Update on estimation of kidney function in diabetic kidney disease

Abstract

The American Diabetes Association recommends annual assessment of glomerular filtration rate (GFR) to screen for diabetic nephropathy. GFR is measured indirectly using markers that, ideally, are eliminated only by glomerular filtration. Measured GFR, although the gold standard, remains cumbersome and expensive. GFR is therefore routinely estimated using creatinine and/or cystatin C and clinical variables. In pediatrics, the Schwartz creatinine-based equation is most frequently used even though combined creatinine and cystatin C-based equations demonstrate stronger agreement with measured GFR. In adults, the CKD Epidemiology Collaboration (CKD-EPI) equations with creatinine and/or cystatin C are the most accurate and precise estimating equations. Despite recent advances, current estimates of GFR lack precision and accuracy before chronic kidney disease stage 3 (GFR<60mL/min/1.73m²). There is therefore an urgent need to improve the methods for estimating and measuring GFR. In this review we examine the current literature and data addressing measurement and estimation of GFR in diabetes.

Introduction

Assessment of renal function through the measurement of glomerular filtration rate (GFR) is an essential tool for nephrologists and diabetologists caring for patients with type 1 and 2 diabetes. GFR evaluation is crucial for the diagnosis of early (renal hyperfiltration [GFR greater than 120–150mL/min/1.73m²) and rapid GFR decline [annual GFR loss greater than 3mL/min/1.73m² or > 3.3%/year] as well as late phenotypes of diabetic kidney disease (impaired GFR [<60mL/min/1.73m²]). Furthermore, individual GFR trajectories over time are strongly associated with incident chronic kidney disease (1, 2). Accordingly, the American Diabetes Association recommends routine screening of GFR in adults with diabetes, and recently expanded screening recommendations to include adolescents with diabetes (3, 4).

The first widely used GFR estimating equations were developed four decades ago to estimate GFR in adults from serum creatinine concentrations. In recent years, a number of new equations have been developed based on serum creatinine and cystatin C assays. Despite advances in GFR measurement, current estimates of GFR lack precision (i.e. too much random error) and accuracy (i.e. too much systematic error) before chronic kidney disease stage 3 (GFR <60 mL/min/1.73m²) (5). A recent DCCT-EDIC paper also reported that changes in eGFR over a 3 year period may not reflect changes in measured GFR (6, 7). This is of particular concern in adolescents and young adults with diabetes, in whom renal hyperfiltration is present in approximately 50% of individuals and which may promote renal injury (8, 9). The dissociation between changes in eGFR vs. measured GFR is of further concern since rapid changes in GFR may be missed due to a lack of acceptable screening methods for subtle changes in renal function (10).

Diabetic nephropathy is the leading cause of end-stage renal disease and dialysis in the US, and is characterized by a long clinically silent period without signs or symptoms of disease (10, 11). In 2009, overall Medicare expenditure for people with chronic kidney disease and diabetes accounted for $18 billion (11). There is therefore an urgent need for improved methods of estimating and measuring GFR. Accordingly, in this review we examine the current literature and data addressing measurement and estimation of GFR in diabetes. We also focus on the early phenotypes of diabetic kidney disease and their potential treatment, including renal hyperfiltration and rapid GFR decline, review of current methods to estimate and measure GFR, challenges that are specific to diabetes, and current and potential treatments to prevent diabetic kidney disease.

Early Diabetic Kidney Disease

Diabetic nephropathy is the leading cause of end-stage renal disease (ESRD) in the western world (10, 12–14). In fact, the 2011 US Renal Data System showed that diabetic nephropathy accounted for 44.5% of all cases of ESRD in the United States in 2009 (11). Diabetic nephropathy is also an important risk factor for coronary artery disease (CAD) (15–17) and overall mortality (15, 18). The natural history of diabetic nephropathy is characterized by a long silent period without overt clinical signs and symptoms of nephropathy (Figure 1). For that reason, early detection of diabetic nephropathy may have a pivotal role in the prevention of ESRD in diabetes (19). While the appearance of microalbuminuria is often the earliest clinical sign of diabetic nephropathy, this classical paradigm has been questioned over the past few years after the demonstration that microalbuminuria does not necessarily imply progressive nephropathy, and may in fact regress to normoalbuminuria (20, 21), and that CKD stage 3 can develop in the absence of microalbuminuria (7, 22). Albuminuria is still an important risk factor in diabetes as it is strongly associated with dyslipidemia and cardiovascular disease (23, 24). Renal hyperfiltration is typically defined by a glomerular filtration rate (GFR) of between 120 mL/min to 150 mL/min/1.73m², or greater than 2 standard deviations above the mean GFR in normal, healthy individuals (9), and is thought to represent the earliest hemodynamic abnormality seen in diabetes (25). Phenotypes of early diabetic nephropathy prior to the loss of renal function, such as renal hyperfiltration and rapid GFR decline are considered stronger predictors of nephropathy progression in type 1 diabetes than albuminuria (10, 26–30). For that reason, GFR is the most clinically relevant measure of kidney function in diabetes. The American Diabetes Association, National Kidney Foundation and International Society of Nephrology recommend annual measurement of estimated glomerular filtration rate to identify and monitor diabetic nephropathy (31–33). However, as we will review, current methods to measure or estimate GFR early in the pathogenesis of diabetic nephropathy in the normal to elevated GFR range present a particular challenge for physicians managing patients with diabetes.

