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Abstract: TH-OR34

The Genetic and Clinical Spectrum of Tubulointerstitial Kidney Disease and Associated Syndromes Revealed Through Whole-Genome Sequencing in the UK 100,000 Genomes Project

Session Information

Category: Genetic Diseases of the Kidneys

  • 1002 Genetic Diseases of the Kidneys: Non-Cystic

Authors

  • Leggatt, Gary, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, United Kingdom
  • Gast, Christine, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, United Kingdom
  • Gilbert, Rodney David, Southampton Children's Hospital, Southampton, Southampton, United Kingdom
  • Veighey, Kristin, University Hospital Southampton NHS Foundation Trust, Southampton, Southampton, United Kingdom
  • Ennis, Sarah, University of Southampton Faculty of Medicine, Southampton, Southampton, United Kingdom
Background

Tubulointerstitial kidney disease (TKD) is a heterogeneous group of monogenic disorders with progressive chronic kidney disease characterised by interstitial fibrosis, tubular atrophy and variable clinical manifestations. TKD includes recessive ciliopathies, autosomal dominant tubulointerstitial kidney diseases (ADTKD) and mitochondrial diseases. The Genomics England (GEL) project offered a unique opportunity to apply a novel discovery approach, synthesising the effect of common and rare variants using a whole-gene-based pathogenicity score (GenePy). This scoring system results in per gene-per person pathogenicity scores, with higher scores representing a higher mutational burden.

Methods

We applied the GenePy scoring system integrating patient zygosity, allele frequency, and deleteriousness metrics. We identified unrelated Europeans for a phenotype-genotype approach of 232 cases with TKD and 8,282 controls with no documented kidney phenotype. GenePy scores were generated for a discrete set of candidate genes for each individual. The highest decile GenePy scores were compared using a one-tailed Mann-Whitney U-test. We then took an unbiased genotype-phenotype approach by calculating GenePy scores for all 78,050 germline genomes. Individuals were ranked by gene score, and individuals with the highest scores were assessed for their phenotype.

Results

The difference in top decile scores between cases and the same proportion of controls was statistically significant for PKD2 (p=2.81x10-6), DNAJB11 (p=3.56x10-5), XPNPEP3 (p=0.0083), UMOD (p=0.0015) and CEP290 (p=0.034). Novel variants consistent with TKD were identified. The unbiased genotype-phenotype approach additionally revealed variants consistent with monogenic TKD in participants recruited for diverse reasons, including cancer.

Conclusion

Using a novel gene-level scoring system, we describe new gene variants associated with TKD and associated phenotypes. Patients were identified in non-kidney disease recruits demonstrating the benefit of an unbiased 'gene first' approach in large scale datasets such as the 100,000 Genomes Project.