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

Author

Listed:
  • Xiaoguang Xu

    (University of Manchester)

  • James M. Eales

    (University of Manchester)

  • Artur Akbarov

    (University of Manchester)

  • Hui Guo

    (University of Manchester)

  • Lorenz Becker

    (University of Manchester)

  • David Talavera

    (University of Manchester)

  • Fehzan Ashraf

    (University of Manchester)

  • Jabran Nawaz

    (University of Manchester)

  • Sanjeev Pramanik

    (University of Manchester)

  • John Bowes

    (University of Manchester)

  • Xiao Jiang

    (University of Manchester)

  • John Dormer

    (University Hospitals of Leicester NHS Trust)

  • Matthew Denniff

    (University of Leicester)

  • Andrzej Antczak

    (Karol Marcinkowski University of Medical Sciences)

  • Monika Szulinska

    (Karol Marcinkowski University of Medical Sciences)

  • Ingrid Wise

    (Federation University Australia)

  • Priscilla R. Prestes

    (Federation University Australia)

  • Maciej Glyda

    (University of Zielona Góra)

  • Pawel Bogdanski

    (Karol Marcinkowski University of Medical Sciences)

  • Ewa Zukowska-Szczechowska

    (Silesian Medical College)

  • Carlo Berzuini

    (University of Manchester)

  • Adrian S. Woolf

    (Manchester University NHS Foundation Trust)

  • Nilesh J. Samani

    (University of Leicester
    Glenfield Hospital)

  • Fadi J. Charchar

    (University of Leicester
    Federation University Australia
    University of Melbourne)

  • Maciej Tomaszewski

    (University of Manchester
    Manchester Academic Health Science Centre)

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.

Suggested Citation

  • Xiaoguang Xu & James M. Eales & Artur Akbarov & Hui Guo & Lorenz Becker & David Talavera & Fehzan Ashraf & Jabran Nawaz & Sanjeev Pramanik & John Bowes & Xiao Jiang & John Dormer & Matthew Denniff & A, 2018. "Molecular insights into genome-wide association studies of chronic kidney disease-defining traits," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-07260-4
    DOI: 10.1038/s41467-018-07260-4
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    Cited by:

    1. Alexandra Barry & Michelle T. McNulty & Xiaoyuan Jia & Yask Gupta & Hanna Debiec & Yang Luo & China Nagano & Tomoko Horinouchi & Seulgi Jung & Manuela Colucci & Dina F. Ahram & Adele Mitrotti & Aditi , 2023. "Multi-population genome-wide association study implicates immune and non-immune factors in pediatric steroid-sensitive nephrotic syndrome," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    2. Xiaoguang Xu & Chachrit Khunsriraksakul & James M. Eales & Sebastien Rubin & David Scannali & Sushant Saluja & David Talavera & Havell Markus & Lida Wang & Maciej Drzal & Akhlaq Maan & Abigail C. Lay , 2024. "Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets," Nature Communications, Nature, vol. 15(1), pages 1-29, December.

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