Figure 1. Stages of Diabetic Nephropathy and Challenges of Determining GFR.

The area of the figure colored green represents glomerular filtration rates (GFR) not accurately estimated by creatinine and cystatin-C based equations. In contrast, the red area is typically accurately estimated by the equations.

Measurement of Glomerular Filtration Rate

GFR is measured indirectly as the clearance of exogenous filtration markers that are eliminated exclusively by glomerular filtration (Table 1). Such markers include inulin (which is considered the gold standard), iohexol, iothalamate, technetium 99m diethylenetriamine pentaacetic acid (^99mTc-DTPA) and chromium 51-ethylenediaminetetraacetic acid (⁵¹Cr-EDTA). As an alternative, urinary clearance techniques are another direct method that can be used to measure GFR, but this remains inconvenient and associated with errors around the timing of urine collections. For these reasons, it is more common to measure GFR by plasma clearance. The major disadvantage of plasma clearance is the duration of testing needed to calculate the clearance curve accurately, which can be up to 8 hours. GFR measurements, by either urinary or plasma clearance techniques, therefore remain impractical and expensive and as a result are not routinely performed in clinical practice. For that reason, GFR is typically estimated through the use of serum concentrations of endogenous filtration markers (i.e. serum creatinine and/or cystatin C, as described below). Although estimated GFR is sufficient for clinical decision making in many circumstances, particularly when GFR is <60 ml/min/1.73m2 (34), patients with diabetes would likely benefit from having their GFR measured using more accurate and precise techniques, due to their increased risk of kidney disease. Furthermore, GFR measurements are estimates of renal function and are affected by excessive intake of drinks containing caffeine (35), protein load (36), exercise (37) and certain medications (e.g. diuretics, antibiotics) (38). Another major challenge specific to diabetes when estimating and measuring GFR is hyperglycemia which is known to influence GFR, as reviewed in detail below (39). The early diagnosis of declining renal function may be important due to the potential for early interventions aimed at delaying the progression to ESRD. Accordingly, to diagnose early diabetic nephropathy, accurate and precise diagnostic tools are necessary.

Table 1.

Methods to measure GFR in pediatrics and adults

Exogenous filtration markers	Comparison with inulin	Reference	Pros	Cons
Inulin - Plasma - Urinary		(96)	- Classically considered gold-standard	- Expensive – the cost of Inutest (Fresenius Kabi Austria GmbH) has increased more than tenfold during recent years - Rigorous and time consuming - Inulin is viscous and slowly reaches its volume of distribution, requiring constant infusion rate with multiple repeat blood and urine collections and careful timing of blood sampling.
51Cr-EDTA - Plasma - Urinary	- Correlation: 0.94 - Difference: +2.2 to 2.8mL/min/1.72m2	(97)	- Isotopic marker freely filtered in glomeruli - Widely available in Europe	- Radioactive - Time consuming - 10–12% is bound to plasma protein
99m Tc-DTPA - Plasma - Urinary	- Correlation: 0.97 - Difference: −15 to +21 mL/min/1.72m2	(98)	- Isotopic marker freely filtered in glomeruli - Widely available in US	- Radioactive - Time consuming - 10–12% is bound to plasma protein
125I-Iothalamate - Plasma	- Correlation: N/A - Difference: +38%	(99)	- Ionic contrast product - Long half-life	- Cannot be used in patients with allergies to iodine - Radioactive - Non-radioactive iothalamate assay is expensive - 10–12% is bound to plasma protein
Iohexol - Plasma - Dried blood spots	- Correlation: 0.92 - Difference: +2.0 to 2.7mL/min/1.72m2	(100)	- Non-ionic contrast - Inexpensive - Not radioactive - Available on DBS - Used in doses 10–50x in neonates for radiographs	- Cannot be used in patients with allergies to iodine - Time consuming - 2% is bound to plasma protein

