Integrative analysis of multi-omics data reveals importance of collagen and the PI3K AKT signalling pathway in CAKUT.

Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) is the leading cause of childhood chronic kidney failure and a significant cause of chronic kidney disease in adults. Genetic and environmental factors are known to influence CAKUT development, but the currently known disease mechanism remains incomplete. Our goal is to identify affected pathways and networks in CAKUT, and thereby aid in getting a better understanding of its pathophysiology. With this goal, the miRNome, peptidome, and proteome of over 30 amniotic fluid samples of patients with non-severe CAKUT was compared to patients with severe CAKUT. These omics data sets were made findable, accessible, interoperable, and reusable (FAIR) to facilitate their integration with external data resources. Furthermore, we analysed and integrated the omics data sets using three different bioinformatics strategies: integrative analysis with mixOmics, joint dimensionality reduction and pathway analysis. The three bioinformatics analyses provided complementary features, but all pointed towards an important role for collagen in CAKUT development and the PI3K-AKT signalling pathway. Additionally, several key genes (CSF1, IGF2, ITGB1, and RAC1) and microRNAs were identified. We published the three analysis strategies as containerized workflows. These workflows can be applied to other FAIR data sets and help gaining knowledge on other rare diseases.

Renal and Extrarenal Phenotypes in Patients With HNF1B Variants and Chromosome 17q12 Microdeletions.

Introduction: Hepatocyte nuclear factor 1-beta (HNF1B) gene variants or the chromosome 17q12 deletion (17q12del) represent the most common monogenic cause of developmental kidney disease. Although neurodevelopmental disorders have been associated with the 17q12del, specific genotype-phenotype associations with respect to kidney function evolution have not yet been fully defined. Here, we aimed to determine whether 17q12del or specific HNF1B variants were associated with kidney survival in a large patient population with HNF1B disease. Methods: This was a retrospective observational study involving 521 patients with HNF1B disease from 14 countries using the European Reference Network for rare kidney diseases with detailed information on the HNF1B genotype (HNF1B variants or the 17q12del). Median follow-up time was 11 years with 6 visits per patient. The primary end point was progression to chronic kidney disease (CKD) stage 3 (estimated glomerular filtration rate [eGFR] < 60 ml/min per 1.73 m2). Secondary end points were the development of hypomagnesemia or extrarenal disorders, including hyperuricemia and hyperglycemia. Results: Progression toward CKD stage 3 was significantly delayed in patients with the 17q12del compared to patients with HNF1B variants (hazard ratio [HR]: 0.29, 95% confidence interval [CI]: 0.19-0.44, P < 0.001). Progression toward CKD stage 3 was also significantly delayed when HNF1B variants involved the HNF1B Pit-1, Oct-1, and Unc-86 homeodomain (POUh) DNA-binding and transactivation domains rather than the POU-specific domain (POUs) DNA-binding domain (HR: 0.15 [95% CI: 0.06-0.37), P < 0.001 and HR: 0.25 (95% CI: 0.11-0.57), P = 0.001, respectively). Finally, the 17q12del was positively associated with hypomagnesemia and negatively associated with hyperuricemia, but not with hyperglycemia. Conclusion: Patients with the 17q12del display a significantly better kidney survival than patients with other HNF1B variants; and for the latter, variants in the POUs DNA-binding domain lead to the poorest kidney survival. These are clinically relevant HNF1B kidney genotype-phenotype correlations that inform genetic counseling.

Improved prenatal assessment of kidney disease using multiple ultrasound features.

