Filtration Markers as Predictors of ESRD and Mortality: Individual Participant Data Meta-Analysis

A Novel Creatinine Muscle Index Based on Creatinine Filtration: Associations with Frailty and Mortality

SIGNIFICANCE STATEMENT

Low muscle mass is related to frailty and increased mortality in older adults. However, muscle mass is not easily assessed in routine clinical practice. This paper describes a novel creatinine muscle index (CMI) on the basis of serum creatinine and cystatin C. CMI was moderately associated with frailty among older adults. A significantly higher proportion of individuals with weak grip strength were in the lowest tertile of CMI. The index was also associated with mortality. These results are consistent with the hypothesis that creatinine filtration may be an index of muscle mass, which may have utility in clinical practice.

BACKGROUND

Low muscle mass is related to frailty and increased mortality in older adults. However, muscle mass is not easily assessed in routine clinical practice.

METHODS

This study describes a novel creatinine muscle index (CMI) on the basis of serum creatinine and cystatin C in a community-based sample of older adults from the Atherosclerosis Risk in Communities Study. Analyses included 4639 participants who attended visit 5 (2011-2013) and 12,786 participants who attended visit 2 (1990-1992). CMI was defined as creatinine filtration (the product of serum creatinine times eGFR on the basis of cystatin C) and was analyzed in sex-specific tertiles. Cross-sectional associations of CMI with a frailty trichotomy, defined by the number (robust [0]/prefrail [1-2]/frail [3-5]) of five frailty components (weight loss, slowness, exhaustion, weakness, and low physical activity), were studied using polychotomous logistic regression and binary logistic regression with each frailty component. Cox regression was used to estimate associations of CMI at visit 5 and visit 2 with mortality. Models were adjusted for demographics, clinical variables, and comorbid conditions.

RESULTS

CMI (tertile 1 versus 3) was moderately associated with frailty (visit 5: adjusted odds ratio 4.23 [95% confidence interval (CI), 2.02 to 8.87] in men and 2.34 [95% CI, 1.41 to 3.89] in women) and with mortality (visit 5: adjusted hazard ratio 1.45 [95% CI, 1.08 to 1.94] in men and 1.55 [95% CI, 1.13 to 2.12] in women; similar results were seen at visit 2).

CONCLUSION

Lower CMI was associated with frailty and increased mortality, two clinical outcomes known to be associated with decreased muscle mass. Creatinine filtration may be an index of muscle mass and have utility in clinical practice, particularly at low levels.

Association of β₂ microglobulin level and glomerular filtration rate in patients with acute leukemia after hematopoietic stem cell transplantation

Hematopoietic stem cell transplantation is a life-saving therapy in patients suffering from acute leukemia. However, kidney complications developed after performing hematopoietic stem cell transplantation can affect the course and prognosis of the disease in patients with acute leukemia. This study is aimed at assessing the functional status of the kidneys in patients with acute leukemia who have undergone hematopoietic stem cell transplantation. The study has observed a group of patients with acute lymphoblastic leukemia and acute myeloid leukemia who have undergone hematopoietic stem cell transplantation. It has been discovered that β2 microglobulin is a sensitive method of analyzing renal function, with the β2 microglobulin threshold urine level not exceeding 0.3 mg/L. The complex diagnostics of kidney function in hematopoietic stem cell transplantation recipients has given the opportunity to identify the relationship between increased β2 microglobulin levels and decreased glomerular filtration rate. It has been determined that β2 microglobulin is a biomarker of renal disorders. The obtained data have showed that β2 microglobulin can be used as a diagnostic marker of reduced kidney function.

Circulating β2 and α1 microglobulins predict progression of nephropathy in diabetic patients: a meta-analysis of prospective cohort studies

AIMS

To study the association of circulating β2 (B2M) and α1 microglobulins (A1M) with diabetic nephropathy (DN) progression, a meta-analysis was performed on the prospective cohort studies.

METHODS

Up to October 2021, a comprehensive search of the PubMed, EMBASE, Scopus, Web of Science, and Cochrane Library databases was performed. The primary outcome (progression of DN) was defined as a decrease in eGFR or the occurrence of end stage renal disease or DN-related mortality. Eligible studies were included in a pooled analysis that used either fixed-effect or random-effect models to compensate for variation in measurement standards between studies. The funnel plot and Egger's test were used to assess publication bias.

