Detection of pro angiogenic and inflammatory biomarkers in patients with CKD

Multiomic profiling of new-onset kidney function decline: insights from the STANISLAS study cohort with a 20-year follow-up

Background

Identifying the biomarkers associated with new-onset glomerular filtration rate (GFR) decrease in an initially healthy population could offer a better understanding of kidney function decline and help improving patient management.

Methods

Here we described the proteomic and transcriptomic footprints associated with new-onset kidney function decline in an initially healthy and well-characterized population with a 20-year follow-up. This study was based on 1087 individuals from the familial longitudinal Suivi Temporaire Annuel Non-Invasif de la Santé des Lorrains Assurés Sociaux (STANISLAS) cohort who attended both visit 1 (from 1993 to 1995) and visit 4 (from 2011 to 2016). New-onset kidney function decline was approached both in quantitative (GFR slope for each individual) and qualitative (defined as a decrease in GFR of >15 ml/min/1.7 m2) ways. We analysed associations of 445 proteins measured both at visit 1 and visit 4 using Olink Proseek® panels and 119 765 genes expressions measured at visit 4 with GFR decline. Associations were assessed using multivariable models. The Bonferroni correction was applied.

Results

We found several proteins (including PLC, placental growth factor (PGF), members of the tumour necrosis factor receptor superfamily), genes (including CCL18, SESN3), and a newly discovered miRNA-mRNA pair (MIR1205-DNAJC6) to be independently associated with new-onset kidney function decline. Complex network analysis highlighted both extracellular matrix and cardiovascular remodelling (since visit 1) as well as inflammation (at visit 4) as key features of early GFR decrease.

Conclusions

These findings lay the foundation to further assess whether the proteins and genes herein identified may represent potential biomarkers or therapeutic targets to prevent renal function impairment.

Small RNA sequencing reveals snoRNAs and piRNA-019825 as novel players in diabetic kidney disease

INTRODUCTION

Micro- and macrovascular complications are common among persons with type 2 diabetes. Recently there has been growing interest to investigate the potential of circulating small non-coding RNAs (sncRNAs) as contributors to the development of diabetic complications. In this study we investigate to what extent circulating sncRNAs levels associate with prevalent diabetic kidney disease (DKD) in persons with type 2 diabetes.

METHODS

Plasma sncRNAs levels were determined using small RNA-seq, allowing detection of miRNAs, snoRNAs, piRNAs, tRNA fragments, and various other sncRNA classes. We tested for differentially expressed sncRNAs in persons with type 2 diabetes, with DKD (n = 69) or without DKD (n = 405). In secondary analyses, we also tested the association with eGFR, albuminuria (UACR), and the plasma proteome.

RESULTS

In total seven sncRNAs were negatively associated with prevalent DKD (all PFDR ≤ 0.05). Including one microRNA (miR-143-5p), five snoRNAs (U8, SNORD118, SNORD24, SNORD107, SNORD87) and a piRNA (piR-019825 | DQ597218). Proteomic analyses showed that the seven sncRNAs, and especially the piRNA piR-019825, were associated with plasma levels of 24 proteins of which several have known associations with kidney function including TNF sR-I (TNFRFS1A), DAN (NBL1) and cystatin C (CST3).

CONCLUSION

We have identified novel small non-coding RNAs, primarily from classes other than microRNAs, that are associated with diabetic kidney disease. Our results show that the involvement of small non-coding RNAs in DKD goes beyond the already known microRNAs and also involves other classes of sncRNA, in particular snoRNAs and the piRNA piR-019825, that have never been studied before in relation to kidney function.

Engineered Extracellular Vesicles in Chronic Kidney Diseases: A Comprehensive Review

Chronic kidney diseases (CKD) present a formidable global health challenge, characterized by a deficiency of effective treatment options. Extracellular vesicles (EVs), recognized as multifunctional drug delivery systems in biomedicine, have gained accumulative interest. Specifically, engineered EVs have emerged as a promising therapeutic approach for targeted drug delivery, potentially addressing the complexities of CKD management. In this review, we systematically dissect EVs, elucidating their classification, biogenesis, composition, and cargo molecules. Furthermore, we explore techniques for EV engineering and strategies for their precise renal delivery, focusing on cargo loading and transportation, providing a comprehensive perspective. Moreover, this review also discusses and summarizes the diverse therapeutic applications of engineered EVs in CKD, emphasizing their anti-inflammatory, immunomodulatory, renoprotective, and tissue-regenerating effects. It critically evaluates the challenges and limitations in translating EV therapies from laboratory settings to clinical applications, while outlining future prospects and emerging trends.