BACKGROUND AND HYPOTHESIS: Congenital anomalies of the kidney and the urinary tract (CAKUT), often discovered in utero, cover a wide spectrum of outcomes ranging from normal postnatal kidney function to fetal death. The current ultrasound workup does not allow for an accurate assessment of the outcome. The present study aimed to significantly improve the ultrasound-based prediction of postnatal kidney survival in CAKUT. METHODS: Histological analysis of kidneys of 15 CAKUT fetuses was performed to better standardize the ultrasound interpretation of dysplasia and cysts. Ultrasound images of 140 CAKUT fetuses with 2-year postnatal follow-up were annotated for amniotic fluid volume and kidney number, size, dysplasia and/or cysts using standardized ultrasound readout. Association of ultrasound features and clinical data (sex and age at diagnosis) with postnatal kidney function was studied using logistic regression. Amniotic fluid proteome associated to kidney dysplasia or cysts was characterized by mass spectrometry. RESULTS: Histologically, poor ultrasound corticomedullary differentiation was associated to dysplastic lesions and ultrasound hyperechogenicity was associated to the presence of microcysts. Of all ultrasound and clinical parameters, reduced amniotic volume, dysplasia and cysts were the best predictors of poor outcome (Odd ratio = 57 [95%CI: 11-481], 20 [3-225] and 7 [1-100], respectively). Their combination into an algorithm improved prediction of postnatal kidney function compared to amniotic volume alone (area under the ROC curve = 0.92 [0.86-0.98] in a 10-fold cross validation). Dysplasia and cysts were correlated (Cramer's V coefficient = 0.44, p<0.0001), but amniotic fluid proteome analysis revealed that they had distinct molecular origin (extracellular matrix and cell contacts versus cellular death, respectively), probably explaining the additivity of their predictive performances. CONCLUSION: Antenatal clinical advice for CAKUT pregnancies can be improved by a more standardized and combined interpretation of ultrasound data.

Benefits and limits of decellularization on mass-spectrometry-based extracellular matrix proteome analysis of mouse kidney.

The extracellular matrix (ECM) is composed of collagens, ECM glycoproteins, and proteoglycans (also named core matrisome proteins) that are critical for tissue structure and function, and matrisome-associated proteins that balance the production and degradation of the ECM proteins. The identification and quantification of core matrisome proteins using mass spectrometry is often hindered by their low abundance and their propensity to form macromolecular insoluble structures. In this study, we aimed to investigate the added value of decellularization in identifying and quantifying core matrisome proteins in mouse kidney. The decellularization strategy combined freeze-thaw cycles and sodium dodecyl sulphate treatment. We found that decellularization preserved 95% of the core matrisome proteins detected in non-decellularized kidney and revealed few additional ones. Decellularization also led to an average of 59 times enrichment of 96% of the core matrisome proteins as the result of the successful removal of cellular and matrisome-associated proteins. However, the enrichment varied greatly among core matrisome proteins, resulting in a misrepresentation of the native ECM composition in decellularized kidney. This should be brought to the attention of the matrisome research community, as it highlights the need for caution when interpreting proteomic data obtained from a decellularized organ.

Performances of acute kidney injury biomarkers vary according to sex.

Background: Before implementing individualized strategies to treat acute kidney injury (AKI), identifying clusters of patients with divergent pathophysiological mechanisms, diagnosis criteria or outcomes is of the utmost importance. Here we studied sex-related molecular mechanisms in cardiac bypass (CBP) surgery patients developing AKI. Methods: We compared the characteristics of 1170 patients referred for CBP surgery using multivariate logistic regression and propensity score-based analysis. Performances of the candidate urinary biomarkers at <4 h post-surgery, urinary neutrophil gelatinase-associated lipocalin (uNGAL), [IGFBP7]·[TIMP-2] product (NephroCheck) and a recently developed AKI signature of 204 urinary peptides (AKI204) to predict AKI were compared in both sexes. Results: Incidence (∼25%) and severity of AKI were similar in men and women, even after adjustment for the usual risk factors of AKI, including baseline estimated glomerular filtration rate, age, diabetes mellitus, length of CBP and red blood cell transfusion. However, at the molecular level, performances of uNGAL, NephroCheck and AKI204 to predict AKI strongly diverged between men and women. In the full cohort, as well as in subgroups of men and women, the multimarker AKI204 signature outperformed uNGAL and NephroCheck and predicted the development of AKI significantly better in women than in men. Analysis of AKI204 at the single-peptide level suggested divergences of AKI mechanisms between sexes due to increased kidney inflammation in women (increased abundance of urinary fragments of osteopontin and uromodulin). Conclusions: In patients referred for CBP surgery, significant clinical and biological differences between men and women as well as sexual dimorphism of AKI biomarker performances were identified. The urinary peptide signature points to sex-related molecular mechanisms underlying AKI.

