Entwicklung eines Workflows zur Kombination und Imputation von SNPs genotypisiert auf unterschiedlichen Array Plattformen
Zusammenfassung der Projektergebnisse
Genome-wide association studies (GWAS) represent an agnostic approach to screen for loci associated with complex traits and diseases by taking into account the genetic variation of single nucleotide polymorphisms (SNPs) or short insertions and deletions (INDELs). The basic principle behind a GWAS is a correlation test performed at a genome-wide level between the genotypes of a SNP (usually the abundance of a selected allele) and a continuous trait or a group having a disease. Combining individual-level data in genetic association studies (mega-analyses) increases statistical power for identifying genetic effects underlying diseases. Batch effects occurring when combining imputed genotypes of different array types are a major limitation. In our project, we developed methods for removing the array-specific batch effect while maximizing the imputation quality. In particular, we developed a two-step imputation workflow that does avoid any array-specific batch effects and can be applied to conduct subsequent GWAS mega-analysis. We tested this workflow in a GWAS using two cohorts of the Study of Health in Pomerania (SHIP), and revealed new susceptibility loci for thyroid volume and goiter. Although no major technical problems were encountered during this project, a substantial delay in the timeline was related due to the pandemic and a shortage in finding qualified young scientists within the field of genetic epidemiology or bioinformatics. All aims of the project could be successfully fulfilled, while the final publication is currently in preparation.
Projektbezogene Publikationen (Auswahl)
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Imputation-powered whole-exome analysis identifies genes associated with kidney function and disease in the UK Biobank. Nature Communications, 14(1).
Wuttke, Matthias; König, Eva; Katsara, Maria-Alexandra; Kirsten, Holger; Farahani, Saeed Khomeijani; Teumer, Alexander; Li, Yong; Lang, Martin; Göcmen, Burulca; Pattaro, Cristian; Günzel, Dorothee; Köttgen, Anna & Fuchsberger, Christian
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Mendelian randomization indicates causal effects of estradiol levels on kidney function in males. Frontiers in Endocrinology, 14.
Nasr, M. Kamal; Schurmann, Claudia; Böttinger, Erwin P. & Teumer, Alexander
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Removing array-specific batch effects in GWAS mega-analyses by applying a two-step imputation workflow. Bioinformatics Advances.
Nasr, M. Kamal; König, Eva; Fuchsberger, Christian; Ghasemi, Sahar; Völker, Uwe; Völzke, Henry; Grabe, Hans J. & Teumer, Alexander
