Dataset Information

Characterisation of transcription factor profiles in polycystic kidney disease (PKD): identification and validation of STAT3 and RUNX1 in the injury/repair response and PKD progression.

ABSTRACT: Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic renal disease, caused in the majority of the cases by a mutation in either the PKD1 or the PKD2 gene. ADPKD is characterised by a progressive increase in the number and size of cysts, together with fibrosis and distortion of the renal architecture, over the years. This is accompanied by alterations in a complex network of signalling pathways. However, the underlying molecular mechanisms are not well characterised. Previously, we defined the PKD Signature, a set of genes typically dysregulated in PKD across different disease models from a meta-analysis of expression profiles. Given the importance of transcription factors (TFs) in modulating disease, we focused in this paper on characterising TFs from the PKD Signature. Our results revealed that out of the 1515 genes in the PKD Signature, 92 were TFs with altered expression in PKD, and 32 of those were also implicated in tissue injury/repair mechanisms. Validating the dysregulation of these TFs by qPCR in independent PKD and injury models largely confirmed these findings. STAT3 and RUNX1 displayed the strongest activation in cystic kidneys, as demonstrated by chromatin immunoprecipitation (ChIP) followed by qPCR. Using immunohistochemistry, we showed a dramatic increase of expression after renal injury in mice and cystic renal tissue of mice and humans. Our results suggest a role for STAT3 and RUNX1 and their downstream targets in the aetiology of ADPKD and indicate that the meta-analysis approach is a viable strategy for new target discovery in PKD. KEY MESSAGES: We identified a list of transcription factors (TFs) commonly dysregulated in ADPKD. Out of the 92 TFs identified in the PKD Signature, 35% are also involved in injury/repair processes. STAT3 and RUNX1 are the most significantly dysregulated TFs after injury and during PKD progression. STAT3 and RUNX1 activity is increased in cystic compared to non-cystic mouse kidneys. Increased expression of STAT3 and RUNX1 is observed in the nuclei of renal epithelial cells, also in human ADPKD samples.

SUBMITTER: Formica C

PROVIDER: S-EPMC6920240 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characterisation of transcription factor profiles in polycystic kidney disease (PKD): identification and validation of STAT3 and RUNX1 in the injury/repair response and PKD progression.

Formica Chiara C Malas Tareq T Balog Judit J Verburg Lotte L 't Hoen Peter A C PAC Peters Dorien J M DJM

Journal of molecular medicine (Berlin, Germany) 20191126 12

Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic renal disease, caused in the majority of the cases by a mutation in either the PKD1 or the PKD2 gene. ADPKD is characterised by a progressive increase in the number and size of cysts, together with fibrosis and distortion of the renal architecture, over the years. This is accompanied by alterations in a complex network of signalling pathways. However, the underlying molecular mechanisms are not well characterised. Pr ...[more]

PMID: 31773180

Similar Datasets

Project description:Rationale & objectivePain is a frequent complication of autosomal dominant polycystic kidney disease (ADPKD) and includes back and abdominal pain. We hypothesized that in adults with early- and late-stage ADPKD, overweight and obesity are independently associated with greater self-reported back, abdominal, and radicular pain at baseline and that weight loss would be associated with decreased pain over a follow-up period.Study designPost hoc analysis of pooled data from 2 randomized trials.Setting & participantsParticipants in the HALT-PKD study A or B. 867 individuals were included in a cross-sectional analysis. 4,248 observations from 871 participants were included in a longitudinal analysis.PredictorOverweight and obesity (cross-sectional); annual change in weight as a time-varying predictor (longitudinal).OutcomePain (Likert-scale responses; cross-sectional); annual change in pain (binary outcome of worsening pain or not worsening; longitudinal).Analytical approachMultivariable ordinal logistic regression (cross-sectional); generalized estimating equation analysis (longitudinal).ResultsParticipants were aged 42±10 years and baseline estimated glomerular filtration rate was 71±26 mL/min/1.73 m2. Back, abdominal, and radicular pain were reported more frequently in individuals with increasing body mass index category (all P < 0.05 for trend). After multivariable adjustment, obesity was associated with increased odds of greater back and radicular pain, but not abdominal pain. Associations remained similar after further adjustment for baseline height-adjusted kidney and liver volume (study A only, n = 457); back pain: OR, 1.88 (95% CI, 1.15-3.08); and radicular pain: OR, 2.92 (95% CI, 1.45-5.91). Longitudinally (median follow-up, 5 years), weight loss (annual decrease in weight ≥ 4%) was associated with decreased adjusted odds of worsening back pain (OR, 0.87 [95% CI, 0.76-0.99]) compared with the reference group (stable weight).LimitationsPost hoc, associative analysis.ConclusionsIn early- and late-stage ADPKD, obesity was associated with greater back and radicular pain independent of total kidney/liver volume. Mild weight loss was associated with favorable effects on back pain.

