Kidney Week

Abstract: FR-OR071

GWAS of Urinary Metabolite Concentrations among CKD Patients Identify 90 Loci

Session Information

• Genetics and Kidney Diseases: Beyond PKD
  October 26, 2018 | Location: 33C, San Diego Convention Center
  Abstract Time: 05:06 PM - 05:18 PM

Category: Genetic Diseases of the Kidney

• 1002 Genetic Diseases of the Kidney: Non-Cystic

Authors

• Kottgen, Anna, Medical Center - University of Freiburg, Freiburg, Germany

Anna Kottgen, MD, MPH

Dr. Kottgen is a Professor and Head of the Institute of Genetic Epidemiology at Freiburg University, Germany, as well as an Adjunct Professor of Epidemiology at the Johns Hopkins Bloomberg School of Public Health. She is interested in using genetics as a tool to gain insights into kidney function and human metabolism in health and disease. She co-directs the international CKDGen Consortium.

• Sekula, Peggy, Medical Center - University of Freiburg, Freiburg, Germany

Peggy Sekula,

• Mohney, Robert P., Metabolon, Inc. , Durham, North Carolina, United States

Robert P. Mohney,

• Kronenberg, Florian, Innsbruck Medical University, Innsbruck, Tirol, Austria

Florian Kronenberg,

• Eckardt, Kai-Uwe, University Medicine-Charite, Berlin, Germany

Kai-Uwe Eckardt,

• Schlosser, Pascal, Medical Center and Faculty of Medicine, University Freiburg, Germany, Freiburg, Germany

Pascal Schlosser,

Background

The kidneys play a central role in metabolite handling. Genetic studies of metabolite concentrations can identify proteins performing these functions. Reduced GFR may represent a challenge model for metabolite handling, facilitating the identification of such loci.

Methods

We carried out GWAS of the urinary concentrations of 1,172 metabolites among 1,221 European ancestry GCKD study participants with eGFR of 30-45 ml/min/1.73m² and UACR <30 mg/g, with further replication among 406 individuals. Dilution-corrected urinary metabolite concentrations were related to HRC-imputed genome-wide genotypes of minor allele frequency >1%, using an additive genetic model and multivariable adjustment. Statistical significance was defined as p<4.3e-11 (5e-8/1172) in a meta-analysis of discovery and replication, with concordant effect sizes.

Results

After correction for multiple testing, there were 246 genome-wide significant associations for 211 metabolites, distributed across 90 independent loci. These included previously identified loci in screens of urine (n=15) and blood (n=55) metabolite concentrations in the general population, and 20 novel loci. Associations between lead SNPs and urinary metabolite concentrations were strong, with p-values as low as <1e-550. Compared to associations of the same genetic variants and urinary metabolites in a healthy population, effects were significantly stronger among CKD patients on average (p<2e-16). The number of metabolites associated with a locus' lead variant ranged up to 30 for missense rs13538 in NAT8, consistent with the function of N-acetyl-transferase in detoxification reactions. Relating genome-wide genotypes to modeled relationships between metabolites (pairwise ratios, clusters) resulted in additional insights such as the identification of candidate substrates for renal transport proteins, a functional readout of renal enzymes, detoxification reactions of drugs commonly prescribed among CKD patients, and facilitated the de-orphanization of SNP-associated metabolites of previously unknown identity.

Conclusion

Our study increases the number of loci associated with urinary metabolite concentrations from 26 to 90, highlights the value of studying genetics of renal metabolism among CKD patients, and provides many novel insights into human renal (patho)physiology.

Funding

• Private Foundation Support