Zebrafish models of cystic kidney disease related ciliopathies

PhD ThesisCystic kidney diseases are a fascinating cluster of discrete conditions and an important, common cause of established renal failure. Both isolated and syndromic inherited cystic kidney diseases are known to be linked by their pathogenesis involving ciliary dysfunction. Interestingly to date, all mutated genes which have been related to cystic kidney disease, encode proteins which are located on cilia, the basal body or centrosomes and are required for ciliary function. To date, over 50 causal genes have been identified and are capable of causing additional disease phenotypes, such as neurological disorders and blindness, often of variable severity. Understanding this clinical heterogeneity may considerably guide appropriate genetic counselling and screening of patients for relevant complications. Zebrafish are a well-recognised animal model, their advantages of: transparency; conserved genome; representative kidney and rapid external development; make them useful for studying organogenesis in the context of disease. Furthermore the ability to perform combined gene knockdown in zebrafish, to study the effect of oliogenicity, which was proposed to influence clinical phenotypes in cystic kidney disease related ciliopathies, was of interest. Using zebrafish models, this work studied the impact of four key genes, independently and in combination: ahi1, cc2d2a, nphp6 and mks3 on the development of cystic kidney disease and ciliopathy phenotypes, to resemble the human diseases nephronophthisis (NPHP), Joubert syndrome (JBTS) and Meckel Gruber syndrome, (MKS). A frequent finding in zebrafish morphants was a reduction in the number of cilia, which was usually associated with abnormal development of left-right body patterning and cystic kidney disease. Additionally, combined gene knockdown of: nphp6 and cc2d2a; ahi1 and cc2d2a; ahi1 and nphp6 was associated with a synergistic increase in disease phenotypes, suggesting an interaction between these genes. In conclusion, zebrafish are a powerful developmental model to study and ideally improve understanding of cystic kidney disease related ciliopathies.Mason Medical Research Group, Medical Research Council and Kidney Research UK

Investigating Embryonic Expression Patterns and Evolution of AHI1 and CEP290 Genes, Implicated in Joubert Syndrome

Joubert syndrome and related diseases (JSRD) are developmental cerebello-oculo-renal syndromes with phenotypes including cerebellar hypoplasia, retinal dystrophy and nephronophthisis (a cystic kidney disease). We have utilised the MRCWellcome Trust Human Developmental Biology Resource (HDBR), to perform in-situ hybridisation studies on embryonic tissues, revealing an early onset neuronal, retinal and renal expression pattern for AHI1. An almost identical pattern of expression is seen with CEP290 in human embryonic and fetal tissue. A novel finding is that both AHI1 and CEP290 demonstrate strong expression within the developing choroid plexus, a ciliated structure important for central nervous system development. To test if AHI1 and CEP290 may have co-evolved, we carried out a genomic survey of a large group of organisms across eukaryotic evolution. We found that, in animals, ahi1 and cep290 are almost always found together; however in other organisms either one may be found independent of the other. Finally, we tested in murine epithelial cells if Ahi1 was required for recruitment of Cep290 to the centrosome. We found no obvious differences in Cep290 localisation in the presence or absence of Ahi1, suggesting that, while Ahi1 and Cep290 may function together in the whole organism, they are not interdependent for localisation within a single cell. Taken together these data support a role for AHI1 and CEP290 in multiple organs throughout development and we suggest that this accounts for the wide phenotypic spectrum of AHI1 and CEP290 mutations in man

Ligand-induced conformational changes in a SMALP-encapsulated GPCR.

The adenosine 2A receptor (A2AR), a G-protein-coupled receptor (GPCR), was solubilised and purified encapsulated in styrene maleic acid lipid particles (SMALPs). The purified A2AR-SMALP was associated with phospholipids characteristic of the plasma membrane of Pichia pastoris, the host used for its expression, confirming that the A2AR-SMALP encapsulated native lipids. The fluorescence spectrum of the A2AR-SMALP showed a characteristic broad emission peak at 330 nm, produced by endogenous Trp residues. The inverse agonist ZM241385 caused 30% increase in fluorescence emission, unusually accompanied by a red-shift in the emission wavelength. The emission spectrum also showed sub-peaks at 321 nm, 335 nm and 350 nm, indicating that individual Trp inhabited different environments following ZM241385 addition. There was no effect of the agonist NECA on the A2AR-SMALP fluorescence spectrum. Substitution of two Trp residues by Tyr suggested that ZM241385 affected the environment and mobility of Trp2466.48 in TM6 and Trp2687.33 at the extracellular face of TM7, causing transition to a more hydrophobic environment. The fluorescent moiety IAEDANS was site-specifically introduced at the intracellular end of TM6 (residue 2316.33) to report on the dynamic cytoplasmic face of the A2AR. The inverse agonist ZM241385 caused a concentration-dependent increase in fluorescence emission as the IAEDANS moved to a more hydrophobic environment, consistent with closing the G-protein binding crevice. NECA generated only 30% of the effect of ZM241385. This study provides insight into the SMALP environment; encapsulation supported constitutive activity of the A2AR and ZM241385-induced conformational transitions but the agonist NECA generated only small effects

