Kidney Week

Abstract: TH-PO715

Genetic Analysis and Genotype-Phenotype Studies of a Cystinuria Cohort

Session Information

• Genetic Diseases of the Kidneys: Non-Cystic - I
  October 25, 2018 | Location: Exhibit Hall, San Diego Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Genetic Diseases of the Kidney

• 1002 Genetic Diseases of the Kidney: Non-Cystic

Authors

• Cogal, Andrea G., Mayo Clinic , Rochester, Minnesota, United States

Andrea G. Cogal,

• Senum, Sarah R., Mayo Clinic , Rochester, Minnesota, United States

Sarah R. Senum,

• Mehta, Ramila A., Mayo Clinic , Rochester, Minnesota, United States

Ramila A. Mehta,

• Modersitzki, Frank, New York University School of Medicine, New York, New York, United States

Frank Modersitzki,

• Lieske, John C., Mayo Clinic , Rochester, Minnesota, United States

John C. Lieske,

• Goldfarb, David S., NYU Langone, New York, New York, United States

David S. Goldfarb,

• Harris, Peter C., Mayo Clinic , Rochester, Minnesota, United States

Peter C. Harris,

Group or Team Name

• Rare Kidney Stone Consortium (RKSC)

Background

Cystinuria is an inherited kidney stone disorder caused by mutations to the SLC3A1 and SLC7A9 genes. While most cases are due to biallelic mutations to either gene, monoallelic and digenic families have been described, with overall considerable disease variability. Nevertheless, clear genotype/phenotype correlations have not been described to date.

Methods

A next generation sequencing (NGS) panel consisting of 90 known and candidate kidney stone genes was developed and validated. A total of 49 unrelated, genetically unscreened individuals with a clinical diagnosis of cystinuria were analyzed using this panel. Preliminary correlations with phenotype were made with the genic groups.

Results

The baseline mean (SD) characteristics of the cohort were: age at diagnosis = 19.6y (12.5), number of stones = 5.8 (6.6), cystine excretion = 939.9mg (323.6), eGFR = 82.1ml/min/1.73m² (24.5), with age at last follow up = 43.8y (14). A total of 34 patients (69.4%) had biallelic SLC3A1 and 11 (22.4%) biallelic SLC7A9 mutations. One SLC3A1 and two SLC7A9 cases had a single detected mutation, and one case had no mutations detected. Large rearrangements, detected by LOG2 ratio analysis of the sequence data and confirmed by Multiplex Ligation-dependent Probe Amplification (MLPA), accounted for 31.9% of all SLC3A1 mutations, mainly the common ex5-9 duplication. Other common mutations were the SLC3A1 missense change p.Met467Thr (21.7% alleles) and the nonsense mutation p.Arg270* (18.8%), while for SLC7A9 the missense mutation p.Gly105Arg accounted for 29.2% of pathogenic alleles. Ten novel mutations were identified for each gene. The only detected correlation with genotype was with baseline mean stone number, SLC3A1 = 7.1 (7.1), SLC7A9 = 2.0 (2.1; p=0.05) in this cohort.

Conclusion

This analysis shows the utility of a panel-based NGS approach in cystinuria populations and more broadly in patients with suspected monogenic stone disease. Other genetic and/or environmental factors likely also contribute to the observed phenotypic variability.

Funding

• NIDDK Support