Use of Proteomics To Investigate Kidney Function Decline over 5 Years

Proteomic profiling of laser capture microdissection kidneys from diabetic nephropathy patients

Diabetic nephropathy (DN) remains the primary cause of end-stage renal disease (ESRD), warranting equal attention and separate analysis of glomerular, tubular, and interstitial lesions in its diagnosis and intervention. This study aims to identify the specific proteomics characteristics of DN, and assess changes in the biological processes associated with DN. 5 patients with DN and 5 healthy kidney transplant donor control individuals were selected for analysis. The proteomic characteristics of glomeruli, renal tubules, and renal interstitial tissue obtained through laser capture microscopy (LCM) were studied using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Significantly, the expression of multiple heat shock proteins (HSPs), tubulins, and heterogeneous nuclear ribonucleoproteins (hnRNPs) in glomeruli and tubules was significantly reduced. Differentially expressed proteins (DEPs) in the glomerulus showed significant enrichment in pathways related to cell junctions and cell movement, including the regulation of actin cytoskeleton and tight junction. DEPs in renal tubules were significantly enriched in glucose metabolism-related pathways, such as glucose metabolism, glycolysis/gluconeogenesis, and the citric acid cycle. Moreover, the glycolysis/gluconeogenesis pathway was a co-enrichment pathway in both DN glomeruli and tubules. Notably, ACTB emerged as the most crucial protein in the protein-protein interaction (PPI) analysis of DEPs in both glomeruli and renal tubules. In this study, we delve into the unique proteomic characteristics of each sub-region of renal tissue. This enhances our understanding of the potential pathophysiological changes in DN, particularly the potential involvement of glycolysis metabolic disorder, glomerular cytoskeleton and cell junctions. These insights are crucial for further research into the identification of disease biomarkers and the pathogenesis of DN.

Protein Biomarkers and Major Cardiovascular Events in Older People With Advanced CKD: The European Quality (EQUAL) Study

Rationale & Objective

Cardiovascular disease is the leading cause of morbidity and mortality in chronic kidney disease (CKD). We investigated 184 inflammatory and cardiovascular proteins to determine their potential as biomarkers for major cardiovascular events (MACEs).

Study Design

The European Quality (EQUAL) is an observational cohort study that enrolled people aged ≥65 years with an estimated glomerular filtration rate ≤20 mL/min/1.73 m2.

Setting & Participants

Recruited participants were split into the discovery (n = 611) and replication cohorts (n = 292).

Exposure

Levels of 184 blood proteins were measured at the baseline visit, and each protein was analyzed individually.

Outcome

MACE.

Analytical Approach

Cox proportional hazard models adjusted for age, sex, estimated glomerular filtration rate, previous MACE, and country were used to determine the risk of MACE. Proteins with false discovery rate adjusted P values of <0.05 in the discovery cohort were tested in the replication cohort. Sensitivity analyses were performed by adjusting for traditional risk factors, CKD-specific risk factors, and level of proteinuria and segregating atherosclerotic and nonatherosclerotic MACE.

Results

During a median follow-up of 2.9 years, 349 people (39%) experienced a MACE. Forty-eight proteins were associated with MACE in the discovery cohort; 9 of these were reproduced in the replication cohort. Three of these proteins maintained a strong association with MACE after adjustment for traditional and CKD-specific risk factors and proteinuria. Tenascin (TNC), fibroblast growth factor-23 (FGF-23), and V-set and immunoglobulin domain-containing protein 2 (VSIG2) were associated with both atherosclerotic and nonatherosclerotic MACE. All replicated proteins except carbonic anhydrase 1 and carbonic anhydrase 3 were associated with nonatherosclerotic MACE.

Limitations

Single protein concentration measurements and limited follow-up time.

Conclusions

Our findings corroborate previously reported relationships between FGF-23, vascular cell adhesion protein-1, TNC, and placental growth factor with cardiovascular outcomes in CKD. We identify 5 proteins not previously linked with MACE in CKD that may be targets for future therapies.

Plain-Language Summary

Kidney disease increases the risk of heart disease, stroke, and other vascular conditions. Blood tests that predict the likelihood of these problems may help to guide treatment, but studies are needed in people with kidney disease. We analyzed blood tests from older people with kidney disease, looking for proteins associated with higher risk of these conditions. Nine proteins were identified, of which 3 showed a strong effect after all other information was considered. This work supports previous research regarding 4 of these proteins and identifies 5 additional proteins that may be associated with higher risk. Further work is needed to confirm our findings and to determine whether these proteins can be used to guide treatment.

Proteomic analysis investigating kidney transplantation outcomes- a scoping review

BACKGROUND

Kidney transplantation is the optimal treatment option for most patients with end-stage kidney disease given the significantly lower morbidity and mortality rates compared to remaining on dialysis. Rejection and graft failure remain common in transplant recipients with limited improvement in long-term transplant outcomes despite therapeutic advances. There is an unmet need in the development of non-invasive biomarkers that specifically monitor graft function and predict transplant pathologies that affect outcomes. Despite the potential of proteomic investigatory approaches, up to now, no candidate biomarkers of sufficient sensitivity or specificity have translated into clinical use. The aim of this review was to collate and summarise protein findings and protein pathways implicated in the literature to date, and potentially flag putative biomarkers worth validating in independent patient cohorts.

METHODS

This review followed the Joanna Briggs' Institute Methodology for a scoping review. MedlineALL, Embase, Web of Science Core Collection, Scopus and Google Scholar databases were searched from inception until December 2022. Abstract and full text review were undertaken independently by two reviewers. Data was collated using a pre-designed data extraction tool.

RESULTS

One hundred one articles met the inclusion criteria. The majority were single-centre retrospective studies of small sample size. Mass spectrometry was the most used technique to evaluate differentially expressed proteins between diagnostic groups and studies identified various candidate biomarkers such as immune or structural proteins.

DISCUSSION

Putative immune or structural protein candidate biomarkers have been identified using proteomic techniques in multiple sample types including urine, serum and fluid used to perfuse donor kidneys. The most consistent findings implicated proteins associated with tubular dysfunction and immunological regulatory pathways such as leukocyte trafficking. However, clinical translation and adoption of candidate biomarkers is limited, and these will require comprehensive evaluation in larger prospective, multicentre trials.

Association Between Serum GDF15 Concentration and Total Mortality in Community-Dwelling Japanese Older Populations: The Involvement of Renal Dysfunction

BACKGROUND

Serum growth differentiation factor 15 (GDF15) is associated with age-related adverse outcomes. However, renal function has not been thoroughly evaluated in studies addressing the association between GDF15 and mortality. We aimed to clarify whether GDF15 is associated with total mortality after carefully controlling renal function markers.

METHODS

We divided 1 801 community-dwelling Japanese older adults into quartiles according to their serum GDF15 concentrations. The correlation of GDF15 with renal function and inflammation markers was assessed by calculating Spearman correlation coefficients. Cumulative survival rates of the quartiles were estimated. In a Cox regression analysis adjusted for confounders, the association between GDF15 and mortality was evaluated. The discriminative capacity of GDF15 for the prediction of mortality was assessed with receiver-operating characteristic analysis.

RESULTS

GDF15 was correlated with cystatin C (r = 0.394), β2-microglobulin (r = 0.382), C-reactive protein (r = 0.124), and interleukin-6 (r = 0.166). The highest GDF15 quartile showed poor survival compared to the others. Older adults with higher GDF15 were associated with an increased mortality risk, independent of demographics and clinically relevant variables (hazard ratio [95% confidence interval]: 1.98 [1.09-3.59]). This significant association disappeared when additionally adjusted for cystatin C (1.65 [0.89-3.05]) or β2-microglobulin (1.69 [0.91-3.12]). The ability to predict mortality was approximately comparable between GDF15 (area under the curve: 0.667), cystatin C (0.691), and β2-microglobulin (0.715).