RESULTS

The meta-analysis included 4398 people from 9 prospective trials (8 cohorts) for B2M and 3110 people from 4 prospective trials (3 cohorts) for A1M. Diabetic individuals with higher B2M levels had an increased risk for DN (relative risk [RR]: 1.81, 95% confidence interval [CI]: 1.56-2.09). Likewise, higher A1M was associated with augmented probability of DN (RR: 1.96, 95% CI: 1.46-2.62). The funnel plot and Egger's tests indicated no publication bias for A1M. Additionally, to compensate for putative publication bias for B2M, using trim and fill analysis, four studies were filled for this marker and the results remained significant (RR: 1.62, 95% CI: 1.37-1.92).

CONCLUSIONS

The elevated serum levels of B2M and A1M could be considered as potential predictors of DN progression in diabetic patients.

PROTOCOL REGISTRATION

PROSPERO CRD42021278300.

Serum metabolomic signatures of plant-based diets and incident chronic kidney disease

BACKGROUND

Greater adherence to plant-based diets is associated with a lower risk of incident chronic kidney disease (CKD). Metabolomics can help identify blood biomarkers of plant-based diets and enhance understanding of underlying mechanisms.

OBJECTIVES

Using untargeted metabolomics, we aimed to identify metabolites associated with 4 plant-based diet indices (PDIs) (overall PDI, provegetarian diet, healthful PDI, and unhealthful PDI) and incident CKD in 2 subgroups within the Atherosclerosis Risk in Communities study.

METHODS

We calculated 4 PDIs based on participants' responses on an FFQ. We used multivariable linear regression to examine the association between 4 PDIs and 374 individual metabolites, adjusting for confounders. We used Cox proportional hazards regression to evaluate associations between PDI-related metabolites and incident CKD. Estimates were meta-analyzed across 2 subgroups (n1 = 1762; n2 = 1960). We calculated C-statistics to assess whether metabolites improved the prediction of those in the highest quintile compared to the lower 4 quintiles of PDIs, and whether PDI- and CKD-related metabolites predicted incident CKD beyond the CKD prediction model.

RESULTS

We identified 82 significant PDI-metabolite associations (overall PDI = 27; provegetarian = 17; healthful PDI = 20; unhealthful PDI = 18); 11 metabolites overlapped across the overall PDI, provegetarian diet, and healthful PDI. The addition of metabolites improved prediction of those in the highest quintile as opposed to the lower 4 quintiles of PDIs compared with participant characteristics alone (range of differences in C-statistics = 0.026-0.104; P value ≤ 0.001 for all tests). Six PDI-related metabolites (glycerate, 1,5-anhydroglucitol, γ-glutamylalanine, γ-glutamylglutamate, γ-glutamylleucine, γ-glutamylvaline), involved in glycolysis, gluconeogenesis, pyruvate metabolism, and γ-glutamyl peptide metabolism, were significantly associated with incident CKD and improved prediction of incident CKD beyond the CKD prediction model (difference in C-statistics for 6 metabolites = 0.005; P value = 0.006).

CONCLUSIONS

In a community-based study of US adults, we identified metabolites that were related to plant-based diets and predicted incident CKD. These metabolites highlight pathways through which plant-based diets are associated with incident CKD.

Envelope method with ignorable missing data

Envelope method was recently proposed as a method to reduce the dimension of responses in multivariate regressions. However, when there exists missing data, the envelope method using the complete case observations may lead to biased and inefficient results. In this paper, we generalize the envelope estimation when the predictors and/or the responses are missing at random. Specifically, we incorporate the envelope structure in the expectation-maximization (EM) algorithm. As the parameters under the envelope method are not pointwise identifiable, the EM algorithm for the envelope method was not straightforward and requires a special decomposition. Our method is guaranteed to be more efficient, or at least as efficient as, the standard EM algorithm. Moreover, our method has the potential to outperform the full data MLE. We give asymptotic properties of our method under both normal and non-normal cases. The efficiency gain over the standard EM is confirmed in simulation studies and in an application to the Chronic Renal Insufficiency Cohort (CRIC) study.