Gestational Age-Related Urinary Peptidome Changes in Preterm and Term Born Infants.

INTRODUCTION: Preterm infants are at risk for a variety of somatic and neurological disorders. In recent years, biofluid proteomics has emerged as a potential diagnostic tool for biomarker analysis. The aim of this study was to determine gestational age (GA)-related patterns of the urinary peptidome in preterm infants for researching potential novel prognostic biomarkers. METHODS: We performed urinary peptidomics in longitudinal samples of 24 preterm (mean GA weeks 28 + 1 [24+1-31 + 6]) and 27 term born controls (mean GA weeks 39 + 2 [37+0-41 + 1]) using capillary electrophoresis combined with mass spectrometry (CE-MS). Peptides were sequenced using CE-MS/MS or LC-MS/MS analysis and were deposited, matched, and annotated in a Microsoft SQL database for statistical analysis. We compared their abundance in urine of preterm and term born infants and performed a validation analysis as well as correlations to GA and clinical risk scores. RESULTS: Our results confirmed significant differences in the abundance of peptides and the hypothesis of age-dependent urinary peptidome changes in preterm and term infants. In preterm infants, SLC38A10 (solute carrier family 38 member 10) is one of the most abundant peptides. Combined urinary peptides correlated with clinical risk scores (p < 0.05). CONCLUSION: This is the first study reporting GA-related urinary peptidome changes of preterm infants detected by CE-MS and a modulation of the peptidome with GA. Further research is required to locate peptidome clusters correlated with specific clinical complications and long-term outcome. This may identify preterm infants at higher risk for adverse outcome who would benefit from early intervention.

CCL7 Chemokine Is a Marker but Not a Therapeutic Target of Acute Kidney Injury.

BACKGROUND: Chemokines orchestrate immune cells activation and infiltration during acute kidney injury (AKI). OBJECTIVES: We aim to test whether deletion of C-C chemokine ligand 7 (CCL7), a small chemokine related to CCL2 (MCP-1), may modulate AKI development and progression toward kidney fibrosis. METHOD: Expression of CCL7 was quantified in murine cortical tubular (MCT) cells exposed to myoglobin or lipopolysaccharide or submitted to metabolic reprogramming. Kidney function (BUN, glomerular filtration rate), expression of CCL7 receptors, and kidney infiltration by inflammatory cells (F4/80+ macrophages, MPO+ neutrophils, and B220+ B-cells) were assessed in wt and Ccl7-/- mice submitted to 3 different models of AKI or kidney fibrosis (uni/bilateral ischemia/reperfusion injury (u/bIRI) and rhabdomyolysis). RESULTS: Toxin exposure of MCT cells, as well as metabolic reprogramming recapitulating AKI changes, led to a dramatic up-regulation of CCL7. In vivo, kidney expression of Ccl7 and Ccl2 significantly increased after AKI and remained increased beyond the acute phase (30 days after uIRI). The expression of the CCL7 receptors was heterogeneous and varied with time. Kidney function, expression of CCL7 receptors and Ccl2, and the number of inflammatory cells within kidneys were similar in wt and Ccl7-/- mice at baseline and at day 2 after AKI. Thirty days after uIRI, kidney fibrosis was similar in both mouse strains. CONCLUSIONS: Despite strong induction of CCL7 after AKI, CCL7 deficiency does not prevent AKI and the transition toward kidney fibrosis and should probably not be further explored as a potential target to prevent or treat AKI.

Fetal biomarkers for lower urinary tract obstruction secondary to posterior urethral valves.