Systematic review and bioinformatics analysis of plasma and serum extracellular vesicles proteome in type 2 diabetes

Background

Type 2 diabetes (T2D) is a complex metabolic ailment marked by a global high prevalence and significant attention in primary healthcare settings due to its elevated morbidity and mortality rates. The pathophysiological mechanisms underlying the onset and progression of this disease remain subjects of ongoing investigation. Recent evidence underscores the pivotal role of the intricate intercellular communication network, wherein cell-derived vesicles, commonly referred to as extracellular vesicles (EVs), emerge as dynamic regulators of diabetes-related complications. Given that the protein cargo carried by EVs is contingent upon the metabolic conditions of the originating cells, particular proteins may serve as informative indicators for the risk of activating or inhibiting signaling pathways crucial to the progression of T2D complications.

Methods

In this study, we conducted a systematic review to analyze the published evidence on the proteome of EVs from the plasma or serum of patients with T2D, both with and without complications (PROSPERO: CRD42023431464).

Results

Nine eligible articles were systematically identified from the databases, and the proteins featured in these articles underwent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. We identified changes in the level of 426 proteins, with CST6, CD55, HBA1, S100A8, and S100A9 reported to have high levels, while FGL1 exhibited low levels.

Conclusion

These proteins are implicated in pathophysiological mechanisms such as inflammation, complement, and platelet activation, suggesting their potential as risk markers for T2D development and progression. Further studies are required to explore this topic in greater detail.

Alterations in the Circulating Proteome Associated with Albuminuria

SIGNIFICANCE STATEMENT

We describe circulating proteins associated with albuminuria in a population of African American Study of Kidney Disease and Hypertension with CKD (AASK) using the largest proteomic platform to date: nearly 7000 circulating proteins, representing approximately 2000 new targets. Findings were replicated in a subset of a general population cohort with kidney disease (ARIC) and a population with CKD Chronic Renal Insufficiency Cohort (CRIC). In cross-sectional analysis, 104 proteins were significantly associated with albuminuria in the Black group, of which 67 of 77 available proteins were replicated in ARIC and 68 of 71 available proteins in CRIC. LMAN2, TNFSFR1B, and members of the ephrin superfamily had the strongest associations. Pathway analysis also demonstrated enrichment of ephrin family proteins.

BACKGROUND

Proteomic techniques have facilitated understanding of pathways that mediate decline in GFR. Albuminuria is a key component of CKD diagnosis, staging, and prognosis but has been less studied than GFR. We sought to investigate circulating proteins associated with higher albuminuria.

METHODS

We evaluated the cross-sectional associations of the blood proteome with albuminuria and longitudinally with doubling of albuminuria in the African American Study of Kidney Disease and Hypertension (AASK; 38% female; mean GFR 46; median urine protein-to-creatinine ratio 81 mg/g; n =703) and replicated in two external cohorts: a subset of the Atherosclerosis Risk in Communities (ARIC) study with CKD and the Chronic Renal Insufficiency Cohort (CRIC).

RESULTS

In cross-sectional analysis, 104 proteins were significantly associated with albuminuria in AASK, of which 67 of 77 available proteins were replicated in ARIC and 68 of 71 available proteins in CRIC. Proteins with the strongest associations included LMAN2, TNFSFR1B, and members of the ephrin superfamily. Pathway analysis also demonstrated enrichment of ephrin family proteins. Five proteins were significantly associated with worsening albuminuria in AASK, including LMAN2 and EFNA4, which were replicated in ARIC and CRIC.

CONCLUSIONS

Among individuals with CKD, large-scale proteomic analysis identified known and novel proteins associated with albuminuria and suggested a role for ephrin signaling in albuminuria progression.

