The usefulness of glycated albumin in patients with diabetes and renal disease: a scoping review

Introduction

Chronic kidney disease (CKD) is considered a public health problem and it is one of the main complications in patients with diabetes mellitus (DM). CKD may be diagnosed by persistent high urinary albumin excretion (albuminuria), low estimated glomerular filtration rate (eGFR), or other signs of kidney damage (1). Around 20% to 40% of DM patients develop kidney disease, called diabetes renal disease (DRD), with or without overt proteinuria (2). DRD can progress to end-stage renal disease (ESRD) requiring dialysis or kidney transplantation. Also, DRD significantly increases cardiovascular risk and health care costs. An appropriate glycaemic control decreases the rate of progression to renal failure in these patients; therefore good control of glycaemia is important since earlier stages of CKD (2).

Glycated haemoglobin (HbA1c) is the standard test for glycaemic monitoring in patients with DM (1). However, this assay is influenced by several pathophysiological conditions that become this test unreliable in patients with CKD, such as anaemia, uraemia, erythropoietin use and treatment by haemodialysis (HD), and its interpretation is difficult (3-5). Glycated albumin (GA) is a promising test with increasing interest in the last years as a potential marker of glycaemic control (6). Biochemically, the glycation of albumin to generate GA is similar to that of haemoglobin to yield HbA1c and it has been proposed as an alternative marker of glycaemic control in conditions wherein erythrocytes lifespan is altered or other condition that affects HbA1c (6). Some data reported that GA may be superior to HbA1c in assessing blood glucose control in diabetes patients with advanced CKD (7) due to GA it is not influenced by anaemia or treatments such as erythropoietin or HD. Also, GA is a short-term glycaemic index and indicates more rapidly variations of glycaemia than HbA1c.

In this way, the objective of this review was to summarize the evidence in the literature about the usefulness and limitations of GA as a glycaemic marker in patients with diabetes with CKD. We present the following article in accordance with the PRISMA Scoping Review reporting checklist (available at https://jlpm.amegroups.com/article/view/10.21037/jlpm-22-2/rc).

GA: a quick overview

GA is derived from non-enzymatic glycation between albumin, the most abundant protein in plasma, and glucose. Glycation is a physiological process that occurs when an N-terminal amino acid residue binds to sugar and produces a chemical product called “fructosamine”. Therefore, GA is a specific type of fructosamine that represents about 80% of the total of glycations in plasma (6). Although glycation is a natural process, it modifies the structure of albumin, leading to a reduction in the antioxidant activity of the protein and affecting its binding properties (8). Besides, advanced glycation stages of albumin induce the formation of advanced glycation end-products (AGEs), which account for additional oxidative events, related to several health complications (9).

Serum albumin is the most sensitive protein to glycation. This is mainly due to its high concentration in the body and its turnover is smaller when compared to other proteins, including haemoglobin (21 days against 120 days) (9). According, GA provides the glycaemic balance over 3 weeks, and it is considered a short-term biomarker for DM (8). When compared to HbA1c, the glycaemic marker recommended for DM monitoring and diagnosis by international consensus (1), GA has some advantages. GA is not affected by haemoglobin turnover, therefore, measurement of GA is not influenced by anaemia and iron deficiency (10), and it is also a good predictor of chronic complications in DM. Then, GA has been accepted as an alternative biomarker of glycaemic control when HbA1c is not reliable (6).

There are several methods proposed for the quantification of GA, as colorimetry, chromatography, immunoassay, and mass spectrometry. In 2002 a new enzymatic method for GA measurement was described (11) and, posteriorly, launched into the market. This method (Lucica GA-L^®, Asahi Kasei Pharma Corporation, Tokyo, Japan) employees an albumin-specific proteinase, which yields a simple, rapid, accurate and easily automatized technique (12,13). After Lucica GA-L^®, other enzymatic assays from different manufacturers have been launched, but with similar performance (14-16).

Although the GA has become highly studied, and its safety and efficiency has been scientifically evaluated, it is still few employed for clinical practice in countries other than Asians (17). One limitation for the applicability of GA in the routine of clinical labs may be the higher cost when compared to HbA1c. We have compared two different assays for GA and the price per test was around $4 to $6, in contrast with HbA1C test that is around $2 to $3 in Brazil (6,15). However, this scenery is likely to change in a near future. Studies show that reference levels of GA vary from approximately 10% to 18% (18), with a considerable low biological variation (19).

