The association of plasma cystatin C proteoforms with diabetic chronic kidney disease

Comparative analysis of plasma affinity depletion methods: Impact on protein composition and phosphopeptide abundance in human plasma

Affinity-based protein depletion and TiO2 enrichment methods play a crucial role in detection of low-abundant proteins and phosphopeptides enrichment, respectively. Here, we assessed the effectiveness of HSA/IgG (HU2) and Human 7 (HU7) depletion methods and their impact on phosphopeptides coverage through comparative proteome analysis, utilizing in-solution digestion and nano-LC-Orbitrap mass spectrometry (MS). Our results demonstrated that both HU2 and HU7 affinity depletion significantly decreased high-abundant proteins by 1.5-7.8-fold (p < 0.001). A total of 1491 proteins were identified, with 48 proteins showing significant expression in the depleted groups. Notably, cadherin-13, neutrophil defensin 1, APM1, and desmoplakin variant protein were exclusively detected in the HU2/HU7-depleted groups. Furthermore, study on effect of depletion on phosphopeptides revealed an increase in tandem MS spectral counts with notable decrease (∼50%) in peptide spectrum matching in depleted groups, which was attributed to significant reduction in protein counts. Our post translation modification workflow for phosphoproteomics detected 42 phosphorylated peptides, corresponding to 12 phosphoproteins with unique peptide match ≥2 (high false discovery rates confidence). Among them, 10 phosphorylated proteins are highly expressed in depleted groups. Overall, these findings offer valuable insights in selection of protein depletion methods for comprehensive plasma proteomics analysis.

Serum Cystatin C as a Risk Factor for Supratherapeutic Digoxin Concentration in Elderly Patients with Heart Failure and Chronic Kidney Disease

BACKGROUND

Digoxin is primarily metabolized by the kidney, and its toxicity is strongly associated with high concentrations, particularly in elderly patients. The purpose of this study was to evaluate the predictive performance of renal function biomarkers for supratherapeutic digoxin concentrations in elderly patients with heart failure (HF) and chronic kidney disease (CKD).

METHODS

Data were retrospectively obtained from elderly patient with HF and CKD who received digoxin treatment from January 2022 and December 2022. Logistic regression was used to assess independent risk factors for supratherapeutic concentrations. The predictive performance of serum creatinine, serum cystatin C, and blood urea nitrogen on supratherapeutic concentrations was compared by receiver operating characteristic analysis.

RESULTS

A total of 115 elderly patients with HF and CKD were enrolled in our study. Supratherapeutic concentrations were detected in 49 patients. Logistic regression analysis showed that estimated glomerular filtration rate calculated by serum cystatin C [eGFRCysC, odds ratio (OR): 0.962, P = 0.006], heart rate (OR: 1.024, P = 0.040), and NYHA class (OR: 3.099, P = 0.010) were independent risk factors for supratherapeutic concentration. Cutoff value for eGFRCysC between the two groups was 41 ml/min/1.73m2. Predictive performance of serum cystatin C was further improved in patients with obesity, CKD stage 4-5, and older than 75 years compared with normal weight, CKD stage 3, and aged 60-75-year-old patients.

CONCLUSIONS

Serum cystatin C is a sensitive renal function biomarker to predict supratherapeutic digoxin concentration in elderly patients with HF and CKD.

Apo CIII Proteoforms, Plasma Lipids, and Cardiovascular Risk in MESA

BACKGROUND

Apo CIII (apolipoprotein CIII) is an important regulator of triglyceride metabolism and was associated with cardiovascular risk in several cohorts. It is present in 4 major proteoforms, a native peptide (CIII0a), and glycosylated proteoforms with zero (CIII0b), 1 (CIII1, most abundant), or 2 (CIII2) sialic acids, which may differentially modify lipoprotein metabolism. We studied the relationships of these proteoforms with plasma lipids and cardiovascular risk.

METHODS

Apo CIII proteoforms were measured by mass spectrometry immunoassay in baseline plasma samples of 5791 participants of Multi-Ethnic Study of Atherosclerosis, an observational community-based cohort. Standard plasma lipids were collected for up to 16 years and cardiovascular events (myocardial infarction, resuscitated cardiac arrest, or stroke) were adjudicated for up to 17 years.