Use of Computation Ecosystems to Analyze the Kidney-Heart Crosstalk

The identification of mediators for physiologic processes, correlation of molecular processes, or even pathophysiological processes within a single organ such as the kidney or heart has been extensively studied to answer specific research questions using organ-centered approaches in the past 50 years. However, it has become evident that these approaches do not adequately complement each other and display a distorted single-disease progression, lacking holistic multilevel/multidimensional correlations. Holistic approaches have become increasingly significant in understanding and uncovering high dimensional interactions and molecular overlaps between different organ systems in the pathophysiology of multimorbid and systemic diseases like cardiorenal syndrome because of pathological heart-kidney crosstalk. Holistic approaches to unraveling multimorbid diseases are based on the integration, merging, and correlation of extensive, heterogeneous, and multidimensional data from different data sources, both -omics and nonomics databases. These approaches aimed at generating viable and translatable disease models using mathematical, statistical, and computational tools, thereby creating first computational ecosystems. As part of these computational ecosystems, systems medicine solutions focus on the analysis of -omics data in single-organ diseases. However, the data-scientific requirements to address the complexity of multimodality and multimorbidity reach far beyond what is currently available and require multiphased and cross-sectional approaches. These approaches break down complexity into small and comprehensible challenges. Such holistic computational ecosystems encompass data, methods, processes, and interdisciplinary knowledge to manage the complexity of multiorgan crosstalk. Therefore, this review summarizes the current knowledge of kidney-heart crosstalk, along with methods and opportunities that arise from the novel application of computational ecosystems providing a holistic analysis on the example of kidney-heart crosstalk.

Biomarker-Development Proteomics in Kidney Transplantation: An Updated Review

Kidney transplantation (KT) is the optimal therapeutic strategy for patients with end-stage renal disease. The key to post-transplantation management is careful surveillance of allograft function. Kidney injury may occur from several different causes that require different patient management approaches. However, routine clinical monitoring has several limitations and detects alterations only at a later stage of graft damage. Accurate new noninvasive biomarker molecules are clearly needed for continuous monitoring after KT in the hope that early diagnosis of allograft dysfunction will lead to an improvement in the clinical outcome. The advent of “omics sciences”, and in particular of proteomic technologies, has revolutionized medical research. Proteomic technologies allow us to achieve the identification, quantification, and functional characterization of proteins/peptides in biological samples such as urine or blood through supervised or targeted analysis. Many studies have investigated proteomic techniques as potential molecular markers discriminating among or predicting allograft outcomes. Proteomic studies in KT have explored the whole transplant process: donor, organ procurement, preservation, and posttransplant surgery. The current article reviews the most recent findings on proteomic studies in the setting of renal transplantation in order to better understand the effective potential of this new diagnostic approach.

Alternative pathway diagnostics

Uncontrolled alternative pathway activation is the primary driver of several diseases, and it contributes to the pathogenesis of many others. Consequently, diagnostic tests to monitor this arm of the complement system are increasingly important. Defects in alternative pathway regulation are strong risk factors for disease, and drugs that specifically block the alternative pathway are entering clinical use. A range of diagnostic tests have been developed to evaluate and monitor the alternative pathway, including assays to measure its function, expression of alternative pathway constituents, and activation fragments. Genetic studies have also revealed many disease-associated variants in alternative pathway genes that predict the risk of disease and prognosis. Newer imaging modalities offer the promise of non-invasively detecting and localizing pathologic complement activation. Together, these various tests help in the diagnosis of disease, provide important prognostic information, and can help guide therapy with complement inhibitory drugs.

Renin: Measurements, Correlates, and Associations With Long-Term Adverse Kidney Outcomes

BACKGROUND

The association of renin with adverse kidney outcomes is largely unknown, and renin measurement strategies vary. We aimed to measure the clinical correlates of different renin measurements and the association between renin and incident chronic kidney disease (CKD), end-stage kidney disease (ESKD), and mortality.

METHODS

We performed a prospective cohort analysis of 9,420 participants in the Atherosclerosis Risk in Communities study followed from 1996 to 1998 through 2019. We estimated longitudinal associations of renin measured using SomaScan modified nucleotide aptamer assay with incident CKD, ESKD, and death using Cox proportional hazards models. Using samples from a subsequent study visit, we compared SomaScan renin with plasma renin activity (PRA) and renin level from Olink, and estimated associations with covariates using univariate and multivariable regression.

RESULTS

Higher SomaScan renin levels were associated with a higher risk of incident CKD (hazard ratio per two-fold higher [HR], 1.14; 95% confidence interval [CI], 1.09 to 1.20), ESKD (HR, 1.20; 95% CI, 1.03 to 1.41), and mortality (HR, 1.08; 95% CI, 1.04 to 1.13) in analyses adjusted for demographic, clinical, and socioeconomic covariates. SomaScan renin was moderately correlated with PRA (r = 0.61) and highly correlated with Olink renin (r = 0.94). SomaScan renin and PRA had similar clinical correlates except for divergent associations with age and beta-blocker use, both of which correlated positively with SomaScan renin but negatively with PRA.