However, there are some conditions that may affect its levels and lead to misinterpretation. For instance, in albumin catabolism increases, as in nephrotic syndrome and hyperthyroidism, wherein lower GA values do not accurately reflect blood glucose concentrations (9). Nephrotic-range proteinuria decreases GA levels independent of the glycaemic status in patients with diabetes with CKD (20). GA is also reported to serve as a safe indicator of glycaemic control in patients with diabetes on dialysis, once the influence of albumin leakage induced by HD on GA levels was reported to be practically negligible (21). Overweight and obese individuals also present a negative correlation with GA, probably because of the chronic inflammation involved, which increases albumin turnover (6,15). In HD patients with DM, GA exhibited inverse correlations with BMI, total lean mass, total fat mass, and truncal fat mass (22). On the other hand, GA values are reported to be higher in conditions in which albumin metabolism is reduced, such as in liver cirrhosis and hypothyroidism (9). Age can also influence GA levels, whereas the effect of gender is not clear (15). Children show higher GA than adults and among adults at older ages, particularly for men, GA seems to be higher (8). In non-diabetic ESRD patients, GA values were influenced by age and nutritional status independent of glycaemia (23). It is well known that there are ethnic differences in HbA1c levels. However, information about the ethnic influence on GA levels is scarce since the majority of studies were carried out in Asian (18).

Several studies showed that glycaemic control, measured by HbA1c or GA, is an independent predictor of clinical outcome and mortality in people with DM (24-29) and targeting lower glycaemic levels has been proven to reduce risks of microvascular DM complications and, in some studies, also macrovascular DM complications (30-34). All these situations must be considered when interpreting markers of glycaemia results.

Review search strategy

This is a scoping review with a systematic search of literature. We searched PubMed (MEDLINE) for reports published up to May 2021 using the search terms related to DM, GA and renal disease combined. Details of all search terms are presented in Table S1. From the papers retrieved, a manual search of their references was conducted. Duplicate were removed and the remaining reports were assessed for eligibility, regardless of the language.

Selection criteria

Inclusion criteria were: (I) cross-sectional or cohort studies that assessed the GA as glycaemic marker in patients with diabetes with renal disease; (II) studies that analysed specifically GA by enzymatic assays. Exclusion criteria were: (I) study that was not performed in patients with diabetes with renal disease; (II) review articles; (III) editorial/comments/letters/case reports; (IV) basic research articles; (V) drug clinical trial reports. Two independent reviewers (FCC and JLC) decided for studies inclusion based upon eligibility criteria. First, we screened the titles of all search results to identify potentially relevant articles. Next, we reviewed the abstracts of these studies to define their relevance, and once judged to be relevant, reviewed the full text of the studies. Finally, we analysed each article, ascertained whether the article was qualified for inclusion and performed findings summary from all included reports. Any disagreements concerning study eligibility or data interpretation were resolved through discussion between reviewers.

Study characteristics

The search strategy identified 311 records, of which 119 were assessed for eligibility. We then excluded 58 papers (27 did not meet the research question; 9 were editorial, comment, letter, case report or book chapter; 8 were drugs clinical trial reports; 5 were basic research studies; 4 were not available in full text, 2 presented missing data and 3 was duplicate). Sixty-one studies met our inclusion criteria and were included in the qualitative synthesis of this review. These studies were related to glycaemic control (35-59), outcomes in patients with diabetes in dialysis (60-75), outcomes in patients with diabetes without overt renal disease (54,58,76-89), technical aspects of GA measurement (12), interfering factors in GA analysis (20-23) and diabetes mellitus post-transplant (DMPT) (90). The search strategy is depicted in Figure 1 and Table 1.

Figure 1 Flowchart of the article selection process. *, removing the 2 duplicates; **, some articles reported findings related to more than one topic and were included in more than one topic accordingly. DMPT, diabetes mellitus post-transplant.

GA and glycaemic control in patients with DM and CKD

The goals and plans of treatment for DM are to prevent or delay complications and optimize quality of life, and in CKD patients are not different. Several studies showed that glycaemic control is an independent predictor of clinical outcome and mortality in people with DM and CKD (24-29). Thus, maintaining blood glucose at recommended levels is essential for people with DM and CKD. However, CKD alters glycaemic control, the results of the HbA1c test, and the excretion of antidiabetic medications. The effects of CKD and dialysis can make blood glucose levels fluctuate widely, placing patients at risk of hypoglycaemia.