RESULTS

Apo CIII proteoform composition differed by age, sex, race and ethnicity, body mass index, and fasting glucose. Notably, CIII1 was lower in older participants, men and Black and Chinese (versus White) participants, and higher in obesity and diabetes. In contrast, CIII2 was higher in older participants, men, Black, and Chinese persons, and lower in Hispanic individuals and obesity. Higher CIII2 to CIII1 ratio (CIII2/III1) was associated with lower triglycerides and higher HDL (high-density lipoprotein) in cross-sectional and longitudinal models, independently of clinical and demographic risk factors and total apo CIII. The associations of CIII0a/III1 and CIII0b/III1 with plasma lipids were weaker and varied through cross-sectional and longitudinal analyses. Total apo CIII and CIII2/III1 were positively associated with cardiovascular disease risk (n=669 events, hazard ratios, 1.14 [95% CI, 1.04-1.25] and 1.21 [1.11-1.31], respectively); however, the associations were attenuated after adjustment for clinical and demographic characteristics (1.07 [0.98-1.16]; 1.07 [0.97-1.17]). In contrast, CIII0b/III1 was inversely associated with cardiovascular disease risk even after full adjustment including plasma lipids (0.86 [0.79-0.93]).

CONCLUSIONS

Our data indicate differences in clinical and demographic relationships of apo CIII proteoforms, and highlight the importance of apo CIII proteoform composition in predicting future lipid patterns and cardiovascular disease risk.

Cystatin C proteoforms in chronic kidney disease

Cystatin C, a cysteine protease inhibitor, is used as a biomarker of renal function. It offers several advantages compared to creatinine, and formulas for the estimation of the glomerular filtration rate based on cystatin C have been developed. Recently, several proteoforms of cystatin C have been discovered, including an intact protein with a hydroxylated proline at the N-terminus, and N-terminal truncated forms. There is little knowledge about the biological significance of these proteoforms.

METHODS

Cross-sectional study of patients with different stages of chronic renal disease (pre-dialysis n = 53; hemodialysis n = 51, renal transplant n = 53). Measurement of cystatin C proteoforms by MALDI-TOF MS, assessment of medicine prescription using the first two levels of the Anatomical Therapeutic chemical system from patients' records.

RESULTS

Patients receiving hemodialysis had the highest cystatin C concentrations, followed by pre-dialysis patients and patients with a renal transplant. In all groups, the most common proteoforms were native cystatin C and CysC 3Pro-OH while the truncated forms made up 28%. The distribution of the different proteoforms was largely independent of renal function and total cystatin C. However, the use of corticosteroids (ATC-L02) and immunosuppressants (ATC-H04) considerably impacted the distribution of proteoforms.

CONCLUSION

The different proteoforms of cystatin C increased proportionally with total cystatin C in patients with chronic kidney disease. Prescription of corticosteroids and immunosuppressants had a significant effect on the distribution of proteoforms. The biological significance of these proteoforms remains to be determined.

A nomogram for predicting the 4-year risk of chronic kidney disease among Chinese elderly adults

BACKGROUND

Chronic kidney disease (CKD) has become a major public health problem across the globe, leading to various complications. This study aimed to construct a nomogram to predict the 4-year risk of CKD among Chinese adults.

METHODS

The study was based on the China Health and Retirement Longitudinal Study (CHARLS). A total of 3562 participants with complete information in CHARLS2011 and CHARLS2015 were included, and further divided into the training cohort and the validation cohort by a ratio of 7:3. Univariate and multivariate logistic regression analyses were used to select variables of the nomogram. The nomogram was evaluated by receiver-operating characteristic curve, calibration plots, and decision curve analysis (DCA).

RESULTS

In all, 2494 and 1068 participants were included in the training cohort and the validation cohort, respectively. A total of 413 participants developed CKD in the following 4 years. Five variables selected by multivariate logistic regression were incorporated in the nomogram, consisting of gender, hypertension, the estimated glomerular filtration rate (eGFR), hemoglobin, and Cystatin C. The area under curve was 0.809 and 0.837 in the training cohort and the validation cohort, respectively. The calibration plots showed agreement between the nomogram-predicted probability and the observed probability. DCA indicated that the nomogram had potential clinical use.

CONCLUSIONS

A predictive nomogram was established and internally validated in aid of identifying individuals at increased risk of CKD.

