Personal information
Scholz, Markus, Prof. Dr. rer. nat.
Institute for Medical Informatics, Statistics and Epidemiology (IMISE), LIFE
Leipzig University (UL)
Current position
Professor of Genetical Statistics and Systems Biology (since 2013)
Role within partner site
Contributes expertise on genetic predisposition, link to LIFE Adult;
Relevant work experience
Molecular epidemiologist with focus on genetic prediction models;
2013– Professor for Genetical Statistics and Biomathematical Modelling at IMISE, University of Leipzig; responsible for the molecular research programme of the LIFE Research Centre for Civilization Diseases
2010–2013 Head of research group Systemsbiological Modelling and Genetical Statistics
2007–2010 Head of research group Genetical Statistics
2006–2010 Head of research group Mathematical Models of Blood Formation
2002–2013 Research assistant at IMISE, Leipzig University
1999–2002 Research assistant at Institute for Mathematics and Informatics, Leipzig University
Professional background
2013 Venia legendi for Medical Bioinformatics, Leipzig University
2012 Postdoctoral qualification (Habilitation) in Biomathematical Modelling
2002 PhD in Mathematics
1999 MSc in Mathematics
Main research focus
Molecular epidemiology, genetical statistics of complex phenotypes (e.g. genome-wide and transcriptome-wide association studies, metabolomics, multi-layer integrative genome analyses, causal inference), biometrics (time series data analyses, multivariate statistics, survival models), biomathematical dynamical diseases and therapy models;
Publications
5 out of 191; SCOPUS h-index 33; * equally contributing authors
Landgraf K, …, Scholz M et al (2020). The obesity susceptibility gene TMEM18 promotes adipogenesis through activation of PPARG. Cell Rep 33:108295. doi: 10.1016/j.celrep.2020.108295.
Scholz M et al (2020). Cohort profile: The Leipzig Research Center for Civilization Diseases-Heart study (LIFE-Heart). Int J Epidemiol 49:1439–1440h.
Tin A, …, Scholz M et al (2019). Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels. Nat Genet 51:1459–1474.
Wuttke M, …, Heid IM, Scholz M, Teumer A, Köttgen A, Pattaro C* (2019). A catalog of genetic loci associated with kidney function from analyses of a million individuals. Nat Genet 51:957–972.
Kirsten H, …, Scholz M (2015). Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci. Hum Mol Genet 24:4746–4763.
Additional information
Committees: Person in charge for the access of Leipzig University to the Saxonian Population Register (since 2019), Examination board of the Master’s course „Clinical Research and Translational Medicine“ (since 2018), German delegate of COST Action CA17129 „Catalysing transcriptomics research in cardiovascular disease (CardioRNA)“ (since 2018), Leader of GMDS working group „Models in Medicine and Biology“ (since 2015);
