Institute of genomics invites applications for doctoral programmes

Supervisors: Erik Abner, Prof. Elin Org

The aim of this doctoral research project is to elucidate the genetic background of chronic respiratory diseases (CRDs), with a focus on the interplay between respiratory viral infections and host genetics. By leveraging health and genetic data from the Estonian Biobank and nasopharyngeal swab collections, this study seeks to identify genetic risk factors for viral infections and their role in disease pathogenesis. Preliminary analyses have identified promising genetic variants involved in the regulation of lung inflammatory responses, which may mediate the development of RSV bronchiolitis and chronic lung diseases. This project employs bioinformatic methodologies to map the genetic mechanisms of CRDs and their interactions with viral infections. The analysis focuses on the interplay between genetic predisposition and environmental influences, particularly viral infections, in disease development. Additionally, it aims to identify genetic and phenotypic overlaps among chronic lung diseases to distinguish underlying molecular mechanisms and define both shared and disease-specific pathogenic factors. To understand the interplay between host genetics and viral infections, the project will integrate phenotypic and genetic data from viral infection datasets, analyzing correlations between genetic predispositions and infection patterns. RNA sequencing will also be carried out to identify viral strains from nasal swab samples, enabling detailed analyses of how specific viral strains interact with host genetics. These comprehensive approaches will provide insights into the genetic and environmental factors contributing to the development and progression of CRDs in the context of viral infections. The findings from this research will advance our understanding of the links between infectious diseases and chronic conditions, paving the way for personalized prevention strategies and targeted therapeutic interventions.

Read more

Supervisors: Jaanika Kronberg, Oliver Aasmets

This aim to explore the role of exposome, metabolites and genetic risk for the development of hypertension. This PhD project will utilise the datasets, knowledge and collaborations from ongoing exposome projects in the Institute of Genomics, by focusing on hypertension which is a risk factor for many non-communicable diseases. The project will also build on ongoing work in the PRG1291 in relation to associations between metabolites and diseases. The project is structured into 3 articles. Article 1 focusses on applying exposome analysis for the development of hypertension. The plan is to use exposome data from the EXPANSE project, phenotype definitions from PRG1291 and hypertension diagnosis data of 210,000 Estonian Biobank participants for survival models. Article 2 combines genetic risk and exposome data. The student will cluster exposome data: air and built environment will be used, with the possibility of social exposome factors from collaborators in the EstBB. Genetic risk scores will be developed based on publicly available summary statistics from the GWAS catalog. The single and combined effects of both exposome clusters and genetic risk will be analysed. Article 3 will build on the results of articles 1 and 2 and analyse hypertension with mediation analysis methods, including both genetic risk and exposome as exposures and metabolites as potential mediators.

Read more

Supervisors: Mait Metspalu, Reedik Mägi, Luca Pagani, Vasili Pankratov

Genome sequencing uncovers rare monogenic diseases affecting 5-7% of people. Polygenic Risk Scores (PRS) amalgamate common genetic variants from GenomeWide Association Studies (GWAS) to assess relative genetic risk for complex diseases. PRS enhances population stratification in screening programs, aids health decisions, identifies comorbidities, and groups individuals by biological pathways. Challenges include PRS transferability across diverse populations, uncertainty in estimation, integrating polygenic and monogenic risk, and adjusting for demographic factors. Ancestry-specific PRS accuracy varies within homogeneous groups, prompting research on enhancing ancestry-informed PRS and assessing prediction accuracy in specific cohorts like the Estonian Biobank. Goals of a PhD project include refining ancestry-specific PRS, assessing prediction accuracy in diverse cohorts, comparing LD-scores, and exploring methods to mitigate PRS transferability issues.

