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Abstract: FR-PO120

Genome-Wide Association Study for AKI in the ASSESS-AKI Study

Session Information

Category: Acute Kidney Injury

  • 103 AKI: Mechanisms

Authors

  • Bhatraju, Pavan K., University of Washington, Seattle, Washington, United States
  • Akilesh, Shreeram, University of Washington, Seattle, Washington, United States
  • Hsu, Chi-yuan, University of California San Francisco, San Francisco, California, United States
  • Liu, Kathleen D., University of California at San Francisco School of Medicine, San Francisco, California, United States
  • Garg, Amit X., London Health Sciences Centre, London, Ontario, Canada
  • Kaufman, James S., VA New York Harbor Healthcare System, New York, New York, United States
  • Kimmel, Paul L., National Institute of Diabetes and Digestive Kidney Diseases (NIDDK), Bethesda, Maryland, United States
  • Go, Alan S., Kaiser Permanente Northern California, Oakland, California, United States
  • Parikh, Chirag R., Johns Hopkins University, Baltimore, Maryland, United States
  • Ikizler, Talat Alp, Vanderbilt University Medical Center, Nashville, Tennessee, United States
  • Himmelfarb, Jonathan, Kidney Research Institute, Seattle, Washington, United States
  • Wurfel, Mark M., University of Washington, Seattle, Washington, United States
  • Schaub, Jennifer A., University of Michigan, Ann Arbor, Michigan, United States

Group or Team Name

  • ASSESS-AKI
Background

Identifying genetic risk factors for AKI could provide insights into pathophysiology and help identify novel pathways for therapeutic development.

Methods

We conducted a genome-wide association study in a multi-ethnic population of 1,370 prospectively enrolled subjects in the ASSESS-AKI Study. Genotyping was completed using the Illumina MEGA chip and the Haplotype Reference Consortium was used for genome-wide multiple imputation. Genetic association testing for AKI was conditioned on: age, sex, diabetes, center and first three principal components of ancestry. Threshold for significance included single-nucleotide polymorphisms (SNPs) with a p < 5 X 10 -6.

Results

Among 637 AKI and 733 non-AKI participants, 5,645,675 SNPs were tested for the association with AKI. Among AKI participants, 72% had Stage 1 AKI and 7% required new dialysis during hospitalization. We found that 56 SNPs in six novel loci were associated with the development of AKI (Figure 1). The SNP with the strongest association with AKI was rs17538288>A. The minor allele of rs17538288 was associated with an increased risk for AKI (adjusted odds ratio 1.53, 95% confidence interval 1.30 – 1.79, p=2.08 x 10-7). Utilizing integrated functional epigenomic analyses, we found that top-performing SNPs localized to regulatory DNA elements in primary human glomerular and cortex cell culture. We also investigated 22 SNPs identified in two prior AKI GWAS studies and found that none of the SNPs replicated in ASSESS-AKI (p<0.05).

Conclusion

We identified six novel genetic loci that were associated with prevalent AKI. Functional annotation in kidney cells/tissue provides insights into the mechanism of kidney injury. Future work will require replication in well-phenotyped AKI cohorts and mechanistic studies to understand the relationship of genetic variation and AKI development.

Funding

  • NIDDK Support