Self-monitoring of blood glucose (SMBG), continuous glucose monitoring (CGM), and HbA1c measurement are recommended for people with diabetes without ESRD by international guideline (1). For daily glycaemic monitoring, CGM and SMBG are frequently used but they are relatively high-cost options to assess real-time blood glucose. For these reasons, CGM and SMBG, even for people with DM and CKD, are not yet widely used but recommended to improve glycaemic control when anti-hyperglycaemic therapies are associated with the risk of hypoglycaemia (such as insulin) are used (2). In accordance with the recommendations of the Kidney Disease Improving Global Outcomes (KDIGO) (2) glycaemic control in patients with DM and CKD should be based on HbA1c measurements. This recommendation is motivated by the fact that in randomized control trials, targeting lower HbA1c values has been proven to reduce risks of microvascular DM complications and, in some studies, also macrovascular DM complications (i.e., cardiovascular events) (30-34) However, in people with DM and CKD HbA1c results may be affected by several factors (2,3). Thus, mainly in ESRD, HbA1c levels should be interpreted with caution (2) and there is an interest in an alternative marker to HbA1c. GA has been proposed as a candidate for alternative long-term glycaemic monitoring (6).

From our initial literature search 26 studies that evaluated the correlations of GA and HbA1c with blood glucose measures among patients with CKD and/or HD were selected and included in this section of our review (35-52,54-60). One additional study (53) with the same objective was identified during review of these studies. Table 2 shows the main characteristics and findings of these studies. The majority of studies reported that GA correlates with HbA1c in patients with CKD, including patients on dialysis (36-38,47,50,51,53,54,57). The association of GA and HbA1c with measures of glycaemia [fasting plasma glucose (FPG), random plasma glucose, or average blood glucose by SMBG or CGM] is similar and suggest that GA may be a useful substitute for HbA1c or as a complement for monitoring glucose control. However, the associations presented inconsistencies and varied widely from strong to none association. Some studies found that the correlation of GA with blood glucose was stronger than the correlation of HbA1c with blood glucose (35,36,39,41,42,46,48,49,53-57). Nevertheless, other studies reported worse correlations of GA with glycaemia than correlations of HbA1c with glycaemia (37,38,40,43-45,47,50-52,59,60). The study of Yajima et al. (55) included only patients on peritoneal dialysis and reported no correlation between CGM and GA (45), while another study found no correlation in a group of patients on HD for a period of less than 6 months.

Considering the inconsistency of findings in available observational studies, the lack of clinical trials based on GA in patients with CKD, and GA is not readily available for use, it might be inappropriate to dispense HbA1c in favour of GA. Besides, the results regarding the influence of stage of CKD on the association of GA with glycaemia also varied, although most studies report no influence, other studies report the influence of CKD severity, including those treated by dialysis (46,47,52,55,57,58). Furthermore, GA to monitor glycaemic control in patients with CKD should be interpreted with caution, since those patients may present diminished serum albumin due to massive proteinuria, malnutrition, or peritoneal dialysis. Studies in patients with CKD found that GA was correlated with albumin, and the GA level can be falsely low in hypoalbuminemia (36,41,47,48). Therefore, some studies to overcome this inaccuracy suggested serum albumin-adjusted GA. In these studies, serum albumin-adjusted GA was not affected by protein loss or renal anaemia, represented glycaemic excursion and glycaemic control better than GA alone or HbA1c in patients with CKD (48,55,89). Considering the limited data concerning serum albumin-adjusted GA, future studies about glycaemic control in patients with CKD should explore and validate this new parameter.

GA and outcomes

Chronic hyperglycaemia is the main cause of diabetes complications and glycaemic control is essential to diabetes management (1). It is very well stablished by large prospective randomized controlled trials that good glycaemic control is associated with reduction of development and progression of retinopathy, neuropathy, and diabetic kidney disease, common diabetes complications, both in type 1 and type 2 DM. Traditionally, HbA1c is the marker of choice to measure glycaemic control, therefore reduction in HbA1c levels are associated with reduction in rates of development and progression of complications (1).