Estimation of Glomerular Filtration Rate

i. Estimation of GFR in adults

There are several equations available to estimate GFR in adults using endogenous filtration markers (serum creatinine and/or cystatin C) (Table 2). The most state-of-the-art equations are the three CKD-EPI equations: CKD-EPI Creatinine, CKD-EPI Cystatin C and CKD-EPI Creatinine and Cystatin C (5). The number of available equations is in part due to the nonequivalent results obtained from using different creatinine and cystatin C assays (40). More recently the accuracy of creatinine measurements has improved with the availability of higher-order reference methods (isotope dilution-mass spectrometry (IDMS) reference methods) (41, 42). Similarly, the number of equations using cystatin C is due to previous lack of an international cystatin C calibrator (40). In 2010, the first certified reference material for serum cystatin C was published (ERM-DA471/IFCC (43, 44). Assay reproducibility over time and between laboratories is important with GFR as it is a longitudinal measure of renal function in research and clinical care.

Table 2.

Adult GFR estimating equations

Names	References	Equations
		Serum creatinine-based
CKD-EPI Creatinine	(5)	eGFR = 141 × min(serum creatinine /κ) * max(serum creatinine/κ) * 0.993age * 1.018 [if female] * 1.159 [if African American]
MDRD	(101)	eGFR = 186 × [serum creatinine (umol/l)/88.4]−1.154 * [age (years)]−0.203 × (0.742 if female) × (1.21 if black)
Mayo quadratic equation	(102)	eGFR = (1.911 + (5.249/screat)- (2.114/(screat*screat))- (0.00686*age) – (0.205 if female))
		Cystatin C-based
CKD-EPI Cystatin C	(5)	eGFR = 133 × min(cystatin C/0.8, 1)−0.499 * max(cystatin C /0.8, 1)−1.328 * 0.996age [ × 0.932 if female]
Tan equation	(103)	eGFR = 87.1/ plasma cystatin C (mg/L) − 6.87
Perkins equation	(104)	eGFR = 100/(cystatin C)
Arnal equation	(105)	eGFR = 74.835/(cystatin C1.333)
MacIsaac equation	(106)	eGFR = (84.6/cystatin) – 3.2
Stevens equation	(107)	eGFR = 127.7/(cystatin C1.17) * [age (years)] −0.13 * (0.91 if female) * (1.06 if black)
CAPA	(40)	eGFR = 130 * cystatin C−1.069 * age−0.117 – 7
		Combined creatinine and cystatin C
CKD-EPI Creatinine and Cystatin C	(5)	eGFR = 135 × min(serum creatinine/k)−a× max(serum creatinine /k)−0.601* min(cystatin C/0.8)−0.375* max( cystatin C/0.8)−0.711* 0.995age[ * 0.969 if female ] [ * 1.08 if black ]
Stevens equation	(108)	eGFR = 177.6 * [serum creatinine (umol/l/88.4)] −0.65 * (cystatin C−0.57) * [age (years)] −0.20 * (0.82 if female) * (1.11 if black)

Both serum creatinine and cystatin C are affected by factors other than GFR, i.e. non-GFR determinants, (Table 3), but cystatin C is considered to be less biased by age and weight compared to creatinine-based measurements, and correlates more closely with direct measures of GFR over a wide spectrum of plasma glucose levels compared to creatinine based measures in experimental studies (45, 46). These data suggest that cystatin C more accurately reflects measured GFR in subjects with type 1 diabetes, favoring its use as an estimate of GFR in this population. Cystatin C has also been shown to be associated with fat mass rather than lean mass in some but not all studies, which may impair the accuracy of GFR estimates by cystatin C in obese patients and in those with significant changes in adiposity (5, 6). The Prevention of Renal and Vascular End-Stage Disease (PREVEND) study also demonstrated an association between cystatin C and c-reactive protein (47), which may explain the association between fat mass and cystatin C, since higher body mass being associated with inflammation and insulin resistance (48, 49). In contrast to cystatin C based equations, creatinine-based GFR estimates are influenced by other confounders, including filtration fraction (FF = GFR/effective renal plasma flow) (50). This implies that creatinine is affected by hyperfiltration and therefore weakens its diagnostic performance as a GFR marker in the presence of hyperfiltration (50), an interaction that has been reported by our group (46).

Table 3.

