Comparative analysis of tools to predict rapid progression in autosomal dominant polycystic kidney disease

Background

Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic kidney disease and shows a wide phenotype. Only patients with rapid progression (RP) are included in clinical trials or are approved to receive disease-modifying drugs. This study aims at comparing different available predictive tools in ADPKD with the Mayo classification (MC) identification of rapid progressors based on high total kidney volume (TKV) according to age.

Methods

A total of 164 ADPKD patients were recruited retrospectively from a single centre. The performance of diverse tools to identify RP defined as being in MC categories 1C–1E was assessed.

Results

A total of 118 patients were MC 1C–1E. The algorithm developed by the European Renal Association–European Dialysis and Transplant Association Working Group on Inherited Kidney Disorders/European Renal Best Practice had a low sensitivity in identifying MC 1C–1E. The sensitivity and specificity of TKV to predict RP depend on the cut-off used. A kidney length of >16.5 cm before age 45 years has high specificity but low sensitivity. Assessing the MC by ultrasonography had high levels of agreement with magnetic resonance imaging (MRI) data, especially for 1A, 1D and 1E. The estimated glomerular filtration rate (eGFR) decline was very sensitive but had low specificity. In contrast, the Predicting Renal Outcome in Polycystic Kidney Disease (PROPKD) score was very specific but had poor sensitivity. Having hypertension before 35 years of age is a good clinical predictor of MC 1C–1E. Family history can be of help in suggesting RP, but by itself it lacks sufficient sensitivity and specificity.

Conclusions

The MC by ultrasonography could be an option in hospitals with limited access to MRI as it performs well generally, and especially at the extremes of the MC, i.e. classes 1A, 1D and 1E. The eGFR decline is sensitive but not very specific when compared with the MC, whereas the PROPKD score is very specific but has low sensitivity. Integrating the different tools currently available to determine RP should facilitate the identification of rapid progressors among patients with ADPKD.

Cost-effective PKHD1 genetic testing for autosomal recessive polycystic kidney disease

BACKGROUND

Genetic diagnosis of autosomal recessive polycystic kidney disease (ARPKD) is challenging due to the length and allelic heterogeneity of the PKHD1 gene. Mutations appear to be clustered at specific exons, depending on the geographic origin of the patient. We aimed to identify the PKHD1 exons most likely mutated in Spanish ARPKD patients.

METHODS

Mutation analysis was performed in 50 ARPKD probands and nine ARPKD-suspicious patients by sequencing PKHD1 exons arranged by their reported mutation frequency. Haplotypes containing the most frequent mutations were analyzed. Other PKD genes (HNF1B, PKD1, PKD2) were sequenced in PKHD1-negative cases.

RESULTS

Thirty-six different mutations (concentrated in 24 PKHD1 exons) were detected, giving a mutation detection rate of 86%. The screening of five exons (58, 32, 34, 36, 37) yielded a 54% chance of detecting one mutation; the screening of nine additional exons (3, 9, 39, 61, 5, 22, 26, 41, 57) increased the chance to 76%. The c.9689delA mutation was present in 17 (34%) patients, all of whom shared the same haplotype. Two HNF1B mutations and one PKD1 variant were detected in negative cases.

CONCLUSIONS

Establishing a PKHD1 exon mutation profile in a specific population and starting the analysis with the most likely mutated exons might significantly enhance the efficacy of genetic testing in ARPKD. Analysis of other PKD genes might be considered, especially in suspicious cases.