ASN's Mission

To create a world without kidney diseases, the ASN Alliance for Kidney Health elevates care by educating and informing, driving breakthroughs and innovation, and advocating for policies that create transformative changes in kidney medicine throughout the world.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005

email@asn-online.org

202-640-4660

The Latest on X

Kidney Week

ASN / Education & Meetings / Kidney Week /

Please note that you are viewing an archived section from 2021 and some content may be unavailable. To unlock all content for 2021, please visit the archives.

Abstract: TH-OR31

Deconvolution of Genetic Variation Using High-Quality Cis-Regulatory Elements Map of Kidney Cells

Session Information

Category: Genetic Diseases of the Kidneys

  • 1002 Genetic Diseases of the Kidneys: Non-Cystic

Authors

  • Han, Seong Kyu, Boston Children's Hospital, Boston, Massachusetts, United States
  • Muto, Yoshiharu, Washington University in St Louis, St Louis, Missouri, United States
  • Wilson, Parker C., Washington University in St Louis, St Louis, Missouri, United States
  • Humphreys, Benjamin D., Washington University in St Louis, St Louis, Missouri, United States
  • Sampson, Matt G., Boston Children's Hospital, Boston, Massachusetts, United States
  • Lee, Dongwon, Boston Children's Hospital, Boston, Massachusetts, United States
Background

Genome-wide association studies (GWAS) have facilitated the discovery of disease- or trait-associated genetic variants that can ultimately lead to improved precision of clinical diagnosis and/or molecular pathogenesis in a translational medicine framework. However, identifying specific cell types within organs in which the GWAS variants exert their function remains a significant challenge, especially for the complex and heterogeneous kidney.

Methods

To tackle this, we constructed high-quality maps of cis-regulatory elements (CREs) for kidney cells to deconvolute GWAS variants for kidney-relevant phenotypes. Specifically, we devised a computational framework using a sequence-based predictive model that maximally detects CREs by identifying open-chromatin regions with marginal read-mappings but harboring CRE sequence features. We applied this method to kidney ATAC-seq data.

Results

Our high-quality CRE maps have enabled us to detect >100,000 CREs for podocytes, a key rare (<1%) cell type involved in kidney filtration function. Newly found CREs explained the significant proportion of SNP-heritability for a major kidney trait (Urinary Albumin-to-Creatinine Ratio (UACR); Pr[hg2]=9.3%). Heritability analysis using these CRE maps uncovered the differential contribution of specific cell types to two major kidney functional traits, UACR and estimated glomerular filtration rate (eGFR). As would be predicted from physiologic understanding, CREs for podocytes and proximal tubule cells (PT) had enriched proportion of SNP-heritability for UACR and eGFR, respectively (UACR: Pr[hg2]/Pr[SNPs]=6.8 for podocyte, 2.3 for PT; eGFR: Pr[hg2]/Pr[SNPs]=-1.9 for podocyte, 4.3 for PT. Moreover, we found the podocyte relevance of a known GWAS variant (rs17831251; OR=2.25, P=4.7×10−103) on PLA2R1 associated with Membranous Nephropathy. Our CRE map showed strong podocyte-unique CRE that overlaps with the index variant, suggesting that the index SNP is potentially the causal variant perturbing podocyte-specific transcriptional regulation of PLA2R1.

Conclusion

Taken together, we expect that the deconvolution of GWAS variants using the high-quality kidney CRE maps will provide cell-type relevance of GWAS variants on genetic effects not captured by single-cell RNA-seq alone.

Funding

  • NIDDK Support