Differentiated mouse kidney tubuloids as a novel in vitro model to study collecting duct physiology.

Kidney tubuloids are cell models that are derived from human or mouse renal epithelial cells and show high similarities with their in vivo counterparts. Tubuloids grow polarized in 3D, allow for long-term expansion, and represent multiple segments of the nephron, as shown by their gene expression pattern. In addition, human tubuloids form tight, functional barriers and have been succesfully used for drug testing. Our knowledge of mouse tubuloids, on the other hand, is only minimal. In this study, we further characterized mouse tubuloids and differentiated them towards the collecting duct, which led to a significant upregulation of collecting duct-specific mRNAs of genes and protein expression, including the water channel AQP2 and the sodium channel ENaC. Differentiation resulted in polarized expression of collecting duct water channels AQP2 and AQP3. Also, a physiological response to desmopressin and forskolin stimulation by translocation of AQP2 to the apical membrane was demonstrated. Furthermore, amiloride-sensitive ENaC-mediated sodium uptake was shown in differentiated tubuloids using radioactive tracer sodium. This study demonstrates that mouse tubuloids can be differentiated towards the collecting duct and exhibit collecting duct-specific function. This illustrates the potential use of mouse kidney tubuloids as novel in vitro models to study (patho)physiology of kidney diseases.

Deep learning body-composition analysis of clinically acquired CT-scans estimates creatinine excretion with high accuracy in patients and healthy individuals.

Assessment of daily creatinine production and excretion plays a crucial role in the estimation of renal function. Creatinine excretion is estimated by creatinine excretion equations and implicitly in eGFR equations like MDRD and CKD-EPI. These equations are however unreliable in patients with aberrant body composition. In this study we developed and validated equations estimating creatinine production using deep learning body-composition analysis of clinically acquired CT-scans. We retrospectively included patients in our center that received any CT-scan including the abdomen and had a 24-h urine collection within 2 weeks of the scan (n = 636). To validate the equations in healthy individuals, we included a kidney donor dataset (n = 287). We used a deep learning algorithm to segment muscle and fat at the 3rd lumbar vertebra, calculate surface areas and extract radiomics parameters. Two equations for CT-based estimate of RenAl FuncTion (CRAFT 1 including CT parameters, age, weight, and stature and CRAFT 2 excluding weight and stature) were developed and compared to the Cockcroft-Gault and the Ix equations. CRAFT1 and CRAFT 2 were both unbiased (MPE = 0.18 and 0.16 mmol/day, respectively) and accurate (RMSE = 2.68 and 2.78 mmol/day, respectively) in the patient dataset and were more accurate than the Ix (RMSE = 3.46 mmol/day) and Cockcroft-Gault equation (RMSE = 3.52 mmol/day). In healthy kidney donors, CRAFT 1 and CRAFT 2 remained unbiased (MPE = - 0.71 and - 0.73 mmol/day respectively) and accurate (RMSE = 1.86 and 1.97 mmol/day, respectively). Deep learning-based extraction of body-composition parameters from abdominal CT-scans can be used to reliably estimate creatinine production in both patients as well as healthy individuals. The presented algorithm can improve the estimation of renal function in patients who have recently had a CT scan. The proposed methods provide an improved estimation of renal function that is fully automatic and can be readily implemented in routine clinical practice.

GFR estimation is complicated by a high incidence of non-steady-state serum creatinine concentrations at the emergency department.