CONCLUSIONS

Serum GDF15 is associated with total mortality in older Japanese after adjustment for major confounders. The increased mortality risk in older adults with higher GDF15 may be partly attributed to decreased renal function.

Migraine, chronic kidney disease and kidney function: observational and genetic analyses

Epidemiological studies demonstrate an association between migraine and chronic kidney disease (CKD), while the genetic basis underlying the phenotypic association has not been investigated. We aimed to help avoid unnecessary interventions in individuals with migraine through the investigation of phenotypic and genetic relationships underlying migraine, CKD, and kidney function. We first evaluated phenotypic associations using observational data from UK Biobank (N = 255,896). We then investigated genetic relationships leveraging genomic data in European ancestry for migraine (Ncase/Ncontrol = 48,975/540,381), CKD (Ncase/Ncontrol = 41,395/439,303), and two traits of kidney function (estimated glomerular filtration rate [eGFR, N = 567,460] and urinary albumin-to-creatinine ratio [UACR, N = 547,361]). Observational analyses suggested no significant association of migraine with the risk of CKD (HR = 1.13, 95% CI = 0.85-1.50). While we did not find any global genetic correlation in general, we identified four specific genomic regions showing significant for migraine with eGFR. Cross-trait meta-analysis identified one candidate causal variant (rs1047891) underlying migraine, CKD, and kidney function. Transcriptome-wide association study detected 28 shared expression-trait associations between migraine and kidney function. Mendelian randomization analysis suggested no causal effect of migraine on CKD (OR = 1.03, 95% CI = 0.98-1.09; P = 0.28). Despite a putative causal effect of migraine on an increased level of UACR (log-scale-beta = 0.02, 95% CI = 0.01-0.04; P = 1.92 × 10-3), it attenuated to null when accounting for both correlated and uncorrelated pleiotropy. Our work does not find evidence supporting a causal association between migraine and CKD. However, our study highlights significant biological pleiotropy between migraine and kidney function. The value of a migraine prophylactic treatment for reducing future CKD in people with migraine is likely limited.

Validation of eGFR for Detecting Associations Between Serum Protein Biomarkers and Subsequent GFR Decline

SIGNIFICANCE STATEMENT

eGFR from creatinine, cystatin C, or both has been primarily used in search of biomarkers for GFR decline. Whether the relationships between biomarkers and eGFR decline are similar to associations with measured GFR (mGFR) decline has not been investigated. This study revealed that some biomarkers showed statistically significant different associations with eGFR decline compared with mGFR decline, particularly for eGFR from cystatin C. The findings indicate that non-GFR-related factors, such as age, sex, and body mass index, influence the relationship between biomarkers and eGFR decline. Therefore, the results of biomarker studies using eGFR, particularly eGFRcys, should be interpreted with caution and perhaps validated with mGFR.

BACKGROUND

Several serum protein biomarkers have been proposed as risk factors for GFR decline using eGFR from creatinine or cystatin C. We investigated whether eGFR can be used as a surrogate end point for measured GFR (mGFR) when searching for biomarkers associated with GFR decline.

METHODS

In the Renal Iohexol Clearance Survey, GFR was measured with plasma iohexol clearance in 1627 individuals without diabetes, kidney, or cardiovascular disease at baseline. After 11 years of follow-up, 1409 participants had one or more follow-up GFR measurements. Using logistic regression and interval-censored Cox regression, we analyzed the association between baseline levels of 12 serum protein biomarkers with the risk of accelerated GFR decline and incident CKD for both mGFR and eGFR.

RESULTS

Several biomarkers exhibited different associations with eGFR decline compared with their association with mGFR decline. More biomarkers showed different associations with eGFRcys decline than with eGFRcre decline. Most of the different associations of eGFR decline versus mGFR decline remained statistically significant after adjustment for age, sex, and body mass index, but several were attenuated and not significant after adjusting for the corresponding baseline mGFR or eGFR.

CONCLUSIONS

In studies of some serum protein biomarkers, eGFR decline may not be an appropriate surrogate outcome for mGFR decline. Although the differences from mGFR decline are attenuated by adjustment for confounding factors in most cases, some persist. Therefore, proposed biomarkers from studies using eGFR should preferably be validated with mGFR.

Proteomic profiling of longitudinal changes in kidney function among middle-aged and older men and women: the KORA S4/F4/FF4 study

BACKGROUND

Due to the asymptomatic nature of the early stages, chronic kidney disease (CKD) is usually diagnosed at late stages and lacks targeted therapy, highlighting the need for new biomarkers to better understand its pathophysiology and to be used for early diagnosis and therapeutic targets. Given the close relationship between CKD and cardiovascular disease (CVD), we investigated the associations of 233 CVD- and inflammation-related plasma proteins with kidney function decline and aimed to assess whether the observed associations are causal.

METHODS

We included 1140 participants, aged 55-74 years at baseline, from the Cooperative Health Research in the Region of Augsburg (KORA) cohort study, with a median follow-up time of 13.4 years and 2 follow-up visits. We measured 233 plasma proteins using a proximity extension assay at baseline. In the discovery analysis, linear regression models were used to estimate the associations of 233 proteins with the annual rate of change in creatinine-based estimated glomerular filtration rate (eGFRcr). We further investigated the association of eGFRcr-associated proteins with the annual rate of change in cystatin C-based eGFR (eGFRcys) and eGFRcr-based incident CKD. Two-sample Mendelian randomization was used to infer causality.

RESULTS

In the fully adjusted model, 66 out of 233 proteins were inversely associated with the annual rate of change in eGFRcr, indicating that higher baseline protein levels were associated with faster eGFRcr decline. Among these 66 proteins, 21 proteins were associated with both the annual rate of change in eGFRcys and incident CKD. Mendelian randomization analyses on these 21 proteins suggest a potential causal association of higher tumor necrosis factor receptor superfamily member 11A (TNFRSF11A) level with eGFR decline.

CONCLUSIONS

We reported 21 proteins associated with kidney function decline and incident CKD and provided preliminary evidence suggesting a potential causal association between TNFRSF11A and kidney function decline. Further Mendelian randomization studies are needed to establish a conclusive causal association.

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.

The use of plasma biomarker-derived clusters for clinicopathologic phenotyping: results from the Boston Kidney Biopsy Cohort

Background

Protein biomarkers may provide insight into kidney disease pathology but their use for the identification of phenotypically distinct kidney diseases has not been evaluated.

Methods

We used unsupervised hierarchical clustering on 225 plasma biomarkers in 541 individuals enrolled into the Boston Kidney Biopsy Cohort, a prospective cohort study of individuals undergoing kidney biopsy with adjudicated histopathology. Using principal component analysis, we studied biomarker levels by cluster and examined differences in clinicopathologic diagnoses and histopathologic lesions across clusters. Cox proportional hazards models tested associations of clusters with kidney failure and death.

Results

We identified three biomarker-derived clusters. The mean estimated glomerular filtration rate was 72.9 ± 28.7, 72.9 ± 33.4 and 39.9 ± 30.4 mL/min/1.73 m2 in Clusters 1, 2 and 3, respectively. The top-contributing biomarker in Cluster 1 was AXIN, a negative regulator of the Wnt signaling pathway. The top-contributing biomarker in Clusters 2 and 3 was Placental Growth Factor, a member of the vascular endothelial growth factor family. Compared with Cluster 1, individuals in Cluster 3 were more likely to have tubulointerstitial disease (P < .001) and diabetic kidney disease (P < .001) and had more severe mesangial expansion [odds ratio (OR) 2.44, 95% confidence interval (CI) 1.29, 4.64] and inflammation in the fibrosed interstitium (OR 2.49 95% CI 1.02, 6.10). After multivariable adjustment, Cluster 3 was associated with higher risks of kidney failure (hazard ratio 3.29, 95% CI 1.37, 7.90) compared with Cluster 1.

