New insights in molecular mechanisms involved in chronic kidney disease using high-resolution plasma proteome analysis

Integrated metabolomics and proteomics reveal biomarkers associated with hemodialysis in end-stage kidney disease

Background: We hypothesize that the poor survival outcomes of end-stage kidney disease (ESKD) patients undergoing hemodialysis are associated with a low filtering efficiency and selectivity. The current gold standard criteria using single or several markers show an inability to predict or disclose the treatment effect and disease progression accurately. Methods: We performed an integrated mass spectrometry-based metabolomic and proteomic workflow capable of detecting and quantifying circulating small molecules and proteins in the serum of ESKD patients. Markers linked to cardiovascular disease (CVD) were validated on human induced pluripotent stem cell (iPSC)-derived cardiomyocytes. Results: We identified dozens of elevated molecules in the serum of patients compared with healthy controls. Surprisingly, many metabolites, including lipids, remained at an elevated blood concentration despite dialysis. These molecules and their associated physical interaction networks are correlated with clinical complications in chronic kidney disease. This study confirmed two uremic toxins associated with CVD, a major risk for patients with ESKD. Conclusion: The retained molecules and metabolite-protein interaction network address a knowledge gap of candidate uremic toxins associated with clinical complications in patients undergoing dialysis, providing mechanistic insights and potential drug discovery strategies for ESKD.

Leucine-Rich Alpha-2 Glycoprotein 1 Accumulates in Complicated Atherosclerosis and Promotes Calcification

Atherosclerosis is the primary cause of cardiovascular disease. The development of plaque complications, such as calcification and neo-angiogenesis, strongly impacts plaque stability and is a good predictor of mortality in patients with atherosclerosis. Despite well-known risk factors of plaque complications, such as diabetes mellitus and chronic kidney disease, the mechanisms involved are not fully understood. We and others have identified that the concentration of circulating leucine-rich α-2 glycoprotein 1 (LRG1) was increased in diabetic and chronic kidney disease patients. Using apolipoprotein E knockout mice (ApoE-/-) (fed with Western diet) that developed advanced atherosclerosis and using human carotid endarterectomy, we showed that LRG1 accumulated into an atherosclerotic plaque, preferentially in calcified areas. We then investigated the possible origin of LRG1 and its functions on vascular cells and found that LRG1 expression was specifically enhanced in endothelial cells via inflammatory mediators and not in vascular smooth muscle cells (VSMC). Moreover, we identified that LRG1 was able to induce calcification and SMAD1/5-signaling pathways in VSMC. In conclusion, our results identified for the first time that LRG1 is a direct contributor to vascular calcification and suggest a role of this molecule in the development of plaque complications in patients with atherosclerosis.

Relationship between plasma leucine-rich α-2-glycoprotein 1 and urinary albumin excretion in patients with type 2 diabetes

Aims

To explore the relationship between plasma leucine-rich α-2-glycoprotein 1 (LRG1) level and the degree of urinary albumin excretion in patients with type 2 diabetes.

Methods

We evaluated 332 patients with type 2 diabetes in a cross-sectional study.

Result

The plasma LRG1 level differed significantly according to the quartiles of urinary albumin excretion (Q1 [<7.7 mg/g], 17.1 μg/mL; Q2 [7.7-15.0 mg/g], 17.5 μg/mL; Q3 [15.1-61.4 mg/g], 18.6 μg/mL; Q4 [≥61.5 mg/g], 22.3 μg/mL; p for trend = 0.003) under adjustment with other covariates. A positive correlation was found between plasma LRG1 level and urinary albumin excretion (ρ = 0.256, p <0.001). According to a multivariate model, the association between LRG1 and urinary albumin excretion remained significant, under adjustment for confounding factors (β = 0.285, p <0.001).

Conclusion

Plasma LRG1 level was independently associated with urinary albumin excretion in patients with type 2 diabetes. This study suggests that LRG1 may be associated with increased excretion of urinary albumin in the early stages of diabetic nephropathy.

Circulating Proteins and Mortality in CKD: A Proteomics Study of the AASK and ARIC Cohorts

Rationale & Objective

Proteomics could provide pathophysiologic insight into the increased risk of mortality in patients with chronic kidney disease (CKD). This study aimed to investigate associations between the circulating proteome and all-cause mortality among patients with CKD.

Study Design

Observational cohort study.

Setting & Participants

Primary analysis in 703 participants in the African American Study of Kidney Disease and Hypertension (AASK) and validation in 1,628 participants with CKD in the Atherosclerosis Risk in Communities (ARIC) study who attended visit 5.

Exposure

Circulating proteins.

Outcome

All-cause mortality.

Analytical Approach

Among AASK participants, we evaluated the associations of 6,790 circulating proteins with all-cause mortality using multivariable Cox proportional hazards models. Proteins with significant associations were further studied in ARIC Visit 5 participants with CKD.

Results

In the AASK cohort, the mean age was 54.5 years, 271 (38.5%) were women, and the mean measured glomerular filtration rate (GFR) was 46 mL/min/1.73 m2. The median follow-up was 9.6 years, and 7 distinct proteins were associated with all-cause mortality at the Bonferroni-level threshold (P < 0.05 of the 6,790) after adjustment for demographics and clinical factors, including baseline measured estimated GFR and proteinuria. In the ARIC visit 5 cohort, the mean age was 77.2 years, 903 (55.5%) were women, the mean estimated GFR was 54 mL/min/1.73 m2 and median follow-up was 6.9 years. Of the 7 proteins found in AASK, 3 (β2-microglobulin, spondin-1, and N-terminal pro-brain natriuretic peptide) were available in the ARIC data, with all 3 significantly associated with death in ARIC.

Limitations

Possibility of unmeasured confounding. Cause of death was not known.

Conclusions

Using large-scale proteomic analysis, proteins were reproducibly associated with mortality in 2 cohorts of participants with CKD.

Plain-Language Summary

Patients with chronic kidney disease (CKD) have a high risk of premature death, with various pathophysiological processes contributing to this increased risk of mortality. This observational cohort study aimed to investigate the associations between circulating proteins and all-cause mortality in patients with CKD using large-scale proteomic analysis. The study analyzed data from the African American Study of Kidney Disease and Hypertension (AASK) study and validated the findings in the Atherosclerosis Risk in Communities (ARIC) Study. A total of 6,790 circulating proteins were evaluated in AASK, and 7 proteins were significantly associated with all-cause mortality. Three of these proteins (β2-microglobulin, spondin-1, and N-terminal pro-brain natriuretic peptide (BNP)) were also measured in ARIC and were significantly associated with death. Additional studies assessing biomarkers associated with mortality among patients with CKD are needed to evaluate their use in clinical practice.

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.

In vivo longitudinal 920 nm two-photon intravital kidney imaging of a dynamic 2,8-DHA crystal formation and tubular deterioration in the adenine-induced chronic kidney disease mouse model

Chronic kidney disease (CKD) is one of the most common renal diseases manifested by gradual loss of kidney function with no symptoms in the early stage. The underlying mechanism in the pathogenesis of CKD with various causes such as high blood pressure, diabetes, high cholesterol, and kidney infection is not well understood. In vivo longitudinal repetitive cellular-level observation of the kidney of the CKD animal model can provide novel insights to diagnose and treat the CKD by visualizing the dynamically changing pathophysiology of CKD with its progression over time. In this study, using two-photon intravital microscopy with a single 920 nm fixed-wavelength fs-pulsed laser, we longitudinally and repetitively observed the kidney of an adenine diet-induced CKD mouse model for 30 days. Interestingly, we could successfully visualize the 2,8-dihydroxyadenine (2,8-DHA) crystal formation with a second-harmonics generation (SHG) signal and the morphological deterioration of renal tubules with autofluorescence using a single 920 nm two-photon excitation. The longitudinal in vivo two-photon imaging results of increasing 2,8-DHA crystals and decreasing tubular area ratio visualized by SHG and autofluorescence signal, respectively, were highly correlated with the CKD progression monitored by a blood test showing increased cystatin C and blood urea nitrogen (BUN) levels over time. This result suggests the potential of label-free second-harmonics generation crystal imaging as a novel optical technique for in vivo CKD progression monitoring.