Uncovering Molecular Heterogeneity in the Kidney With Spatially Targeted Mass Spectrometry

The kidney functions through the coordination of approximately one million multifunctional nephrons in 3-dimensional space. Molecular understanding of the kidney has relied on transcriptomic, proteomic, and metabolomic analyses of kidney homogenate, but these approaches do not resolve cellular identity and spatial context. Mass spectrometry analysis of isolated cells retains cellular identity but not information regarding its cellular neighborhood and extracellular matrix. Spatially targeted mass spectrometry is uniquely suited to molecularly characterize kidney tissue while retaining in situ cellular context. This review summarizes advances in methodology and technology for spatially targeted mass spectrometry analysis of kidney tissue. Profiling technologies such as laser capture microdissection (LCM) coupled to liquid chromatography tandem mass spectrometry provide deep molecular coverage of specific tissue regions, while imaging technologies such as matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) molecularly profile regularly spaced tissue regions with greater spatial resolution. These technologies individually have furthered our understanding of heterogeneity in nephron regions such as glomeruli and proximal tubules, and their combination is expected to profoundly expand our knowledge of the kidney in health and disease.

The Human Proteoform Atlas: a FAIR community resource for experimentally derived proteoforms

The Human Proteoform Atlas (HPfA) is a web-based repository of experimentally verified human proteoforms on-line at http://human-proteoform-atlas.org and is a direct descendant of the Consortium of Top-Down Proteomics' (CTDP) Proteoform Atlas. Proteoforms are the specific forms of protein molecules expressed by our cells and include the unique combination of post-translational modifications (PTMs), alternative splicing and other sources of variation deriving from a specific gene. The HPfA uses a FAIR system to assign persistent identifiers to proteoforms which allows for redundancy calling and tracking from prior and future studies in the growing community of proteoform biology and measurement. The HPfA is organized around open ontologies and enables flexible classification of proteoforms. To achieve this, a public registry of experimentally verified proteoforms was also created. Submission of new proteoforms can be processed through email vianrtdphelp@northwestern.edu, and future iterations of these proteoform atlases will help to organize and assign function to proteoforms, their PTMs and their complexes in the years ahead.

Immunoaffinity Capillary Electrophoresis in the Era of Proteoforms, Liquid Biopsy and Preventive Medicine: A Potential Impact in the Diagnosis and Monitoring of Disease Progression

Over the years, multiple biomarkers have been used to aid in disease screening, diagnosis, prognosis, and response to therapy. As of late, protein biomarkers are gaining strength in their role for early disease diagnosis and prognosis in part due to the advancements in identification and characterization of a distinct functional pool of proteins known as proteoforms. Proteoforms are defined as all of the different molecular forms of a protein derived from a single gene caused by genetic variations, alternative spliced RNA transcripts and post-translational modifications. Monitoring the structural changes of each proteoform of a particular protein is essential to elucidate the complex molecular mechanisms that guide the course of disease. Clinical proteomics therefore holds the potential to offer further insight into disease pathology, progression, and prevention. Nevertheless, more technologically advanced diagnostic methods are needed to improve the reliability and clinical applicability of proteomics in preventive medicine. In this manuscript, we review the use of immunoaffinity capillary electrophoresis (IACE) as an emerging powerful diagnostic tool to isolate, separate, detect and characterize proteoform biomarkers obtained from liquid biopsy. IACE is an affinity capture-separation technology capable of isolating, concentrating and analyzing a wide range of biomarkers present in biological fluids. Isolation and concentration of target analytes is accomplished through binding to one or more biorecognition affinity ligands immobilized to a solid support, while separation and analysis are achieved by high-resolution capillary electrophoresis (CE) coupled to one or more detectors. IACE has the potential to generate rapid results with significant accuracy, leading to reliability and reproducibility in diagnosing and monitoring disease. Additionally, IACE has the capability of monitoring the efficacy of therapeutic agents by quantifying companion and complementary protein biomarkers. With advancements in telemedicine and artificial intelligence, the implementation of proteoform biomarker detection and analysis may significantly improve our capacity to identify medical conditions early and intervene in ways that improve health outcomes for individuals and populations.

Roles of Hydrogen Sulfide Donors in Common Kidney Diseases

Hydrogen sulfide (H2S) plays a key role in the regulation of physiological processes in mammals. The decline in H2S level has been reported in numerous renal disorders. In animal models of renal disorders, treatment with H2S donors could restore H2S levels and improve renal functions. H2S donors suppress renal dysfunction by regulating autophagy, apoptosis, oxidative stress, and inflammation through multiple signaling pathways, such as TRL4/NLRP3, AMP-activated protein kinase/mammalian target of rapamycin, transforming growth factor-β1/Smad3, extracellular signal-regulated protein kinases 1/2, mitogen-activated protein kinase, and nuclear factor kappa B. In this review, we summarize recent developments in the effects of H2S donors on the treatment of common renal diseases, including acute/chronic kidney disease, renal fibrosis, unilateral ureteral obstruction, glomerulosclerosis, diabetic nephropathy, hyperhomocysteinemia, drug-induced nephrotoxicity, metal-induced nephrotoxicity, and urolithiasis. Novel H2S donors can be designed and applied in the treatment of common renal diseases.