BACKGROUND: Acquiring a reliable estimate of glomerular filtration rate (eGFR) at the emergency department (ED) is important for clinical management and for dosing renally excreted drugs. However, renal function formulas such as CKD-EPI can give biased results when serum creatinine (SCr) is not in steady-state because the assumption that urinary creatinine excretion is constant is then invalid. We assessed the extent of this by analysing variability in SCr in patients who visited the ED of a tertiary care centre. METHODS: Data from ED visits at the University Medical Centre Utrecht, the Netherlands between 2012 and 2019 were extracted from the Utrecht Patient Oriented Database. Three measurement time points were defined for each visit: last SCr measurement before visit as baseline (SCr-BL), first measurement during visit (SCr-ED) and a subsequent measurement between 6 and 24 hours during admission (SCr-H1). Non-steady-state SCr was defined as exceeding the Reference Change Value (RCV), with 15% decrease or 18% increase between successive SCr measurements. Exceeding the RCV was deemed as a significant change. RESULTS: Of visits where SCr-BL and SCr-ED were measured (N = 47,540), 28.0% showed significant change in SCr. Of 17,928 visits admitted to the hospital with a SCr-H1 after SCr-ED, 27,7% showed significant change. More than half (55%) of the patients with SCr values available at all three timepoints (11,054) showed at least one significant change in SCr over time. CONCLUSION: One third of ED visits preceded and/or followed by creatinine measurement show non-stable serum creatinine concentration. At the ED automatically calculated eGFR should therefore be interpreted with great caution when assessing kidney function.

Defining the variety of cell types in developing and adult human kidneys by single-cell RNA sequencing.

The kidney is among the most complex organs in terms of the variety of cell types. The cellular complexity of human kidneys is not fully unraveled and this challenge is further complicated by the existence of multiple progenitor pools and differentiation pathways. Researchers disagree on the variety of renal cell types due to a lack of research providing a comprehensive picture and the challenge to translate findings between species. To find an answer to the number of human renal cell types, we discuss research that used single-cell RNA sequencing on developing and adult human kidney tissue and compares these findings to the literature of the pre-single-cell RNA sequencing era. We find that these publications show major steps towards the discovery of novel cell types and intermediate cell stages as well as complex molecular signatures and lineage pathways throughout development. The variety of cell types remains variable in the single-cell literature, which is due to the limitations of the technique. Nevertheless, our analysis approaches an accumulated number of 41 identified cell populations of renal lineage and 32 of non-renal lineage in the adult kidney, and there is certainly much more to discover. There is still a need for a consensus on a variety of definitions and standards in single-cell RNA sequencing research, such as the definition of what is a cell type. Nevertheless, this early-stage research already proves to be of significant impact for both clinical and regenerative medicine, and shows potential to enhance the generation of sophisticated in vitro kidney tissue.

[Pharmacotherapy in patients with loss of renal function]. / Farmacotherapie bij nierfunctieverlies.

When dosing renally excreted drugs in patients with kidney disease, it is important to have a reliable estimate of renal function. The estimated glomerular filtration rate (eGFR) is often used in the clinic, although this measure can be inaccurate in certain situations. Choosing the appropriate drug and dosage should therefore not be solely based on the eGFR. In this review, we discuss the physiology behind renal function estimation and drug dosing and propose a step by step approach to dosing renally excreted drugs in patients with kidney disease.

Dalteparin and anti-Xa: a complex interplay of therapeutic drug monitoring.

BACKGROUND: Monitoring low-molecular-weight heparins is generally not required. However, guidelines advise to monitor anti-Xa levels in patients with renal insufficiency or a BMI above 50, and in pregnancy. Measuring anti-Xa levels is a complex challenge since sampling should be performed three to five hours after subcutaneous injection and after steady state concentrations have been reached. Strict compliance is pivotal for justified dose adjustments. OBJECTIVES: We questioned compliance to our protocol and performed this study to explore that. METHODS: This retrospective cohort study included patients ≥ 18 years receiving therapeutic dalteparin in a Dutch academic medical centre. Patients with a first anti-Xa level measured between February 23rd and December 30th, 2017 were selected. According to our local guideline, monitoring anti-Xa activity is indicated in patients on therapeutic doses of dalteparin who are pregnant, morbidly obese (BMI > 50), or have renal insufficiency (clearance < 60 ml/min). Accurate sampling was defined as measuring levels after at least three injections (after which a patient may reach steady state) and then four hours after the injection with dalteparin. The frequency of compliance to our protocol was assessed. RESULTS: We included 158 patients with 396 anti-Xa levels, of which 41% (65/158) of all first anti-Xa levels were drawn without appropriate indication. Almost half, 48% (211/396), were sampled incorrectly and 25% of these (53/211) were followed by a dose adjustment. In total, 74% (293/396) of the samples were not indicated or were taken at the wrong time. CONCLUSIONS: Monitoring anti-Xa levels is a complex clinical challenge. This study showed that non-compliance with recommendations for anti-Xa monitoring was high, often resulting in unjustified dose adjustments.