Today, prenatal diagnosis of congenital urogenital malformations is mostly dependent on anatomical variations found on imaging. However, these findings can mislead us in telling us when to intervene, and about post-natal prognosis. Since many findings are dependent on multiple assessments, delayed diagnosis can occur, leading to less optimal outcomes compared to early intervention. Analyses of fetal urinary biomarkers have been proposed as a method of finding biological changes that are predictive for diagnosis and prognosis in fetuses at risk of kidney disease. We interviewed a group of researchers that have demonstrated that by combining multiple omics traits extracted from fetal urine, the biological variability found in single omics data can be circumvented. By analyzing multiple fetal urine peptides and metabolites at single time point, the prognostic power of postnatal renal outcome in fetuses with lower urinary tract obstruction is significantly increased. In this interview, we inquired about the technical aspects of the tests, challenges, and limitations the research group have come across, and how they envision the future for multi-omics fetal analysis in the clinic.

Urinary peptidomic liquid biopsy for non-invasive differential diagnosis of chronic kidney disease.

BACKGROUND AND HYPOTHESIS: Specific urinary peptides hold information on disease pathophysiology, which, in combination with artificial intelligence, could enable non-invasive assessment of chronic kidney disease (CKD) aetiology. Existing approaches are generally specific for the diagnosis of single aetiologies. We present the development of models able to simultaneously distinguish and spatially visualize multiple CKD aetiologies. METHODS: The urinary peptide data of 1850 healthy control (HC) and CKD [diabetic kidney disease (DKD), immunoglobulin A nephropathy (IgAN) and vasculitis] participants were extracted from the Human Urinary Proteome Database. Uniform manifold approximation and projection (UMAP) coupled to a support vector machine algorithm was used to generate multi-peptide models to perform binary (DKD, HC) and multiclass (DKD, HC, IgAN, vasculitis) classifications. This pipeline was compared with the current state-of-the-art single-aetiology CKD urinary peptide models. RESULTS: In an independent test set, the developed models achieved 90.35% and 70.13% overall predictive accuracies, respectively, for the binary and the multiclass classifications. Omitting the UMAP step led to improved predictive accuracies (96.14% and 85.06%, respectively). As expected, the HC class was distinguished with the highest accuracy. The different classes displayed a tendency to form distinct clusters in the 3D space based on their disease state. CONCLUSION: Urinary peptide data present an effective basis for CKD aetiology differentiation using machine learning models. Although adding the UMAP step to the models did not improve prediction accuracy, it may provide a unique visualization advantage. Additional studies are warranted to further validate the pipeline's clinical potential as well as to expand it to other CKD aetiologies and also other diseases.

Single-cell RNA sequencing identifies senescence as therapeutic target in rhabdomyolysis-induced acute kidney injury.

BACKGROUND: The role of macrophages in the development of rhabdomyolysis-induced acute kidney injury (RM-AKI) has been established, but an in-depth understanding of the changes in the immune landscape could help to improve targeted strategies. Whereas senescence is usually associated with chronic kidney processes, we also wished to explore whether senescence could also occur in AKI and whether senolytics could act on immune cells. METHODS: Single-cell RNA sequencing was used in the murine glycerol-induced RM-AKI model to dissect the transcriptomic characteristics of CD45+ live cells sorted from kidneys 2 days after injury. Public datasets from murine AKI models were reanalysed to explore cellular senescence signature in tubular epithelial cells (TECs). A combination of senolytics (dasatinib and quercetin, DQ) was administered to mice exposed or not to RM-AKI. RESULTS: Unsupervised clustering of nearly 17 000 single-cell transcriptomes identified seven known immune cell clusters. Sub-clustering of the mononuclear phagocyte cells revealed nine distinct cell sub-populations differently modified with RM. One macrophage cluster was particularly interesting since it behaved as a critical node in a trajectory connecting one major histocompatibility complex class IIhigh (MHCIIhigh) cluster only present in Control to two MHCIIlow clusters only present in RM-AKI. This critical cluster expressed a senescence gene signature, that was very different from that of the TECs. Senolytic DQ treatment blocked the switch from a F4/80highCD11blow to F4/80lowCD11bhigh phenotype, which correlated with prolonged nephroprotection in RM-AKI. CONCLUSIONS: Single-cell RNA sequencing unmasked novel transitional macrophage subpopulation associated with RM-AKI characterized by the activation of cellular senescence processes. This work provides a proof-of-concept that senolytics nephroprotective effects may rely, at least in part, on subtle immune modulation.

