Data from: Molecular insights into genome-wide association studies of chronic kidney disease-defining traits

Xiaoguang Xu, James M. Eales, Artur Akbarov, Hui Guo, Lorenz Becker, David Talavera, Fezhan Ashraf, Jabran Nawaz, Sanjeev Pramanik, John Bowes, Xiao Jiang, John Dormer, Matthew Denniff, Andrzej Antczak, Monika Szulinska, Ingrid Wise, Priscilla R. Prestes, Maciej Glyda, Pawel Bogdanski, Ewa Zukowska-Szczechowska, Carlo Berzuini, Adrian S. Woolf, Nilesh J. Samani, Fadi J. Charchar & Maciej Tomaszewski
Genome-wide association studies (GWAS) have identified >100 loci of chronic kidney disease-defining traits (CKD-dt). Molecular mechanisms underlying these associations remain elusive. Using 280 kidney transcriptomes and 9958 gene expression profiles from 44 non-renal tissues we uncover gene expression partners (eGenes) for 88.9% of CKD-dt GWAS loci. Through epigenomic chromatin segmentation analysis and variant effect prediction we annotate functional consequences to 74% of these loci. Our colocalisation analysis and Mendelian randomisation in >130,000 subjects demonstrate causal...
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