Nature Communications (Mar 2024)

Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets

  • 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,
  • Priscilla R. Prestes,
  • Jeniece Regan,
  • Avantika R. Diwadkar,
  • Matthew Denniff,
  • Grzegorz Rempega,
  • Jakub Ryszawy,
  • Robert Król,
  • John P. Dormer,
  • Monika Szulinska,
  • Marta Walczak,
  • Andrzej Antczak,
  • Pamela R. Matías-García,
  • Melanie Waldenberger,
  • Adrian S. Woolf,
  • Bernard Keavney,
  • Ewa Zukowska-Szczechowska,
  • Wojciech Wystrychowski,
  • Joanna Zywiec,
  • Pawel Bogdanski,
  • A. H. Jan Danser,
  • Nilesh J. Samani,
  • Tomasz J. Guzik,
  • Andrew P. Morris,
  • Dajiang J. Liu,
  • Fadi J. Charchar,
  • Human Kidney Tissue Resource Study Group,
  • Maciej Tomaszewski

DOI
https://doi.org/10.1038/s41467-024-46132-y
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 29

Abstract

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Abstract Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.