Non-GFR determinants of creatinine and cystatin C

Creatinine	Cystatin C
Increasing age ↑	Increasing age ↑
Male gender ↑	Male gender ↑
Lean muscle mass ↑	Thyroid dysfunction (inconclusive)
Malnutrition	Fat mass (inconclusive)
Protein diet ↑	Inflammation (inconclusive)
Inflammation ↑	Very large doses of glucocorticoids ↑
Certain medications (cimetidine, trimethoprim, dronedarone, cobicistat)

GFR estimated by cystatin C also appears to better predict micro- and macrovascular complications in subjects with type 1 diabetes compared to creatinine-based equations (17, 26, 49, 51). Cystatin C more accurately detects rapid GFR decline than creatinine-based measurements in type 1 diabetes subjects with normal renal function (51). Rapid GFR decline estimated by cystatin C is also associated with a higher risk for cardiovascular complications and mortality than creatinine based GFR estimated (52, 53). Furthermore, Skupien et al demonstrated that GFR staging with cystatin C is superior for predicting ESRD and mortality compared to GFR with creatinine and cystatin C, which suggests that serum creatinine counters the predictive ability of serum cystatin C in adults with type 1 diabetes (54). Finally, Shlipak et al demonstrated that the use of cystatin C compared to creatinine strengthens the association between eGFR and risk of death and ESRD in 11 diverse general-population studies that included both diabetic and non-diabetic participants (27). One limitation to the use of cystatin C has been the cost (approximately USD $5–6 vs. $1–3 for serum creatinine), although this difference is much less than in the past.

Despite the possible superiority of cystatin C compared to creatinine, estimates of GFR by both serum creatinine and cystatin remain imperfect (17, 55, 56). The creatinine and cystatin-C based eGFR equations are associated with greater variability when eGFR >60 mL/min/1.73m² (5). However, by the time eGFR is ≤60 mL/min/1.73m² almost half of renal function has already been lost (32). A study by Rognant et al. demonstrated that the mean absolute bias of CKD-EPI creatinine was −12.7 ± 12 mL/min/1.73 m² compared to measured GFR, with an interquartile range of 16 mL/min/1.73m², and 10% (P10) and 30% (P30) accuracies were, respectively 28.0 and 80.1% (57). In other words, 28% of study participants had GFR estimates with less than a 10% bias, and 80.1% had GFR estimates with a bias up to 30% compared to measured GFR (this would be an eGFR of 70–130 mL/min/1.73 m² for a ‘true’ GFR of 100 mL/min/1.73 m²). Furthermore, when eGFR is >90mL/min/1.73m², agreement (concordance) between eGFR calculated by CKD-EPI cystatin C and eGFR calculated by CKD-EPI creatinine in the same individual has been reported to be as low as 56% (53, 58). For that reason, improved methods to easily and accurately measure GFR as well as changes in renal function in the normal and hyperfiltration range are needed (10, 59).

ii. Estimation of GFR in pediatrics

The American Diabetes Association recently recommended routine screening of glomerular filtration rate (GFR) in adolescents with type 1 diabetes in the Type 1 Diabetes Through the Life Span: A Position Statement of the American Diabetes Association from 2014 and in the 2015 Standards of Care, although this is not yet routinely performed clinically (3, 4). There are developmental changes during childhood and adolescence that affect measurement of GFR, including growth spurts due to the rapid increase in muscle mass and extracellular volume (60). Numerous equations have been formulated to estimate GFR in pediatric and adolescent patients (61, 62) (Table 4). These equations are derived from different populations with a variety of underlying nephropathies and with significant variability in GFR (Table 4). To our knowledge, no single equation has been specifically developed or validated in adolescents with type 1 or type 2 diabetes. Furthermore, the majority of GFR equations have been based on non-standardized creatinine and cystatin C assays (63). The Schwartz creatinine based equation from 2009, adjusted to be traceable to isotope dilution mass spectrometry, is the most widely used in clinical practice, but has been demonstrated to be most accurate in the range of 25–75 mL/min/1.73m² (64). Stronger agreement with measured GFR is observed with cystatin C and combined creatinine and cystatin C equations (e.g. CKiD, Schwartz, Bouvet combined creatinine and cystatin C equations) compared to creatinine equations (62, 64). Berg et al. recently reported unstable performance of standardized creatinine based equations across levels of measured GFR in comparison with standardized cystatin C equations in children (63). The diagnostic accuracy of the various cystatin C and combined creatinine cystatin C equations varies with GFR (65), which is in part a function of the GFR levels in the cohorts of patients used to derive the equations (Table 4). For instance, the CKiD and Zappitelli equations demonstrate higher accuracy in GFR <90mL/min/1.73m², whereas the Bouvet, Bokenkamp and Filler equations have greater accuracy in GFR categories ≥135mL/min/1.73m² (65). For that reason, applying these equations in clinical practice and research requires knowledge of the expected GFR, which is not always possible. The lack of a single equation that performs well across the span of GFR in pediatrics has limited the use of estimating equations to measure longitudinal changes in GFR. Recently, Berg et al. demonstrated accuracy (P30, percentage of GFR estimates within 30% of measured GFR) of 75%, 85%, 88%, 83% and 95% for GFR estimated by Berg cystatin C equation in children with inulin measured GFR of <30, 30–59, 60–89, 90–119 and ≥120 mL/min/1.73m² respectively (63). Caucasian and Asian pediatric and adult subjects (CAPA) equations also performed well across the span of GFR with accuracy of 80%, 85%, 98%, 84% and 90% for inulin measured GFR of <30, 30–59, 60–89, 90–119 and ≥120 mL/min/1.73m² respectively (63).

