# ADPKD: Disease Spectrum & Genotype-Phenotype Correlations

> **NIH NIH R01** · MAYO CLINIC ROCHESTER · 2020 · $15,035

## Abstract

Autosomal dominant polycystic kidney disease (ADPKD) is a common monoallelic disorder associated with
progressive cyst development and resulting in end stage renal failure (ESRD) in 50% of patients by 60y.
However, there is considerable phenotypic variability, extending from in utero onset to patients with adequate
renal function into old age. Autosomal dominant polycystic liver disease (ADPLD), as traditionally defined,
results in PLD with minimal renal cysts. Classically there have been considered two ADPKD genes, PKD1 and
PKD2, encoding PC1 and PC2, and two ADPLD genes, PRKCSH and SEC63, but in the past few years
greater genetic heterogeneity has been described, with nine genes now implicated overall. Recent data also
indicates an overlap in etiology and pathogenesis associated with ADPKD and ADPLD, with the efficient
biogenesis and localization of the PC-complex central to both disorders. During the last funding period we
identified a novel gene, GANAB, which is associated with both disorders, where the encoded protein, GII is
involved in the maturation and trafficking of PC1.
 In this proposal we will take advantage of advances in next generation sequencing (NGS)
methodologies, and large populations of ADPKD and ADPLD patients that have been assembled and
screened for the classic genes, to hunt for novel genes for these disorders (Aim 1). The phenotype associated
with these genes will be characterized (Aim 3) along with their mechanism of action (Aim 2). NGS methods will
be perfected to screen the segmentally duplicated locus, PKD1, and to identify missed mutations at the known
loci, including those present in just some cells due to mosaicism (Aim 1). The significance of many PKD1
nontruncating variants has been difficult to evaluate (classed as variants of unknown significance; VUS), but
recently evidence that some are incompletely penetrant alleles partially explains phenotypic variability in PKD1
populations. In Aim 2 improved in silico predictions, in combination with machine learning, will improve the
understanding of the pathogenicity and penetrance of VUS. A cellular assay of the biogenesis and trafficking
of this PC-complex will also be employed to quantify the penetrance of VUS. The mechanism of pathogenesis
will be explored in animal models with ultralow penetrant (ULP) Pkd1 or Pkd2 alleles. Employing the large
clinically, imaging, and genetically well-defined populations phenotypic groupings of patients will be defined
that will then be compared to the genic and PKD1 allelic groups (Aim 3). This iterative process will allow the
Variant Score (VS) associated with each PKD1 VUS to be refined. In a separate population the revised VS,
alone and in combination with clinical, functional, and imaging data, will be employed to generate a
comprehensive, predictive algorithm for ADPKD (Aim 3). Disease modifiers to severe disease, via biallelic
ADPKD, and due to alleles at other loci will also be identified and characterized in the cellula...

## Key facts

- **NIH application ID:** 10148997
- **Project number:** 3R01DK058816-19S1
- **Recipient organization:** MAYO CLINIC ROCHESTER
- **Principal Investigator:** Peter C. Harris
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $15,035
- **Award type:** 3
- **Project period:** 2001-08-01 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10148997

## Citation

> US National Institutes of Health, RePORTER application 10148997, ADPKD: Disease Spectrum & Genotype-Phenotype Correlations (3R01DK058816-19S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10148997. Licensed CC0.

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