Project description:BackgroundEpidemiological studies have suggested that elevated serum uric acid may contribute to the progression of chronic kidney disease. However, no large prospective study has examined whether hyperuricemia is an independent risk factor for the progression of autosomal dominant polycystic kidney disease (ADPKD).MethodsWe measured uric acid in stored serum samples from the 2-year study visit of 671 participants from the HALT PKD multicenter trials. Participants were categorized according to uric acid tertiles. For Study A (participants aged 15-49 years with preserved kidney function, n=350), we used linear mixed effects models to examine the association between uric acid and repeated measures of height-adjusted total kidney volume (htTKV), the primary outcome for Study A. For Study B (participants aged 18-64 with decreased kidney function, n=321), we used Cox proportional hazards models to assess the hazard for the combined endpoint of 50% loss in estimated glomerular filtration rate (eGFR), end-stage kidney disease (ESKD), or death, the primary outcome for Study B. To assess the association of uric acid with the slope of eGFR decline (secondary outcome of HALT A and B), we used linear mixed effects models for the combined population of Study A and B.ResultsIn the unadjusted model, the annual change in htTKV was 2.7% higher in the highest uric acid tertile compared to the lowest (p<0.001), but this difference became insignificant after adjustment for gender. Men had faster TKV growth than women (p<0.001). There was no difference in eGFR decline between the 3 uric acid tertiles. Hazard ratios for the clinical endpoint were 2.9 (95% confidence interval, 1.9-4.4) and 1.8 (1.1-2.8) respectively in the high and medium uric acid groups in unadjusted and partially adjusted models (p<0.001), but the significance was lost after adjustment for baseline eGFR. Results were similar when uric acid was examined as a continuous variable.ConclusionElevated serum uric acid is not an independent risk factor for disease progression in ADPKD.

Project description:Autosomal polycystic kidney disease (ADPKD) is a frequent monogenic renal disease, characterised by fluid-filled cysts that are thought to result from multiple deregulated pathways such as cell proliferation and apoptosis. MicroRNAs (miRNAs) are small non-coding RNAs that regulate the expression of many genes associated with such biological processes and human pathologies. To explore the possible regulatory role of miRNAs in PKD, the PKD/Mhm (cy/+) rat, served as a model to study human ADPKD. A parallel microarray-based approach was conducted to profile the expression changes of mRNAs and miRNAs in PKD/Mhm rats. 1,573 up- and 1,760 down-regulated genes were differentially expressed in PKD/Mhm. These genes are associated with 17 pathways (such as focal adhesion, cell cycle, ECM-receptor interaction, DNA replication and metabolic pathways) and 47 (e.g., cell proliferation, Wnt and Tgf? signaling) Gene Ontologies. Furthermore, we found the similar expression patterns of deregulated genes between PKD/Mhm (cy/+) rat and human ADPKD, PKD1(L3/L3), PKD1(-/-), Hnf1?-deficient, and Glis2(lacZ/lacZ) models. Additionally, several differentially regulated genes were noted to be target hubs for miRNAs. We also obtained 8 significantly up-regulated miRNAs (rno-miR-199a-5p, -214, -146b, -21, -34a, -132, -31 and -503) in diseased kidneys of PKD/Mhm rats. Additionally, the binding site overrepresentation and pathway enrichment analyses were accomplished on the putative targets of these 8 miRNAs. 7 out of these 8 miRNAs and their possible interactions have not been previously described in ADPKD. We have shown a strong overlap of functional patterns (pathways) between deregulated miRNAs and mRNAs in the PKD/Mhm (cy/+) rat model. Our findings suggest that several miRNAs may be associated in regulating pathways in ADPKD. We further describe novel miRNAs and their possible targets in ADPKD, which will open new avenues to understand the pathogenesis of human ADPKD. Furthermore they could serve as a useful resource for anti-fibrotic therapeutics.

Dataset Information

Characterisation of transcription factor profiles in polycystic kidney disease (PKD): identification and validation of STAT3 and RUNX1 in the injury/repair response and PKD progression.

Publications

Characterisation of transcription factor profiles in polycystic kidney disease (PKD): identification and validation of STAT3 and RUNX1 in the injury/repair response and PKD progression.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets