skip to main content


The NSF Public Access Repository (NSF-PAR) system and access will be unavailable from 11:00 PM ET on Friday, July 12 until 9:00 AM ET on Saturday, July 13 due to maintenance. We apologize for the inconvenience.

Title: Prioritized polycystic kidney disease drug targets and repurposing candidates from pre-cystic and cystic mouse Pkd2 model gene expression reversion
Abstract Background

Autosomal dominant polycystic kidney disease (ADPKD) is one of the most prevalent monogenic human diseases. It is mostly caused by pathogenic variants inPKD1orPKD2genes that encode interacting transmembrane proteins polycystin-1 (PC1) and polycystin-2 (PC2). Among many pathogenic processes described in ADPKD, those associated with cAMP signaling, inflammation, and metabolic reprogramming appear to regulate the disease manifestations. Tolvaptan, a vasopressin receptor-2 antagonist that regulates cAMP pathway, is the only FDA-approved ADPKD therapeutic. Tolvaptan reduces renal cyst growth and kidney function loss, but it is not tolerated by many patients and is associated with idiosyncratic liver toxicity. Therefore, additional therapeutic options for ADPKD treatment are needed.


As drug repurposing of FDA-approved drug candidates can significantly decrease the time and cost associated with traditional drug discovery, we used the computational approach signature reversion to detect inversely related drug response gene expression signatures from the Library of Integrated Network-Based Cellular Signatures (LINCS) database and identified compounds predicted to reverse disease-associated transcriptomic signatures in three publicly availablePkd2kidney transcriptomic data sets of mouse ADPKD models. We focused on a pre-cystic model for signature reversion, as it was less impacted by confounding secondary disease mechanisms in ADPKD, and then compared the resulting candidates’ target differential expression in the two cystic mouse models. We further prioritized these drug candidates based on their known mechanism of action, FDA status, targets, and by functional enrichment analysis.


With this in-silico approach, we prioritized 29 unique drug targets differentially expressed inPkd2ADPKD cystic models and 16 prioritized drug repurposing candidates that target them, including bromocriptine and mirtazapine, which can be further tested in-vitro and in-vivo.


Collectively, these results indicate drug targets and repurposing candidates that may effectively treat pre-cystic as well as cystic ADPKD.

Graphical Abstract 
more » « less
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ;
Publisher / Repository:
Springer Science + Business Media
Date Published:
Journal Name:
Molecular Medicine
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Background

    Chronic rhinosinusitis symptomatology begins in early childhood individuals with cystic fibrosis (CF). Cystic fibrosis transmembrane conductance regulator (CFTR) function contributes to sinus development and disease. Genetic variants of the bitter taste receptorTAS2R38have been suggested to contribute to sinus disease severity in individuals without CF. Our objective was to explore whether functionalTAS2R38haplotypes and CFTR function are associated with sinus disease or the need for sinus surgery in individuals with CF.


    We conducted a retrospective study using prospectively collected data from the CF Twin‐Sibling Study. The function of CFTR was assessed via chloride conductance. Genotyping of theTAS2R38gene identified patients who were homozygous for the functional haplotype, heterozygous, or homozygous for nonfunctional haplotypes. Clustered multivariate logistic regression was performed, controlling for sex and family relationship.


    A total of 1291 patients were evaluated. Patients with ≤1% CFTR function were 1.56 times more likely to require sinus surgery than those with >1% CFTR function (p= 0.049). CFTR function did not correlate significantly with the presence of sinus disease (p= 0.30). In addition, there were no statistically significant differences in diagnosis of sinus disease or need for sinus surgery between patients with functional and nonfunctionalTAS2R38haplotypes.


    CFTR function correlates with need for sinus surgery, whereasTAS2R38function does not appear to contribute to sinus disease or the need for sinus surgery in patients with CF.

    more » « less
  2. Background

    Chronic rhinosinusitis (CRS) is a significant manifestation of cystic fibrosis (CF) with wide‐ranging symptom and disease severity. The goal of the study was to determine clinical variables that correlate with outcome measures of disease severity.


    A prospective, longitudinal, observational study of 33 adults with symptomatic CRS treated in a CF‐focused otolaryngology clinic was performed. Symptom severity, the presence of rhinosinusitis exacerbations, and endoscopic appearance were assessed, and regression analysis was used to determine clinical predictors of disease outcome.


    Thirty‐three adults with CF‐CRS were included in the study and followed for a mean of 15 months. Rhinosinusitis exacerbations occurred in 61% of participants during the study, and female sex increased the odds of presenting with an exacerbation visit. Sinus disease exacerbations were associated with an odds ratio of 2.07 for presenting with a pulmonary exacerbation at the next visit. CF‐related diabetes was found to be associated with worse symptoms and endoscopic appearance. Infection withStaphylococcus aureuspredicted worsening of symptoms, whereas infections withPseudomonas aeruginosaimproved over time. Allergic rhinitis was associated with worse endoscopic appearance, and nasal steroid use was associated with improved endoscopic appearance.