Abcc6 deficiency prevents rhabdomyolysis-induced acute kidney injury.

Rhabdomyolysis is a risk factor for acute kidney injury, transition towards chronic kidney disease, and death. The role of calcium phosphate deposits in the mechanisms of rhabdomyolysis-induced acute kidney injury (RAKI) is still unclear. Better insight of the role calcium in RAKI could lead to new therapeutic avenues. Here, we show in a mice model of RAKI that calcium phosphate deposits were frequent in the kidney (hydroxyapatite) and partly correlated with the severity of the kidney injury. However, the intensity of deposits was highly heterogeneous between mice. Treatment with sodium chloride, sodium bicarbonate or inorganic pyrophosphate (PPi; an inhibitor of the calcium phosphate crystallization), or combinations thereof, did not improve kidney outcomes and hydroxyapatite deposition during RAKI. Unexpectedly, Abcc6 knockout mice (ko), characterized by PPi deficiency, developed less severe RAKI despite similar rhabdomyolysis severity, and had similar hydroxyapatite deposition suggesting alternative mechanisms. This improved kidney outcome at day 2 translated to a trend in improved glomerular filtration rate at month 2 in Abcc6-/-mice and to significantly less interstitial fibrosis. In addition, whereas the pattern of infiltrating cells at day 2 was similar between wt and ko mice, kidneys of Abcc6-/- mice were characterized by more CD19+ B-cells, less CD3+ T-cells and a lower R1/R2 macrophage ratio at month 2. In summary, kidney calcium phosphate deposits are frequent in RAKI but hydration with sodium bicarbonate or sodium chloride does not modify the kidney outcome. Blocking ABCC6 emerges as a new option to prevent RAKI and subsequent transition toward kidney fibrosis.

Calprotectin is a contributor to and potential therapeutic target for vascular calcification in chronic kidney disease.

Vascular calcification is an important risk factor for cardiovascular (CV) mortality in patients with chronic kidney disease (CKD). It is also a complex process involving osteochondrogenic differentiation of vascular smooth muscle cells (VSMCs) and abnormal deposition of minerals in the vascular wall. In an observational, multicenter European study, including 112 patients with CKD from Spain and 171 patients on dialysis from France, we used serum proteome analysis and further validation by ELISA to identify calprotectin, a circulating damage-associated molecular pattern protein, as being independently associated with CV outcome and mortality. This was confirmed in an additional cohort of 170 patients with CKD from Sweden, where increased serum calprotectin concentrations correlated with increased vascular calcification. In primary human VSMCs and mouse aortic rings, calprotectin exacerbated calcification. Treatment with paquinimod, a calprotectin inhibitor, as well as pharmacological inhibition of the receptor for advanced glycation end products and Toll-like receptor 4 inhibited the procalcifying effect of calprotectin. Paquinimod also ameliorated calcification induced by the sera of uremic patients in primary human VSMCs. Treatment with paquinimod prevented vascular calcification in mice with chronic renal failure induced by subtotal nephrectomy and in aged apolipoprotein E-deficient mice as well. These observations identified calprotectin as a key contributor of vascular calcification, and increased circulating calprotectin was strongly and independently associated with calcification, CV outcome, and mortality in patients with CKD. Inhibition of calprotectin might therefore be a promising strategy to prevent vascular calcification in patients with CKD.

Prognosis and Personalized In Silico Prediction of Treatment Efficacy in Cardiovascular and Chronic Kidney Disease: A Proof-of-Concept Study.