Risk Factors for CKD Progression: Overview of Findings from the CRIC Study

The Chronic Renal Insufficiency Cohort (CRIC) Study is an ongoing, multicenter, longitudinal study of nearly 5500 adults with CKD in the United States. Over the past 10 years, the CRIC Study has made significant contributions to the understanding of factors associated with CKD progression. This review summarizes findings from longitudinal studies evaluating risk factors associated with CKD progression in the CRIC Study, grouped into the following six thematic categories: (1) sociodemographic and economic (sex, race/ethnicity, and nephrology care); (2) behavioral (healthy lifestyle, diet, and sleep); (3) genetic (apoL1, genome-wide association study, and renin-angiotensin-aldosterone system pathway genes); (4) cardiovascular (atrial fibrillation, hypertension, and vascular stiffness); (5) metabolic (fibroblast growth factor 23 and urinary oxalate); and (6) novel factors (AKI and biomarkers of kidney injury). Additionally, we highlight areas where future research is needed, and opportunities for interdisciplinary collaboration.

Proton pump inhibitors use and risk of chronic kidney disease and end-stage renal disease

INTRODUCTION

A possible association between long-term proton pump inhibitors (PPI) use and chronic kidney disease (CKD) has been recently described. Due to the potential health risk of this association, in the absence of proper clinical trials, we have decided to carry out a systematic review followed by meta-analysis.

EVIDENCE ACQUISITION

PubMed, Cochrane Library, and Lilacs databases were searched. Studies that reported an association between PPI use and CKD or End-stage Renal Disease (ESRD) published until December 23, 2019, were included. All selected studies present high quality according to the New-Castle-Ottawa. The risk ratio (RR) and confidence interval (CI) were pooled using a random-effects model in CKD outcome analysis and fixed effects model for ESRD. A total of 10 observational studies were selected.

EVIDENCE SYNTHESIS

Compared to patients who did not use PPI, the RR for CKD associated with PPI use was 1.35 (95% CI 1.15-1.56) with P<0.001, and the RR for ESRD associated with PPI use was 1.49 (95% CI 1.41-1.56) with P<0.001.

CONCLUSIONS

This study indicates the presence of a significant association between PPI use and an increased risk of CKD and ESRD and reiterates the need for the medical prescription of this class of drugs to be made following the guidelines of the FDA.

A Review of Specific Biomarkers of Chronic Renal Injury and Their Potential Application in Nonclinical Safety Assessment Studies

A host of novel renal biomarkers have been developed over the past few decades which have enhanced monitoring of renal disease and drug-induced kidney injury in both preclinical studies and in humans. Since chronic kidney disease (CKD) and acute kidney injury (AKI) share similar underlying mechanisms and the tubulointerstitial compartment has a functional role in the progression of CKD, urinary biomarkers of AKI may provide predictive information in chronic renal disease. Numerous studies have explored whether the recent AKI biomarkers could improve upon the standard clinical biomarkers, estimated glomerular filtration rate (eGFR), and urinary albumin to creatinine ratio, for predicting outcomes in CKD patients. This review is an introduction to alternative assays that can be utilized in chronic (>3 months duration) nonclinical safety studies to provide information on renal dysfunction and to demonstrate specific situations where these assays could be utilized in nonclinical drug development. Novel biomarkers such as symmetrical dimethyl arginine, dickkopf homolog 3, and cystatin C predict chronic renal injury in animals, act as surrogates for GFR, and may predict changes in GFR in patients over time, ultimately providing a bridge from preclinical to clinical renal monitoring.

The Role of Glomerular Epithelial Injury in Kidney Function Decline in Patients With Diabetic Kidney Disease in the TRIDENT Cohort

Introduction

Although diabetic kidney disease (DKD) is responsible for more than half of all chronic and end-stage kidney disease (ESKD), the association of light (LM) and electron microscopic (EM) structural changes with clinical parameters and prognosis in DKD is incompletely understood.

