Genetic Epidemiology

Prof. dr. Fernando Rivadeneira

In recent years, there has been major progress in human genomics, particularly in the identification of the genes which are involved in the pathogenesis of major disorders in Western societies. This progress has been achieved by genome wide association (GWA) analyses in which case-control studies have been characterized by dense arrays of genetic markers. Successes have been achieved for a wide range of disorders varying from macular degeneration, Crohn’s disease, multiple sclerosis, rheumatoid arthritis, diabetes and HIV. These developments have led to a stream of novel disease genes, highlighting new aetiological pathways and improving the understanding of the molecular basis of these diseases. The research program of NIHES offers student to participate in this rapidly developing field, performing hands-on analysis of data available with the Genetic epidemiology unit. This may concern genome wide association studies or studies of candidate genes/pathways with multiple outcomes. The research program of the genetic-epidemiology group combines successfully methodological and empirical research. The methodological research program focuses on several aspects of genome wide association studies including meta-analysis and gene interaction. The statistical methods group targets both the design and the analysis of genomic research.

Dr. Jeroen van Rooij, Prof. Dr. Joyce van Meurs

Following on several decades of gene finding for many diseases, genetic testing takes an increasing role in our health care. Currently, we perform diagnostic genetic tests in the case when a patient presents with a specific disorder and a positive family history of this disease (e.g., breast cancer of coronary artery disease). Having identified a causal genetic variant, we can then screen relatives for their carrier status and prevent the disease process by providing screening or lifestyle or medical interventions. A more recent development is to perform this type of testing in a preventive matter; in patients without prior indication or even in individuals outside of the health care system. Though this way, we may identify people at strongly increased risk for a range of disease, before these disease manifest, and perform personalized and preventive health care. In our group, we perform various projects to identify and validate the genetic risk scores that might be used clinically, but also project investigating the ethical and logistics of such a preventive effort, when implemented local (at the Erasmus MC) or nationally (though the general practitioners). As part of the NIHES program, students participate in the various pilot efforts ongoing in this field. Possible projects include extracting specific genetic risk scores from literature (e.g., for a specific disease or set of diseases) and validating their accuracy in the Rotterdam Study population as a proxy for the Dutch population; integration of genetic risk factors with clinical risk factors and the suggested approach for clinical implementation; studies of the implementation procedures (e.g., ethical, psychological aspects); understanding the biological mechanisms of disease through annotation of genetic variants; or a combination of these processes. Many projects are ongoing, and the precise research question for a student can be determined in communication with our group and in accordance with preferences of the student.

Dr. Cindy G. Boer and Prof. Dr. Joyce van Meurs

In the last decade, thousands of DNA variants (single nucleotide variations, SNVs) have been associated, through Genome Wide association Studies (GWAS) to complex disease risk (examples: osteoarthritis, diabetes, bone mineral density ,etc.). However, how these variants confer risk for complex disease is for the vast majority of DNA variants still unknown. Yet, if we want to use genetics to better understand the pathology of the disase or to identify novel treatment targets, it is vital to undertand how genetic variants confer risk for the studied disease. We need to elucidate the function of these SNVs by Identification of effector genes, disease pathways and mechanisms. The research in our group focuses on the discovery and interpretation of of genome-wide association findings. This is done using data from large-scale population based cohorts (the Rotterdam Study), multi-omics data (proteomics, transcriptomics and epigenomics) from population cohorts and bioinformatics databases and, through other post-GWAS analysis. As part of the NIHES program studens may join one of several ongoing projects. Examples of possible projects may be; performing genome-wide association studies using the Rotterdam Study dataset and in other genetic data sets, extracting multi-omics data (RNAseq, Chipseq, annotation) from bioinformatics databases to annotate genetic variants, multi-omics and disease risk, or combinations of these. Exact details of possible projects are determined by which projects are currently available and the preference of the student. Students are encouraged to communicate with our group.

Assist-Prof. dr. Mohsen Ghanbari

Molecular and systems epidemiology are emerging innovative fields of research in which molecular, cellular, and organism levels of function are incorporated into computational models and epidemiologic studies to investigate determinants of diseases at multiple levels as well as their interactions. Although epidemiology has been proven valuable to identify associations between exposure and disease at population level. Yet, traditional epidemiology does so without obtaining information of the biological processes that underlie these associations. Molecular and systems epidemiology could enhance the measurement of exposure, effect, and susceptibility, and also give a fascinating insight into biological mechanisms, and generate novel hypotheses about disease mechanisms. This knowledge will lead to the identification of early etiologic, diagnostic, and prognostic biomarkers of disease and also allow us to better target preventive strategies, and yield new therapeutics for complex diseases. The availability of various clinical outcomes and high-throughput omics data in the Rotterdam Study cohort has created a great opportunity for genetic epidemiological studies to integrate various omics datasets (genetics, epigenetics, transcriptomics, proteomics and metabolomics) and build a comprehensive and dynamic model of the molecular changes in diseases for better understanding the etiology, biomarker and drug discovery.