    Sex, CF‐related diabetes, sinonasal infection status, allergic rhinitis, and nasal steroid use may all modulate severity of CF‐CRS in adults. Sinusitis exacerbation may be a precursor to pulmonary exacerbation.

    more » « less
  3. Background

    The purpose of this retrospective review was to determine how patient‐related factors and culture data affect neo‐osteogenesis in patients with chronic rhinosinusitis (CRS) and patients with cystic fibrosis (CF) with CRS.


    Information from a database associated with a large tertiary medical center was used to assess adult patients with CF CRS and non‐CF CRS (total, n = 102; CF CRS, n = 31; non‐CF CRS, n = 71). Radiologic evidence of neo‐osteogenesis was measured using the Global Osteitis Scoring Scale (GOSS), and mucosal disease was assessed using the Lund‐Mackay score (LMS) by 2 independent reviewers who were blinded to the patient's disease state. Bacterial cultures were obtained endoscopically. Multiple logistic regression models were used to evaluate the effect of age, sex, number of previous surgeries, CF, and culture species on the odds of neo‐osteogenesis.


    Fifty‐one of the 102 patients (50%) met radiologic criteria for neo‐osteogenesis. Sixty‐nine patients (67.6%) with CF CRS and non‐CF CRS had culture data. In the multiple logistic regression model, male gender was significantly associated with neo‐osteogenesis (odds ratio [OR], 5.2; 95% confidence interval [CI], 1.68‐17.86;p= 0.006).Pseudomonas aeruginosawas not associated with neo‐osteogenesis (OR, 3.12; 95% CI, 0.84‐12.80;p= 0.097). Age, number of surgeries, CF,Staphylococcus aureus, and coagulase‐negativeStaphylococcuswere not statistically significant.


    To our knowledge, this is the first study to assess risk factors associated with neo‐osteogenesis and patients with CF CRS. Interestingly, male gender was the only significant predictor of neo‐osteogenesis.

    more » « less
  4. Abstract

    Given the severity of the SARS-CoV-2 pandemic, a major challenge is to rapidly repurpose existing approved drugs for clinical interventions. While a number of data-driven and experimental approaches have been suggested in the context of drug repurposing, a platform that systematically integrates available transcriptomic, proteomic and structural data is missing. More importantly, given that SARS-CoV-2 pathogenicity is highly age-dependent, it is critical to integrate aging signatures into drug discovery platforms. We here take advantage of large-scale transcriptional drug screens combined with RNA-seq data of the lung epithelium with SARS-CoV-2 infection as well as the aging lung. To identify robust druggable protein targets, we propose a principled causal framework that makes use of multiple data modalities. Our analysis highlights the importance of serine/threonine and tyrosine kinases as potential targets that intersect the SARS-CoV-2 and aging pathways. By integrating transcriptomic, proteomic and structural data that is available for many diseases, our drug discovery platform is broadly applicable. Rigorous in vitro experiments as well as clinical trials are needed to validate the identified candidate drugs.

    more » « less
  5. Abstract

    The escalating drug addiction crisis in the United States underscores the urgent need for innovative therapeutic strategies. This study embarked on an innovative and rigorous strategy to unearth potential drug repurposing candidates for opioid and cocaine addiction treatment, bridging the gap between transcriptomic data analysis and drug discovery. We initiated our approach by conducting differential gene expression analysis on addiction-related transcriptomic data to identify key genes. We propose a novel topological differentiation to identify key genes from a protein–protein interaction network derived from DEGs. This method utilizes persistent Laplacians to accurately single out pivotal nodes within the network, conducting this analysis in a multiscale manner to ensure high reliability. Through rigorous literature validation, pathway analysis and data-availability scrutiny, we identified three pivotal molecular targets, mTOR, mGluR5 and NMDAR, for drug repurposing from DrugBank. We crafted machine learning models employing two natural language processing (NLP)-based embeddings and a traditional 2D fingerprint, which demonstrated robust predictive ability in gauging binding affinities of DrugBank compounds to selected targets. Furthermore, we elucidated the interactions of promising drugs with the targets and evaluated their drug-likeness. This study delineates a multi-faceted and comprehensive analytical framework, amalgamating bioinformatics, topological data analysis and machine learning, for drug repurposing in addiction treatment, setting the stage for subsequent experimental validation. The versatility of the methods we developed allows for applications across a range of diseases and transcriptomic datasets.

    more » « less