Serum and urine profiling by high-throughput TMT-based proteomics for the investigation of renal dysfunction in canine babesiosis

Canine babesiosis is a tick-borne disease caused by Babesia canis, with acute kidney injury as one of the common complications. In the study 8 healthy control dogs and 22 dogs with naturally occurring babesiosis were enrolled, with the aim to analyse differences in serum and urinary proteomes between healthy dogs and dogs with different degree of renal dysfunction in babesiosis using a label-based high-throughput quantitative proteomic approach. In serum, 58 proteins were found differentially abundant between healthy controls and groups of dogs with different degrees of renal dysfunction in babesiosis, while in urine there were 259 differentially abundant proteins. In addition, altered biological pathways were detected in the diseased dogs using bioinformatics tools and validation of several candidate biomarkers was performed. SIGNIFICANCE: The main aim of this comprehensive study was to perform analyses of serum and urinary proteomes of dogs with renal dysfunction in babesiosis compared to healthy dogs using, for the first time, a high-throughput proteomic method and functional enrichment analyses. Serum and urine samples of the same dogs were investigated in order to gain a more complete picture of pathologic changes taking place in renal dysfunction in babesiosis. We highlighted two putative biomarkers validated herein which could be of importance for early diagnosis of renal dysfunction in canine babesiosis, as they are easily accessible from urine and their concentration rises before the appearance of azotaemia: urinary neutrophil gelatinase-associated lipocalin (NGAL) and urinary liver-type fatty acid-binding protein (L-FABP).

Stage II of Chronic Kidney Disease—A Tipping Point in Disease Progression?

Chronic kidney disease (CKD) is the progressive loss of renal function. Although advances have been made in understanding the progression of CKD, key molecular events in complex pathophysiological mechanisms that mark each stage of renal failure remain largely unknown. Changes in plasma protein profiles in different disease stages are important for identification of early diagnostic markers and potential therapeutic targets. The goal of this study was to determine the molecular profile of each CKD stage (from 1 to 5), aiming to specifically point out markedly expressed or downregulated proteins. We performed a cross-sectional shotgun-proteomic study of pooled plasma across CKD stages and compared them to healthy controls. After sample pooling and heparin-column purification we analysed proteomes from healthy to CKD stage 1 through 5 participants’ plasma by liquid-chromatography/mass-spectrometry. We identified 453 proteins across all study groups. Our results indicate that key events, which may later affect the course of disease progression and the overall pathophysiological background, are most pronounced in CKD stage 2, with an emphasis on inflammation, lipoprotein metabolism, angiogenesis and tissue regeneration. We hypothesize that CKD stage 2 is the tipping point in disease progression and a suitable point in disease course for the development of therapeutic solutions.

Circulating Plasma Biomarkers in Biopsy-Confirmed Kidney Disease

BACKGROUND AND OBJECTIVES

Biomarkers for noninvasive assessment of histopathology and prognosis are needed in patients with kidney disease.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Using a proteomics assay, we measured a multimarker panel of 225 circulating plasma proteins in a prospective cohort study of 549 individuals with biopsy-confirmed kidney diseases and semiquantitative assessment of histopathology. We tested the associations of each biomarker with histopathologic lesions and the risks of kidney disease progression (defined as ≥40% decline in eGFR or initiation of KRT) and death.

RESULTS

After multivariable adjustment and correction for multiple testing, 46 different proteins were associated with histopathologic lesions. The top-performing markers positively associated with acute tubular injury and interstitial fibrosis/tubular atrophy were kidney injury molecule-1 (KIM-1) and V-set and Ig domain-containing protein 2 (VSIG2), respectively. Thirty proteins were significantly associated with kidney disease progression, and 35 were significantly associated with death. The top-performing markers for kidney disease progression were placental growth factor (hazard ratio per doubling, 5.4; 95% confidence interval, 3.4 to 8.7) and BMP and activin membrane-bound inhibitor (hazard ratio, 3.0; 95% confidence interval, 2.1 to 4.2); the top-performing markers for death were TNF-related apoptosis-inducing ligand receptor-2 (hazard ratio, 2.9; 95% confidence interval, 2.0 to 4.0) and CUB domain-containing protein-1 (hazard ratio, 2.4; 95% confidence interval, 1.8 to 3.3).

CONCLUSION

We identified several plasma protein biomarkers associated with kidney disease histopathology and adverse clinical outcomes in individuals with a diverse set of kidney diseases.

PODCAST

This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021_12_28_CJN09380721.mp3.

Association of Plasma Leucine-Rich Alpha-2 Glycoprotein 1 (LRG1) with All-Cause and Cause-Specific Mortality in Individuals with Type 2 Diabetes

BACKGROUND

Leucine-rich alpha-2 glycoprotein 1 (LRG1) is a circulating protein in the transforming growth factor-beta superfamily. We sought to study whether LRG1 might predict risk for all-cause and cause-specific mortality in individuals with type 2 diabetes.

METHODS

2012 outpatients with type 2 diabetes were followed for a median of 7.2 years and 188 death events were identified. Association of LRG1 with risk for mortality was assessed by multivariable Cox regression models.

RESULTS

Participants with a higher concentration of LRG1 had an increased risk for all-cause mortality [HR (95% CI), 1.76 (1.03-3.01), 1.75 (1.03-2.98), and 4.37 (2.72-7.02) for quartiles 2, 3, and 4, respectively, compared to quartile 1]. The association remained significant after adjustment for known cardio-renal risk factors including estimated glomerular filtration rate and albuminuria [adjusted HR 2.76 (1.66-4.59), quartile 4 versus 1]. As a continuous variable, a 1-SD increment in LRG1 was associated with 1.34 (1.14-1.57)-fold adjusted risk for all-cause mortality. High plasma LRG1 was independently associated with mortality attributable to cardiovascular disease, infection, and renal diseases. Adding LRG1 into a clinical variable-based model improved discrimination (c statistics from 0.828 to 0.842, P = 0.006) and reclassification (net reclassification improvement 0.47, 95% CI 0.28-0.67) for prediction of 5-year all-cause mortality.

CONCLUSION

Plasma LRG1 predicts risk for all-cause mortality and mortality attributable to cardiovascular disease, infection, and renal disease independent of known cardio-renal risk factors. It may be a potential novel biomarker to improve risk stratification in individuals with type 2 diabetes.

Comparative analysis of therapeutic effects between medium cut-off and high flux dialyzers using metabolomics and proteomics: exploratory, prospective study in hemodialysis

In this single-center prospective study of 20 patients receiving maintenance hemodialysis (HD), we compared the therapeutic effects of medium cut-off (MCO) and high flux (HF) dialyzers using metabolomics and proteomics. A consecutive dialyzer membrane was used for 15-week study periods: 1st HF dialyzer, MCO dialyzer, 2nd HF dialyzer, for 5 weeks respectively. ¹H-nuclear magnetic resonance was used to identify the metabolites and liquid chromatography-tandem mass spectrometry (LC–MS/MS) analysis was used to identify proteins. To compare the effects of the HF and MCO dialyzers, orthogonal projection to latent structure discriminant analysis (OPLS-DA) was performed. OPLS-DA showed that metabolite characteristics could be significantly classified by 1st HF and MCO dialyzers. The Pre-HD metabolites with variable importance in projection scores ≥ 1.0 in both 1st HF versus MCO and MCO versus 2nd HF were succinate, glutamate, and histidine. The pre-HD levels of succinate and histidine were significantly lower, while those of glutamate were significantly higher in MCO period than in the HF period. OPLS-DA of the proteome also substantially separated 1st HF and MCO periods. Plasma pre-HD levels of fibronectin 1 were significantly higher, and those of complement component 4B and retinol-binding protein 4 were significantly lower in MCO than in the 1st HF period. Interestingly, as per Ingenuity Pathway Analysis, an increase in epithelial cell proliferation and a decrease in endothelial cell apoptosis occurred during the MCO period. Overall, our results suggest that the use of MCO dialyzers results in characteristic metabolomics and proteomics profiles during HD compared with HF dialyzers, which might be related to oxidative stress, insulin resistance, complement-coagulation axis, inflammation, and nutrition.

