Principal Investigator: Dr. Alexander Teumer
Department: University of Greifswald, Institute for Community Medicine, Walther-Rathenau-Str. 48,Greifswald, MV 17475, Germany
1) Dr Christian Fuchsberger
2) Dr Mathias Gorski
3) Dr Yong Li
Collaborating Institutions and Addresses:
1) European Academy of Bolzano/Bozen, Center for Biomedicine, Via Galvani 31, Bolzano, 39100, Italy
2) University of Regensburg, Department of Genetic Epidemiology, Franz-Joseph-Strauss-Allee 11, Regensburg, 91053, Germany
3) University Hospital Freiburg, Medical Biometry and Statistics, Berliner Allee 29, Freiburg, 79110, GermanyTags: 20272, albuminuria, CKD, eGFR, GWAS, kidney
1a: Chronic kidney disease (CKD) is a major health issue associated with cardiovascular outcomes. To expand the knowledge of its biological basis, large-scale meta-analyses of genome-wide association studies (GWAS) of renal function have already been conducted, but much unexplained heritability remains. The aim of the proposed research is to carry out GWAS of kidney function related traits and kidney disease, and to characterize known genetic risk loci in a large sample size for context-specific effects. We aim to analyze the UKBB data by itself and meta-analyze it with data from other cohorts and the CKDGen Consortium.
1b: CKD is a major health issue affecting >10% of adults in many countries worldwide. By finding genetic susceptibility loci we will increase our knowledge of biological and functional pathways underlying impaired kidney function. This knowledge will eventually support the improvement of the prevention, diagnosis and treatment of kidney diseases.
1c: We will check genetic markers across the whole human genome for association with kidney function measures estimated based on serum creatinine and urinary albumin-to-creatinine ratio, kidney disease, and decline of renal function over time. By revealing associated genetic loci and genes, we will obtain insight into the biological functions that may cause kidney diseases. This knowledge will eventually help to improve the prevention of the disease, and the design and development of drugs for the condition.
1d: Full cohort with available genetic data (imputed Axiom Genotyping Array data)
We would like to extend our application to also investigate traits and diseases (including serum and urine biomarkers) that are either influencing or are influenced by kidney function (e.g. the metabolome and thyroid function and other endocrine traits such as glycemic parameters). Even in case the specific traits are not (yet) available in the UK Biobank, we like to use the already available information to complement analyses on these traits and diseases when summary statistics are derived in other studies, i.e. by building a linkage-disequilibrium reference panel for finemapping of genetic associations using summary statistics or by integrating genotype-endpoint associations in the UKBB with kidney-function related loci identified in other settings.
Last updated Jun 10, 2019