Methods

This is an interim analysis of 62 patients diagnosed with biopsy-confirmed DKD from the multicenter TRIDENT (Transformative Research in Diabetic Nephropathy) study. Twelve LM and 8 EM descriptors, representing changes in glomeruli, tubulointerstitium, and vasculature were analyzed for their relationship with clinical measures of renal function. Patients were followed every 6 months.

Results

Multivariable linear regression analysis revealed that estimated glomerular filtration rate (eGFR) upon enrollment correlated the best with interstitial fibrosis. On the other hand, the rate of kidney function decline (eGFR slope) correlated the most with glomerular lesions including global glomerulosclerosis and mesangiolysis. Unbiased clustering analysis based on histopathologic data identified 3 subgroups. The first cluster, encompassing subjects with the mildest histologic lesions, had the most preserved kidney function. The second and third clusters had similar degrees of kidney dysfunction and structural damage, but differed in the degree of glomerular epithelial cell and podocyte injury (podocytopathy DKD subtype). Cox proportional hazard analysis showed that subjects in cluster 2 had the highest risk to reach ESKD (hazard ratio: 17.89; 95% confidence interval: 2.13–149.79). Glomerular epithelial hyperplasia and interstitial fibrosis were significant predictors of ESKD in the multivariate model.

Conclusion

The study highlights the association between fibrosis and kidney function and identifies the role of glomerular epithelial changes and kidney function decline.

New Potential Biomarkers for Chronic Kidney Disease Management-A Review of the Literature

The prevalence of chronic kidney disease (CKD) is increasing worldwide, and the mortality rate continues to be unacceptably high. The biomarkers currently used in clinical practice are considered relevant when there is already significant renal impairment compromising the early use of potentially successful therapeutic interventions. More sensitive and specific biomarkers to detect CKD earlier on and improve patients' prognoses are an important unmet medical need. The aim of this review is to summarize the recent literature on new promising early CKD biomarkers of renal function, tubular lesions, endothelial dysfunction and inflammation, and on the auspicious findings from metabolomic studies in this field. Most of the studied biomarkers require further validation in large studies and in a broad range of populations in order to be implemented into routine CKD management. A panel of biomarkers, including earlier biomarkers of renal damage, seems to be a reasonable approach to be applied in clinical practice to allow earlier diagnosis and better disease characterization based on the underlying etiologic process.

Alternative kidney filtration markers and the risk of major macrovascular and microvascular events, and all-cause mortality in individuals with type 2 diabetes in the ADVANCE trial

BACKGROUND

Creatinine-based estimated glomerular filtration rate (eGFR) is biased in the setting of obesity and other conditions. Alternative kidney filtration markers may be useful in adults with diabetes, but few studies examined the associations with risk of clinical outcomes.

METHODS

In the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial, we evaluated whether baseline levels and change in eGFR based on creatinine (Cr), cystatin c (Cys), β₂ -microglobulin (B2M), eGFR_Cr-Cys , and the average of three estimates (eGFR_Cr-Cys-B2M ) assessed in 7217 participants at baseline and a random sample of 640 participants at the 1-year visit are associated with clinical outcomes. We examined associations with major macrovascular and microvascular events together and separately and all-cause mortality using Cox regression models, adjusting for established risk factors.

RESULTS

Over a median follow-up of 5 years, 1313 major macrovascular (n = 748) and microvascular events (n = 637), and 743 deaths occurred. Lower levels of eGFR based on all filtration markers individually and combined were associated with 1.4 to 3.0 times higher risk of major macrovascular and microvascular events (combined and separately) and all-cause mortality. Per 30% decline in eGFR_Cys , eGFR _Cr-Cys , and eGFR_Cr-Cys-B2M were associated with a >2-fold higher risk of all clinical outcomes.

CONCLUSIONS

In adults with type 2 diabetes, baseline levels of eGFR based on alternative filtration markers and per 30% decline in eGFR_Cys , eGFR _Cr-Cys , and eGFR_Cr-Cys-B2M were associated with clinical outcomes. Measurement of alternative filtration markers, particularly B2M in adults with type 2 diabetes may be warranted.