Proteomic Biomarkers in the Cardiorenal Syndrome: Toward Deciphering Molecular Pathophysiology

Cardiorenal syndrome (CRS) is defined by coexisting heart and renal dysfunctions. Malfunction of 1 organ may cause dysfunction of the other with variable causative disease that defines the type of CRS (1-5). Numerous studies showed that the prevalence of cardiovascular disease is increased in patients with chronic kidney disease (CKD). Similarly, CKD affects a large proportion of patients with heart failure. This overlap between primary heart or primary kidney disease blurs cause-effect inferences of the initiator/target organ. The classical subdivision of CRS in 5 categories does not provide pathophysiological suggestions for targeted intervention. It seems timely to revisit the value of CRS biomarkers in a pathophysiology-centered approach. We systematically reviewed the literature in CRS, which revealed 53 clinical studies describing the use of 44 biomarkers and 4 proteomic panels. All biomarkers are involved in at least one of the CRS comorbidities. Among the pathways affected, inflammation, aberrant glucose metabolism, neurohormonal activation, and oxidative stress are well described. There is growing evidence that fibrosis may be the "cornerstone" that unifies most of the pathways leading to CRS. Formation of excess fibrous connective tissue antedates CRS in many cases. This review highlights that biomarkers reflecting fibrosis may be of substantial clinical value in the early detection, prognostication, and guiding treatment of CRS. Biomarkers detecting changes in collagen turnover in the extracellular matrix of heart and kidney appear able to depict subclinical changes in the fibrotic remodeling of tissues and constitute a promising approach toward personalized intervention in CRS.

Association of Genetic Variants for Plasma LRG1 With Rapid Decline in Kidney Function in Patients With Type 2 Diabetes

CONTEXT

Elevated levels of plasma leucine-rich α-2-glycoprotein 1 (LRG1), a component of transforming growth factor beta signaling, are associated with development and progression of chronic kidney disease in patients with type 2 diabetes (T2D). However, whether this relationship is causal is uncertain.

OBJECTIVES

To identify genetic variants associated with plasma LRG1 levels and determine whether genetically predicted plasma LRG1 contributes to a rapid decline in kidney function (RDKF) in patients with T2D.

DESIGN AND PARTICIPANTS

We performed a genome-wide association study of plasma LRG1 among 3694 T2D individuals [1881 (983 Chinese, 420 Malay, and 478 Indian) discovery from Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes cohort and 1813 (Chinese) validation from Diabetic Nephropathy cohort]. One- sample Mendelian randomization analysis was performed among 1337 T2D Chinese participants with preserved glomerular filtration function [baseline estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2)]. RDKF was defined as an eGFR decline of 3 mL/min/1.73 m2/year or greater.

RESULTS

We identified rs4806985 variant near LRG1 locus robustly associated with plasma LRG1 levels (meta P = 6.66 × 10-16). Among 1337 participants, 344 (26%) developed RDKF, and the rs4806985 variant was associated with higher odds of RDKF (meta odds ratio = 1.23, P = 0.030 adjusted for age and sex). Mendelian randomization analysis provided evidence for a potential causal effect of plasma LRG1 on kidney function decline in T2D (P < 0.05).

CONCLUSION

We demonstrate that genetically influenced plasma LRG1 increases the risk of RDKF in T2D patients, suggesting plasma LRG1 as a potential treatment target. However, further studies are warranted to elucidate underlying pathways to provide insight into diabetic kidney disease prevention.

Applying Proteomics and Integrative "Omics" Strategies to Decipher the Chronic Kidney Disease-Related Atherosclerosis

Patients with chronic kidney disease (CKD) are at increased risk of atherosclerosis and premature mortality, mainly due to cardiovascular events. However, well-known risk factors, which promote “classical” atherosclerosis are alone insufficient to explain the high prevalence of atherosclerosis-related to CKD (CKD-A). The complexity of the molecular mechanisms underlying the acceleration of CKD-A is still to be defied. To obtain a holistic picture of these changes, comprehensive proteomic approaches have been developed including global protein profiling followed by functional bioinformatics analyses of dysregulated pathways. Furthermore, proteomics surveys in combination with other “omics” techniques, i.e., transcriptomics and metabolomics as well as physiological assays provide a solid ground for interpretation of observed phenomena in the context of disease pathology. This review discusses the comprehensive application of various “omics” approaches, with emphasis on proteomics, to tackle the molecular mechanisms underlying CKD-A progression. We summarize here the recent findings derived from global proteomic approaches and underline the potential of utilizing integrative systems biology, to gain a deeper insight into the pathogenesis of CKD-A and other disorders.

Understanding glomerular diseases through proteomics

INTRODUCTION

Chronic kidney disease is avery common and complex chronic disease. Uncovering the pathological patterns of CKD on the molecular level of bio-fluids and tissue appears to be both vital and promising for a more favorable outcome. We reviewed recently discovered proteomics biomarkers for CKD to provide new insight into disease pathology.

AREAS COVERED

We review the application of proteome analysis in the context of CKD with various etiologies within the last 5 years. Proteins and peptides associated with CKD as derived from multiple sources (urine, blood and tissue) are reported along with their various biological pathways.

EXPERT OPINION

A systematic and theoretical comprehension of the CKD pathology is essential for its successful management. The underlying complexity of the disease further requires specific conditions for reliable and interpretable results. In this context, clinical proteomics has resulted in first encouraging findings in CKD. A more complete understanding of the biological pathways related to the disease, based on the scope of a holistic proteomic approach, could improve substantially the management of CKD, especially when in conjunction with the current trend of personalized medicine.

LRG1 Mitigates Renal Interstitial Fibrosis through Alleviating Capillary Rarefaction and Inhibiting Inflammatory and Pro-Fibrotic Cytokines

INTRODUCTION

Increasing evidence has demonstrated that loss of peritubular capillaries plays a critical role in renal interstitial fibrosis. Leucine-rich α2-glycoprotein-1 (LRG1) has been observed promoting angiogenesis in the ocular disease mouse model and myocardial infarction model. We aimed to explore the role of LRG1 in renal interstitial fibrosis.

METHODS

We analyzed the expression of LRG1 in the plasma and kidney of CKD patients by ELISA and immunohistochemistry. Relationships between the expression of LRG1 in plasma and kidney and renal fibrosis and inflammation were analyzed. Tube formation assay was used to detect the angiogenesis in the human umbilical vein endothelial cell lines (HUVECs). And real-time PCR was used to detect the mRNA expression of LRG1, inflammatory factors, renal tubular injury indicators, pro-fibrotic cytokines, and CD31. We examined the effects of genetic ablation of LRG1 on renal fibrosis induced by unilateral ureteral obstruction (UUO) mice model at day 7.

RESULTS

We demonstrated that the expression of LRG1 in renal tissues and plasma samples was upregulated in CKD patients. And the expression of LRG1 was elevated in human renal tubular epithelial cell line (HK-2) cells in response to the stimulation of TNF-α in vitro, and in kidney after UUO in vivo. The deficiency of the LRG1 gene aggravated renal fibrosis, inflammatory cells infiltration, and capillary rarefaction after UUO. In vitro, LRG1 promoted the tube formation of HUVEC cells. LRG1 inhibits fibronectin secretion induced by TGF-β1 in HK-2 and overexpression of LRG1 in HK-2 cells decreased fibronectin secretion.

CONCLUSION

LRG1 may prevent renal fibrosis by inhibiting the secretion of inflammatory and pro-fibrotic cytokines and promoting angiogenesis.

Human body-fluid proteome: quantitative profiling and computational prediction

Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein-protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.