Conclusion

Plasma biomarkers may identify clusters of individuals with kidney disease that associate with different clinicopathologic diagnoses, histopathologic lesions and adverse outcomes, and may uncover biomarker candidates and relevant pathways for further study.

High-throughput proteomics: a methodological mini-review

Proteomics plays a vital role in biomedical research in the post-genomic era. With the technological revolution and emerging computational and statistic models, proteomic methodology has evolved rapidly in the past decade and shed light on solving complicated biomedical problems. Here, we summarize scientific research and clinical practice of existing and emerging high-throughput proteomics approaches, including mass spectrometry, protein pathway array, next-generation tissue microarrays, single-cell proteomics, single-molecule proteomics, Luminex, Simoa and Olink Proteomics. We also discuss important computational methods and statistical algorithms that can maximize the mining of proteomic data with clinical and/or other 'omics data. Various principles and precautions are provided for better utilization of these tools. In summary, the advances in high-throughput proteomics will not only help better understand the molecular mechanisms of pathogenesis, but also to identify the signature signaling networks of specific diseases. Thus, modern proteomics have a range of potential applications in basic research, prognostic oncology, precision medicine, and drug discovery.

The Growth Factors: Potential Biomarkers and Therapeutic Targets in Kidney Diseases

BACKGROUND

Kidney diseases are a prevalent health problem worldwide. Although substantial progress has been made in understanding the pathophysiology of kidney disease, currently there is no satisfactory clinical treatment available to prevent or treat kidney disease. Therefore, strategies to establish early diagnosis, identify the key molecules, and develop novel therapeutic interventions to slow the progression of kidney diseases and reduce their complications are encouraged.

SUMMARY

The growth factors play a crucial role in the development of kidney diseases. The altered levels of growth factors are usually detected in circulation and urine in the disease course. A growing body of studies has suggested that growth factors, receptors, and related regulators are promising biomarkers for the diagnosis and/or prognosis and potential therapeutic targets for the treatment of kidney diseases. In this review, we summarize recent advances in the potential applications of growth factors for diagnostic biomarkers and therapeutic targets in kidney diseases and highlight their performances in clinical trials.

KEY MESSAGES

Most diagnostic and therapeutic strategies targeting growth factors are still far from clinical implementation. The better understanding of growth factor-regulated pathophysiology and the progress of new intervention approaches are expected to facilitate the clinical translation of growth factor-based diagnosis and therapy of kidney diseases.

Up-Date on Diabetic Nephropathy

Diabetes is one of the leading causes of kidney disease. Diabetic kidney disease (DKD) is a major cause of end-stage kidney disease (ESKD) worldwide, and it is linked to an increase in cardiovascular (CV) risk. Diabetic nephropathy (DN) increases morbidity and mortality among people living with diabetes. Risk factors for DN are chronic hyperglycemia and high blood pressure; the renin-angiotensin-aldosterone system blockade improves glomerular function and CV risk in these patients. Recently, new antidiabetic drugs, including sodium-glucose transport protein 2 inhibitors and glucagon-like peptide-1 agonists, have demonstrated additional contribution in delaying the progression of kidney disease and enhancing CV outcomes. The therapeutic goal is regression of albuminuria, but an atypical form of non-proteinuric diabetic nephropathy (NP-DN) is also described. In this review, we provide a state-of-the-art evaluation of current treatment strategies and promising emerging treatments.

Elevated Serum Osteoprotegerin is Associated with Reduced Risks of Albuminuria and CKD Progression in Patients with Type 2 Diabetes

OBJECTIVE

To analyze the correlation between serum osteoprotegerin (OPG) level and chronic kidney disease (CKD) at different CKD stages in patients with type 2 diabetes.

METHODS

All subjects were hospitalized patients with type 2 diabetes. Medical history collection, physical examinations, and blood and urine samples testing were performed. Stages of CKD (G1-5) were defined by eGFR, groups of persistent albuminuria (normal, microalbuminuria and massive albuminuria) were divided by UACR, and categories of CKD progression risks (low, moderate and high or very high risk) were recommended by the Kidney Disease: Improving Global Outcomes (KDIGO). Serum OPG level was determined by enzyme-linked immunosorbent assay in the central laboratory.

RESULTS

Four hundred and eighty-four patients were included in the study. The average level of OPG of all subjects was 941.30 (547.53-1332.62) pg/mL. The levels of OPG decreased gradually with the aggravation of albuminuria (P = 0.007, P _{for trend}=0.003) and CKD progression (P = 0.001, P _{for trend}=0.001). No differences were found between OPG levels and stages of CKD (P = 0.31). After the adjustment, each 100 pg/mL increase in OPG levels could reduce the risk of massive albuminuria (OR 0.92, 95% CI 0.86-0.99, P = 0.02) and the high or very high risk of CKD progression (OR 0.94, 95% CI 0.89-0.99, P = 0.04) by multivariate logistic regression analysis. No correlations were found between OPG and stages of CKD.

CONCLUSION

In patients with type 2 diabetes, elevated serum osteoprotegerin is associated with albuminuria and the risk of CKD progression, and may delay the progression of CKD.

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.

Growth differentiation factor-15 and incident chronic kidney disease: a population-based cohort study

Background

The relationship between growth differentiation factor 15 (GDF-15) and the development of chronic kidney disease (CKD) is still unclear. We sought to examine whether plasma GDF-15 was related to incident CKD and kidney function decline using a large prospective cohort study.

Methods

4318 participants of the Malmö Diet and Cancer Study-Cardiovascular Cohort were examined in 1991-1994. Incidence of CKD was followed prospectively by linkage with national patient registers. Estimated glomerular filtration rate (eGFR) was available for all participants at baseline, and was re-measured in a subgroup of 2744 subjects after 16.6 ± 1.49 years. Incidence of CKD was examined in relation to GDF-15 using Cox regression analysis. Logistic regression was used to examine the association of GDF-15 with eGFR change and eGFR-based CKD. Models were carefully corrected for potential confounders including baseline eGFR, N-terminal pro-B-type natriuretic peptide, and competing risk from death.

Results

165 patients developed CKD after 19.2 ± 4.04 years of follow-up. The adjusted hazard ratio (95% confidence interval, CI) for CKD in 4th versus 1st quartile of GDF-15 was 2.37 (1.33, 4.24) (p for trend < 0.01). Each per 1 standard deviation increase in GDF-15 was associated with a decline in eGFR of − 0.97 mL/min/1.73 m² (95% CI, − 1.49 ~ − 0.45; p < 0.001). GDF-15 was also significantly associated eGFR-based CKD in 2713 subjects with baseline eGFR ≥60 mL/min/1.73 m².

Conclusions

GDF-15 predicted incidence of CKD and eGFR decline in the general population, independent of a wide range of potential risk factors and competing risk of death.

Novel biomarkers of inflammation, kidney function and chronic kidney disease in the general population

BACKGROUND

Inflammatory processes have been implicated in the development of chronic kidney disease (CKD). We investigated the association of a large panel of inflammatory biomarkers reflecting aspects of immunity with kidney function and CKD incidence.

METHODS

We used data from two independent population-based studies, KORA F4 (discovery, n = 1,110, mean age 70.3 years, 48.7% male) and ESTHER (replication, n = 1,672, mean age 61.9 years, 43.6% male). Serum levels of biomarkers were measured using proximity extension assay technology. The association of biomarkers with estimated glomerular filtration rate (eGFR) at baseline and with incident CKD was investigated using linear and logistic regression models adjusted for cardiorenal risk factors. Independent results from prospective analyses of both studies were pooled. The significance level was corrected for multiple testing by false-discovery rate (PFDR < 0.05.).