How best to estimate glomerular filtration rate? Novel filtration markers and their application

PURPOSE OF REVIEW

Chronic kidney disease is an increasing health burden. Estimating equations using serum concentrations of creatinine and cystatin C facilitate the assessment of kidney function as reflected in estimated glomerular filtration rate (eGFR). Reduced eGFR is associated with increased risk for numerous adverse outcomes and is an important aspect in many clinical situations. However, current equations are suboptimal in some clinical settings. The review focuses on approaches to improve the estimation of GFR and aims to familiarize the reader with the underlying methodological hypotheses how new markers could contribute to improve the overall performance of estimating equations.

RECENT FINDINGS

Low molecular weight proteins such as β-trace-protein and β-2-microglobulin, as well as newly discovered metabolites, show promise as new filtration markers, as they might be beneficial in populations in which creatinine or cystatin C are inaccurate. We propose that the combination of multiple novel markers, alone or in combination with creatinine, cystatin C or demographics, can potentially improve GFR estimation. For special populations such as dialysis patients, separate equations have been developed to estimate residual kidney function.

SUMMARY

Current GFR estimating equations are an essential part of routine clinical practice but have limitations. The use of multiple markers combined in a single equation appears to be the most promising approach. Future research is required to validate proposed equations in diverse populations.

Serum kidney injury molecule 1 and β2-microglobulin perform as well as larger biomarker panels for prediction of rapid decline in renal function in type 2 diabetes

AIMS/HYPOTHESIS

As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≤ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts.

METHODS

We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested case-control sample set from the Collaborative Atorvastatin in Diabetes Study (CARDS). We analysed 42 biomarkers measured on the SDR and GoDARTS samples by a variety of methods including standard ELISA, multiplexed ELISA (Luminex) and mass spectrometry. The subset of 21 Luminex biomarkers was also measured on the CARDS samples. We used the event definition of loss of >20% of baseline eGFR during follow-up from a baseline eGFR of 30-75 ml min^-1 [1.73 m]^-2. A total of 403 individuals experienced an event during a median follow-up of 7 years. We used discrete-time logistic regression models with tenfold cross-validation to assess association of biomarker panels with loss of kidney function.

RESULTS

Twelve biomarkers showed significant association with eGFR decline adjusted for covariates in one or more of the sample sets when evaluated singly. Kidney injury molecule 1 (KIM-1) and β₂-microglobulin (B2M) showed the most consistent effects, with standardised odds ratios for progression of at least 1.4 (p < 0.0003) in all cohorts. A combination of B2M and KIM-1 added to clinical covariates, including baseline eGFR and albuminuria, modestly improved prediction, increasing the area under the curve in the SDR, Go-DARTS and CARDS by 0.079, 0.073 and 0.239, respectively. Neither the inclusion of additional Luminex biomarkers on top of B2M and KIM-1 nor a sparse mass spectrometry panel, nor the larger multiplatform panels previously identified, consistently improved prediction further across all validation sets.

CONCLUSIONS/INTERPRETATION

Serum KIM-1 and B2M independently improve prediction of renal decline from an eGFR of 30-75 ml min^-1 [1.73 m]^-2 in type 2 diabetes beyond clinical factors and prior eGFR and are robust to varying sample storage conditions. Larger panels of biomarkers did not improve prediction beyond these two biomarkers.

Novel glomerular filtration markers

Chronic kidney disease is currently assessed by estimated glomerular filtration rate, a mathematical construct based on creatinine or creatinine and cystatin concentration. Creatinine-based equations have improved with standardization efforts and the Modification of Diet in Renal Disease Study (MDRD) and CKD-Epidemiology Collaboration Study (CKD-EPI). Because the measurement of creatinine is subject to interference from non-GFR determinants, alternative markers have long been sought. These have included cystatin C and low molecular weight proteins like β2-microglobulin and beta trace protein. Tubular disease often occurs before glomerular filtration is impaired and investigators have investigated the excretion of other low molecular weight proteins such as Neutrophil Gelatinase-Associated Lipocalin (NGAL) and Kidney Injury Molecule-1 and N-acetyl-β-d-glucosaminidase. While preliminary, there is some evidence linking these analytes with GFR, disease stage and mortality. Although asymmetrical dimethyl arginine, an inhibitor of nitric oxide, has been shown to be associated with progression of renal disease, symmetric dimethyl arginine may be a better marker. Recent work has also explored the potential of microRNA (miRNA) analysis and metabolomics studies to further elucidate this complex pathophysiologic disease process. Investigators hope to improve our ability to detect CKD by the use of test panels, i.e., various marker combinations thereof. Unfortunately, most of these markers lack standardization unlike traditional measures that rely on creatinine and cystatin C measurement.

