- Title
- Molecular insights into genome-wide association studies of chronic kidney disease-defining traits
- Creator
- Xu, Xiaoguang; Eales, James; Akbarov, Artur; Guo, Hui; Becker, Lorenz; Talavera, David; Ashraf, Fehzan; Nawaz, Jabran; Pramanik, Sanjeev; Bowes, John; Jiang, Xiao; Dormer, John; Denniff, Matthew; Antczak, Andrzej; Szulinska, Monika; Wise, Ingrid; Prestes, Priscilla; Glyda, Maciej; Bogdanski, Pawel; Zukowska-Szczechowska, Ewa; Berzuini, Carlo; Woolf, Adrian; Samani, Nilesh; Charchar, Fadi; Tomaszewski, Maciej
- Date
- 2018
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/166983
- Identifier
- vital:13555
- Identifier
-
https://doi.org/10.1038/s41467-018-07260-4
- Identifier
- ISBN:2041-1723
- Abstract
- 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.
- Publisher
- Nature Research
- Relation
- Nature communications Vol. 9, no. 1 (2018), p. 1-12
- Rights
- http://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright © 2018, The Author(s).
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- MD Multidisciplinary; Gene expression profiling; Single nucleotide polymorphism; Expression quantitative
- Full Text
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