability of protein-protein interaction networks. Nucleic Acids Res. 2017;45(D1):D408-d14.

Wik L, Nordberg N, Broberg J, Björkesten J, Assarsson E, Henriksson S, et al. Proximity Extension Assay in Combination with Next-Generation Sequencing for High-throughput Proteome-wide Analysis. Mol Cell Proteomics. 2021;20:100168.

Petrera A, von Toerne C, Behler J, Huth C, Thorand B, Hilgendorff A, et al. Multiplatform Approach for Plasma Proteomics: Complementarity of Olink Proximity Extension Assay Technology to Mass Spectrometry-Based Protein Profiling. J Proteome Res. 2021;20(1):751-62.

Contact Details

Dr. Vincent ten Cate
Clinical Epidemiology and Systems Medicine, Center for Thrombosis and Hemostasis, Mainz
Preventive Cardiology and Medical Prevention, University Medical Center Mainz

Prof. Philipp Wild
Clinical Epidemiology and Systems Medicine, Center for Thrombosis and Hemostasis, Mainz
Preventive Cardiology and Medical Prevention, University Medical Center Mainz
Systems Medicine, Institute of Molecular Biology