Prostaglandins in the pathogenesis of kidney diseases

Prostaglandins (PGs) are important lipid mediators produced from arachidonic acid via the sequential catalyzation of cyclooxygenases (COXs) and specific prostaglandin synthases. There are five subtypes of PGs, namely PGE2, PGI2, PGD2, PGF2α, and thromboxane A2 (TXA2). PGs exert distinct roles by combining to a diverse family of membrane-spanning G protein-coupled prostanoid receptors. The distribution of these PGs, their specific synthases and receptors vary a lot in the kidney. This review summarized the recent findings of PGs together with the COXs and their specific synthases and receptors in regulating renal function and highlighted the insights into their roles in the pathogenesis of various kidney diseases.

Role of Kidney Biopsies for Biomarker Discovery in Diabetic Kidney Disease

Although estimated glomerular filtration rate and albuminuria are well-established biomarkers of diabetic kidney disease (DKD), additional biomarkers are needed, especially for the early stages of the disease when both albuminuria and estimated glomerular filtration rate may still be in the normal range and are less helpful for identifying those at risk of progression. Traditional biomarker studies for early DKD are challenging because of a lack of good early clinical end points, and most rely on changes in existing imprecise biomarkers to assess the value of new biomarkers. There are well-characterized changes in kidney structure, however, that are highly correlated with kidney function, always precede the clinical findings of DKD and, at preclinical stages, predict DKD progression. These structural parameters may thus serve as clinically useful end points for identifying new biomarkers of early DKD. In addition, investigators are analyzing tissue transcriptomic data to identify pathways involved in early DKD which may have associated candidate biomarkers measurable in blood or urine, and differentially expressed microRNAs and epigenetic modifications in kidney tissue are beginning to yield important observations which may be useful in identifying new clinically useful biomarkers. This review examines the emerging literature on the use of kidney tissue in biomarker discovery in DKD.

Estimated Glomerular Filtration Rate From a Panel of Filtration Markers-Hope for Increased Accuracy Beyond Measured Glomerular Filtration Rate?

The recent Kidney Disease Improving Global Outcomes 2012 CKD guidelines recommend estimating GFR from serum creatinine (eGFR_cr) as a first-line test to assess kidney function and using cystatin C or measured glomerular filtration rate (GFR) as confirmatory tests. eGFR_cr may be inaccurate in people with variation in muscle mass or diet, and eGFR_cys is not more accurate than eGFR_cr. eGFR_crcys is more accurate than either, but it is not independent of eGFR_cr. Measured GFR is not practical and is susceptible to error due to variation in clearance methods and in the behavior of exogenous filtration markers. Over the past few years, we have hypothesized, and begun to test the hypothesis, that a panel of filtration markers (panel eGFR) from a single blood draw would require fewer demographic or clinical variables and could estimate GFR as accurately as measured GFR. In this article, we describe the conceptual background and rationale for this hypothesis and summarize our work thus far including evaluation of novel low-molecular-weight proteins and metabolites and then outline how we envision that such a panel could be used in clinical practice, research, and public health.

