The Estonian Genome Centre was established aside from Estonian Biobank to lead the genetic research related to human health and diseases.
In addition to functional genomics, as new fields of research, the Estonian Genome Centre has successfully launched systems biology, microbiome and pharmacogenetics, bringing to Estonia experts with an international background.
The research at the Estonian Genome Centre directly supports the activities of the Estonian National Personalized Medicine Program, both with the development of polygenic risk scores and with the improvement of genotyping chip data. As new directions, we see multi-level analysis of the health trajectories of biobank participants, analysis of molecular profiles at DNA, RNA, proteins, metabolites and cellular traits level, and hypothesis-free data mining using machine learning and AI techniques.
Our research group aims to identify, characterize and quantify interindividual variability in drug response by comprehensive analysis of the human genome and health data. We combine data on drug plasma concentrations, treatment failure, adverse drug reactions, and genomic data from participants of the Estonian Biobank. We use text-mining tools to extract treatment outcomes from electronic health records, and have developed different methods for the analysis of longitudinal effects of medication use, and how genetic variants influence this variability.
The identified associations are tested using functional and pharmacokinetic studies. The results will serve as a basis for variants that should be included for preemptive pharmacogenomic testing, which could ultimately reduce the health and economic burden of low drug efficacy and unnecessary side effects caused by genetic variants.
The research group of pharmacogenetics is led by Professor Lili Milani, firstname.lastname@example.org
Studies the interactions between the genome and metabolome with regard to human diseases. This includes work with metabolomics data sets collected with NMR and mass spectrometry. We search for associations between genomic markers and metabolite levels as well as more complicated patterns in these data sets with the intent to understand and predict common diseases. This work requires creating new bioinformatics algorithms, scripts and tools (C++, Python) as well as conducting high-performance cluster computations.
The research group of metabolomics and systems is led by Associate Professor Toomas Haller, email@example.com
It is known that the genome apparently healthy individuals actually harbors dozens of gene-disrupting variants (predicted to result in loss of function at the protein level). On the other hand, many phenotypic traits show inconsistent inheritance patterns due to penetrance and expressivity. The very first readout of genomic information is RNA, where cells have evolved several quality control mechanisms to minimize the impact of potentially harmful mutations. Our aim is to understand how mRNA regulation contributes to the buffering of such deleterious genetic variants.
The research group of mRNA is led by Associate Professor Tarmo Annilo, firstname.lastname@example.org
The human intestinal tract is colonized by thousands of different species of microorganisms, collectively called the microbiota. The gut microbiome (collection of all microbial genes) encodes much more genes than the human genome and provides us with numerous complementary functions. The microbial community has a critical role in many aspects of health, including immunity and metabolism. Our group addresses questions about the relationships between microbiome and human host, where we currently focus on two major areas:
1) we explore the host-microbiome interactions in the development of type 2 diabetes and
2) elucidate the direct and indirect mechanisms through which the human microbiome shapes the efficacy and toxicity of commonly used drugs.
The research group of the microbiome is led by Associate Professor Elin Org, email@example.com
Research group of functional genomics is focused on understanding the molecular function of human genome variation. The group's broader scientific interest lies in understanding the genetic architecture of complex human phenotypes, focusing on intermediate molecular measurements (such as levels of gene expression in human tissues, cellular fractions and circulating small molecules) and human stature to estimate the role of both rare and common genetic variation of phenotypic outcomes through various models of inheritance (additive, recessive, epistatic and epigenetic). We implement a range of bioinformatics and genetic epidemiology techniques to map endophenotypes quantitive trait loci (QTL) and to annotate known disease associations with downstream molecular mechanisms.
The research group of functional genomics is led by Professor Tõnu Esko, firstname.lastname@example.org
The bioinformatics research group handles the quality control and processing of multi-omics data and offers general bioinformatics support for all research groups within the Genome Centre. Method development plays an important role in the scientific activities of the group, including software for genome-wide association studies (GWAMA, MR-MEGA, SCOPA), as well as novel solutions for DNA copy number variant detection and analysis. In addition, the members of the group are involved in projects studying the genetic background of different traits and diseases related to metabolic health and female reproductive health.
The research group of functional genomics is led by Professor Reedik Mägi, email@example.com
Mental health problems are extremely prevalent in modern societies, with every second individual affected during their lifetime. However, the causal mechanisms of such problems are not well understood. This is hindering advancements in novel prevention and treatment strategies to improve the quality of life of affected individuals and their family members. Our research team aims to advance the understanding of the causes and consequences of mental health problems across the lifespan and move towards better and personalized prevention and treatment strategies.
The research group of neuropsychiatric genomics is led by Associate Professor Kelli Lehto, firstname.lastname@example.org
The research group is focused on understanding the role of genetic variation in chronic diseases. We are developing novel computational tools and analytical methods to assess overall disease risks and combining the knowledge gained with other risk factors (e.g. age, gender, environmental factors and health behavior) to use this information to prevent and diagnose disease earlier and to identify potential therapeutic targets.
In 2022–2023 we are focusing on three phenotypes:
Prof. Andres Metspalu is a member of the Coordination Group of the 1+ Million Genome initiative (“1 + MG Roadmap 2020-2022”), also the leader of WP10 (common complex disease genomics and PGx) and co-leader of WP12 Genome of Europe.
Ongoing research fundings where Prof. Andres Metspalu is the coordinator from Institute of Genomics or PI:
Research group of human disease genomics is led by Professor Andres Metspalu, email@example.com.
Members of the research group:
In collaboration with: