Abstract: SA-PO408
Unraveling the Genetic Contributions to Kidney Disease with the Kidney Genome Atlas
Session Information
- Genetic Diseases of the Kidney - III
November 09, 2019 | Location: Exhibit Hall, Walter E. Washington Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Genetic Diseases of the Kidneys
- 1002 Genetic Diseases of the Kidneys: Non-Cystic
Authors
- Soare, Thomas, Goldfinch Bio, Cambridge, Massachusetts, United States
- Zhang, Wei, Goldfinch Bio, Cambridge, Massachusetts, United States
- Tebbe, Adam, Goldfinch Bio, Cambridge, Massachusetts, United States
- Mandal, Vinay, Goldfinch Bio, Cambridge, Massachusetts, United States
- Borges, Diego, Goldfinch Bio, Cambridge, Massachusetts, United States
- Chennagiri, Niru, Goldfinch Bio, Cambridge, Massachusetts, United States
- Kretzler, Matthias, U.Michigan, Ann Arbor, Michigan, United States
- Nadkarni, Girish N., Ichan School of Medicine, New York, New York, United States
- Gbadegesin, Rasheed A., Duke University Medical Center, Durham, North Carolina, United States
- Wenke, Jamie L., Nashville Biosciences, Nashville, Tennessee, United States
- Macarthur, Daniel G., Broad Institute, Cambridge, Massachusetts, United States
- Reilly, John F., Goldfinch Bio, Cambridge, Massachusetts, United States
- Mundel, Peter H., Goldfinch Bio, Cambridge, Massachusetts, United States
- Walsh, Liron, Goldfinch Bio, Cambridge, Massachusetts, United States
- Tibbitts, Thomas T., Goldfinch Bio, Cambridge, Massachusetts, United States
Background
Focal segmental glomerulosclerosis (FSGS) is a progressive kidney disorder with limited treatment options. To discover novel drug targets for FSGS, we built the Kidney Genome Atlas (KGA), which currently contains whole-genome sequences (>30X) on 23000 individuals, including 3000 cases of FSGS, other proteinuric disorders, and diabetic nephropathy. Each patient genome is linked to longitudinal clinical records, and for a subset of 400 patients the KGA also includes matched transcriptomes from microdissected glomerular and tubulointerstitial samples. Our aim was to elucidate mechanisms of disease through genome-wide association studies (GWAS) of (1) disease severity in cases, (2) case-control status, and (3) gene expression in cases.
Methods
To measure disease severity, we calculated a combined Z-score based on age at presentation and eGFR slope, which was estimated using a Bayesian hierarchical linear model on 1797 patients with at least 3 eGFR measurements. Then we conducted an association study on this continuous phenotype with the burden of likely deleterious variants at the gene level. Additionally, we conducted a GWAS on case-control status and an expression quantitative trait loci (eQTL) analysis on a subset of 300 patients with transcriptomic data.
Results
As proof of principle, among all cases we found that two copies of APOL1 risk alleles were associated with earlier age at presentation (p=5e-6) and more rapid decline in eGFR slope (p=1e-2), and most strongly associated with the combined Z-score of age at presentation and eGFR slope (p=2e-8). A preliminary association test of the combined Z-score with variant burden in each of 15765 protein-coding genes showed one genome-wide significant association (FDR=0.01). A preliminary GWAS in AFR ancestry cases and controls (n=904) showed minimal impact of potential confounders, such as ancestry or sequencing batch differences (lambda=1.03). A preliminary eQTL analysis revealed 3562 genes had eQTLs in either microdissected glomeruli or tubules.
Conclusion
Integrating longitudinal clinical data, whole genome sequences, and transcriptomes from microdissected tissues is a promising approach to unraveling the molecular mechanisms of kidney diseases.
Funding
- NIDDK Support –