Novel Filtration Markers for GFR Estimation

Creatinine-based glomerular filtration rate estimation (eGFR_cr) has been improved and refined since the 1970s through both the Modification of Diet in Renal Disease (MDRD) Study equation in 1999 and the CKD Epidemiology Collaboration (CKD-EPI) equation in 2009, with current clinical practice dependent primarily on eGFR for accurate assessment of GFR. However, researchers and clinicians have recognized limitations of relying on creatinine as the only filtration marker, which can lead to inaccurate GFR estimates in certain populations due to the influence of non-GFR determinants of serum or plasma creatinine. Therefore, recent literature has proposed incorporation of multiple serum or plasma filtration markers into GFR estimation to improve precision and accuracy and decrease the impact of non-GFR determinants for any individual biomarker. To this end, the CKD-EPI combined creatinine-cystatin C equation (eGFR_cr-cys) was developed in 2012 and demonstrated superior accuracy to equations relying on creatinine or cystatin C alone (eGFR_cr or eGFR_cys). Now, the focus has broadened to include additional novel filtration markers to further refine and improve GFR estimation. Beta-2-microglobulin (B2M) and beta-trace-protein (BTP) are two filtration markers with established assays that have been proposed as candidates for improving both GFR estimation and risk prediction. GFR estimating equations based on B2M and BTP have been developed and validated, with the CKD-EPI combined BTP-B2M equation (eGFR_BTP-B2M) demonstrating similar performance to eGFR and eGFR. Additionally, several studies have demonstrated that both B2M and BTP are associated with outcomes in CKD patients, including cardiovascular events, ESRD and mortality. This review will primarily focus on these two biomarkers, and will highlight efforts to identify additional candidate biomarkers through metabolomics-based approaches.

The Association of Serum Free Light Chains With Mortality and Progression to End-Stage Renal Disease in Chronic Kidney Disease: Systematic Review and Individual Patient Data Meta-analysis

OBJECTIVE

To clarify the associations between polyclonal serum free light chain (sFLC) levels and adverse outcomes in patients with chronic kidney disease (CKD) by conducting a systematic review and individual patient data meta-analyses.

PATIENTS AND METHODS

On December 28, 2016, we searched 4 databases (MEDLINE, Embase, CINAHL, and PubMed) and conference proceedings for studies presenting independent analyses of associations between sFLC levels and mortality or progression to end-stage renal disease (ESRD) in patients with CKD. Study quality was assessed in 5 domains: sample selection, measurement, attrition, reporting, and funding.

RESULTS

Five prospective cohort studies were included, judged moderate to good quality, involving 3912 participants in total. In multivariable meta-analyses, sFLC (kappa+lambda) levels were independently associated with mortality (5 studies, 3680 participants; hazard ratio [HR], 1.04 [95% CI, 1.03-1.06] per 10 mg/L increase in sFLC levels) and progression to ESRD (3 studies, 1848 participants; HR, 1.01 [95% CI, 1.00-1.03] per 10 mg/L increase in sFLC levels). The sFLC values above the upper limit of normal (43.3 mg/L) were independently associated with mortality (HR, 1.45 [95% CI, 1.14-1.85]) and ESRD (HR, 3.25 [95% CI, 1.32-7.99]).

CONCLUSION

Higher levels of sFLCs are independently associated with higher risk of mortality and ESRD in patients with CKD. Future work is needed to explore the biological role of sFLCs in adverse outcomes in CKD, and their use in risk stratification.

Filtration Markers, Cardiovascular Disease, Mortality, and Kidney Outcomes in Stable Kidney Transplant Recipients: The FAVORIT Trial

Cystatin C and beta-2-microglobulin (B2M) are filtration markers associated with adverse outcomes in nontransplant populations, sometimes with stronger associations than for creatinine. We evaluated associations of estimated glomerular filtration rate from cystatin C (eGFR_cys ), B2M (eGFR_B2M ), and creatinine (eGFR_cr ) with cardiovascular outcomes, mortality, and kidney failure in stable kidney transplant recipients using a case-cohort study nested within the Folic Acid for Vascular Outcome Reduction in Transplantation (FAVORIT) Trial. A random subcohort was selected (N = 508; mean age 51.6 years, median transplant vintage 4 years, 38% women, 23.6% nonwhite race) with enrichment for cardiovascular events (N = 306; 54 within the subcohort), mortality (N = 208; 68 within the subcohort), and kidney failure (N = 208; 52 within the subcohort). Mean eGFR_cr , eGFR_cys , and eGFR_B2M were 46.0, 43.8, and 48.8 mL/min/1.73m² , respectively. After multivariable adjustment, hazard ratios for eGFR_cys and eGFR_B2M <30 versus 60+ were 2.02 (95% confidence interval [CI] 1.09-3.76; p = 0.03) and 2.56 (1.35-4.88; p = 0.004) for cardiovascular events; 3.92 (2.11-7.31) and 4.09 (2.21-7.54; both p < 0.001) for mortality; and 9.49 (4.28-21.00) and 15.53 (6.99-34.51; both p < 0.001) for kidney failure. Associations persisted with additional adjustment for baseline eGFR_cr . We conclude that cystatin C and B2M are strongly associated with cardiovascular events, mortality, and kidney failure in stable kidney transplant recipients.