N-Terminal Proteoforms in Human Disease

The collection of chemically different protein variants, or proteoforms, by far exceeds the number of protein-coding genes in the human genome. Major contributors are alternative splicing and protein modifications. In this review, we focus on those proteoforms that differ at their N termini with a molecular link to disease. We describe the main underlying mechanisms that give rise to such N-terminal proteoforms, these being splicing, initiation of protein translation, and protein modifications. Given their role in several human diseases, it is becoming increasingly clear that several of these N-terminal proteoforms may have potential as therapeutic interventions and/or for diagnosing and prognosing their associated disease.

Association of circulating cystatin C levels with type 2 diabetes mellitus: a systematic review and meta-analysis

INTRODUCTION

This study aimed to systemically summarize the present literature about circulating cystatin C (Cys C) levels in type 2 diabetes mellitus (T2DM) and provide a more precise evaluation of Cys C levels in T2DM.

MATERIAL AND METHODS

Relevant studies about Cys C concentrations in T2DM were searched in PubMed, EMBASE and the Cochrane Library database (up to Oct 31 2018). We computed the pooled standard mean difference (SMD) with its 95% confidence interval (CI) of Cys C levels through a random-effect model. The Q test and the I² statistic were used to assess and quantify between-study heterogeneity; publication bias was evaluated through a funnel plot and Egger's linear regression test.

RESULTS

After the literature search and screening process, 14 studies with 723 T2DM patients and 473 healthy controls were finally included in the meta-analysis. The results showed that T2DM patients had significantly higher Cys C levels compared to healthy controls (SMD = 1.39, 95% CI: 0.92-1.86, p < 0.001). Publication bias was not detected based on the symmetrical shape of the funnel plot and the results of Egger's test (p = 0.452). Subgroup analyses suggested that variables of human race, age, gender, study sample size and disease duration have a relationship with Cys C level in T2DM patients.

CONCLUSIONS

Overall, our study suggests that patients with T2DM have an elevated circulating Cys C level compared to healthy controls, and it is associated with race, age, gender, study sample size and disease duration. Further investigations are still needed to explore the causal relationship of aberrant Cys C concentrations in T2DM.

Value of elastography point quantification in improving the diagnostic accuracy of early diabetic kidney disease

BACKGROUND

Diabetic kidney disease (DKD) is a common complication of diabetes. The patient’s prognosis is poor once DKD progresses to advanced stage. Accurate diagnosis and timely treatment of early DKD are important for improving patient’s prognosis and reducing mortality.

AIM

To explore the value of elastography point quantification (ElastPQ) in improving the accuracy of early DKD diagnosis.

METHODS

A total of 69 patients with type 2 diabetes were recruited from Naval Military Medical University Affiliated Gongli Hospital. Patients were divided into early DKD group and medium DKD group according to pathological results and urinary albumin excretion rate (UAER). Another 40 patients with simple diabetes were included as the diabetes group. The baseline data, laboratory diagnostic indicators, and ultrasound indicators for each patient were recorded. The differences of the indicators in the three groups were compared. Multivariate logistic regression was used to analyze the influencing factors of the development from simple diabetes into early DKD and from early DKD into medium DKD. Receiver operating characteristic analyses of potential indicators in identifying early DKD and medium DKD, and early DKD and simple diabetes were established.

RESULTS

Multivariate logistic regression analysis showed that UAER (P < 0.001), renocortical Young's Modulus (YM) (P < 0.001), and renal parenchymal thickness (P = 0.013) were the independent influencing factors of the development from early DKD into medium DKD. Diabetes duration (P = 0.041), UAER (P = 0.034), and renocortical YM (P = 0.017) were the independent influencing factors of the development from simple diabetes into early DKD. Receiver operating characteristic analysis indicated that UAER, renocortical YM, and renal parenchymal thickness were accurate in identifying early DKD and medium DKD [all area under curve (AUC) > 0.9]. The accuracy of UAER (AUC = 0.744), diabetes duration (AUC = 0.757), and renocortical YM (AUC = 0.782) for the diagnosis of early DKD and simple diabetes were limited. However, the combined diagnosis of UAER, diabetes duration, and renocortical YM was accurate in identifying early DKD and simple diabetes (AUC = 0.906), which was significantly higher than any of the three indicators (all P < 0.05).

