Renal compartment–specific genetic variation analyses identify new pathways in chronic kidney disease

Chengxiang Qiu, Shizheng Huang, Jihwan Park, Yo Son Park, Yi An Ko, Matthew J. Seasock, Joshua S. Bryer, Xiang Xi Xu, Wen Chao Song, Matthew Palmer, Jon Hill, Paolo Guarnieri, Julie Hawkins, Carine M. Boustany-Kari, Steven S. Pullen, Christopher D. Brown, Katalin Susztak

Research output: Contribution to journalArticle

38 Scopus citations

Abstract

Chronic kidney disease (CKD), a condition in which the kidneys are unable to clear waste products, affects 700 million people globally. Genome-wide association studies (GWASs) have identified sequence variants for CKD; however, the biological basis of these GWAS results remains poorly understood. To address this issue, we created an expression quantitative trait loci (eQTL) atlas for the glomerular and tubular compartments of the human kidney. Through integrating the CKD GWAS with eQTL, single-cell RNA sequencing and regulatory region maps, we identified novel genes for CKD. Putative causal genes were enriched for proximal tubule expression and endolysosomal function, where DAB2, an adaptor protein in the TGF-β pathway, formed a central node. Functional experiments confirmed that reducing Dab2 expression in renal tubules protected mice from CKD. In conclusion, compartment-specific eQTL analysis is an important avenue for the identification of novel genes and cellular pathways involved in CKD development and thus potential new opportunities for its treatment.

Original languageEnglish (US)
Pages (from-to)1721-1731
Number of pages11
JournalNature medicine
Volume24
Issue number11
DOIs
StatePublished - Nov 1 2018

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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    Qiu, C., Huang, S., Park, J., Park, Y. S., Ko, Y. A., Seasock, M. J., Bryer, J. S., Xu, X. X., Song, W. C., Palmer, M., Hill, J., Guarnieri, P., Hawkins, J., Boustany-Kari, C. M., Pullen, S. S., Brown, C. D., & Susztak, K. (2018). Renal compartment–specific genetic variation analyses identify new pathways in chronic kidney disease. Nature medicine, 24(11), 1721-1731. https://doi.org/10.1038/s41591-018-0194-4