A rapid high-performance semi-automated tool to measure total kidney volume from MRI in autosomal dominant polycystic kidney disease.

OBJECTIVES: To develop a high-performance, rapid semi-automated method (Sheffield TKV Tool) for measuring total kidney volume (TKV) from magnetic resonance images (MRI) in patients with autosomal dominant polycystic kidney disease (ADPKD). METHODS: TKV was initially measured in 61 patients with ADPKD using the Sheffield TKV Tool and its performance compared to manual segmentation and other published methods (ellipsoidal, mid-slice, MIROS). It was then validated using an external dataset of MRI scans from 65 patients with ADPKD. RESULTS: Sixty-one patients (mean age 45 ± 14 years, baseline eGFR 76 ± 32 ml/min/1.73 m2) with ADPKD had a wide range of TKV (258-3680 ml) measured manually. The Sheffield TKV Tool was highly accurate (mean volume error 0.5 ± 5.3% for right kidney, - 0.7 ± 5.5% for left kidney), reproducible (intra-operator variability - 0.2 ± 1.3%; inter-operator variability 1.1 ± 2.9%) and outperformed published methods. It took less than 6 min to execute and performed consistently with high accuracy in an external MRI dataset of T2-weighted sequences with TKV acquired using three different scanners and measured using a different segmentation methodology (mean volume error was 3.45 ± 3.96%, n = 65). CONCLUSIONS: The Sheffield TKV Tool is operator friendly, requiring minimal user interaction to rapidly, accurately and reproducibly measure TKV in this, the largest reported unselected European patient cohort with ADPKD. It is more accurate than estimating equations and its accuracy is maintained at larger kidney volumes than previously reported with other semi-automated methods. It is free to use, can run as an independent executable and will accelerate the application of TKV as a prognostic biomarker for ADPKD into clinical practice. KEY POINTS: • This new semi-automated method (Sheffield TKV Tool) to measure total kidney volume (TKV) will facilitate the routine clinical assessment of patients with ADPKD. • Measuring TKV manually is time consuming and laborious. • TKV is a prognostic indicator in ADPKD and the only imaging biomarker approved by the FDA and EMA

Structural basis for receptor activity-modifying protein-dependent selective peptide recognition by a G protein-coupled receptor

Association of receptor activity-modifying proteins (RAMP1-3) with the G protein-coupled receptor (GPCR) calcitonin receptor-like receptor (CLR) enables selective recognition of the peptides calcitonin gene-related peptide (CGRP) and adrenomedullin (AM) that have diverse functions in the cardiovascular and lymphatic systems. How peptides selectively bind GPCR:RAMP complexes is unknown. We report crystal structures of CGRP analog-bound CLR:RAMP1 and AM-bound CLR:RAMP2 extracellular domain heterodimers at 2.5 and 1.8 Å resolutions, respectively. The peptides similarly occupy a shared binding site on CLR with conformations characterized by a β-turn structure near their C termini rather than the α-helical structure common to peptides that bind related GPCRs. The RAMPs augment the binding site with distinct contacts to the variable C-terminal peptide residues and elicit subtly different CLR conformations. The structures and accompanying pharmacology data reveal how a class of accessory membrane proteins modulate ligand binding of a GPCR and may inform drug development targeting CLR:RAMP complexes

Effects of rare kidney diseases on kidney failure: a longitudinal analysis of the UK National Registry of Rare Kidney Diseases (RaDaR) cohort