RESULTS

In the KORA F4 discovery study, 52 out of 71 inflammatory biomarkers were inversely associated with eGFR estimated based on serum creatinine. Top biomarkers included CD40, TNFRSF9 and IL10RB. Forty-two of these 52 biomarkers were replicated in the ESTHER study. Nine of the 42 biomarkers were associated with incident CKD independently of cardiorenal risk factors in the meta-analysis of the KORA (n = 142, mean follow-up of 6.5 years) and ESTHER (n = 103, mean follow-up of 8 years) studies. Pathway analysis revealed the involvement of inflammatory and immunomodulatory processes reflecting cross-communication of innate and adaptive immune cells.

CONCLUSIONS

Novel and known biomarkers of inflammation were reproducibly associated with kidney function. Future studies should investigate their clinical utility and underlying molecular mechanisms in independent cohorts.

Longitudinal Bottom-Up Proteomics of Serum, Serum Extracellular Vesicles, and Cerebrospinal Fluid Reveals Candidate Biomarkers for Early Detection of Glioblastoma in a Murine Model

Glioblastoma Multiforme (GBM) is a brain tumor with a poor prognosis and low survival rates. GBM is diagnosed at an advanced stage, so little information is available on the early stage of the disease and few improvements have been made for earlier diagnosis. Longitudinal murine models are a promising platform for biomarker discovery as they allow access to the early stages of the disease. Nevertheless, their use in proteomics has been limited owing to the low sample amount that can be collected at each longitudinal time point. Here we used optimized microproteomics workflows to investigate longitudinal changes in the protein profile of serum, serum small extracellular vesicles (sEVs), and cerebrospinal fluid (CSF) in a GBM murine model. Baseline, pre-symptomatic, and symptomatic tumor stages were determined using non-invasive motor tests. Forty-four proteins displayed significant differences in signal intensities during GBM progression. Dysregulated proteins are involved in cell motility, cell growth, and angiogenesis. Most of the dysregulated proteins already exhibited a difference from baseline at the pre-symptomatic stage of the disease, suggesting that early effects of GBM might be detectable before symptom onset.

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.

Plasma Proteomics of Renal Function: A Transethnic Meta-Analysis and Mendelian Randomization Study

BACKGROUND

Studies on the relationship between renal function and the human plasma proteome have identified several potential biomarkers. However, investigations have been conducted largely in European populations, and causality of the associations between plasma proteins and kidney function has never been addressed.

METHODS

A cross-sectional study of 993 plasma proteins among 2882 participants in four studies of European and admixed ancestries (KORA, INTERVAL, HUNT, QMDiab) identified transethnic associations between eGFR/CKD and proteomic biomarkers. For the replicated associations, two-sample bidirectional Mendelian randomization (MR) was used to investigate potential causal relationships. Publicly available datasets and transcriptomic data from independent studies were used to examine the association between gene expression in kidney tissue and eGFR.

RESULTS

In total, 57 plasma proteins were associated with eGFR, including one novel protein. Of these, 23 were additionally associated with CKD. The strongest inferred causal effect was the positive effect of eGFR on testican-2, in line with the known biological role of this protein and the expression of its protein-coding gene (SPOCK2) in renal tissue. We also observed suggestive evidence of an effect of melanoma inhibitory activity (MIA), carbonic anhydrase III, and cystatin-M on eGFR.

CONCLUSIONS

In a discovery-replication setting, we identified 57 proteins transethnically associated with eGFR. The revealed causal relationships are an important stepping stone in establishing testican-2 as a clinically relevant physiological marker of kidney disease progression, and point to additional proteins warranting further investigation.

Plasma Protein Profile of Incident Myocardial Infarction, Ischemic Stroke, and Heart Failure in 2 Cohorts

Background The aim is to study common etiological pathways for 3 major cardiovascular diseases (CVD), as reflected in multiple proteins. Methods and Results Eighty-four proteins were measured using the proximity extension technique in 870 participants in the PIVUS (Prospective Investigation of Uppsala Seniors Study) cohort on 3 occasions (age 70, 75, and 80 years). The sample was followed for incident myocardial infarction, ischemic stroke or heart failure. The same proteins were measured in an independent validation sample, the ULSAM (Uppsala Longitudinal Study of Adult Men) cohort in 595 participants at age 77. During a follow-up of up to 15 years in PIVUS and 9 years in ULSAM, 222 and 167 individuals experienced a CVD. Examining associations with the 3 outcomes separately in a meta-analysis of the 2 cohorts, 6 proteins were related to incident myocardial infarction, 25 to heart failure, and 8 proteins to ischemic stroke following adjustment for traditional risk factors. Growth differentiation factor 15 and tumor necrosis factor-related apoptosis-inducing ligand receptor 2 were related to all 3 CVDs. Including estimated glomerular filtration rate in the models attenuated some of these relationships. Fifteen proteins were related to a composite of all 3 CVDs using a discovery/validation approach when adjusting for traditional risk factors. A selection of 7 proteins by lasso in PIVUS improved discrimination of incident CVD by 7.3% compared with traditional risk factors in ULSAM. Conclusions We discovered and validated associations of multiple proteins with incident CVD. Only a few proteins were associated with all 3 diseases: myocardial infarction, ischemic stroke, and heart failure.

Serum syndecan-1, hyaluronan and thrombomodulin levels in patients with lupus nephritis

OBJECTIVES

We investigated circulating syndecan-1, HA and thrombomodulin levels in patients with biopsy-proven Class III/IV ± V LN and their clinico-pathological associations. Patients with non-renal SLE or non-lupus chronic kidney disease, and healthy subjects served as controls.

METHODS

Serum syndecan-1, HA and thrombomodulin levels were determined by ELISAs.

RESULTS

Syndecan-1, HA and thrombomodulin levels were significantly higher during active LN compared with remission (P < 0.01, for all), and correlated with the level of proteinuria, estimated glomerular filtration rate, anti-dsDNA antibodies, complement 3 and serum creatinine. Longitudinal studies showed that syndecan-1 and thrombomodulin levels increased prior to clinical renal flare by 3.6 months, while HA level increased at the time of nephritic flare, and the levels decreased in parallel with treatment response. Receiver operating characteristic curve analysis showed that syndecan-1 and thrombomodulin levels distinguished patients with active LN from healthy subjects, LN patients in remission, patients with active non-renal lupus and patients with non-lupus chronic kidney disease (receiver operating characteristic area under curve of 0.98, 0.91, 0.82 and 0.95, respectively, for syndecan-1; and area under curve of 1.00, 0.84, 0.97 and 0.79, respectively, for thrombomodulin). HA level distinguished active LN from healthy subjects, LN patients in remission and non-lupus chronic kidney disease (receiver operating characteristic area under curve of 0.82, 0.71 and 0.90, respectively) but did not distinguish between renal vs non-renal lupus. Syndecan-1 and thrombomodulin levels correlated with the severity of interstitial inflammation, while HA level correlated with chronicity grading in kidney biopsies of active LN.

CONCLUSION

Our findings suggest potential utility of serum syndecan-1, thrombomodulin and HA levels in clinical management, and their potential contribution to LN pathogenesis.

Urinary Growth Differentiation Factor-15 (GDF15) levels as a biomarker of adverse outcomes and biopsy findings in chronic kidney disease

BACKGROUND

Growth Differentiation Factor-15 (GDF15) is a member of the TGF-β superfamily. Increased serum GDF15 has been associated with increased risk of chronic kidney disease (CKD) progression. However, no prior studies have addressed the significance of urinary GDF15 in adult CKD.

METHODS

We measured serum and urinary GDF15 in a prospective cohort of 84 patients who underwent kidney biopsy and assessed their association with outcomes (survival, kidney replacement therapy) during a follow-up of 29 ± 17 months.