CONCLUSION

ElastPQ is of great value in the diagnosis of early DKD. When combined with the diabetes duration and UAER, it is expected to diagnose accurately early DKD.

Biomarkers for predicting outcomes in chronic kidney disease

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

Mass Spectrometric Studies of Apolipoprotein Proteoforms and Their Role in Lipid Metabolism and Type 2 Diabetes

Apolipoproteins function as structural components of lipoprotein particles, cofactors for enzymes, and ligands for cell-surface receptors. Most of the apoliporoteins exhibit proteoforms, arising from single nucleotide polymorphisms (SNPs) and post-translational modifications such as glycosylation, oxidation, and sequence truncations. Reviewed here are recent studies correlating apolipoproteins proteoforms with the specific clinical measures of lipid metabolism and cardiometabolic risk. Targeted mass spectrometric immunoassays toward apolipoproteins A-I, A-II, and C-III were applied on large cross-sectional and longitudinal clinical cohorts. Several correlations were observed, including greater apolipoprotein A-I and A-II oxidation in patients with diabetes and cardiovascular disease, and a divergent apoC-III proteoforms association with plasma triglycerides, indicating significant differences in the metabolism of the individual apoC-III proteoforms. These are the first studies of their kind, correlating specific proteoforms with clinical measures in order to determine their utility as potential clinical biomarkers for disease diagnosis, risk stratification, and therapy decisions. Such studies provide the impetus for the further development and clinical translation of MS-based protein tests.

The diagnostic value of serum creatinine and cystatin c in evaluating glomerular filtration rate in patients with chronic kidney disease: a systematic literature review and meta-analysis

BACKGROUND

Serum biomarkers, such as serum creatinine (SCr) and serum cystatin C (SCysC), have been widely used to evaluate renal function in patients who have chronic kidney disease (CKD).

OBJECTIVE

This article aims to assess the value of determining SCr and SCysC levels in patients that have long-term kidney disease. Approaches: MEDLINE, EmBase, the Cochrane Library and other databases were searched using both MeSH terms and text words to collect research that assessed the diagnostic value of using SCr and SCysC to evaluate Glomerular Filtration Rate (GFR) in patients with CKD. Data were converted into fourfold tables. Summary Receiver Operating Characteristic Curves and meta-analyses were accomplished via Meta-Disc version 1.4.

RESULTS

In total, 21 relevant articles involving 3112 study subjects were included in our review. Results showed that the collective sensitivity for SCr and SCysC was 0.77 (95% CI: 0.69-0.84) and 0.87 (95% CI: 0.82-0.91), respectively. The pooled specificity for SCr and SCysC was 0.91 (95% CI: 0.86-0.94) and 0.87 (95% CI: 0.82-0.91), respectively. Subgroup analyses demonstrated that when GFR cut-off values are set to 60 (ml/min/1.73 m²), the pooled sensitivity is 0.94 (95% CI: 0.90-0.96) for SCysC and 0.75 (95% CI: 0.68-0.82) for SCr.

CONCLUSIONS

The diagnostical accuracy for impaired kidney function favors SCysC. Confidence intervals for the pooled sensitivity and specificity for SCr and SCysC overlap. However, SCysC is more sensitive for estimating GFR than SCr when GFR cut-off values are set to 60 (ml/min/1.73 m²).

Association of Cystatin C Proteoforms with Estimated Glomerular Filtration Rate

Background

Cystatin C (CysC), a marker for chronic kidney disease, exists as three sequence proteoforms, in addition to the wild-type sequence: one contains hydroxyproline at position 3 (3Pro-OH), the two others have truncated sequences (des-S and des-SSP). Here, we examine correlations between each of these CysC proteoforms and estimated glomerular filtration rate (eGFR), a diagnostic criterion for chronic kidney disease (CKD).

Methods

CysC proteoform concentrations were determined from the plasma of 297 diabetes patients at a baseline time point and nine-months later, using a mass spectrometric immunoassay, and were correlated with eGFR calculations.

Results

In all samples, 3Pro-OH was the most abundant CysC proteoform, followed by the wild-type proteoform. Least abundant were the truncated CysC proteoforms, des-S and des-SSP, although they demonstrated stronger negative correlation with eGFR than the 3Pro-OH and wild-type proteoforms. The des-SSP truncated proteoform exhibited negative predictive value for eGFR.

Conclusions

The truncated CysC proteoforms show potential for clinical and prognostic utility in CKD staging. This could be useful in populations where current methods do not provide satisfactory solutions.