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Mapping eGFR loci to the renal transcriptome and phenome in the VA Million Veteran Program

Author

Listed:
  • Jacklyn N. Hellwege

    (Tennessee Valley Healthcare System (626)/Vanderbilt University
    Vanderbilt University Medical Center)

  • Digna R. Velez Edwards

    (Tennessee Valley Healthcare System (626)/Vanderbilt University
    Vanderbilt University Medical Center
    Vanderbilt University Medical Center)

  • Ayush Giri

    (Tennessee Valley Healthcare System (626)/Vanderbilt University
    Vanderbilt University Medical Center)

  • Chengxiang Qiu

    (University of Pennsylvania)

  • Jihwan Park

    (University of Pennsylvania)

  • Eric S. Torstenson

    (Tennessee Valley Healthcare System (626)/Vanderbilt University
    Vanderbilt University Medical Center)

  • Jacob M. Keaton

    (Tennessee Valley Healthcare System (626)/Vanderbilt University
    Vanderbilt University Medical Center)

  • O. D. Wilson

    (Vanderbilt University Medical Center)

  • Cassianne Robinson-Cohen

    (Vanderbilt University Medical Center)

  • Cecilia P. Chung

    (Tennessee Valley Healthcare System (626)/Vanderbilt University
    Vanderbilt University Medical Center)

  • Christianne L. Roumie

    (Veteran Affairs Administration Tennessee Valley VA Health Care System Geriatric Research Education Clinical Center (GRECC)
    Vanderbilt University Medical Center)

  • Derek Klarin

    (VA Boston Health Care System
    Harvard Medical School
    Broad Institute of Harvard and MIT
    Harvard Medical School)

  • Scott M. Damrauer

    (Corporal Michael Crescenz VA Medical Center
    University of Pennsylvania)

  • Scott L. DuVall

    (VA Salt Lake City Health Care System
    University of Utah School of Medicine)

  • Edward Siew

    (Vanderbilt University Medical Center)

  • Elvis A. Akwo

    (Vanderbilt University Medical Center)

  • Matthias Wuttke

    (Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Centre—University of Freiburg)

  • Mathias Gorski

    (University of Regensburg
    University Hospital Regensburg)

  • Man Li

    (VA Boston Health Care System
    University of Utah School of Medicine)

  • Yong Li

    (Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Centre—University of Freiburg)

  • J. Michael Gaziano

    (Broad Institute of Harvard and MIT
    Harvard Medical School
    VA Boston Healthcare System)

  • Peter W. F. Wilson

    (Atlanta VA Medical Center
    Emory Clinical Cardiovascular Research Institute)

  • Philip S. Tsao

    (VA Palo Alto Health Care System
    Department of Medicine, Stanford University School of Medicine)

  • Christopher J. O’Donnell

    (VA Boston Health Care System
    Harvard Medical School)

  • Csaba P. Kovesdy

    (Memphis VA Medical Center
    University of Tennessee Health Science Center)

  • Cristian Pattaro

    (Eurac Research)

  • Anna Köttgen

    (Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Centre—University of Freiburg
    Johns Hopkins Bloomberg School of Public Health)

  • Katalin Susztak

    (University of Pennsylvania)

  • Todd L. Edwards

    (Tennessee Valley Healthcare System (626)/Vanderbilt University
    Vanderbilt University Medical Center)

  • Adriana M. Hung

    (Tennessee Valley Healthcare System (626)/Vanderbilt University
    Vanderbilt University Medical Center)

Abstract

Chronic kidney disease (CKD), defined by low estimated glomerular filtration rate (eGFR), contributes to global morbidity and mortality. Here we conduct a transethnic Genome-Wide Association Study of eGFR in 280,722 participants of the Million Veteran Program (MVP), with replication in 765,289 participants from the Chronic Kidney Disease Genetics (CKDGen) Consortium. We identify 82 previously unreported variants, confirm 54 loci, and report interesting findings including association of the sickle cell allele of betaglobin among non-Hispanic blacks. Our transcriptome-wide association study of kidney function in healthy kidney tissue identifies 36 previously unreported and nine known genes, and maps gene expression to renal cell types. In a Phenome-Wide Association Study in 192,868 MVP participants using a weighted genetic score we detect associations with CKD stages and complications and kidney stones. This investigation reinterprets the genetic architecture of kidney function to identify the gene, tissue, and anatomical context of renal homeostasis and the clinical consequences of dysregulation.

Suggested Citation

  • Jacklyn N. Hellwege & Digna R. Velez Edwards & Ayush Giri & Chengxiang Qiu & Jihwan Park & Eric S. Torstenson & Jacob M. Keaton & O. D. Wilson & Cassianne Robinson-Cohen & Cecilia P. Chung & Christian, 2019. "Mapping eGFR loci to the renal transcriptome and phenome in the VA Million Veteran Program," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11704-w
    DOI: 10.1038/s41467-019-11704-w
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    Cited by:

    1. Xiujie Liang & Hongbo Liu & Hailong Hu & Eunji Ha & Jianfu Zhou & Amin Abedini & Andrea Sanchez-Navarro & Konstantin A. Klötzer & Katalin Susztak, 2024. "TET2 germline variants promote kidney disease by impairing DNA repair and activating cytosolic nucleotide sensors," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    2. Parker C. Wilson & Yoshiharu Muto & Haojia Wu & Anil Karihaloo & Sushrut S. Waikar & Benjamin D. Humphreys, 2022. "Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression," Nature Communications, Nature, vol. 13(1), pages 1-20, December.

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