(1) Background: Kidney and cardiovascular diseases are responsible for a large fraction of population morbidity and mortality. Early, targeted, personalized intervention represents the ideal approach to cope with this challenge. Proteomic/peptidomic changes are largely responsible for the onset and progression of these diseases and should hold information about the optimal means of treatment and prevention. (2) Methods: We investigated the prediction of renal or cardiovascular events using previously defined urinary peptidomic classifiers CKD273, HF2, and CAD160 in a cohort of 5585 subjects, in a retrospective study. (3) Results: We have demonstrated a highly significant prediction of events, with an HR of 2.59, 1.71, and 4.12 for HF, CAD, and CKD, respectively. We applied in silico treatment, implementing on each patient's urinary profile changes to the classifiers corresponding to exactly defined peptide abundance changes, following commonly used interventions (MRA, SGLT2i, DPP4i, ARB, GLP1RA, olive oil, and exercise), as defined in previous studies. Applying the proteomic classifiers after the in silico treatment indicated the individual benefits of specific interventions on a personalized level. (4) Conclusions: The in silico evaluation may provide information on the future impact of specific drugs and interventions on endpoints, opening the door to a precision-based medicine approach. An investigation into the extent of the benefit of this approach in a prospective clinical trial is warranted.

Urinary peptides provide information about the risk of mortality across a spectrum of diseases and scenarios.

BACKGROUND: There is evidence of pre-established vulnerability in individuals that increases the risk of their progression to severe disease or death, although the mechanisms causing this are still not fully understood. Previous research has demonstrated that a urinary peptide classifier (COV50) predicts disease progression and death from SARS-CoV-2 at an early stage, indicating that the outcome prediction may be partly due to vulnerabilities that are already present. The aim of this study is to examine the ability of COV50 to predict future non-COVID-19-related mortality, and evaluate whether the pre-established vulnerability can be generic and explained on a molecular level by urinary peptides. METHODS: Urinary proteomic data from 9193 patients (1719 patients sampled at intensive care unit (ICU) admission and 7474 patients with other diseases (non-ICU)) were extracted from the Human Urinary Proteome Database. The previously developed COV50 classifier, a urinary proteomics biomarker panel consisting of 50 peptides, was applied to all datasets. The association of COV50 scoring with mortality was evaluated. RESULTS: In the ICU group, an increase in the COV50 score of one unit resulted in a 20% higher relative risk of death [adjusted HR 1.2 (95% CI 1.17-1.24)]. The same increase in COV50 in non-ICU patients resulted in a higher relative risk of 61% [adjusted HR 1.61 (95% CI 1.47-1.76)], consistent with adjusted meta-analytic HR estimate of 1.55 [95% CI 1.39-1.73]. The most notable and significant changes associated with future fatal events were reductions of specific collagen fragments, most of collagen alpha I (I). CONCLUSION: The COV50 classifier is predictive of death in the absence of SARS-CoV-2 infection, suggesting that it detects pre-existing vulnerability. This prediction is mainly based on collagen fragments, possibly reflecting disturbances in the integrity of the extracellular matrix. These data may serve as a basis for proteomics-guided intervention aiming towards manipulating/ improving collagen turnover, thereby reducing the risk of death.

Machine Learning-Based Urine Peptidome Analysis to Predict and Understand Mechanisms of Progression to Kidney Failure.

Introduction: The identification of patients with chronic kidney disease (CKD) at risk of progressing to kidney failure (KF) is important for clinical decision-making. In this study we assesed whether urinary peptidome (UP) analysis may help classify patients with CKD and improve KF risk prediction. Methods: The UP was analyzed using capillary electrophoresis coupled to mass spectrometry in a case-cohort sample of 1000 patients with CKD stage G3 to G5 from the French CKD-Renal Epidemiology and Information Network (REIN) cohort. We used unsupervised and supervised machine learning to classify patients into homogenous UP clusters and to predict 3-year KF risk with UP, respectively. The predictive performance of UP was compared with the KF risk equation (KFRE), and evaluated in an external cohort of 326 patients. Results: More than 1000 peptides classified patients into 3 clusters with different CKD severities and etiologies at baseline. Peptides with the highest discriminative power for clustering were fragments of proteins involved in inflammation and fibrosis, highlighting those derived from α-1-antitrypsin, a major acute phase protein with anti-inflammatory and antiapoptotic properties, as the most significant. We then identified a set of 90 urinary peptides that predicted KF with a c-index of 0.83 (95% confidence interval [CI]: 0.81-0.85) in the case-cohort and 0.89 (0.83-0.94) in the external cohort, which were close to that estimated with the KFRE (0.85 [0.83-0.87]). Combination of UP with KFRE variables did not further improve prediction. Conclusion: This study shows the potential of UP analysis to uncover new pathophysiological CKD progression pathways and to predict KF risk with a performance equal to that of the KFRE.

