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Kidney Week

Abstract: TH-OR084

Transethnic Genome-Wide Association Studies of Kidney Function Measures Identify Associations at >300 Genomic Loci

Session Information

Category: CKD (Non-Dialysis)

  • 1901 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Author

  • Wuttke, Matthias, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany

Group or Team Name

  • CKDGen Consortium
Background

Chronic kidney disease (CKD) affects 10% of the adult population globally. Reduced estimated glomerular filtration rate (eGFR) is the primary measure used to define CKD. Although previous[MW1] genetic studies have revealed many loci associated with eGFR, most of the genetic variation is still unexplained. The CKDGen Consortium is an international collaborative effort aimed at identifying the genetic underpinnings of renal health.

Methods

In an ongoing effort, 121 studies totaling >750,000 participants from five different ethnicities contributed genome-wide association summary statistics relating log-transformed creatinine-based eGFR (CKD-EPI formula) to ~9 million high-quality 1KGP- or HRC-imputed genetic markers, using an additive genetic model adjusted for sex and age. Summary statistics were combined using fixed-effects inverse variance-weighted meta-analysis.

Results

Across ethnicities, 308 genomic loci (1 Mb-segments, MHC region joined) contained at least one significantly eGFR-associated SNP (p<5E-08). The LD score regression intercept was 1.04, suggesting no residual inflation of the test-statistics. Of the 308 loci, 228 were novel (mapping outside of 500 kb of previously reported index variants), and 80 were consistent with previous findings. Loci were characterized by their association with blood urea nitrogen and CKD, by tissue-specific enrichment of expressed genes, as well as by their heterogeneity correlated with ancestry.
Approximate conditional meta-analysis among European-ancestry individuals identified 277 independent trait-associated variants, which together explained 7.6% of the phenotypic variance, almost doubling previous estimates. We fine-mapped 212 non-overlapping regions, of which 46 contained >1 independent SNPs. Credible sets with 99% probability for including a causal variant consisted of 7-74 SNPs (IQR). There were 20 single-SNP sets; for example, rs881858 (close to VEGFA) maps to open chromatin and represents a CTCF binding site.

Conclusion

Ongoing analyses include gene expression, tissue enrichment and network analyses of gene expression, and functional follow-up studies. These results of the largest genetic screen of kidney function to date will enhance the understanding of the biologic mechanisms of this trait.