RESULTS

There was a statistically significant correlation between serum and urine GDF15 values. However, while serum GDF15 values increased with decreasing glomerular filtration rate, urinary GDF15 did not. Immunohistochemistry located kidney GDF15 expression mainly in tubular cells, and kidney GDF15 staining correlated with urinary GDF15 values. Urine GDF15 was significantly higher in patients with a histologic diagnosis of diabetic nephropathy than in diabetic patients without diabetic nephropathy. This was not the case for serum GDF15. Both serum and urine GDF15 were negatively associated with patient survival in multivariate models. However, when both urine and serum GDF15 were present in the model, lower urine GDF15 predicted patient survival [B coefficient (SEM) - 0.395 (0.182) p 0.03], and higher urine GDF15 predicted a composite of mortality or kidney replacement therapy [0.191 (0.06) p 0.002], while serum GDF15 was not predictive. Decision tree analysis yielded similar results. The area under the curve (AUC) of the receiver operating curve (ROC) for urine GDF15 as a predictor of mortality was 0.95 (95% CI 0.89-1.00, p < 0.001).

CONCLUSIONS

In conclusion, urinary GDF15 is associated with kidney histology patterns, mortality and the need for renal replacement therapy (RRT) in CKD patients who underwent a kidney biopsy.

Urinary liver-type fatty acid-binding protein is independently associated with graft failure in outpatient kidney transplant recipients

Urinary liver-type fatty acid-binding protein (uL-FABP) is a biomarker of kidney hypoxia and ischemia, and thus offers a novel approach to identify early kidney insults associated with increased risk of graft failure in outpatient kidney transplant recipients (KTR). We investigated whether uL-FABP is associated with graft failure and whether it improves risk prediction. We studied a cohort of 638 outpatient KTR with a functional graft ≥1-year. During a median follow-up of 5.3 years, 80 KTR developed graft failure. uL-FABP (median 2.11, interquartile range 0.93-7.37 µg/24"/>h) was prospectively associated with the risk of graft failure (hazard ratio 1.75; 95% confidence interval 1.27-2.41 per 1-SD increment; P = .001), independent of potential confounders including estimated glomerular filtration rate and proteinuria. uL-FABP showed excellent discrimination ability for graft failure (c-statistic of 0.83) and its addition to a prediction model composed by established clinical predictors of graft failure significantly improved the c-statistic to 0.89 (P for F-test <.001). These results were robust to several sensitivity analyses. Further validation studies are warranted to evaluate the potential use of a risk-prediction model including uL-FABP to improve identification of outpatient KTR at high risk of graft failure in clinical care.

Longitudinal course of GDF15 levels before acute hospitalization and death in the general population

Growth differentiation 15 (GDF15) is a potential novel biomarker of biological aging. To separate the effects of chronological age and birth cohort from biological age, longitudinal studies investigating the associations of GDF15 levels with adverse health outcomes are needed. We investigated changes in GDF15 levels over 10 years in an age-stratified sample of the general population and their relation to the risk of acute hospitalization and death. Serum levels of GDF15 were measured three times in 5-year intervals in 2176 participants aged 30, 40, 50, or 60 years from the Danish population-based DAN-MONICA cohort. We assessed the association of single and repeated GDF15 measurements with the risk of non-traumatic acute hospitalizations. We tested whether changes in GDF15 levels over 10 years differed according to the frequency of hospitalizations within 2 years or survival within 20 years, after the last GDF15 measurement. The change in GDF15 levels over time was dependent on age and sex. Higher GDF15 levels and a greater increase in GDF15 levels were associated with an increased risk of acute hospitalization in adjusted Cox regression analyses. Participants with more frequent admissions within 2 years, and those who died within 20 years, after the last GDF15 measurement already had elevated GDF15 levels at baseline and experienced greater increases in GDF15 levels during the study. The change in GDF15 levels was associated with changes in C-reactive protein and biomarkers of kidney, liver, and cardiac function. Monitoring of GDF15 starting in middle-aged could be valuable for the prediction of adverse health outcomes.

Growth Differentiation Factor 15: A Biomarker with High Clinical Potential in the Evaluation of Kidney Transplant Candidates

Kidney transplantation implies a significant improvement in patient survival. Nevertheless, early mortality after transplant remains high. Growth differentiation factor 15 (GDF-15) is a novel biomarker under study as a mortality predictor in multiple scenarios. The aim of this study is to assess the utility of GDF-15 to predict survival in kidney transplant candidates. For this purpose, 395 kidney transplant recipients with pretransplant stored serum samples were included. The median GDF-15 was 5331.3 (50.49-16242.3) pg/mL. After a mean of 90.6 ± 41.5 months of follow-up, 82 (20.8%) patients died. Patients with higher GDF-15 levels (high risk tertile) had a doubled risk of mortality after adjustment by clinical characteristics (p = 0.009). After adjustment by EPTS (Estimated Post Transplant Survival score) the association remained significant for medium hazards ratios (HR) 3.24 95%CI (1.2-8.8), p = 0.021 and high risk tertiles HR 4.3 95%CI (1.65-11.54), p = 0.003. GDF-15 improved the prognostic accuracy of EPTS at 1-year (ΔAUC = 0.09, p = 0.039) and 3-year mortality (ΔAUC = 0.11, p = 0.036). Our study suggests an independent association between higher GDF-15 levels and mortality after kidney transplant, adding accuracy to the EPTS score, an established risk prediction model currently used in kidney transplant candidates.

A Paradigm to Discover Biomarkers Associated With Chronic Kidney Disease Progression

Biomarker discovery in the field of risk prediction in chronic kidney disease (CKD) embraces the prospect of improving our ability to risk stratify future adverse outcomes and thereby guide patient care in a new era of personalised medicine. However, many studies that report biomarkers predictive of CKD progression share a key methodological limitation: failure to characterise patients' renal progression precisely. This weakens any observable association between a biomarker and an outcome poorly defined by a patient's change in renal function over time. In this commentary, we discuss the need for a better approach in this research arena and describe a compelling strategy that has the advantage of offering robust and meaningful biomarker exploration relevant to CKD progression.

Use of proteomics to identify biomarkers associated with chronic kidney disease and long-term outcomes in patients with myocardial infarction

BACKGROUND

Patients with chronic kidney disease (CKD) have poor outcomes following myocardial infarction (MI). We performed an untargeted examination of 175 biomarkers to identify those with the strongest association with CKD and to examine the association of those biomarkers with long-term outcomes.

METHODS

A total of 175 different biomarkers from MI patients enrolled in the Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies (SWEDEHEART) registry were analysed either by a multiple reaction monitoring mass spectrometry assay or by a multiplex assay (proximity extension assay). Random forests statistical models were used to assess the predictor importance of biomarkers, CKD and outcomes.

RESULTS

A total of 1098 MI patients with a median estimated glomerular filtration rate of 85 mL min^-1 /1.73 m² were followed for a median of 3.2 years. The random forests analyses, without and with adjustment for differences in demography, comorbidities and severity of disease, identified six biomarkers (adrenomedullin, TNF receptor-1, adipocyte fatty acid-binding protein-4, TNF-related apoptosis-inducing ligand receptor 2, growth differentiation factor-15 and TNF receptor-2) to be strongly associated with CKD. All six biomarkers were also amongst the 15 strongest predictors for death, and four of them were amongst the strongest predictors of subsequent MI and heart failure hospitalization.

CONCLUSION

In patients with MI, a proteomic approach could identify six biomarkers that best predicted CKD. These biomarkers were also amongst the most important predictors of long-term outcomes. Thus, these biomarkers indicate underlying mechanisms that may contribute to the poor prognosis seen in patients with MI and CKD.

GDF15: A Hormone Conveying Somatic Distress to the Brain

GDF15 has recently gained scientific and translational prominence with the discovery that its receptor is a GFRAL-RET heterodimer of which GFRAL is expressed solely in the hindbrain. Activation of this receptor results in reduced food intake and loss of body weight and is perceived and recalled by animals as aversive. This information encourages a revised interpretation of the large body of previous research on the protein. GDF15 can be secreted by a wide variety of cell types in response to a broad range of stressors. We propose that central sensing of GDF15 via GFRAL-RET activation results in behaviors that facilitate the reduction of exposure to a noxious stimulus. The human trophoblast appears to have hijacked this signal, producing large amounts of GDF15 from early pregnancy. We speculate that this encourages avoidance of potential teratogens in pregnancy. Circulating GDF15 levels are elevated in a range of human disease states, including various forms of cachexia, and GDF15-GFRAL antagonism is emerging as a therapeutic strategy for anorexia/cachexia syndromes. Metformin elevates circulating GDF15 chronically in humans and the weight loss caused by this drug appears to be dependent on the rise in GDF15. This supports the concept that chronic activation of the GDF15-GFRAL axis has efficacy as an antiobesity agent. In this review, we examine the science of GDF15 since its identification in 1997 with our interpretation of this body of work now being assisted by a clear understanding of its highly selective central site of action.

