Detail

Keywords

Data Interpretation, Statistical; Epidemiology; Genomics; Metagenomics

Research interests

Focus 1 – Genetic Epidemiology & Data Science

My research focuses on genetic epidemiology and the integration of large-scale molecular and clinical data. I apply a broad range of analytical approaches—including genome-wide association studies (GWAS), polygenic risk scoring (PRS), Mendelian Randomization (MR), and genomic structural equation modeling (gSEM)—to uncover shared genetic architectures and causal mechanisms across complex diseases. Beyond human genetics, my work extends to microbial systems: I study the epidemiology and evolution of bacteriophage–bacteria interactions, combining metagenomic sequencing, phage isolation from clinical and environmental sources, and experimental phage evolution. These complementary projects aim to understand how genetic variation—whether in humans or microbes—shapes health, disease, and therapeutic potential.

Focus 2 – ME/CFS

I lead a project on rare genetic variants in ME/CFS, aiming to identify novel contributors to disease susceptibility and immune dysregulation. In parallel, I collaborate on studies investigating mast cell activity and molecular immune regulation in ME/CFS. My work is closely linked to the DecodeME initiative and to emerging efforts to establish an Austrian ME/CFS reference center, ensuring that research advances remain clinically relevant and connected to patient needs.

Techniques, methods & infrastructure

I was awarded a PhD in Biotechnology from the University of Life Science in Vienna in 2015. I recieved PostDoctoral training at the Department of Epidemiology and Biostatistic of the Imperial College London and worked for the 100.000 Geneomes Project before I started my current post at MedUni Wien.

In recent projects and collaborations I applied the following methods and techniques: 

• Genetic analysis, WGS (https://github.com/Mwielscher/derma-genomics ) GATK pipeline running on Google cloud with increase security measures (developed in collaboration with Hatem Navar)
• scRNA sequencing (https://github.com/Mwielscher/scRNAseq ) this repository also contains instructions on how to use the Vienna Scientic cluster
• Phage discovery (https://github.com/Mwielscher/AD_phageDiscovery) scripts that help to discover phages in meta genomic samples
• Epidemiology (https://github.com/Mwielscher/EWAS_CRP ) scripts from EWAS to Mendelian Randomization
• Epidemiology II – We are running several projects analyzing data from from MedUni’s RDA (Research Documentation and Analysis platform)

Grants

• TAI1074525: NextGen directed evolution: Decoding phage dark matter (2025)
  Source of Funding: FWF (Austrian Science Fund), 1000 ideas program
  Coordinator of the collaborative project
• ME-CFS24-002 Genetic architecture of chronic fatigue syndrome (2024)
  Source of Funding: WWTF (Vienna Science and Technology Fund), ME/CFS - Understanding ME/CFS
  Principal Investigator
• ME-CFS24-004 The impact of mast cell activation on epithelial and endothelial barrier dysregulation in post-infectious ME/CFS (2024)
  Source of Funding: WWTF (Vienna Science and Technology Fund), ME/CFS - Understanding ME/CFS
  Principal Investigator

Selected publications

1. Wielscher, M. et al. (2025) ‘Modeling Sleep Genetics Uncovers Distinct Disease Risks in Night vs. Day Workers’. Available at: https://doi.org/10.21203/rs.3.rs-7528705/v1.
2. Wielscher, M. et al. (2023) ‘The phageome in normal and inflamed human skin’, Science Advances, 9(39). Available at: https://doi.org/10.1126/sciadv.adg4015.
3. Wielscher, M. et al. (2022) ‘DNA methylation signature of chronic low-grade inflammation and its role in cardio-respiratory diseases’, Nature Communications, 13(1). Available at: https://doi.org/10.1038/s41467-022-29792-6.
4. Wielscher, M. et al. (2021) ‘Genetic correlation and causal relationships between cardio-metabolic traits and lung function impairment’, Genome Medicine, 13(1). Available at: https://doi.org/10.1186/s13073-021-00914-x.
5. Wielscher, M. et al. (2015) ‘Diagnostic Performance of Plasma DNA Methylation Profiles in Lung Cancer, Pulmonary Fibrosis and COPD’, EBioMedicine, 2(8), pp. 929–936. Available at: https://doi.org/10.1016/j.ebiom.2015.06.025.