Supervisors: Teele Palumaa, Priit Palta

This project investigates the genetic and metabolic mechanisms underlying eye diseases and their associations with lifestyle and systemic conditions using an integrative approach combining epidemiology, genetics, and metabolomics. The doctoral candidate will complete a placement at East Tallinn Central Hospital Eye Clinic to gain insights into the Estonian healthcare system, enabling the development of precise phenotype definitions to facilitate advanced analyses. First, the project will characterise the genetic and metabolic underpinnings of all major eye diseases using rigorous phenotyping from the available healthcare data. Genome-wide association studies (GWAS) and metabolomic analyses will identify genetic variants and metabolite profiles associated with disease prevalence and progression, with findings validated in external datasets like the UK Biobank and FinnGen. Second, the project will examine how lifestyle factors, such as physical activity, nutrition, smoking, sleep, and circadian rhythms, contribute to eye disease risks. Using phenome-wide association studies, GWAS, and polygenic risk scores, the study will uncover shared biological pathways linking lifestyle traits to eye diseases, providing insights for prevention and public health strategies. Finally, the project explores bidirectional relationships between eye diseases and systemic conditions, including cardiovascular disease, diabetes, and hypertension. Advanced downstream analyses such as genetic linkage, pleiotropy, and network analysis will identify shared mechanisms and causal pathways connecting systemic and ocular health. This project equips the doctoral student with advanced research skills and deep expertise in Estonian Biobank healthcare data, enabling impactful contributions to academia and precision medicine.

Read more

Supervisors: Lehti Saag, Kristiina Tambets, Alena Kushniarevich

This project focuses on advancing our understanding of the genetic history of the Eastern Baltic through the analysis of ancient DNA (aDNA) and integrating cutting-edge bioinformatic methods. aDNA offers rich insights into past human migrations, adaptation, and social structures, but it poses challenges due to DNA degradation and contamination. Traditional aDNA studies primarily rely on allele frequency differences, but recent developments in imputation methods and haplotypebased analyses provide new opportunities for more precise genetic reconstructions of past populations. The project's aim is to enhance the understanding of the genetic history of the Eastern Baltic using both traditional allele frequency analyses and more sophisticated haplotype-based approaches. The first objective involves processing genomic data from ancient Eastern Baltic individuals and analysing it using allele frequency methods. This will provide a broad overview of genetic affinities and population history. The second objective focuses on haplotype-based analyses, which will allow for finer insights into admixture processes and kinship practices in the region by imputing genotypes with an enriched reference panel. Lastly, the project seeks to explore the relationship between human populations and their environment by gathering spatiotemporal data on material culture, climate, and vegetation. Using this data, the project will model how changes in genetic ancestry intersect with environmental and cultural shifts over time. Overall, the project aims to contribute to a deeper, more detailed understanding of the genetic history of the Eastern Baltic and its broader implications for human population dynamics and past societies.

Read more

Supervisors: Triin Laisk, Reedik Mägi

Cyclical fluctuations in female sex hormones, such as estrogen and progesterone, influence women’s physical, emotional, and cognitive health. Sensitivity to these hormones is widespread but often underestimated and underreported. Individual hormone sensitivity is reflected in conditions such as premenstrual syndrome (PMS), responses to hormonal medications, certain pregnancy-related conditions, and (peri)menopausal symptoms. While conditions reflecting hormonal sensitivity are partially heritable, their genetic determinants remain largely uncharacterized. This project is based on data from the Estonian Biobank, which includes 210,000 participants, 136,000 of whom are women. The aim of the study is to map the genetic architecture and biological basis of hormonal sensitivity.

Read more

Supervisors: Ene Reimann, Reedik Mägi

In this project, we aim to map the role of genetics and genomics in the development and progression of chronic inflammatory diseases such as osteoarthritis (OA), rheumatoid arthritis (RA), and spondylarthritis (SpA). Rheumatic diseases are very common affecting more than 40% of the European population and cause significant morbidity, pain and shortening of life expectancy. For that, we will study the events leading to disease onset using data from the Estonian Biobank. We will use a standardized GWAS analysis workflow to assess the associations between genetic variations and rheumatic diseases and inflammation in order to identify potential genetic biomarkers. Similarly, we will analyse the associations with metabolite profiles using NMR metabolites available in the Estonian Biobank. These data, together with other available omics datasets and risk scores, will be used to build new risk prediction models for rheumatic diseases. Within this project we also aim to map the shared genetics of different musculoskeletal diseases.