Risk of ESRD and Mortality Associated With Change in Filtration Markers

BACKGROUND

Using change in estimated glomerular filtration rate (eGFR) based on creatinine concentration as a surrogate outcome in clinical trials of chronic kidney disease has been proposed. Risk for end-stage renal disease (ESRD) and all-cause mortality associated with change in concentrations of other filtration markers has not been studied in chronic kidney disease populations.

STUDY DESIGN

Observational analysis of 2 clinical trials.

SETTING & PARTICIPANTS

Participants in the MDRD (Modification of Diet in Renal Disease; n=317) Study and AASK (African American Study of Kidney Disease and Hypertension; n=373).

PREDICTORS

Creatinine, cystatin C, β-trace protein (BTP), and β₂-microglobulin (B2M) were measured in serum samples collected at the 12- and 24-month follow-up visits, along with measured GFR (mGFR) at these time points.

OUTCOMES

ESRD and all-cause mortality.

MEASUREMENTS

Poisson regression was used to estimate incidence rate ratios and 95% CIs for ESRD and all-cause mortality during long-term follow-up (10-16 years) per 30% decline in mGFR or eGFR for each filtration marker and the average of all 4 markers.

RESULTS

1-year decline in mGFR, eGFR_cr, eGFR_BTP, and the average of the 4 filtration markers was significantly associated with increased risk for incident ESRD in both studies (all P≤0.02). Compared to mGFR, only decline in eGFR_BTP was statistically significantly more strongly associated with ESRD risk in both studies (both P≤0.03). Decline in eGFR_cr, but not mGFR or the other filtration markers, was significantly associated with risk for all-cause mortality in AASK only (incidence rate ratio per 30% decline, 4.17; 95% CI, 1.78-9.74; P<0.001), but this association was not significantly different from decline in mGFR (P=0.2).

LIMITATIONS

Small sample size.

CONCLUSIONS

Declines in mGFR, eGFR_cr, eGFR_BTP, and the average of 4 filtration markers (creatinine, cystatin C, BTP, and B2M) were consistently associated with progression to ESRD.

Rediscovering Beta-2 Microglobulin As a Biomarker across the Spectrum of Kidney Diseases

There is currently an unmet need for better biomarkers across the spectrum of renal diseases. In this paper, we revisit the role of beta-2 microglobulin (β₂M) as a biomarker in patients with chronic kidney disease and end-stage renal disease. Prior to reviewing the numerous clinical studies in the area, we describe the basic biology of β₂M, focusing in particular on its role in maintaining the serum albumin levels and reclaiming the albumin in tubular fluid through the actions of the neonatal Fc receptor. Disorders of abnormal β₂M function arise as a result of altered binding of β₂M to its protein cofactors and the clinical manifestations are exemplified by rare human genetic conditions and mice knockouts. We highlight the utility of β₂M as a predictor of renal function and clinical outcomes in recent large database studies against predictions made by recently developed whole body population kinetic models. Furthermore, we discuss recent animal data suggesting that contrary to textbook dogma urinary β₂M may be a marker for glomerular rather than tubular pathology. We review the existing literature about β₂M as a biomarker in patients receiving renal replacement therapy, with particular emphasis on large outcome trials. We note emerging proteomic data suggesting that β₂M is a promising marker of chronic allograft nephropathy. Finally, we present data about the role of β₂M as a biomarker in a number of non-renal diseases. The goal of this comprehensive review is to direct attention to the multifaceted role of β₂M as a biomarker, and its exciting biology in order to propose the next steps required to bring this recently rediscovered biomarker into the twenty-first century.