Urinary mRNA Signatures as Predictors of Renal Function Decline in Patients With Biopsy-Proven Diabetic Kidney Disease

The clinical manifestations of diabetic kidney disease (DKD) are more heterogeneous than those previously reported, and these observations mandate the need for the recruitment of patients with biopsy-proven DKD in biomarker research. In this study, using the public gene expression omnibus (GEO) repository, we aimed to identify urinary mRNA biomarkers that can predict histological severity and disease progression in patients with DKD in whom the diagnosis and histologic grade has been confirmed by kidney biopsy. We identified 30 DKD-specific mRNA candidates based on the analysis of the GEO datasets. Among these, there were significant alterations in the urinary levels of 17 mRNAs in patients with DKD, compared with healthy controls. Four urinary mRNAs-LYZ, C3, FKBP5, and G6PC-reflected tubulointerstitial inflammation and fibrosis in kidney biopsy and could predict rapid progression to end-stage kidney disease independently of the baseline eGFR (tertile 1 vs. tertile 3; adjusted hazard ratio of 9.68 and 95% confidence interval of 2.85-32.87, p < 0.001). In conclusion, we demonstrated that urinary mRNA signatures have a potential to indicate the pathologic status and predict adverse renal outcomes in patients with DKD.

Hypoalbuminemia: a price worth paying for improved dialytic removal of middle-molecular-weight uremic toxins?

Hemodiafiltration (HDF) increases the removal of middle-molecular-weight uremic toxins and may improve outcomes in patients with end-stage kidney disease (ESKD), but it requires complex equipment and comes with risks associated with infusion of large volumes of substitution solution. New high-flux hemodialysis membranes with improved diffusive permeability profiles do not have these limitations and offer an attractive alternative to HDF. However, both strategies are associated with increased albumin loss into the dialysate, raising concerns about the potential for decreased serum albumin concentrations that have been associated with poor outcomes in ESKD. Many factors can contribute to hypoalbuminemia in ESKD, including protein energy wasting, inflammation, volume expansion, renal loss and loss into the dialysate; of these factors, loss into the dialysate is not necessarily the most important. Furthermore, recent studies suggest that mild hypoalbuminemia per se is not an independent predictor of increased mortality in dialysis patients, but in combination with inflammation it is a poor prognostic sign. Thus, whether hypoalbuminemia predisposes to increased morbidity and mortality may depend on the presence or absence of inflammation. In this review we summarize recent findings on the role of dialysate losses in hypoalbuminemia and the importance of concomitant inflammation on outcomes in patients with ESKD. Based on these findings, we discuss whether hypoalbuminemia may be a price worth paying for increased dialytic removal of middle-molecular-weight uremic toxins.

Leucine-rich α2-glycoprotein-1 upregulation in plasma and kidney of patients with lupus nephritis

BACKGROUND

Increased leucine-rich α2-glycoprotein-1 (LRG1) has been observed in various inflammatory and autoimmune diseases. We aimed to explore the expression and role of LRG1 in lupus nephritis (LN).

METHODS

Plasma LRG1 (pLRG1) was measured by enzyme-linked immunosorbent assay in 101 patients with renal biopsy-proven LN and 21 healthy controls (HC). Relationships between pLRG1 and clinical and pathological characteristics were analyzed. The expression of LRG1 in peripheral blood leukocytes and kidney was detected by flow cytometry, immunohistochemistry and immunofluorescence, respectively. Further cell experiments were focused on the role of LRG1.

RESULTS

We found that LRG1 was expressed in plasma, some peripheral blood leukocytes, proximal tubule and several inflammatory cells. The levels of LRG1 in plasma, peripheral blood leukocytes and kidney were elevated in LN patients as compared to HC. Plasma expression levels of LRG1 correlated positively with renal function and renal disease activity, and reflect specific pathologic lesions in the kidneys of patients with LN. Interleukin-1β and interleukin-6, not tumor necrosis factor-α and interferon γ induced the LRG1 expression in human renal tubular epithelial cell line. Moreover, stimulation of recombinant human LRG1 could inhibit late apoptosis, promote proliferation and regulate expression of inflammatory factors and cytokines.

CONCLUSIONS

Plasma expression levels of LRG1 were associated with renal function, disease activity, and pathology in LN. It might also be involved in renal inflammation, proliferation and apoptosis of endothelial cells. LRG1 might be a potential prognosis novel predictor in LN patients.

Plasma Leucine-Rich α-2-Glycoprotein 1 Predicts Cardiovascular Disease Risk in End-Stage Renal Disease

Plasma leucine-Rich α-2-glycoprotein 1 (LRG1) is an innovative biomarker for inflammation and angiogenesis. Many adverse pathophysiological changes including inflammation, atherosclerosis, and premature mortality is associated with End-stage renal disease (ESRD). However, whether levels of plasma LRG1 correlate with the co-morbidities of ESRD patients is unknown. Plasma LRG1 and high-sensitivity C-reactive protein (hsCRP) were analyzed by ELISA in 169 hemodialysis patients from the Immunity in ESRD (iESRD) study. Patient demographics and comorbidities at the time of enrollment were recorded. Peripheral blood monocyte and T cell subsets were assessed by multicolor flow cytometry. In the univariate analysis, a higher level of LRG1 was associated with the presence of cardiovascular disease (CVD) and peripheral arterial occlusive disease (PAOD). In multivariate logistic regression models, higher LRG1 tertile was significantly associated with PAOD (odds ratio = 3.49) and CVD (odds ratio = 1.65), but not with coronary artery disease, history of myocardial infarction, or stroke after adjusting for gender, diabetes, hemoglobin, albumin, calcium-phosphate product, and level of hsCRP. In addition, the level of LRG1 had a positive correlation with IL-6, hsCRP, and also more advanced T cell differentiation. The association suggests that LRG1 participates in the progression of atherosclerosis by inducing inflammation. Therefore, the role of LRG1 in coexisting inflammatory response should be further investigated in the pathogenesis of cardiovascular morbidity and mortality in patients with ESRD.

Multiplexed MRM-based protein quantification of putative prognostic biomarkers for chronic kidney disease progression in plasma

Current diagnostic measures for Chronic Kidney Disease (CKD) include detection of reduced estimated glomerular filtration rate (eGFR) and albuminuria, which have suboptimal accuracies in predicting disease progression. The disease complexity and heterogeneity underscore the need for multiplex quantification of different markers. The goal of this study was to determine the association of six previously reported CKD-associated plasma proteins [B2M (Beta-2-microglobulin), SERPINF1 (Pigment epithelium-derived factor), AMBP (Protein AMBP), LYZ (Lysozyme C), HBB (Hemoglobin subunit beta) and IGHA1 (Immunoglobulin heavy constant alpha 1)], as measured in a multiplex format, with kidney function, and outcome. Antibody-free, multiple reaction monitoring mass spectrometry (MRM) assays were developed, characterized for their analytical performance, and used for the analysis of 72 plasma samples from a patient cohort with longitudinal follow-up. The MRM significantly correlated (Rho = 0.5–0.9) with results from respective ELISA. Five proteins [AMBP, B2M, LYZ, HBB and SERPINF1] were significantly associated with eGFR, with the three former also associated with unfavorable outcome. The combination of these markers provided stronger associations with outcome (p < 0.0001) compared to individual markers. Collectively, our study describes a multiplex assay for absolute quantification and verification analysis of previously described putative CKD prognostic markers, laying the groundwork for further use in prospective validation studies.

Proteomic Analysis of Human Serum from Patients with Chronic Kidney Disease

Chronic kidney disease (CKD) is an important public health problem in the world. The aim of our research was to identify novel potential serum biomarkers of renal injury. ELISA assay showed that cytokines and chemokines IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12 (p70), IL-13, IL-15, IL-17, Eotaxin, FGFb, G-CSF, GM-CSF, IP-10, MCP-1, MIP-1α, MIP-1β, PDGF-1bb, RANTES, TNF-α and VEGF were significantly higher (R > 0.6, p value < 0.05) in the serum of patients with CKD compared to healthy subjects, and they were positively correlated with well-established markers (urea and creatinine). The multiple reaction monitoring (MRM) quantification method revealed that levels of HSP90B2, AAT, IGSF22, CUL5, PKCE, APOA4, APOE, APOA1, CCDC171, CCDC43, VIL1, Antigen KI-67, NKRF, APPBP2, CAPRI and most complement system proteins were increased in serum of CKD patients compared to the healthy group. Among complement system proteins, the C8G subunit was significantly decreased three-fold in patients with CKD. However, only AAT and HSP90B2 were positively correlated with well-established markers and, therefore, could be proposed as potential biomarkers for CKD.

