NIH – GIANT - Biological Insights from Genetic Investigation of ANthropometric Traits (GIANT) Across the Allelic Spectrum
15.08.2017 - 31.07.2022
We focus on deciphering the genetic basis of obesity and of adult height. Obesity is an enormous public health problem with no safe and effective therapies that foretells a future epidemic of diabetes, cardiovascular disease, cancer, and early death. Understanding the specific genetic and biological factors that control susceptibility or resistance to obesity will provide crucial clues that can guide the design of new, critically-needed interventions and therapies. Adult height is the endpoint of childhood growth, a fundamental developmental process and marker of childhood health, but is also the classic model polygenic trait because it is highly heritable and easily measured. As such, studying height has facilitated the development (by us and others) of genetic and computational methods that have been applied broadly to other polygenic traits and diseases.
Aim 1. Perform the largest GWAS to date, using >1.5 million deeply imputed samples from multiple ancestries, focused on measures of obesity and height. Within the GIANT framework, we will coordinate the generation of and perform the meta-analysis of deeply imputed GWAS data, to find associated variants not discoverable in previous GWAS. We will provide infrastructure for imputation to deep reference panels (including the haplotype reference consortium panel), and perform QC and meta-analysis of association data.
Aim 2. Assemble and analyze data from >100,000 exome and whole genome sequences to discover low frequency and rare variants, coding and noncoding, that influence measures of obesity and height. We will make available infrastructure/software for sequence processing, variant calling and analysis. We will QC and perform meta-analysis of single variant associations and gene-based tests of rarer coding variants.
Aim 3. Integrate the association results from common and rare/low-frequency variants, and use complementary data sets to implicate causal genes and biological processes. We will use the GWAS results to guide association tests of aggregations of rare noncoding variants from sequence data. We will also use integrative computational methods – developed, tested and/or refined using height – to interpret the association results for obesity. We will use expression, metabolite, epigenetic, and other genomic data to prioritize genes, gene sets, regulatory elements and metabolites as likely causal contributors to obesity
ASTRA - Tartu Ülikooli ASTRA projekt PER ASPERA
November 2016 – August 2022
Andres Metspalu, Maris Väli-Täht, Allen Kaasik
The project focusses on strengthening the core laboratories of University of Tartu through further development and modernization of equipment base and furnishing possible laboratory workspaces for cooperation opportunities with businesses.
The wider aim of the project is to develop uniform competence centre on the basis of existing core laboratories, which would ensure the sustainable development of existing technologies. The action therefore unites upgrading of infrastructure, databases and development of operational competence. The ultimate goal is to provide the highest level of know-how for businesses and health care sectors.
DocuMental - digital support system for mental health
01.03.2017 – 30.11.2017
Connected Health Cluster
The project will develop a documental electronic support system, which is a decision-making support system for mental health diagnosis and treatment services. The support system will help reduce medical errors, improve mental health management, reduce the time spent by the specialist for initial assessment of condition and to improve the correct implementation of clinical guidelines in clinical practice. The support system also allows to raise the quality of the patient consultation and the time spent. The system will help to improve the patient's involvement in the treatment process, enabling a better exchange of information between the patient and the medical team and allowing the patient to monitor their treatment plan, and psychiatric status.
ESKO - PUT1660 - Utilizing special human populations to quantify the impact of rare DNA sequence variants in human health
Eesti Genoomikakeskus II /Estonian Center of Genomics/Roadmap II (project No. 2014-2020.4.01.16-0125)
Andres Metspalu, Maris Alver
JJ Pilot (VP1GV16402) - Pilot study to obtain an overview of available genotypic and phenotypic information in the biobank database
in collaboration with Janssen Research & Development LLC
The feasibility study will provide a report on data availability and technical requirements for three main objectives: 1) characterize genetic variations associated with Diabetes Mellitus Type 1 (T1D) in the Estonian GeneBank population 2) identify and characterize individuals with or at -risk of T1D; 3) evaluate feasibility of recruiting their siblings and children in potential observatonal or interventional study.