Since the early 2000’s, when GA test became available (11), several studies analysed the association of GA levels and diabetes complications. Recently, a meta-analysis (91) that included 25,932 patients with diabetes undergoing dialysis from 12 studies, with follow-up up to 11 years, showed that higher GA levels were associated with the risk of all-cause mortality in dialysis patients with DM regardless of the type of dialysis, whereas higher GA was not associated with cardiovascular mortality. However, these results were modest and showed a small effect size. The studies included in this meta-analysis were very heterogeneous. The authors related limitations to their study such as the presence of many CKD-related variables that may affect GA levels, lack of randomized controlled trials, inclusion of small observational and cross-sectional studies and that most studies were carried out in Asian countries. All these factors would difficult the applicability of the results to all populations (91).

In this review, our systematic search identified 30 articles that evaluated the association of GA with DM complications in patients with dialysis treatment (54,58,61-75) and without dialysis treatment (76-89). Most of these studies were carried out in Asian countries (54,58,76,77,80-87) and only two studies were conducted by American centres (78,79).

Fifteen studies analysed the association of GA with complications in patients with diabetes undergoing dialysis treatment (54,58,61-75). The characteristics and main findings of these reports are described in Table 3. The majority of these studies reported the relationship of GA levels with mortality and showed that higher GA levels are related to higher risk for all-cause mortality and also for cardiovascular disease (CVD) mortality in patients with diabetes under dialysis treatment (61,62,65,67-75). The degree of these interactions varied from weak to modest in all studies. Twelve of these studies were included in the recent meta-analysis by Copur et al. (91). Kumeda et al. showed that increased GA values were associated with increased arterial stiffening (63) and Yamada et al. reported that GA values were associated with the presence of peripheral vascular calcification (64). Murea et al. reported that improved glycaemic control based on GA predicted cardiovascular-related hospitalizations and hospital length of stay in patients with diabetes on HD treatment (66). Most of these studies were carried out in Japan (61-64,68,70,72-75), 3 in American centres (65-67), one in Taiwan (69) and one in Germany (71).

Table 4 shows the main characteristics and findings of 15 studies reporting the association of GA and DRD, retinopathy or CVD in patients with diabetes without dialysis treatment (76-89).

Two studies reported a positive association of GA with urinary N-acetyl-β-D-glucosaminidase (uNAG), an early marker of renal tubulopathy, in patients with type 1 (84) and type 2 (85) DM, with early DRD. Some longitudinal studies evaluated prospectively or retrospectively the association of GA with DRD and all showed that AG levels are associated with an increased risk of development and/or progression of DRD in type 1 and type 2 DM patients (79-82). Selvin et al. also showed that GA was strongly associated with prevalent retinopathy at high GA levels in patients with DM (79) and other study reported that the variability in GA levels rather than GA levels was associated with the development and progression of DRD (82). In general, observational studies reported the same relationship between GA and microvascular complications (54,58,76-78,83). In type 1 DM, both HbA1c and GA were similarly associated with microvascular complications (78). And in type 2 DM, studies showed that GA levels are associated with microalbuminuria, degree of renal dysfunction and in the prediction of DRD presence (54,58,76,77). However, Umayahara et al. reported that GA/HbA1c ratio was associated with diabetic retinopathy, but not with DRD (83). Very few studies evaluated the association of GA and CVD (78,80,86). GA levels were not associated with cardiovascular complications (78), and also were not associated with carotid artery atherosclerosis in type 1 DM patients (80). Although, Vijayaraghavan et al. reported that GA levels increase when the ejection fraction decreases and moreover it also increases based on the number of vessels obstructed (86).

Most of these studies were carried out in Asian countries (76,77,80-86). Only two studies were conducted by American centres (78,79).

Finally, Abe et al. (87) investigated the rate of ‘burnt-out diabetes’ condition in DM patients on peritoneal dialysis and reported that the rate was significantly decreased when taking the upper limit of GA values in the general population (16%) into account. Parrinello et al. (88) analysed the association of HbA1c, GA and other biomarkers with incident CVD, incident ESRD, and prevalent retinopathy in a large cohort of White and Blacks participants, with and without DM. They found that the prognostic value of GA, HbA1c and other biomarkers were similar by race with all DM long-term complications studied.