Transforming growth factor beta (TGF-β) is activated by the CtBP2-p300-AP1 transcriptional complex in chronic renal failure

Chronic renal failure (CRF), also known as chronic kidney disease (CKD), is a common renal disorder characterized by gradual kidney dysfunction. Molecular dissection reveals that transforming growth factor beta (TGF-β) plays a central role in the pathogenesis of CRF. However, the mechanism underlying TGF-β upregulation has not been demonstrated. Here, we verified that the elevated level of TGF-β was associated with the severity of CRF stages and the activation of TGF-β-mediated signaling in 120 renal biopsies from CRF patients. By analyzing the promoter region of the TGFB1 gene, we identified one AP-1 (activator protein 1) and four NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) binding sites. Knockdown of two AP-1 subunits (c-Jun and c-FOS) or blockage of AP-1 signaling with two inhibitors T-5224 and SR11302 could cause the downregulation of TGFB1, whereas knockdown of two NF-κB subunits (p65 and p50) or blockage of NF-κB signaling with two inhibitors TPCA1 and BOT-64 could not change the expression of TGFB1. Using mass spectrometry and coimmunoprecipitation analyses, we found that both c-Jun and c-FOS formed a complex with CtBP2 (C-terminal binding protein 2) and histone acetyltransferase p300. Our in vitro data demonstrated that induction of CtBP2 by recombinant IL-1β (interleukin-1 beta) led to the upregulation of TGFB1 and the activation of TGF-β downstream signaling, while knockdown of CtBP2 resulted in the reversed effects. Using chromatin immunoprecipitation assays, we revealed that the CtBP2-p300-AP1 complex specifically bound to the promoter of TGFB and that knockdown or blockage of CtBP2 significantly decreased the occupancies of the p300 and AP-1 subunits. Our results support a model in which the CtBP2-p300-AP1 transcriptional complex activates the expression of TGFB1, increasing its production and extracellular secretion. The secreted TGF-β binds to its receptors and initiates downstream signaling.

A Functional Landscape of CKD Entities From Public Transcriptomic Data

Introduction

To develop effective therapies and identify novel early biomarkers for chronic kidney disease, an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in chronic kidney disease (CKD) origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for 9 kidney disease entities that account for most of CKD worldwide. Our primary goal was to demonstrate the possibilities and potential on data analysis and integration to the nephrology community.

Methods

We integrated data from 5 publicly available studies and compared glomerular gene expression profiles of disease with that of controls from nontumor parts of kidney cancer nephrectomy tissues. A major challenge was the integration of the data from different sources, platforms, and conditions that we mitigated with a bespoke stringent procedure.

Results

We performed a global transcriptome-based delineation of different kidney disease entities, obtaining a transcriptomic diffusion map of their similarities and differences based on the genes that acquire a consistent differential expression between each kidney disease entity and nephrectomy tissue. We derived functional insights by inferring the activity of signaling pathways and transcription factors from the collected gene expression data and identified potential drug candidates based on expression signature matching. We validated representative findings by immunostaining in human kidney biopsies indicating, for example, that the transcription factor FOXM1 is significantly and specifically expressed in parietal epithelial cells in rapidly progressive glomerulonephritis (RPGN) whereas not expressed in control kidney tissue. Furthermore, we found drug candidates by matching the signature on expression of drugs to that of the CKD entities, in particular, the Food and Drug Administration-approved drug nilotinib.

Conclusion

These results provide a foundation to comprehend the specific molecular mechanisms underlying different kidney disease entities that can pave the way to identify biomarkers and potential therapeutic targets. To facilitate further use, we provide our results as a free interactive Web application: https://saezlab.shinyapps.io/ckd_landscape/. However, because of the limitations of the data and the difficulties in its integration, any specific result should be considered with caution. Indeed, we consider this study rather an illustration of the value of functional genomics and integration of existing data.

The Inability of Podocytes to Proliferate: Cause, Consequences, and Origin

This study presents a theoretical analysis of the problems related to the inability of podocytes to proliferate. The basis of these problems is the very high rate of glomerular filtration. Podocytes do not in general die by apoptosis or necrosis but are lost by detachment from the glomerular basement membrane (GBM) as viable cells. Podocytes situated on the outside of the filtration barrier and attached to the GBM only by their foot processes are permanently exposed to the flow dynamic forces of the high filtration rate tending to detach them from the GBM. The major challenge seems to consist of the high shear stresses on the foot processes within the filtration slits due to filtrate flow. Healthy podocytes are able to resist this challenge, injured podocytes are not, and may undergo foot process detachment, leading to a gap in the podocyte cover of the GBM. This represents a mortal event. Like a dam break, such a leak cannot be repaired. The ongoing exposure to filtrate flow prevents any attempt to close the gap, thus preventing any regeneration including cell proliferation. An improvement of this precarious situation consists of healing by scarring that may involve only one lobule of the glomerulus, permitting the remaining lobules to maintain filtration. An answer to the question of which waste product requires such a high filtration rate for its excretion may be in the huge quantity of circulating peptides, a problem that dates far back in evolution.

Membrane innovation: closer to native kidneys

Modern methods in analytical biochemistry have established that uraemia is associated with the retention of proteins, both in their native state and post-translationally modified, over a wide range of molecular weights up to 60 kDa. Evidence is accumulating that these higher molecular weight retention solutes are important uraemic toxins, and therapies such as online haemodiafiltration (HDF), which enhance their removal, are associated with improved outcomes. However, HDF has limitations regarding cost, clinical implementation and the need for an external source of sterile substitution solution to maintain fluid balance. New membranes that have a solute removal profile more closely approaching that of the glomerular filtration barrier when used for conventional haemodialysis, while at the same time not allowing the passage of clinically significant amounts of beneficial proteins, are needed to address these limitations. Tighter control of the molecular characteristics of the polymers used for membrane fabrication, along with the introduction of additives and improvements in the manufacturing process, has led to membranes with a tighter pore size distribution that allows the use of an increased absolute pore size without leaking substantial amounts of albumin. At the same time, the wall thickness and internal diameter of membrane fibres have been decreased, enhancing convective transport within the dialyser without the need for an external source of substitution solution. These new expanded range membranes provide a solute removal profile more like that of the native kidney than currently available membranes when used in conventional haemodialysis.

Pre-clinical model of severe glutathione peroxidase-3 deficiency and chronic kidney disease results in coronary artery thrombosis and depressed left ventricular function

Background

Chronic kidney disease (CKD) patients have deficient levels of glutathione peroxidase-3 (GPx3). We hypothesized that GPx3 deficiency may lead to cardiovascular disease in the presence of chronic kidney disease due to an accumulation of reactive oxygen species and decreased microvascular perfusion of the myocardium. Methods. To isolate the exclusive effect of GPx3 deficiency in kidney disease-induced cardiac disease, we studied the GPx3 knockout mouse strain (GPx3-/-) in the setting of surgery-induced CKD. Results. Ribonucleic acid (RNA) microarray screening of non-stimulated GPx3-/- heart tissue show increased expression of genes associated with cardiomyopathy including myh7, plac9, serpine1 and cd74 compared with wild-type (WT) controls. GPx3-/- mice underwent surgically induced renal mass reduction to generate a model of CKD. GPx3-/- + CKD mice underwent echocardiography 4 weeks after injury. Fractional shortening (FS) was decreased to 32.9 ± 5.8% in GPx3-/- + CKD compared to 62.0% ± 10.3 in WT + CKD (P < 0.001). Platelet aggregates were increased in the myocardium of GPx3-/- + CKD. Asymmetric dimethylarginine (ADMA) levels were increased in both GPx3-/- + CKD and WT+ CKD. ADMA stimulated spontaneous platelet aggregation more quickly in washed platelets from GPx3-/-. In vitro platelet aggregation was enhanced in samples from GPx3-/- + CKD. Platelet aggregation in GPx3-/- + CKD samples was mitigated after in vivo administration of ebselen, a glutathione peroxidase mimetic. FS improved in GPx3-/- + CKD mice after ebselen treatment.

