A Low-Cost Sequencing Platform for Rapid Genotyping in ADPKD and its Impact on Clinical Care

Abstract

Introduction: Autosomal-dominant polycystic kidney disease (ADPKD) is the most common genetic cause of kidney failure. Because of the heterogeneity in disease progression in ADPKD, parameters predicting future outcome are important. The disease-causing genetic variant is one of these parameters.

Methods: A multiplex polymerase chain reaction (PCR)-based panel (MPP) was established for analysis of 6 polycystic kidney disease (PKD) genes (PKD1, PKD2, HNF1B, GANAB, DZIP1L, and PKHD1) in 441 patients with ADPKD. Selected patients were additionally sequenced using Sanger sequencing or a custom enrichment-based gene panel. Results were combined with clinical characteristics to assess the impact of genetic data on clinical decision-making. Variants of unclear significance (VUS) were considered diagnostic based on a classic ADPKD clinical phenotype.

Results: Using the MPP, disease-causing variants were detected in 65.3% of patients. Sanger sequencing and the custom gene panel in 32 patients who were MPP-negative revealed 20 variants missed by MPP, (estimated overall false negative rate 24.6%, false-positive rate 9.4%). Combining clinical and genetic data revealed that knowledge of the genotype could have impacted the treatment decision in 8.2% of patients with a molecular genetic diagnosis. Sequencing only the PKD1 pseudogene homologous region in MPP-negative patients resulted in an acceptable false-negative rate of 3.28%.

Conclusion: The MPP yields rapid genotype information at lower costs and allows for simple extension of the panel for new disease genes. Additional sequencing of the PKD1 pseudogene homologous region is required in negative cases. Access to genotype information even in settings with limited resources is important to allow for optimal patient counseling in ADPKD.

Keywords: ADPKD; CKD; PKD; Sanger sequencing; next generation sequencing.

Graphical abstract

Figure 1

Study design. A total of 441 clinically diagnosed patients with ADPKD were tested for genetic variants causing PKD using a new multiplex PCR-based panel containing 6 PKD genes. To test the performance, a subset of randomly selected patients was also tested using Sanger sequencing and/or a custom gene panel, consecutively. ADPKD, autosomal-dominant polycystic kidney disease; PKD, polycystic kidney disease.

Figure 2

Distribution of genetic variants detected using the multiplex PCR-based panel (MPP). (a) Pie and donut chart indicating the distribution of the variants detected in the ADPKD cohort using the MPP. The total number of patients for each variant are mentioned (GANAB VUS and HNF1B VUS: 1 patient each). In 91 patients identified as having a disease-causing variant that achieved at least a ACMG3 classification, this variant was also investigated by Sanger sequencing, and the results were confirmed in all but 2 cases. One of the 91 patients was additionally tested using the custom gene panel, confirming the result in this specific case. (b) 25 patients who did not show any findings using the MPP underwent Sanger sequencing to fill all gaps resulting from the MPP (sequencing of gaps only in 4 patients and of the entire PKD1 gene in 21 patients). (c) 10 patients with no findings in the MPP and one patient with a finding were screened using the custom gene panel containing 22 genes. (d) Pie and donut chart showing the distribution of variants detected in the ADPKD cohort using all available information from the MPP, Sanger sequencing and the custom gene panel. ADPKD, autosomal-dominant polycystic kidney disease; NMD, no mutation detected; PKD, polycystic kidney disease; VUS, variant of uncertain significance.

Figure 3

Genetic classification and clinical findings. (b) Stacked bar chart shows the distribution of patients in the ADPKD cohort with an ACMG class 3 or higher genetic variant and imaging relative to the different Mayo classes. The numbers in the columns indicate the absolute number of patients. (b) The 3 plots show log height adjusted TKV in relation to the age of each patient. Each plot shows all patients with a particular variant in color and all other patients in gray. The line in each graph represents a fitted linear model. (c) The 3 plots show eGFR in relation to the age of each patient. Each plot shows all patients with a particular variant in color and all other patients in gray. The line in each graph represents a fitted linear model. (d) The stacked bar chart shows the distribution of arterial hypertension, urologic symptoms, or both among patients in the ADPKD cohort with an ACMG class 3 or higher genetic variant, imaging, and age 35 years or older. Arterial hypertension or urologic symptoms are counted only if onset was before age 35 years. The numbers in the columns indicate the absolute number of patients. AH, arterial hypertension; eGFR, estimated glomerular filtration rate; HtTKV, height adjusted total kidney volume; PKD, polycystic kidney disease; PKD1T, PKD 1 truncating; PKD1NT, PKD 1 nontruncating; US, urological symptoms.

Figure 4

Recommendation for tolvaptan in correlation with genetic results and clinical findings. (a) The stacked bar chart shows the distribution of the different Mayo classes among the recommendations for taking tolvaptan. (b) The stacked bar chart shows the distribution of the different genetic variants between the recommendations for taking tolvaptan. The numbers inside the stacked bar indicate the total number of patients. 1A+B Mayo classes 1A and 1B, 1C Mayo class 1C, 1D+E Mayo classes 1D and 1E. PKD, polycystic kidney disease.