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

Research output: Contribution to journalArticle

  • External authors:
  • Xiaoguang Xu
  • Artur Akbarov
  • Lorenz Becker
  • Fehzan Ashraf
  • Jabran Nawaz
  • Sanjeev Pramanik
  • Xiao Jiang
  • John Dormer
  • Matthew Denniff
  • A Antczak
  • Monika Sszulinska
  • Ingrid Wise
  • Priscilla R Prestes
  • Maciej Glyda
  • Pawel Bogdanski
  • Ewa Zukowska-Szczechowska
  • Carlo Berzuini
  • Nilesh Samani
  • Fadi J. Charchar

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.

Bibliographical metadata

Original languageEnglish
JournalNature Communications
Volume9
Early online date22 Nov 2018
DOIs
StatePublished - 2018