Background: Individuals with rare kidney diseases account for 5–10% of people with chronic kidney disease, but constitute more than 25% of patients receiving kidney replacement therapy. The National Registry of Rare Kidney Diseases (RaDaR) gathers longitudinal data from patients with these conditions, which we used to study disease progression and outcomes of death and kidney failure. // Methods: People aged 0–96 years living with 28 types of rare kidney diseases were recruited from 108 UK renal care facilities. The primary outcomes were cumulative incidence of mortality and kidney failure in individuals with rare kidney diseases, which were calculated and compared with that of unselected patients with chronic kidney disease. Cumulative incidence and Kaplan–Meier survival estimates were calculated for the following outcomes: median age at kidney failure; median age at death; time from start of dialysis to death; and time from diagnosis to estimated glomerular filtration rate (eGFR) thresholds, allowing calculation of time from last eGFR of 75 mL/min per 1·73 m2 or more to first eGFR of less than 30 mL/min per 1·73 m2 (the therapeutic trial window). // Findings: Between Jan 18, 2010, and July 25, 2022, 27 285 participants were recruited to RaDaR. Median follow-up time from diagnosis was 9·6 years (IQR 5·9–16·7). RaDaR participants had significantly higher 5-year cumulative incidence of kidney failure than 2·81 million UK patients with all-cause chronic kidney disease (28% vs 1%; p<0·0001), but better survival rates (standardised mortality ratio 0·42 [95% CI 0·32–0·52]; p<0·0001). Median age at kidney failure, median age at death, time from start of dialysis to death, time from diagnosis to eGFR thresholds, and therapeutic trial window all varied substantially between rare diseases. // Interpretation: Patients with rare kidney diseases differ from the general population of individuals with chronic kidney disease: they have higher 5-year rates of kidney failure but higher survival than other patients with chronic kidney disease stages 3–5, and so are over-represented in the cohort of patients requiring kidney replacement therapy. Addressing unmet therapeutic need for patients with rare kidney diseases could have a large beneficial effect on long-term kidney replacement therapy demand. // Funding: RaDaR is funded by the Medical Research Council, Kidney Research UK, Kidney Care UK, and the Polycystic Kidney Disease Charity

Description and Cross-Sectional Analyses of 25,880 Adults and Children in the UK National Registry of Rare Kidney Diseases Cohort

Introduction: The National Registry of Rare Kidney Diseases (RaDaR) collects data from people living with rare kidney diseases across the UK, and is the world’s largest, rare kidney disease registry. We present the clinical demographics and renal function of 25,880 prevalent patients and sought evidence of bias in recruitment to RaDaR. // Methods: RaDaR is linked with the UK Renal Registry (UKRR, with which all UK patients receiving kidney replacement therapy [KRT] are registered). We assessed ethnicity and socioeconomic status in the following: (i) prevalent RaDaR patients receiving KRT compared with patients with eligible rare disease diagnoses receiving KRT in the UKRR, (ii) patients recruited to RaDaR compared with all eligible unrecruited patients at 2 renal centers, and (iii) the age-stratified ethnicity distribution of RaDaR patients with autosomal dominant polycystic kidney disease (ADPKD) was compared to that of the English census. // Results: We found evidence of disparities in ethnicity and social deprivation in recruitment to RaDaR; however, these were not consistent across comparisons. Compared with either adults recruited to RaDaR or the English population, children recruited to RaDaR were more likely to be of Asian ethnicity (17.3% vs. 7.5%, P-value < 0.0001) and live in more socially deprived areas (30.3% vs. 17.3% in the most deprived Index of Multiple Deprivation (IMD) quintile, P-value < 0.0001). // Conclusion: We observed no evidence of systematic biases in recruitment of patients into RaDaR; however, the data provide empirical evidence of negative economic and social consequences (across all ethnicities) experienced by families with children affected by rare kidney diseases

An artificial intelligence generated automated algorithm to measure total kidney volume in ADPKD