Conclusion

These results suggest GPx3 deficiency is a substantive contributing factor to the development of kidney disease-induced cardiac disease.

Functional secretome analysis reveals Annexin-A1 as important paracrine factor derived from fetal mesenchymal stem cells in hepatic regeneration

Background

Human mesenchymal stem/stromal cells (MSCs) and their secreted molecules exert beneficial effects in injured tissues by promoting tissue regeneration and angiogenesis and by inhibiting inflammation and fibrosis. We have previously demonstrated that the therapeutic activity of fetal MSCs derived from amniotic fluid (AF-MSCs) and their hepatic progenitor-like cells (HPL) is mediated by paracrine effects in a mouse model of acute hepatic failure (AHF).

Methods

Herein, we have combined proteomic profiling of the AF-MSCs and HPL cell secretome with ex vivo and in vivo functional studies to identify specific soluble factors, which underpin tissue regeneration in AHF.

Findings

The anti-inflammatory molecule Annexin-A1 (ANXA1) was detected at high levels in both AF-MSC and HPL cell secretome. Further functional analyses revealed that the shRNA-mediated knock-down of ANXA1 in MSCs (shANXA1-MSCs) decreased their proliferative, clonogenic and migratory potential, as well as their ability to differentiate into HPL cells. Liver progenitors (oval cells) from AHF mice displayed reduced proliferation when cultured ex vivo in the presence of conditioned media from shANXA1-MSCs compared to control MSCs secretome. Intra-hepatic delivery of conditioned media from control MSCs but not shANXA1-MSCs reduced liver damage and circulating levels of pro-inflammatory cytokines in AHF.

Interpretation

Collectively, our study uncovers secreted Annexin-A1 as a novel effector of MSCs in liver regeneration and further underscores the potential of cell-free therapeutic strategies for liver diseases.

Fund

Fondation Santé, GILEAD Asklipeios Grant, Fellowships of Excellence – Siemens, IKY, Reinforcement of Postdoctoral Researchers, IKY.

Clinical Proteomics in Kidney Disease: From Discovery to Clinical Application

Proteome analysis has been applied in multiple studies in the context of chronic kidney disease, aiming at improving our knowledge on the molecular pathophysiology of the disease. The approach is generally based on the hypothesis that proteins are key in maintaining kidney function, and disease is a clinical consequence of a significant change of the protein level. Knowledge on critical proteins and their alteration in disease should in turn enable identification of ideal biomarkers that could guide patient management. In addition, all drugs currently employed target proteins. Hence, proteome analysis also promises to enable identifying the best suited therapeutic target, and, in combination with biomarkers, could be used as the rationale basis for personalized intervention. To assess the current status of proteome analysis in the context of CKD, we present the results of a systematic review, of up-to-date scientific research, and give an outlook on the developments that can be expected in near future. Based on the current literature, proteome analysis has already seen implementation in the management of CKD patients, and it is expected that this approach, also supported by the positive results generated to date, will see advanced high-throughput application.

Circulating proteins as predictors of cardiovascular mortality in end-stage renal disease

Introduction

Proteomic profiling of end-stage renal disease (ESRD) patients could lead to improved risk prediction and novel insights into cardiovascular disease mechanisms. Plasma levels of 92 cardiovascular disease-associated proteins were assessed by proximity extension assay (Proseek Multiplex CVD-1, Olink Bioscience, Uppsala, Sweden) in a discovery cohort of dialysis patients, the Mapping of Inflammatory Markers in Chronic Kidney disease cohort [MIMICK; n = 183, 55% women, mean age 63 years, 46 cardiovascular deaths during follow-up (mean 43 months)]. Significant results were replicated in the incident and prevalent hemodialysis arm of the Salford Kidney Study [SKS dialysis study, n = 186, 73% women, mean age 62 years, 45 cardiovascular deaths during follow-up (mean 12 months)], and in the CKD5-LD-RTxcohort with assessments of coronary artery calcium (CAC)-score by cardiac computed tomography (n = 89, 37% women, mean age 46 years).

Results

In age and sex-adjusted Cox regression in MIMICK, 11 plasma proteins were nominally associated with cardiovascular mortality (in order of significance: Kidney injury molecule-1 (KIM-1), Matrix metalloproteinase-7, Tumour necrosis factor receptor 2, Interleukin-6, Matrix metalloproteinase-1, Brain-natriuretic peptide, ST2 protein, Hepatocyte growth factor, TNF-related apoptosis inducing ligand receptor-2, Spondin-1, and Fibroblast growth factor 25). Only plasma KIM-1 was associated with cardiovascular mortality after correction for multiple testing, but also after adjustment for dialysis vintage, cardiovascular risk factors and inflammation (hazard ratio) per standard deviation (SD) increase 1.84, 95% CI 1.26–2.69, p = 0.002. Addition of KIM-1, or nine of the most informative proteins to an established risk-score (modified AROii CVM-score) improved discrimination of cardiovascular mortality risk from C = 0.777 to C = 0.799 and C = 0.823, respectively. In the SKS dialysis study, KIM-1 predicted cardiovascular mortality in age and sex adjusted models (hazard ratio per SD increase 1.45, 95% CI 1.03–2.05, p = 0.034) and higher KIM-1 was associated with higher CACscores in the CKD5-LD-RTx-cohort.

Conclusions

Our proteomics approach identified plasma KIM-1 as a risk marker for cardiovascular mortality and coronary artery calcification in three independent ESRD-cohorts. The improved risk prediction for cardiovascular mortality by plasma proteomics merit further studies.

Electronic supplementary material

The online version of this article (10.1007/s40620-018-0556-5) contains supplementary material, which is available to authorized users.

The CKD plasma lipidome varies with disease severity and outcome

BACKGROUND

Various alterations in lipid metabolism have been observed in patients with chronic kidney disease (CKD).

OBJECTIVES

To determine the levels of lipid species in plasma from CKD and hemodialysis (HD) patients and test their association with CKD severity and patient outcome.

METHODS

Seventy-seven patients with CKD stage 2 to HD were grouped into classes of CKD severity at baseline and followed-up for 3.5 years for the occurrence of transition to HD or death (combined outcome). Plasma levels of phosphatidylcholines (PCs), lysophosphatidylcholines (LPCs), sphingomyelins (SMs), and fatty acids were analyzed by flow-injection analysis coupled to tandem mass spectrometry or gas chromatography coupled with mass spectrometry. Kruskal Wallis rank tests and Cox regressions were used to analyze the association of lipids with CKD severity and the risk of combined outcome, respectively.

RESULTS

The plasma level of PCs, LPCs, and SMs was decreased in HD patients compared with nondialyzed CKD patients (all P < .05), whereas esterified and/or nonesterified fatty acids level did not change. Thirty-four lipids displayed significantly lower abundance in plasma of HD patients, whereas elaidic acid (C18:1ω9t) level was increased (P < .001). The total amount of LPCs and individual LPCs were associated with better outcome (P < .05). In particular, LPC 18:2 and LPC 20:3 were statistically associated with outcome in adjusted models (P < .05).

DISCUSSION

In HD patients, a reduction in plasma lipids is observed. Some of the alterations, namely reduced LPCs, were associated with the risk of adverse outcome. These changes could be related to metabolic dysfunctions.

Noninvasive diagnosis of chronic kidney diseases using urinary proteome analysis

Background

In spite of its invasive nature and risks, kidney biopsy is currently required for precise diagnosis of many chronic kidney diseases (CKDs). Here, we explored the hypothesis that analysis of the urinary proteome can discriminate different types of CKD irrespective of the underlying mechanism of disease.

Methods

We used data from the proteome analyses of 1180 urine samples from patients with different types of CKD, generated by capillary electrophoresis coupled to mass spectrometry. A set of 706 samples served as the discovery cohort, and 474 samples were used for independent validation. For each CKD type, peptide biomarkers were defined using statistical analysis adjusted for multiple testing. Potential biomarkers of statistical significance were combined in support vector machine (SVM)-based classifiers.