CONCLUSIONS

SomaScan aptamer-based renin level was associated with a higher risk of CKD, ESKD, and mortality. It was moderately correlated with PRA, sharing generally similar clinical covariate associations.

Impact of Early Proteinuria Reduction in Glomerular Disease and Decline of Kidney Function: A Retrospective Cohort

Background: In glomerular disease, the degree of proteinuria is closely related to the progression of chronic kidney disease, and its reduction is associated with a slower decline in the glomerular filtration rate (eGFR) and consequent improvement in the renal prognosis. The aim of this study was to evaluate the impact of proteinuria reduction on the decline of the eGFR in patients with glomerular disease, during the first year after the diagnosis. Methods: This was a retrospective analysis of patients with primary glomerular disease, followed at the Nephrology Department of Centro Hospitalar Universitário Lisboa Norte, during 2019. We analyzed demographic, clinical and laboratorial characteristics (creatinine, GFR, urine analysis and quantification of proteinuria determined by the proteinuria/creatinuria ratio, in the first morning urine or a 24 h urine sample). The outcome assessed was the decline in renal function, defined as a reduction in the GFR ≥ 25%, during the follow-up period. Results: We analyzed 197 patients with glomerular disease, with a mean age of 41.7 ± 19.7 years and follow-up time of 6.5 ± 5.3 years. At the time of the diagnosis, the eGFR was 81.5 ± 49.8 mL/min/1.73 m2 and proteinuria was 3.5 g/24 h (IQR 5.8). At one-year follow-up, median proteinuria was 0.9 g/24 h (IQR 2.4). At the end of the follow-up, mean eGFR was 72.1 ± 43.3 mL/min/1.73 m2. Proteinuria (p = 0.435) and the eGFR (p = 0.880) at the time of diagnosis did not correlate with long-term decline in the eGFR. Proteinuria < 1 g/24 h (HR 0.45 (95% CI 0.25−0.83) p = 0.011) after the first year was protective against long-term decline in the eGFR. It maintained this association with the long-term eGFR decline, independently of the duration of the follow-up (HR 0.30 (95% CI 0.17−0.52) p < 0.001). Conclusions: Proteinuria reduction to lower than 1 g/24 h, during the first year after diagnosis, was a protective factor for the long-term decline of kidney function, having a more important role than proteinuria or the GFR at the time of the diagnosis.

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.

Graphene-Based Biosensors for Molecular Chronic Inflammatory Disease Biomarker Detection

Chronic inflammatory diseases, such as cancer, diabetes mellitus, stroke, ischemic heart diseases, neurodegenerative conditions, and COVID-19 have had a high number of deaths worldwide in recent years. The accurate detection of the biomarkers for chronic inflammatory diseases can significantly improve diagnosis, as well as therapy and clinical care in patients. Graphene derivative materials (GDMs), such as pristine graphene (G), graphene oxide (GO), and reduced graphene oxide (rGO), have shown tremendous benefits for biosensing and in the development of novel biosensor devices. GDMs exhibit excellent chemical, electrical and mechanical properties, good biocompatibility, and the facility of surface modification for biomolecular recognition, opening new opportunities for simple, accurate, and sensitive detection of biomarkers. This review shows the recent advances, properties, and potentialities of GDMs for developing robust biosensors. We show the main electrochemical and optical-sensing methods based on GDMs, as well as their design and manufacture in order to integrate them into robust, wearable, remote, and smart biosensors devices. We also describe the current application of such methods and technologies for the biosensing of chronic disease biomarkers. We also describe the current application of such methods and technologies for the biosensing of chronic disease biomarkers with improved sensitivity, reaching limits of detection from the nano to atto range concentration.

Expanded Haemodialysis as a Current Strategy to Remove Uremic Toxins

Chronic kidney disease (CKD) is characterized by the retention of solutes named uremic toxins, which strongly associate with high morbidity and mortality. Mounting evidence suggests that targeting uremic toxins and/or their pathways may decrease the risk of cardiovascular disease in CKD patients. Dialysis therapies have been developed to improve removal of uremic toxins. Advances in our understanding of uremic retention solutes as well as improvements in dialysis membranes and techniques (HDx, Expanded Hemodialysis) will offer the opportunity to ameliorate clinical symptoms and outcomes, facilitate personalized and targeted dialysis treatment, and improve quality of life, morbidity and mortality.