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Genotype, Kidney Size Predict Rapid Progression of ADPKD – Renal and Urology News

Combining genotype and kidney length can identify nearly 9 out of 10 patients with rapid progression of autosomal dominant polycystic kidney disease (ADPKD), investigators report.

In a real-world cohort of 618 patients with ADPKD seen at a UK specialist clinic from 2010 to 2021, 123 patients (19.9%) progressed to kidney failure by July 2021.1 At baseline, estimated glomerular filtration rate (eGFR), genotype, and ultrasound mean kidney length were available for a majority of patients.

In a multivariate logistic regression model, the PKD1-truncating genotype and a height-adjusted mean kidney length (htMKL) of more than 9.5 cm/m emerged as independent predictors for rapid disease progression, Albert C.M. Ong, DM, of the University of Sheffield in the UK, and colleagues reported in Nephrology Dialysis Transplantation. Rapid eGFR decline was defined as more than 2.5 mL/min/year.

In a model, the combination of the PKD1 truncating genotype and a height-adjusted mean kidney length cutoff of 9.5 cm/m had a positive predictive value of 88% and a negative predictive value of 55% for rapid progression. The model improved prediction for patients older than 40 years and those with stage 3-4 chronic kidney disease. The combination also had a positive predictive value of 100% and a negative predictive value of 63% for kidney failure by age 60 years.

These study findings indicate that the combination of genotype and mean kidney length or kidney volume is able to capture the process of cyst initiation and expansion in an individual patient providing predictive value for subsequent kidney function decline, Dr Ong stated.

“Our model appears to be at least equivalent in performance to PROPKD, although this needs to be confirmed in a validation cohort where the performance of both could be directly compared.”

Future studies should attempt to find additional factors that predict progression to improve the negative predictive value of the model, he noted.

In the meantime, the investigators said the model could improve patient selection for treatment. Tolvaptan has been approved to treat ADPKD in patients with a rapid decline in eGFR of more than 2.5 mL/min/year or at risk for rapid progression.

Most patients in this cohort were diagnosed between ages 21 and 60 years. Variants in the PKD1 and PKD2 genes accounted for approximately 70% of ADPKD cases. However, 24% of patients were genetically unresolved, including 17% with no mutation detected and 7% with variants of uncertain significance mainly in PKD1. Patients with no mutation detected had features suggestive of a more benign course of disease progression and kidney failure compared with patients with known genotypes, according to the investigators.

A study published in the Clinical Journal of the American Society of Nephrology illustrated the pros and cons of the current Mayo Imaging Classification System (MICS) for predicting kidney outcomes in ADPKD.2 Currently, MICS uses a single measurement of height-adjusted total kidney volume for age to classify kidney growth rate in patients but does not include ADPKD genotype.

Per MICS, annual kidney growth rate increases from a constant 1.5% in class 1A to more than 6% in class 1E. In the study of 618 patients, kidney growth and eGFR decline estimates overlapped considerably between the classes. Actual annual eGFR decline, however, did not differ significantly from predicted values for classes 1A, 1B, 1C, and 1D, but was significantly slower for class 1E.

Kidney failure developed in 97 (16%) of patients during follow-up. MICS predicted the development of kidney failure, but the sensitivity (37.1%) and positive predictive values (59.0%) were limited.

“The rate of eGFR decline predicted by the equation was overestimated in patients with class 1E, in patients aged [less than] 40 and [more than] 60 years and those with PKD2 mutations,” Ron. T. Gansevoort, MD, of the University Medical Center Groningen in The Netherlands, and colleagues reported.

“To optimize kidney outcome predictions for individuals, it may be necessary to develop a classification that incorporates volumetric parameters, clinical and genetic data, and biochemical measurements.”


  1. Chen EWC, Chong J, Valluru MK, et al. Combining genotype with height-adjusted kidney length predicts rapid progression of ADPKD. Nephrol Dial Transplant. Published online January 15, 2024. doi:10.1093/ndt/gfad270
  2. Bais T, Geertsema P, Knol MGE, et al; DIPAK Consortium. Validation of the Mayo imaging classification system for predicting kidney outcomes in ADPKD. Clin J Am Soc Nephrol. Published online February 26, 2024. doi:10.2215/CJN.0000000000000427