Proteomic profiles before and during weight loss: Results from randomized trial of dietary intervention

Inflammatory and cardiovascular biomarkers have been associated with obesity, but little is known about how they change upon dietary intervention and concomitant weight loss. Further, protein biomarkers might be useful for predicting weight loss in overweight and obese individuals. We performed secondary analyses in the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) randomized intervention trial that included healthy 609 adults (18–50 years old) with BMI 28–40 kg/m², to evaluate associations between circulating protein biomarkers and BMI at baseline, during a weight loss diet intervention, and to assess predictive potential of baseline blood proteins on weight loss. We analyzed 263 plasma proteins at baseline and 6 months into the intervention using the Olink Proteomics CVD II, CVD III and Inflammation arrays. BMI was assessed at baseline, after 3 and 6 months of dietary intervention. At baseline, 102 of the examined inflammatory and cardiovascular biomarkers were associated with BMI (>90% with successful replication in 1,584 overweight/obese individuals from a community-based cohort study) and 130 tracked with weight loss shedding light into the pathophysiology of obesity. However, out of 263 proteins analyzed at baseline, only fibroblast growth factor 21 (FGF-21) predicted weight loss, and none helped individualize dietary assignment.

Growth Differentiation Factor 15 in Children with Chronic Kidney Disease and after Renal Transplantation

Growth differentiation factor 15 (GDF-15) is strongly associated with cardiovascular disease (CVD). The aim of our study was to evaluate plasma and urinary levels of GDF-15 after pediatric renal transplantation (Rtx) and in children with chronic kidney disease (CKD) and its associations to cardiovascular risk factors. In this cross-sectional study, GDF-15 was measured in plasma and urine from 53 children with a renal transplant and 83 children with CKD and related to cardiovascular risk factors (hypertension, obesity, and cholesterol) and kidney function. Forty healthy children served as a control group. Plasma levels of GDF-15 (median and range) for a Tx (transplantation) cohort, CKD cohort, and healthy controls were, respectively, 865 ng/L (463-3039 ng/L), 508 ng/L (183-3279 ng/L), and 390 ng/L (306-657 ng/L). The CKD and Tx cohorts both had significantly higher GDF-15 levels than the control group (p < 0.001). Univariate associations between GDF-15 and hyperuricemia (p < 0.001), elevated triglycerides (p = 0.028), low HDL (p = 0.038), and obesity (p = 0.028) were found. However, mGFR (p < 0.001) and hemoglobin (p < 0.001) were the only significant predictors of GDF-15 in an adjusted analysis. Urinary GDF-15/creatinine ratios were 448 ng/mmol (74-5013 ng/mmol) and 540 ng/mmol (5-14960 ng/mmol) in the Tx cohort and CKD cohort, respectively. In the CKD cohort, it was weakly correlated to mGFR (r = -0.343, p = 0.002). Plasma levels of GDF-15 are elevated in children with CKD and after Rtx. The levels were not associated with traditional cardiovascular risk factors but strongly associated with renal function.

Growth differentiation factor 15 (GDF-15) is a potential biomarker of both diabetic kidney disease and future cardiovascular events in cohorts of individuals with type 2 diabetes: a proteomics approach

Background: Diabetic kidney disease (DKD) is a leading risk factor for end-stage renal disease and is one of the most important risk factors for cardiovascular disease in patients with diabetes. It is possible that novel markers portraying the pathophysiological underpinning processes may be useful.Aim: To investigate the associations between 80 circulating proteins, measured by a proximity extension assay, and prevalent DKD and major adverse cardiovascular events (MACE) in type 2 diabetes.Methods: We randomly divided individuals with type 2 diabetes from three cohorts into a two-thirds discovery and one-third replication set (total n = 813, of whom 231 had DKD defined by estimated glomerular filtration rate <60 mg/mL/1.73 m² and/or urinary albumin-creatinine ratio ≥3 g/mol). Proteins associated with DKD were also assessed as predictors for incident major adverse cardiovascular events (MACE) in persons with DKD at baseline.Results: Four proteins were positively associated with DKD in models adjusted for age, sex, cardiovascular risk factors, glucose control, and diabetes medication: kidney injury molecule-1 (KIM-1, odds ratio [OR] per standard deviation increment, 1.65, 95% confidence interval [CI] 1.27-2.14); growth differentiation factor 15 (GDF-15, OR 1.40, 95% CI 1.16-1.69); myoglobin (OR 1.57, 95% CI 1.30-1.91), and matrix metalloproteinase 10 (MMP-10, OR 1.43, 95% CI 1.17-1.74). In patients with DKD, GDF-15 was significantly associated with increased risk of MACE after adjustments for baseline age, sex, microalbuminuria, and kidney function and (59 MACE events during 7 years follow-up, hazard ratio per standard deviation increase 1.43 [95% CI 1.03-1.98]) but not after further adjustments for cardiovascular risk factors.Conclusion: Our proteomics approach confirms and extends previous associations of higher circulating levels of GDF-15 with both micro- and macrovascular disease in patients with type 2 diabetes. Our data encourage additional studies evaluating the clinical utility of our findings.

Identification of novel pheno-groups in heart failure with preserved ejection fraction using machine learning

Objective

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome. We aimed to derive HFpEF phenotype-based groups ('phenogroups') based on clinical and echocardiogram data using machine learning, and to compare clinical characteristics, proteomics and outcomes across the phenogroups.

Methods

We applied model-based clustering to 32 echocardiogram and 11 clinical and laboratory variables collected in stable condition from 320 HFpEF outpatients in the Karolinska-Rennes cohort study (56% female, median 78 years (IQR: 71–83)). Baseline proteomics and the composite end point of all-cause mortality or heart failure (HF) hospitalisation were used in secondary analyses.

Results

We identified six phenogroups, for which significant differences in the prevalence of concomitant atrial fibrillation (AF), anaemia and kidney disease were observed (p<0.05). Fifteen out of 86 plasma proteins differed between phenogroups (false discovery rate, FDR<0.05), including biomarkers of HF, AF and kidney function. The composite end point was significantly different between phenogroups (log-rank p<0.001), at short-term (100 days), mid-term (18 months) and longer-term follow-up (1000 days). Phenogroup 2 was older, with poorer diastolic and right ventricular function and higher burden of risk factors as AF (85%), hypertension (83%) and chronic obstructive pulmonary disease (30%). In this group a third experienced the primary outcome to 100 days, and two-thirds to 18 months (HR (95% CI) versus phenogroups 1, 3, 4, 5, 6: 1.5 (0.8–2.9); 5.7 (2.6–12.8); 2.9 (1.5–5.6); 2.7 (1.6–4.6); 2.1 (1.2–3.9)).

Conclusions

Using machine learning we identified distinct HFpEF phenogroups with differential characteristics and outcomes, as well as differential levels of inflammatory and cardiovascular proteins.

Animal Models and Renal Biomarkers of Diabetic Nephropathy

Diabetes mellitus (DM) is the first cause of end stage chronic kidney disease (CKD). Animal models of the disease can shed light on the pathogenesis of the diabetic nephropathy (DN) and novel and earlier biomarkers of the condition may help to improve diagnosis and prognosis. This review summarizes the most important features of animal models used in the study of DN and updates the most recent progress in biomarker research.