A universal predictive and mechanistic urinary peptide signature in acute kidney injury.

BACKGROUND: The delayed diagnosis of acute kidney injury (AKI) episodes and the lack of specificity of current single AKI biomarkers hamper its management. Urinary peptidome analysis may help to identify early molecular changes in AKI and grasp its complexity to identify potential targetable molecular pathways. METHODS: In derivation and validation cohorts totalizing 1170 major cardiac bypass surgery patients and in an external cohort of 1569 intensive care unit (ICU) patients, a peptide-based score predictive of AKI (7-day KDIGO classification) was developed, validated, and compared to the reference biomarker urinary NGAL and NephroCheck and clinical scores. RESULTS: A set of 204 urinary peptides derived from 48 proteins related to hemolysis, inflammation, immune cells trafficking, innate immunity, and cell growth and survival was identified and validated for the early discrimination (< 4 h) of patients according to their risk to develop AKI (OR 6.13 [3.96-9.59], p < 0.001) outperforming reference biomarkers (urinary NGAL and [IGFBP7].[TIMP2] product) and clinical scores. In an external cohort of 1569 ICU patients, performances of the signature were similar (OR 5.92 [4.73-7.45], p < 0.001), and it was also associated with the in-hospital mortality (OR 2.62 [2.05-3.38], p < 0.001). CONCLUSIONS: An overarching AKI physiopathology-driven urinary peptide signature shows significant promise for identifying, at an early stage, patients who will progress to AKI and thus to develop tailored treatments for this frequent and life-threatening condition. Performance of the urine peptide signature is as high as or higher than that of single biomarkers but adds mechanistic information that may help to discriminate sub-phenotypes of AKI offering new therapeutic avenues.

Refining Kidney Survival in 383 Genetically Characterized Patients With Nephronophthisis.

Introduction: Nephronophthisis (NPH) comprises a group of rare disorders accounting for up to 10% of end-stage kidney disease (ESKD) in children. Prediction of kidney prognosis poses a major challenge. We assessed differences in kidney survival, impact of variant type, and the association of clinical characteristics with declining kidney function. Methods: Data was obtained from 3 independent sources, namely the network for early onset cystic kidney diseases clinical registry (n = 105), an online survey sent out to the European Reference Network for Rare Kidney Diseases (n = 60), and a literature search (n = 218). Results: A total of 383 individuals were available for analysis: 116 NPHP1, 101 NPHP3, 81 NPHP4 and 85 NPHP11/TMEM67 patients. Kidney survival differed between the 4 cohorts with a highly variable median age at onset of ESKD as follows: NPHP3, 4.0 years (interquartile range 0.3-12.0); NPHP1, 13.5 years (interquartile range 10.5-16.5); NPHP4, 16.0 years (interquartile range 11.0-25.0); and NPHP11/TMEM67, 19.0 years (interquartile range 8.7-28.0). Kidney survival was significantly associated with the underlying variant type for NPHP1, NPHP3, and NPHP4. Multivariate analysis for the NPHP1 cohort revealed growth retardation (hazard ratio 3.5) and angiotensin-converting enzyme inhibitor (ACEI) treatment (hazard ratio 2.8) as 2 independent factors associated with an earlier onset of ESKD, whereas arterial hypertension was linked to an accelerated glomerular filtration rate (GFR) decline. Conclusion: The presented data will enable clinicians to better estimate kidney prognosis of distinct patients with NPH and thereby allow personalized counseling.