Introduction Accurate tools to inform individual prognosis in patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Here, we report an artificial intelligence (AI) generated method for routinely measuring total kidney volume (TKV). Methods An ensemble U-net algorithm was created using the nnUNet approach. The training and internal cross-validation cohort consisted of all 1.5T MRI data acquired using 5 different MRI scanners (454 kidneys, 227 scans) in the CYSTic consortium which was first manually segmented by a single human operator. As an independent validation cohort, we utilised 48 sequential clinical MRI scans with reference results of manual segmentation acquired by 6 individual analysts at a single centre. The tool was then implemented for clinical use and its performance analysed. Results The training / internal validation cohort was younger (mean age 44.0 vs 51.5 years) and the female-male ratio higher (1.2 v 0.94) compared to the clinical validation cohort. The majority of CYSTic patients had PKD1 mutations (79%) and typical disease (Mayo Imaging Class 1, 86%). The median DICE score on the clinical validation dataset between the algorithm and human analysts was 0.96 for left and right kidneys with a median TKV error of -1.8%. The time taken to manually segment kidneys in the CYSTic dataset was 56 (±28) min whereas manual corrections of the algorithm output took 8.5 (±9.2) min per scan. Conclusions Our AI-based algorithm demonstrates performance comparable to manual segmentation. Its rapidity and precision in real-world clinical cases demonstrate its suitability for clinical application

Magnetic resonance imaging biomarkers for chronic kidney disease: a position paper from the European Cooperation in Science and Technology Action PARENCHIMA

Functional renal magnetic resonance imaging (MRI) has seen a number of recent advances, and techniques are now available that can generate quantitative imaging biomarkers with the potential to improve the management of kidney disease. Such biomarkers are sensitive to changes in renal blood flow, tissue perfusion, oxygenation and microstructure (including inflammation and fibrosis), processes that are important in a range of renal diseases including chronic kidney disease. However, several challenges remain to move these techniques towards clinical adoption, from technical validation through biological and clinical validation, to demonstration of cost-effectiveness and regulatory qualification. To address these challenges, the European Cooperation in Science and Technology Action PARENCHIMA was initiated in early 2017. PARENCHIMA is a multidisciplinary pan-European network with an overarching aim of eliminating the main barriers to the broader evaluation, commercial exploitation and clinical use of renal MRI biomarkers. This position paper lays out PARENCHIMA’s vision on key clinical questions that MRI must address to become more widely used in patients with kidney disease, first within research settings and ultimately in clinical practice. We then present a series of practical recommendations to accelerate the study and translation of these techniques

Effects of rare kidney diseases on kidney failure: a longitudinal analysis of the UK National Registry of Rare Kidney Diseases (RaDaR) cohort.

BACKGROUND: Individuals with rare kidney diseases account for 5-10% of people with chronic kidney disease, but constitute more than 25% of patients receiving kidney replacement therapy. The National Registry of Rare Kidney Diseases (RaDaR) gathers longitudinal data from patients with these conditions, which we used to study disease progression and outcomes of death and kidney failure. METHODS: People aged 0-96 years living with 28 types of rare kidney diseases were recruited from 108 UK renal care facilities. The primary outcomes were cumulative incidence of mortality and kidney failure in individuals with rare kidney diseases, which were calculated and compared with that of unselected patients with chronic kidney disease. Cumulative incidence and Kaplan-Meier survival estimates were calculated for the following outcomes: median age at kidney failure; median age at death; time from start of dialysis to death; and time from diagnosis to estimated glomerular filtration rate (eGFR) thresholds, allowing calculation of time from last eGFR of 75 mL/min per 1·73 m2 or more to first eGFR of less than 30 mL/min per 1·73 m2 (the therapeutic trial window). FINDINGS: Between Jan 18, 2010, and July 25, 2022, 27 285 participants were recruited to RaDaR. Median follow-up time from diagnosis was 9·6 years (IQR 5·9-16·7). RaDaR participants had significantly higher 5-year cumulative incidence of kidney failure than 2·81 million UK patients with all-cause chronic kidney disease (28% vs 1%; p<0·0001), but better survival rates (standardised mortality ratio 0·42 [95% CI 0·32-0·52]; p<0·0001). Median age at kidney failure, median age at death, time from start of dialysis to death, time from diagnosis to eGFR thresholds, and therapeutic trial window all varied substantially between rare diseases. INTERPRETATION: Patients with rare kidney diseases differ from the general population of individuals with chronic kidney disease: they have higher 5-year rates of kidney failure but higher survival than other patients with chronic kidney disease stages 3-5, and so are over-represented in the cohort of patients requiring kidney replacement therapy. Addressing unmet therapeutic need for patients with rare kidney diseases could have a large beneficial effect on long-term kidney replacement therapy demand. FUNDING: RaDaR is funded by the Medical Research Council, Kidney Research UK, Kidney Care UK, and the Polycystic Kidney Disease Charity