Interactions Between Diet Quality and Interleukin-6 Genotypes Are Associated With Metabolic and Renal Function Parameters in Mexican Patients With Type 2 Diabetes Mellitus

OBJECTIVE

The aim of this study was to evaluate the interaction between diet quality and interleukin (IL)-6 genotypes and its association with metabolic and renal function parameters in Mexican patients with type 2 diabetes mellitus (T2DM).

DESIGN AND METHODS

Using an analytical cross-sectional design, 219 patients with T2DM (92 men; age 62 ± 10 years) were evaluated for selected metabolic and renal function parameters. Diet quality according to the Healthy Eating Index was evaluated and classified as good diet or poor diet in all patients. IL-6 serum concentrations and genotypes and haplotypes for IL6-597G > A (rs180097), -572G > C (rs180096), and -174G > C (rs180095) polymorphisms were determined.

RESULTS

Eighty-two percent of patients reported having a poor diet. Carriers of alleles -572C and -174C showed higher high-density lipoprotein cholesterol levels (44 ± 12 vs. 40 ± 9 mg/dL; P = .01) and lower total cholesterol levels (184 ± 33 vs. 197 ± 42 mg/dL; P = .03) than did those homozygous for G/G. Neither IL6 genotypes nor haplotypes were significantly associated with serum concentrations of IL-6. Some significant interactions between IL6 genotypes/haplotypes and diet quality were associated with body mass index, waist circumference, high-density lipoprotein cholesterol levels, and estimated glomerular filtration rate.

CONCLUSIONS

Interactions between diet quality and IL6 genotypes/haplotypes were associated with the main metabolic and renal function parameters in Mexican patients with T2DM. It will be important to consider genetic profiles in designing dietary portfolios and nutritional interventions for the management of such patients.

Association of plasma macrophage colony-stimulating factor with cardiovascular morbidity and all-cause mortality in chronic hemodialysis patients

Background

Cardiovascular disease (CVD) events are the main cause of death in long-term hemodialysis (HD) patients. Macrophage colony- stimulating factor (M-CSF) is actively involved in the formation of atherosclerosis and causes plaque instability, thrombosis and the development of acute coronary syndromes. However, little information is available on the role of M-CSF in HD patients. We aimed to investigate the association between plasma M-CSF levels and CVD events as well as all-cause mortality in patients undergoing long-term HD.

Methods

Fifty two HD patients and 8 healthy controls were recruited in this study. HD patients were followed up from September 2014 to May 2017. The primary end point was CVD event, the secondary outcome was death from any cause. Patients were divided into two groups with low and high M-CSF levels based on the optimal cut-off value determined by the ROC curve. Cox regression analyses were used to assess the predictive value of plasma M-CSF for CVD events and all-cause mortality in HD patients. We tested the levels of plasma M-CSF and other inflammatory cytokines in surviving HD patients using ELISA or CBA kit.

Results

The average plasma level of M-CSF in 52 patients was approximately twice that of healthy controls (992.4 vs. 427.2 pg/mL; p <  0.05). During 32 months of follow-up, 26 patients (50.0%) had at least one CVD event and 8 patients (15.4%) died. The mean plasma M-CSF concentration increased in survivors after follow-up compared to that detected at baseline (1277.8 ± 693.3 vs. 997.2 ± 417.4 pg/mL; p <  0.05). Multivariate Cox regression analysis showed that plasma M-CSF is an independent risk factor for CVD events in HD patients (p <  0.05). In the Cox regression model after adjusting for gender and age, high M-CSF levels were related to an increased risk of all-cause death (p <  0.05). We also found that M-CSF levels were positively correlated with IL-6 and IL-18 levels (both p < 0.05), which are the major pathogentic cytokines that contribute to HD-related CVD events.

Conclusion

M-CSF is a prognostic factor for CVD events and all-cause mortality in HD patients.

Systemic Inflammation Precedes Microalbuminuria in Diabetes

Aim

The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2.

Methods

Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis.

Results

The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001).

Conclusion

In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors.

Targeted Proteomic Analysis Detects Acute T Cell-Mediated Kidney Allograft Rejection in Belatacept-Treated Patients

BACKGROUND

There is an unmet need for reliable minimally invasive diagnostic biomarkers for immunological allograft monitoring and for the detection of acute kidney transplant rejection. Here, targeted proteomic analysis was applied to compare 92 proteins in sera of belatacept-treated patients who had biopsy-proven, acute T-cell-mediated rejection (aTCMR) with patients without aTCMR.

METHODS

Proximity extension immunoassay was used to measure 92 inflammation-related protein concentrations in the prerejection and rejection sera of 11 patients with aTCMR and 9 patients without aTCMR. This assay uses 2 matched oligonucleotide-labeled antibody probes for each protein and polymerase chain reaction to measure normalized protein expression values.

RESULTS

Five proteins (CD5, CD8A, NCR1, TNFRSF4, and TNFRSF9) were expressed significantly higher in samples with aTCMR compared with samples without aTCMR (adjusted P-value < 0.014) and had a good predictive capacity for aTCMR [area under the curve in a receiver-operator curve ranged from 0.83 to 0.91 (P < 0.014)]. These proteins are associated with CD8 cytotoxic T-cell and NK cell functions. Nonhierarchical clustering analysis showed distinct clustering of samples with aTCMR and samples without aTCMR. This clustering was not found in prerejection samples (1 month after transplantation). In prerejection samples, IFN-γ was expressed at a significantly lower level (normalized protein expression value median -0.15, interquartile range: -0.27 to 0.04) than in samples of patients without rejection (median 0.13, interquartile range: -0.07 to 0.15, adjusted P-value = 0.00367).

CONCLUSIONS

Targeted proteomic analysis with proximity extension immunoassay is a promising minimally invasive technique to diagnose aTCMR in kidney transplant recipients.

TRAIL, OPG, and TWEAK in kidney disease: biomarkers or therapeutic targets?

Ligands and receptors of the tumor necrosis factor (TNF) superfamily regulate immune responses and homeostatic functions with potential diagnostic and therapeutic implications. Kidney disease represents a global public health problem, whose prevalence is rising worldwide, due to the aging of the population and the increasing prevalence of diabetes, hypertension, obesity, and immune disorders. In addition, chronic kidney disease is an independent risk factor for the development of cardiovascular disease, which further increases kidney-related morbidity and mortality. Recently, it has been shown that some TNF superfamily members are actively implicated in renal pathophysiology. These members include TNF-related apoptosis-inducing ligand (TRAIL), its decoy receptor osteoprotegerin (OPG), and TNF-like weaker inducer of apoptosis (TWEAK). All of them have shown the ability to activate crucial pathways involved in kidney disease development and progression (e.g. canonical and non-canonical pathways of the transcription factor nuclear factor-kappa B), as well as the ability to regulate cell proliferation, differentiation, apoptosis, necrosis, inflammation, angiogenesis, and fibrosis with double-edged effects depending on the type and stage of kidney injury. Here we will review the actions of TRAIL, OPG, and TWEAK on diabetic and non-diabetic kidney disease, in order to provide insights into their full clinical potential as biomarkers and/or therapeutic options against kidney disease.

Blood and urine biomarkers in chronic kidney disease: An update

INTRODUCTION

Chronic kidney disease (CKD) is a silent disease. Most CKD patients are unaware of their condition during the early stages of the disease which poses a challenge for healthcare professionals to institute treatment or start prevention. The trouble with the diagnosis of CKD is that in most parts of the world, it is still diagnosed based on measurements of serum creatinine and corresponding calculations of eGFR. There are controversies with the current staging system, especially in the methodology to diagnose and prognosticate CKD.

OBJECTIVE

The aim of this review is to examine studies that focused on the different types of samples which may serve as a good and promising biomarker for early diagnosis of CKD or to detect rapidly declining renal function among CKD patient.

