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

Xiaoguang Xu, James Eales, Artur Akbarov, Hui Guo, Lorenz Becker, David Talavera, Fehzan Ashraf, Jabran Nawaz, Sanjeev Pramanik, John Bowes, Xiao Jiang, John Dormer, Matthew Denniff, A Antczak, Monika Sszulinska, Ingrid Wise, Priscilla R Prestes, Maciej Glyda, Pawel Bogdanski, Ewa Zukowska-SzczechowskaCarlo Berzuini, Adrian S. Woolf, Nilesh Samani, Fadi J. Charchar, Maciej Tomaszewski

Research output: Contribution to journalArticlepeer-review


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 effects of three eGenes (NAT8B, CASP9 and MUC1) on estimated glomerular filtration rate. We identify a common alternative splice variant in MUC1 (a gene responsible for rare Mendelian form of kidney disease) and observe increased renal expression of a specific MUC1 mRNA isoform as a plausible molecular mechanism of the GWAS association signal. These data highlight the variants and genes underpinning the associations uncovered in GWAS of CKD-dt.
Original languageEnglish
Article number4800
JournalNature Communications
Issue number1
Early online date22 Nov 2018
Publication statusPublished - 22 Nov 2018


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