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Guay-Woodford Lab

Our Research

ARPKD Mechanistic Studies

Decoding reno-protective mechanisms in mouse Pkhd1 models: Implications for ARPKD therapeutics

Funding: NIH/NIDDK R01 DK121530

Our R01-funded research is focused on two related observations in ARPKD pathogenesis: 1) species-specific differences in Myc expression in mutant kidneys, and 2) species-specific differences in PKHD1/Pkhd1 renal phenotype. In human ARPKD, both PKHD1 missense and truncating mutations are associated with renal cystic disease, with two PKHD1 truncating mutations in trans typically causing severe renal cystic disease. However, mouse Pkhd1 models, including the Pkhd1 exon 67 deletion (encoding most of the carboxy terminal domain (CTD) of the FPC protein), have no renal phenotype. Given phylogenetic conservation in Myc regulatory activity, we propose the absence of a renal disease phenotype in Pkhd1 mutant mice results from genetic robustness in mouse kidneys.  Experimentally, we are testing the hypothesis that mouse renal epithelia can compensate for the loss of FPC-CTD function through species-specific regulation of Myc expression and other compensatory transcriptional mechanisms. While these reno-protective mechanisms are not normally operative in human renal epithelia, they may identify new opportunities for therapeutic targeting in human ARPKD renal disease. 

Team Members

  • Naoe Harifuji, Ph.D. 
  • Girija Thiruvengadam, Ph.D. 
  • Chaozhe (George), M.D. 
  • Maryanne C. Odinakachukwu 

Clinical and Genetic Characterization of Childhood PKD

Funding: NIH/NIDDK U54 DK126087 and Moran Family Foundation

We have established the recessive HRFD Clinical Database, a clinical resource that is integrated with a state-of-the-art HRFD Repository containing genotypes for ARPKD and other HRFD patients, as well as patient-associated bio-materials (DNA, human urine-derived renal epithelial cells and HRFD tissues). More recently, we have launched the American node (ADPedKD-US) of the newly established global ADPedKD, an international multicenter observational study of childhood ADPKD. 

Our overarching goal is to compile a sufficient volume of clinical data, genetic information and biological specimens in a centralized resource to accelerate discovery research in childhood cystic kidney diseases and integrate the resulting data to serve as the foundation for the development of new, targeted interventional strategies.

In addition, as a partner in the Health Experience Research Network (HERN) we are applying the Database of Individual Patient Experiences (DIPEx) approach (developed in the UK by researchers at Oxford University) to collect detailed information on patient/caregiver experiences with the goal of amplifying the patient’s voice in HRFD-related clinical and translational research (CTR). This methodology has proven an effective platform for integrating patient perspectives and experiences into the conception, design and conduct of all phases of CTR, thereby enhancing patient recruitment and retention rates. 

Team Members

  • Jasmine Jaber, M.S. 
  • Girija Thiruvengadam, Ph.D. 
  • Emmanuèle C. Délot, Ph.D.
  • Daisy Le, Ph.D. (George Washington University)

PKDnet: ARPKD Learning Network

Funding: Moran Family Foundation

In collaboration with Erum Hartung, M.D., M.T.R., (Children’s Hospital of Philadelphia (CHOP)), we are developing prototype algorithms that identify ARPKD directly from electronic health records by harnessing the power of PEDSnet, a longitudinal data resource developed by eight collaborating children’s hospitals. We have completed data quality analysis and developed a list of variables to be included in the machine learning model. The various versions of the prototype algorithm perform well using CHOP data. To date, the PEDSnet team has identified a cohort of 75 patients with ARPKD and generated a set of 150 controls, consisting of 100 patients with at least one nephrology visit, 25 patients with at least one GI visit and a liver diagnosis, and 25 patients at least one NICU visit. Our ongoing work will focus on formally evaluating the performance of the algorithm at CHOP using manual chart reviews, and then testing and refining the algorithm on datasets from other PEDSnet sites.

Team Members

  • Lisa Guay-Woodford, M.D.