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Updated: Jul 5, 2025
Use of Ultra-high Field MRI in Small Rodent Models of Polycystic Kidney Disease for In Vivo Phenotyping and Drug Monitoring
Published on: June 23, 2015
Combining genotype with height-adjusted kidney length predicts rapid progression of ADPKD
Eugene W C Chen1,2, Jiehan Chong1,2, Manoj K Valluru1
1Academic Nephrology Unit, Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield, UK.
Introduction:
Our main objective was to identify baseline prognostic factors predictive of rapid disease progression in a large unselected clinical autosomal dominant polycystic kidney disease (ADPKD) cohort.
Methods:
A cross-sectional analysis was performed in 618 consecutive ADPKD patients assessed and followed-up for over a decade. A total of 123 patients (19.9%) had reached kidney failure by the study date. Data were available for the following: baseline eGFR (n = 501), genotype (n = 549), baseline ultrasound mean kidney length (MKL, n = 424) and height-adjusted baseline MKL (HtMKL, n = 377). Rapid disease progression was defined as an annualized eGFR decline (∆eGFR) of >2.5 mL/min/year by linear regression over 5 years (n = 158). Patients were further divided into slow, rapid and very rapid ∆eGFR classes for analysis. Genotyped patients were classified into several categories: PKD1 (T, truncating; or NT, non-truncating), PKD2, other genes (non-PKD1 or -PKD2), no mutation detected or variants of uncertain significance.
Results:
A PKD1-T genotype had the strongest influence on the probability of reduced baseline kidney function by age. A multivariate logistic regression model identified PKD1-T genotype and HtMKL (>9.5 cm/m) as independent predictors for rapid disease progression. The combination of both factors increased the positive predictive value for rapid disease progression over age 40 years and of reaching kidney failure by age 60 years to 100%. Exploratory analysis in a subgroup with available total kidney volumes showed higher positive predictive value (100% vs 80%) and negative predictive value (42% vs 33%) in predicting rapid disease progression compared with the Mayo Imaging Classification (1C-E).
Conclusion:
Real-world longitudinal data confirm the importance of genotype and kidney length as independent variables determining ∆eGFR. Individuals with the highest risk of rapid disease progression can be positively selected for treatment based on this combination.
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