Results

For seven different types of CKD, several potential urinary biomarker peptides (ranging from 116 to 619 peptides) were defined and combined into SVM-based classifiers specific for each CKD. These classifiers were validated in an independent cohort and showed good to excellent accuracy for discrimination of one CKD type from the others (area under the receiver operating characteristic curve ranged from 0.77 to 0.95). Sequence analysis of the biomarkers provided further information that may clarify the underlying pathophysiology.

Conclusions

Our data indicate that urinary proteome analysis has the potential to identify various types of CKD defined by pathological assessment of renal biopsies and current clinical practice in general. Moreover, these approaches may provide information to model molecular changes per CKD.

Benefit of Apabetalone on Plasma Proteins in Renal Disease

INTRODUCTION

Apabetalone, a small molecule inhibitor, targets epigenetic readers termed BET proteins that contribute to gene dysregulation in human disorders. Apabetalone has in vitro and in vivo anti-inflammatory and antiatherosclerotic properties. In phase 2 clinical trials, this drug reduced the incidence of major adverse cardiac events in patients with cardiovascular disease. Chronic kidney disease is associated with a progressive loss of renal function and a high risk of cardiovascular disease. We studied the impact of apabetalone on the plasma proteome in patients with impaired kidney function.

METHODS

Subjects with stage 4 or 5 chronic kidney disease and matched controls received a single dose of apabetalone. Plasma was collected for pharmacokinetic analysis and for proteomics profiling using the SOMAscan 1.3k platform. Proteomics data were analyzed with Ingenuity Pathway Analysis to identify dysregulated pathways in diseased patients, which were targeted by apabetalone.

RESULTS

At baseline, 169 plasma proteins (adjusted P value <0.05) were differentially enriched in renally impaired patients versus control subjects, including cystatin C and β2 microglobulin, which correlate with renal function. Bioinformatics analysis of the plasma proteome revealed a significant activation of 42 pathways that control immunity and inflammation, oxidative stress, endothelial dysfunction, vascular calcification, and coagulation. At 12 hours postdose, apabetalone countered the activation of pathways associated with renal disease and reduced the abundance of disease markers, including interleukin-6, plasminogen activator inhibitor-1, and osteopontin.

CONCLUSION

These data demonstrated plasma proteome dysregulation in renally impaired patients and the beneficial impact of apabetalone on pathways linked to chronic kidney disease and its cardiovascular complications.

Plasma proteomic analysis reveals altered protein abundances in cardiovascular disease

BACKGROUND

Cardiovascular disease (CVD) describes the pathological conditions of the heart and blood vessels. Despite the large number of studies on CVD and its etiology, its key modulators remain largely unknown. To this end, we performed a comprehensive proteomic analysis of blood plasma, with the scope to identify disease-associated changes after placing them in the context of existing knowledge, and generate a well characterized dataset for further use in CVD multi-omics integrative analysis.

METHODS

LC-MS/MS was employed to analyze plasma from 32 subjects (19 cases of various CVD phenotypes and 13 controls) in two steps: discovery (13 cases and 8 controls) and test (6 cases and 5 controls) set analysis. Following label-free quantification, the detected proteins were correlated to existing plasma proteomics datasets (plasma proteome database; PPD) and functionally annotated (Cytoscape, Ingenuity Pathway Analysis). Differential expression was defined based on identification confidence (≥ 2 peptides per protein), statistical significance (Mann-Whitney p value ≤ 0.05) and a minimum of twofold change.

RESULTS

Peptides detected in at least 50% of samples per group were considered, resulting in a total of 3796 identified proteins (838 proteins based on ≥ 2 peptides). Pathway annotation confirmed the functional relevance of the findings (representation of complement cascade, fibrin clot formation, platelet degranulation, etc.). Correlation of the relative abundance of the proteins identified in the discovery set with their reported concentrations in the PPD was significant, confirming the validity of the quantification method. The discovery set analysis revealed 100 differentially expressed proteins between cases and controls, 39 of which were verified (≥ twofold change) in the test set. These included proteins already studied in the context of CVD (such as apolipoprotein B, alpha-2-macroglobulin), as well as novel findings (such as low density lipoprotein receptor related protein 2 [LRP2], protein SZT2) for which a mechanism of action is suggested.

CONCLUSIONS

This proteomic study provides a comprehensive dataset to be used for integrative and functional studies in the field. The observed protein changes reflect known CVD-related processes (e.g. lipid uptake, inflammation) but also novel hypotheses for further investigation including a potential pleiotropic role of LPR2 but also links of SZT2 to CVD.

Biomarkers for predicting outcomes in chronic kidney disease

PURPOSE OF REVIEW

Current biomarkers for chronic kidney disease (CKD) are limited by lack of sensitivity and inability to prognosticate CKD progression. Significant recent research has better characterized novel biomarker candidates that are associated with CKD progression and cardiovascular mortality in CKD. This review discusses the most significant advances within the past year.

RECENT FINDINGS

We discuss biomarkers for outcomes in CKD under two categories: emerging (defined as having been validated in an independent cohort), which include serum cystatin C, serum β-trace protein, β2-microglobulin, soluble urokinase-type plasminogen activator receptor, soluble tumor necrosis factor receptors 1/2, urinary monocyte chemotactic protein-1, neutrophil gelatin-associated lipocalin, kidney injury molecule-1, and fibroblast growth factor-23; and novel (which have shown associations in smaller observational studies but have not been validated yet), which include indoxyl sulfate, p-cresyl sulfate, trimethylamine-N-oxide, IL-18, Klotho, markers of endothelial dysfunction, vimentin, and procollagen type III N-terminal propeptide. Further, we also discuss future directions for biomarker research including unbiased -omics approaches.

SUMMARY

There are a number of promising biomarkers that can better prognosticate outcomes in and progression of CKD. Further research is warranted to examine whether these biomarkers validate independently as well, and if their incorporation improves clinical practice or trial enrollment.

Ultrasensitive detection of lysozyme in droplet-based microfluidic devices

Lysozyme (LYS) is a bacteriolytic enzyme, available in secretions such as saliva, tears and human milk. LYS is an important defence molecule of the innate immune system, and its overexpression can be a consequence of diseases such as leukemia, kidney disease and sarcoidosis. This paper reports on a digital microfluidic-based approach that combines the gold nanoparticle-enhanced chemiluminescence with aptamer interaction to detect human lysozyme into droplets 20 nanoliters in volume. The described method allows identifying LYS with a 44.6 femtomolar limit of detection, using sample volume as low as 1μL and detection time in the range of 10min. We used luminol to generate the chemiluminescence and demonstrated that the compartmentalization of LYS in droplets also comprising gold nanoparticles provided enhanced luminescence. We functionalized the gold nanoparticles with a thiolated aptamer to achieve the required selectivity that allowed us to detect LYS in human serum.

Examining hemodialyzer membrane performance using proteomic technologies

The success and the quality of hemodialysis therapy are mainly related to both clearance and biocompatibility properties of the artificial membrane packed in the hemodialyzer. Performance of a membrane is strongly influenced by its interaction with the plasma protein repertoire during the extracorporeal procedure. Recognition that a number of medium-high molecular weight solutes, including proteins and protein-bound molecules, are potentially toxic has prompted the development of more permeable membranes. Such membrane engineering, however, may cause loss of vital proteins, with membrane removal being nonspecific. In addition, plasma proteins can be adsorbed onto the membrane surface upon blood contact during dialysis. Adsorption can contribute to the removal of toxic compounds and governs the biocompatibility of a membrane, since surface-adsorbed proteins may trigger a variety of biologic blood pathways with pathophysiologic consequences. Over the last years, use of proteomic approaches has allowed polypeptide spectrum involved in the process of hemodialysis, a key issue previously hampered by lack of suitable technology, to be assessed in an unbiased manner and in its full complexity. Proteomics has been successfully applied to identify and quantify proteins in complex mixtures such as dialysis outflow fluid and fluid desorbed from dialysis membrane containing adsorbed proteins. The identified proteins can also be characterized by their involvement in metabolic and signaling pathways, molecular networks, and biologic processes through application of bioinformatics tools. Proteomics may thus provide an actual functional definition as to the effect of a membrane material on plasma proteins during hemodialysis. Here, we review the results of proteomic studies on the performance of hemodialysis membranes, as evaluated in terms of solute removal efficiency and blood-membrane interactions. The evidence collected indicates that the information provided by proteomic investigations yields improved molecular and functional knowledge and may lead to the development of more efficient membranes for the potential benefit of the patient.