Mortality due to bleeding, myocardial infarction and stroke in dialysis patients.

Essentials Mortality due to bleeding vs. arterial thrombosis in dialysis patients is unknown. We compared death causes of 201 918 dialysis patients with the general population. Dialysis was associated with increased mortality risks of bleeding and arterial thrombosis. Clinicians should be aware of the increased bleeding and thrombosis risks. SUMMARY: Background Dialysis has been associated with both bleeding and thrombotic events. However, there is limited information on bleeding as a cause of death versus arterial thrombosis as a cause of death. Objectives To investigate the occurrence of bleeding, myocardial infarction and stroke as causes of death in the dialysis population as compared with the general population. Methods We included 201 918 patients from 11 countries providing data to the ERA-EDTA Registry who started dialysis treatment between 1994 and 2011, and followed them for 3 years. Age-standardized and sex-standardized mortality rate ratios for bleeding, myocardial infarction and stroke as causes of death were calculated in dialysis patients as compared with the European general population. Associations between potential risk factors and these causes of death in dialysis patients were investigated by calculating hazard ratios (HRs) with 95% confidence intervals (CIs) by the use of Cox proportional-hazards regression. Results As compared with the general population, the age-standardized and sex-standardized mortality rate ratios in dialysis patients were 12.8 (95% CI 11.9-13.7) for bleeding as a cause of death (6.2 per 1000 person-years among dialysis patients versus 0.3 per 1000 person-years in the general population), 13.4 (95% CI 13.0-13.9) for myocardial infarction (22.5 versus 0.9 per 1000 person-years), and 12.4 (95% CI 11.9-12.9) for stroke (14.3 versus 0.7 per 1000 person-years). Conclusion Dialysis patients have highly increased risks of death caused by bleeding and arterial thrombosis as compared with the general population. Clinicians should be aware of the increased mortality risks caused by these conditions.

Chronic kidney disease and bleeding risk in patients at high cardiovascular risk: a cohort study.

Essentials The association between chronic kidney disease and bleeding is unknown. We followed 10 347 subjects at high cardiovascular risk for bleeding events. Chronic kidney disease was associated with a 1.5-fold increased bleeding risk. Especially albuminuria rather than decreased kidney function was associated with bleeding events. SUMMARY: Background There are indications that patients with chronic kidney disease have an increased bleeding risk. Objectives To investigate the association between chronic kidney disease and bleeding in patients at high cardiovascular risk. Methods We included 10 347 subjects referred to the University Medical Center Utrecht (the Netherlands) from September 1996 to February 2015 for an outpatient visit with classic risk factors for arterial disease or with symptomatic arterial disease (Second Manifestation of Arterial disease [SMART] cohort). Patients were staged according to the KDIGO guidelines, on the basis of estimated glomerular filtration rate (eGFR) and albuminuria, and were followed for the occurrence of major hemorrhagic events until March 2015. Hazard ratios (HRs) with 95% confidence intervals (CIs) for bleeding were calculated with Cox proportional hazards analyses. Results The incidence rate for bleeding in subjects with chronic kidney disease was 8.0 per 1000 person-years and that for subjects without chronic kidney disease was 3.5 per 1000 person-years. Patients with chronic kidney disease (n = 2443) had a 1.5-fold (95% CI 1.2-1.9) increased risk of bleeding as compared with subjects without chronic kidney disease (n = 7904) after adjustment. Subjects with an eGFR of < 45 mL min-1  1.73 m-2 with albuminuria had a 3.5-fold (95% CI 2.3-5.3) increased bleeding risk, whereas an eGFR of < 45 mL min-1  1.73 m-2 without albuminuria was not associated with an increased bleeding risk (HR 1.3, 95% CI 0.7-2.5). Conclusion Chronic kidney disease is a risk factor for bleeding in patients with classic risk factors for arterial disease or with symptomatic arterial disease, especially in the presence of albuminuria.