METHOD

The review of international literature was made on paper and electronic databases Nature, PubMed, Springer Link and Science Direct. The Scopus index was used to verify the scientific relevance of the papers. Publications were selected based on the inclusion and exclusion criteria.

RESULT

63 publications were found to be compatible with the study objectives. Several biomarkers of interest with different sample types were taken for comparison.

CONCLUSION

Biomarkers from urine samples yield more significant outcome as compare to biomarkers from blood samples. But, validation and confirmation with a different type of study designed on a larger population is needed. More comparison studies on different types of samples are needed to further illuminate which biomarker is the better tool for the diagnosis and prognosis of CKD.

Big science and big data in nephrology

There have been tremendous advances during the last decade in methods for large-scale, high-throughput data generation and in novel computational approaches to analyze these datasets. These advances have had a profound impact on biomedical research and clinical medicine. The field of genomics is rapidly developing toward single-cell analysis, and major advances in proteomics and metabolomics have been made in recent years. The developments on wearables and electronic health records are poised to change clinical trial design. This rise of 'big data' holds the promise to transform not only research progress, but also clinical decision making towards precision medicine. To have a true impact, it requires integrative and multi-disciplinary approaches that blend experimental, clinical and computational expertise across multiple institutions. Cancer research has been at the forefront of the progress in such large-scale initiatives, so-called 'big science,' with an emphasis on precision medicine, and various other areas are quickly catching up. Nephrology is arguably lagging behind, and hence these are exciting times to start (or redirect) a research career to leverage these developments in nephrology. In this review, we summarize advances in big data generation, computational analysis, and big science initiatives, with a special focus on applications to nephrology.

Longitudinal effects of aging on plasma proteins levels in older adults - associations with kidney function and hemoglobin levels

BACKGROUND

A targeted proteomics chip has been shown to be useful to discover novel associations of proteins with cardiovascular disease. We investigated how these proteins change with aging, and whether this change is related to a decline in kidney function, or to a change in hemoglobin levels.

MATERIAL AND METHODS

In the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study, including 1,016 participants from the general population aged 70 at baseline, 84 proteins were measured at ages 70, 75, 80. At these occasions, glomerular filtration rate (eGFR) was estimated and the hemoglobin levels were measured.

RESULTS

Sixty-one of the 84 evaluated proteins changed significantly during the 10-year follow-up (multiple testing-adjusted alpha = 0.00059), most showing an increase. The change in eGFR was inversely related to changes of protein levels for the vast majority of proteins (74%). The change in hemoglobin was significantly related to the change in 40% of the evaluated proteins, with no obvious preference of the direction of these relationships.

CONCLUSION

The majority of evaluated proteins increased with aging in adults. Therefore, normal ranges for proteins might be given in age-strata. The increase in protein levels was associated with the degree of reduction in eGFR for the majority of proteins, while no clear pattern was seen for the relationships between the proteins and the change in hemoglobin levels. Studies on changes in urinary proteins are warranted to understand the association between the reduction in eGFR and increase in plasma protein levels.

Fatty Acid-Binding Protein 4 in Cardiovascular and Metabolic Diseases

Fatty acid-binding proteins (FABPs), a family of lipid chaperones, contribute to systemic metabolic regulation via several lipid signaling pathways. Fatty acid-binding protein 4 (FABP4), known as adipocyte FABP (A-FABP) or aP2, is mainly expressed in adipocytes and macrophages and plays important roles in the development of insulin resistance and atherosclerosis in relation to metabolically driven low-grade and chronic inflammation, referred to as ‘metaflammation’. FABP4 is secreted from adipocytes in a non-classical pathway associated with lipolysis and acts as an adipokine for the development of insulin resistance and atherosclerosis. Circulating FABP4 levels are associated with several aspects of metabolic syndrome and cardiovascular disease. Ectopic expression and function of FABP4 in cells and tissues are also related to the pathogenesis of several diseases. Pharmacological modification of FABP4 function by specific inhibitors, neutralizing antibodies or antagonists of unidentified receptors would be novel therapeutic strategies for several diseases, including obesity, diabetes mellitus, atherosclerosis and cardiovascular disease. Significant roles of FABP4 as a lipid chaperone in physiological and pathophysiological conditions and the possibility of FABP4 being a therapeutic target for metabolic and cardiovascular diseases are discussed in this review.

Tumour necrosis factor-related apoptosis-inducing ligand expression in patients with diabetic nephropathy

Objective:

The objective of this study was to evaluate the expression profile of tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) in patients with diabetic nephropathy (DN).

Methods:

A total of 126 Chinese subjects were enrolled in this study, including 42 patients with diabetes mellitus (DM), 42 patients with DN and 42 healthy controls. Real-time polymerase chain reaction was performed to analyze levels of TRAIL mRNA in peripheral blood mononuclear cells (PBMCs). Serum levels of soluble TRAIL (sTRAIL) and various cytokines were detected with a commercially available enzyme-linked immunosorbent assay kit.

Results:

Compared with the control group, the levels of TRAIL mRNA in PBMCs and sTRAIL in sera were both significantly decreased in the DM and DN patients (P < 0.05). Conversely, levels of interleukin (IL)-1, IL-6, tumour necrosis factor-α and monocyte chemotactic protein-1 were higher in the DN group than in the control group. Serum levels of TRAIL positively correlated with TRAIL mRNA levels in all of the subjects examined (P < 0.05).

Conclusions:

These results provide support and a theoretical basis for further research of TRAIL in regard to the pathogenesis of DN.

Dendritic cell maturation in the corneal epithelium with onset of type 2 diabetes is associated with tumor necrosis factor receptor superfamily member 9

Type 2 diabetes mellitus is characterized by a low-grade inflammation; however, mechanisms leading to this inflammation in specific tissues are not well understood. The eye can be affected by diabetes; thus, we hypothesized that inflammatory changes in the eye may parallel the inflammation that develops with diabetes. Here, we developed a non-invasive means to monitor the status of inflammatory dendritic cell (DC) subsets in the corneal epithelium as a potential biomarker for the onset of inflammation in type 2 diabetes. In an age-matched cohort of 81 individuals with normal and impaired glucose tolerance and type 2 diabetes, DCs were quantified from wide-area maps of the corneal epithelial sub-basal plexus, obtained using clinical in vivo confocal microscopy (IVCM). With the onset of diabetes, the proportion of mature, antigen-presenting DCs increased and became organized in clusters. Out of 92 plasma proteins analysed in the cohort, tumor necrosis factor receptor super family member 9 (TNFRSF9) was associated with the observed maturation of DCs from an immature to mature antigen-presenting phenotype. A low-grade ocular surface inflammation observed in this study, where resident immature dendritic cells are transformed into mature antigen-presenting cells in the corneal epithelium, is a process putatively associated with TNFRSF9 signalling and may occur early in the development of type 2 diabetes. IVCM enables this process to be monitored non-invasively in the eye.

Biomarkers of diabetic kidney disease

Diabetic kidney disease (DKD) remains one of the leading causes of reduced lifespan in diabetes. The quest for both prognostic and surrogate endpoint biomarkers for advanced DKD and end-stage renal disease has received major investment and interest in recent years. However, at present no novel biomarkers are in routine use in the clinic or in trials. This review focuses on the current status of prognostic biomarkers. First, we emphasise that albuminuria and eGFR, with other routine clinical data, show at least modest prediction of future renal status if properly used. Indeed, a major limitation of many current biomarker studies is that they do not properly evaluate the marginal increase in prediction on top of these routinely available clinical data. Second, we emphasise that many of the candidate biomarkers for which there are numerous sporadic reports in the literature are tightly correlated with each other. Despite this, few studies have attempted to evaluate a wide range of biomarkers simultaneously to define the most useful among these correlated biomarkers. We also review the potential of high-dimensional panels of lipids, metabolites and proteins to advance the field, and point to some of the analytical and post-analytical challenges of taking initial studies using these and candidate approaches through to actual clinical biomarker use.