Plasma Leucine-Rich α-2-Glycoprotein 1 Predicts Rapid eGFR Decline and Albuminuria Progression in Type 2 Diabetes Mellitus

CONTEXT

Abnormal angiogenesis plays an important role in pathogenesis of diabetic kidney disease (DKD). Leucine-rich α-2 glycoprotein 1 (LRG1) is a newly identified angiogenic factor.

OBJECTIVE

To study whether plasma LRG1 may independently predict progression of DKD in individuals with type 2 diabetes mellitus (T2DM).

DESIGN AND SETTING

Prospective cohort study in a regional hospital.

PATIENTS

In total, 1226 T2DM participants were followed for a mean ± standard deviation (SD) of 3.1 ± 0.4 years.

MAIN OUTCOMES

Albuminuria progression was defined as elevation in albuminuria level to a higher category. Chronic kidney disease (CKD) progression [rapid estimated glomerular filtration rate (eGFR) decline] was defined as a 40% or greater deterioration in eGFR in 3 years.

RESULTS

Both participants with albuminuria progression and those with CKD progression had higher plasma LRG1 levels at baseline. LRG1 independently predicted albuminuria progression above traditional risk factors, including baseline eGFR and urine albumin to creatinine ratio. A 1-SD increment in LRG1 was associated with a 1.26-fold [95% confidence interval (CI), 1.04 to 1.53, P = 0.018] higher adjusted risk for albuminuria progression. The association of LRG1 with microalbuminuria to macroalbuminuria progression was stronger than its association with normoalbuminuria to microalbuminuria progression [odds ratio (OR), 1.51; 95% CI, 1.04 to 2.18, P = 0.029 vs OR, 1.09; 95% CI, 0.86 to 1.37, P = 0.486, per 1-SD LRG1 increment]. Also, LRG1 independently predicted CKD progression above traditional risk factors. A 1-SD increment in LRG1 was associated with a 1.48-fold (95% CI, 1.04 to 2.11, P = 0.032) higher adjusted risk for CKD progression.

CONCLUSIONS

Plasma LRG1 predicts both albuminuria and CKD progression beyond traditional risk factors. It may play a role in the pathologic pathway leading to progression of DKD in T2DM.

The nephrologist of tomorrow: towards a kidney-omic future

Omics refers to the collective technologies used to explore the roles and relationships of the various types of molecules that make up the phenotype of an organism. Systems biology is a scientific discipline that endeavours to quantify all of the molecular elements of a biological system. Therefore, it reflects the knowledge acquired by omics in a meaningful manner by providing insights into functional pathways and regulatory networks underlying different diseases. The recent advances in biotechnological platforms and statistical tools to analyse such complex data have enabled scientists to connect the experimentally observed correlations to the underlying biochemical and pathological processes. We discuss in this review the current knowledge of different omics technologies in kidney diseases, specifically in the field of pediatric nephrology, including biomarker discovery, defining as yet unrecognized biologic therapeutic targets and linking omics to relevant standard indices and clinical outcomes. We also provide here a unique perspective on the field, taking advantage of the experience gained by the large-scale European research initiative called "Systems Biology towards Novel Chronic Kidney Disease Diagnosis and Treatment" (SysKid). Based on the integrative framework of Systems biology, SysKid demonstrated how omics are powerful yet complex tools to unravel the consequences of diabetes and hypertension on kidney function.

Pericytes and immune cells contribute to complement activation in tubulointerstitial fibrosis

We have examined the pathogenic role of increased complement expression and activation during kidney fibrosis. Here, we show that PDGFRβ-positive pericytes isolated from mice subjected to obstructive or folic acid injury secrete C1q. This was associated with increased production of proinflammatory cytokines, extracellular matrix components, collagens, and increased Wnt3a-mediated activation of Wnt/β-catenin signaling, which are hallmarks of myofibroblast activation. Real-time PCR, immunoblots, immunohistochemistry, and flow cytometry analysis performed in whole kidney tissue confirmed increased expression of C1q, C1r, and C1s as well as complement activation, which is measured as increased synthesis of C3 fragments predominantly in the interstitial compartment. Flow studies localized increased C1q expression to PDGFRβ-positive pericytes as well as to CD45-positive cells. Although deletion of C1qA did not prevent kidney fibrosis, global deletion of C3 reduced macrophage infiltration, reduced synthesis of C3 fragments, and reduced fibrosis. Clodronate mediated depletion of CD11bF4/80 high macrophages in UUO mice also reduced complement gene expression and reduced fibrosis. Our studies demonstrate local synthesis of complement by both PDGFRβ-positive pericytes and CD45-positive cells in kidney fibrosis. Inhibition of complement activation represents a novel therapeutic target to ameliorate fibrosis and progression of chronic kidney disease.

Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease

The past decade has resulted in multiple new findings of potential proteomic biomarkers of diabetic kidney disease (DKD). Many of these biomarkers reflect an important role in the (patho)physiology and biological processes of DKD. Situations in which proteomics could be applied in clinical practice include the identification of individuals at risk of progressive kidney disease and those who would respond well to treatment, in order to tailor therapy for those at highest risk. However, while many proteomic biomarkers have been discovered, and even found to be predictive, most lack rigorous external validation in sufficiently powered studies with renal endpoints. Moreover, studies assessing short-term changes in the proteome for therapy-monitoring purposes are lacking. Collaborations between academia and industry and enhanced interactions with regulatory agencies are needed to design new, sufficiently powered studies to implement proteomics in clinical practice.

Development of a MALDI MS-based platform for early detection of acute kidney injury

PURPOSE

Septic acute kidney injury (AKI) is associated with poor outcome. This can partly be attributed to delayed diagnosis and incomplete understanding of the underlying pathophysiology. Our aim was to develop an early predictive test for AKI based on the analysis of urinary peptide biomarkers by MALDI-MS.

EXPERIMENTAL DESIGN

Urine samples from 95 patients with sepsis were analyzed by MALDI-MS. Marker search and multimarker model establishment were performed using the peptide profiles from 17 patients with existing or within the next 5 days developing AKI and 17 with no change in renal function. Replicates of urine sample pools from the AKI and non-AKI patient groups and normal controls were also included to select the analytically most robust AKI markers.

RESULTS

Thirty-nine urinary peptides were selected by cross-validated variable selection to generate a support vector machine multidimensional AKI classifier. Prognostic performance of the AKI classifier on an independent validation set including the remaining 61 patients of the study population (17 controls and 44 cases) was good with an area under the receiver operating characteristics curve of 0.82 and a sensitivity and specificity of 86% and 76%, respectively.

CONCLUSION AND CLINICAL RELEVANCE

A urinary peptide marker model detects onset of AKI with acceptable accuracy in septic patients. Such a platform can eventually be transferred to the clinic as fast MALDI-MS test format.

Proteomic Investigations into Hemodialysis Therapy

The retention of a number of solutes that may cause adverse biochemical/biological effects, called uremic toxins, characterizes uremic syndrome. Uremia therapy is based on renal replacement therapy, hemodialysis being the most commonly used modality. The membrane contained in the hemodialyzer represents the ultimate determinant of the success and quality of hemodialysis therapy. Membrane's performance can be evaluated in terms of removal efficiency for unwanted solutes and excess fluid, and minimization of negative interactions between the membrane material and blood components that define the membrane's bio(in)compatibility. Given the high concentration of plasma proteins and the complexity of structural functional relationships of this class of molecules, the performance of a membrane is highly influenced by its interaction with the plasma protein repertoire. Proteomic investigations have been increasingly applied to describe the protein uremic milieu, to compare the blood purification efficiency of different dialyzer membranes or different extracorporeal techniques, and to evaluate the adsorption of plasma proteins onto hemodialysis membranes. In this article, we aim to highlight investigations in the hemodialysis setting making use of recent developments in proteomic technologies. Examples are presented of why proteomics may be helpful to nephrology and may possibly affect future directions in renal research.