GA and post-transplantation diabetes mellitus (PTDM)

A specific type of DM that may occur after kidney transplantation is known as renal PTDM (1). Its development is associated with the use of immunosuppressive therapy, such as calcineurin inhibitors and corticosteroids. Only one study has specifically evaluated the accuracy of GA in the diagnosis of renal PTDM (90), but data is lacking about the performance of GA in the monitoring of DM in patients who underwent kidney transplantation. Estimated incidence of renal PTDM during the first year after transplant is about 20% (92). Studies have shown that the occurrence of PTDM increases the risk for CVD and mortality in kidney transplant recipients (93). The recommended test to detect this condition is oral glucose tolerance test (OGTT), once it has presented higher sensitivity to identify patients with PTDM during the first year after transplant when compared to FPG and HbA1c (1) Due to the inconvenience and high cost of performing an OGTT in all transplanted patients in the clinical setting, the use of FPG is highly spread. However, other diagnostic alternatives have also been accessed. The use of HbA1c alone in the first months after transplant has shown not to be adequate for the screening of PTDM, because it has presented low sensitivity and a great number of positive cases would be missed (94). In a cross-sectional study performed at the fourth month post-transplant (90), GA showed moderate diagnostic accuracy for renal PTDM when compared to OGTT and/or HbA1c as diagnostic criteria. The use of a single GA cut-point was not enough to properly screen and diagnose PTDM however GA ≥17% presented high specificity to rule in the disease. Nevertheless, this study did not show that GA was superior to HbA1c to detect PTDM in the initial months after kidney transplantation (90). There is still a gap in the literature regarding the association between GA levels and the development of adverse clinical outcomes in patients who develop PTDM after kidney transplantation or who had pre-existing DM.

Conclusions

GA, a short-term glycemic marker, has been pointed as an alternative test to HbA1C in patients with DM. It is indicated in clinical situations where HbA1c is not a reliable marker due to situations which may interference with the metabolism of hemoglobin. Also, it is especially indicated for patients on hemodialysis since its levels are not affected by the presence of anemia, uremia or hemolytic processes. In early 2000’s, a new enzymatic method to measure GA was described and showed to be simple, rapid, accurate and easily automatized. In the last years, many studies have evaluated the role of GA in the monitoring of DM. This review summarized the main findings of these studies.

Data from observational studies showed that the association of GA and HbA1c with measures of glycaemia is similar supporting that GA may be a substitute for HbA1c. Several studies showed that higher GA levels were associated with the risk of all-cause mortality in dialysis patients with DM regardless of the type of dialysis, whereas higher GA was not associated with cardiovascular mortality. These interactions varied from weak to modest in all studies. Other studies reported the association of GA and DRD, retinopathy or CVD in patients with diabetes without dialysis treatment. In patients with early nephropathy, several studies reported positive association between GA and microvascular complications although very few showed association of GA and DCV. The majority of these studies were carried out in Asian populations and the applicability of these results to all populations may not be straight forward. In addition, there is a lack of clinical trials and prospective studies that analysed GA in DM patients with and without CKD and these studies are warranted.

Although evidences show that GA may be a useful glycemic marker and prognostic factor in patients with CKD it should be used with caution in situations that its levels may be falsely altered as in the presence of massive proteinuria with low serum albumin. It should be highlighted that the choice of which test to use must be guided by the clinical patient features and accessibility to tests. Further, it is necessary an international consensus about laboratory issues and clinical use of GA, to guarantee its inclusion in the routine of clinical laboratory worldwide, thus improving the future controlling of DM patients.

In conclusion, GA is a promisor biomarker for the management of DM patients with and without CKD.

Acknowledgments

Funding: This work was partially supported by the Research Incentive Fund (FIPE) of the Hospital de Clinicas de Porto Alegre (HCPA) (FIPE/ HCPA, GPPG 190320); PhD scholarship from Programa de Excelência Acadêmica da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES-PROEX) to FCC; and an undergraduate scholarship from Fundação de Amparo à Pesquisa do Rio Grande do Sul (FAPERGS) to LGS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Footnote

Provenance and Peer Review: This article was commissioned by the Guest Editor (Rafael Noal Moresco) for the series “Laboratory Medicine in Diabetic Kidney Disease” published in Journal of Laboratory and Precision Medicine. The article has undergone external peer review.

Reporting Checklist: The authors have completed the PRISMA Scoping Review reporting checklist (available at https://jlpm.amegroups.com/article/view/10.21037/jlpm-22-2/rc).

Peer Review File: Available at https://jlpm.amegroups.com/article/view/10.21037/jlpm-22-2/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jlpm.amegroups.com/article/view/10.21037/jlpm-22-2/coif). The series “Laboratory Medicine in Diabetic Kidney Disease” was commissioned by the editorial office without any funding or sponsorship. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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