Table 4.

Pediatric GFR estimating equations

Name	Equation	Reference Method	Cohort GFR Median or Range Used for Data Generation	References
Serum creatinine-based
Schwartz	eGFR = [length (cm) * k] / Scr k = 0.45 for infants 1 to 52 weeks old k = 0.55 for children 1 to 13 years old k = 0.55 for adolescent females 13–18 years old k = 0.7 for adolescent males 13–18 years old	Inulin	3–220 mL/min/1.73m2 ¥	(109)
Schwartz 2009	eGFR = 0.413 * Ht / Scr	Iohexol	41 mL/min/1.73m2	(62)
Cystatin C-based
Filler	eGFR = 10(1.962 + (1.123 * log(1/cystatin C))	99mTc-DTPA	103 mL/min/1.73m2	(65)
Bökenkamp	eGFR = 137/cystatin C – 20.4	Inulin	77 mL/min/1.73m2	(65)
Berg	eGFR = 91 * cystatin C−1.213	Inulin	84 mL/min/1.73m2	(63)
CAPA	eGFR = 130 * cystatin C−1.069 * age−0.117 − 7	Inulin and iohexol	103 mL/min/1.73m2	(40)
Combined creatinine and cystatin C
Zappitelli	eGFR = 25.38[1/CysC]0.331[1/Scr]0.602[1.88height]	Iothalamate	74 mL/min/1.73m2	(65)
Bouvet	eGFR = 46.1[1.2/CysC]0.33[(96/88.4)/(Scr)]0.55[weight/45]0.77[age/14]0.17	51Cr-EDTA	92 mL/min/1.73m2	(110)
Schwartz	eGFR = 39.1[height (m)/Scr (mg/dl)](0.516) x [1.8/cystatin C (mg/L)](0.294)[30/BUN (mg/dl)](0.169)[1.099](male)[height (m)/1.4](0.188)	Iohexol	41 mL/min/1.73m2	(62)

^¥Schwartz et al. measured GFR on 186 subjects between ages of 6 month to 20 years, and the GFR distribution had a bimodal appearance, with peaks in the 10–30mL/min/1.73m² and 110–140mL/min/1.73m². The 10–30 are those with advanced renal disease, and 110–140mL/min/1.73m² are those children with normal kidney function (109).

While these newer standardized equations hold promise, there are no currently published equations that have been validated against measured GFR in youth with diabetes. An additional challenge in measuring GFR in diabetes is the acute effect of blood glucose, as discussed below. This is of particular concern in adolescents and young adults with type 1 diabetes, in whom renal hyperfiltration is common and may promote renal injury, or rapid change in GFR may be missed due to lack of accurate screening method for GFR.

Acute hyperglycemia increases GFR

Multiple factors can influence GFR measurements, but in people with diabetes, an additional challenge in measuring GFR is the acute effect of blood glucose, which was established in studies dating back to the 1970s, although generally not accounted for in current clinical or research assessments of GFR in people with diabetes. Hyperglycemia is known to affect renal hemodynamic function and increase GFR by up to 20 mL/min/1.73 m² (46, 66–69). The mechanism responsible for the increase GFR in the setting of acute glycemia is incompletely understood, but has been in part attributed to the effect of hyperglycemia on renin–angiotensin–aldosterone system (RAAS) (70, 71). We have previously demonstrated that RAAS blockade by aliskiren (a direct renin inhibitor) blunts the increased GFR as measured by inulin clearance provoked by hyperglycemia (72). Moreover, hyperglycemia has been proposed to increase proximal tubular glucose delivery causing a maladaptive increase in glucose reabsorption along with sodium via sodium-glucose cotransporter 2 (SGLT-2) in the proximal tube. Distal sodium chloride delivery to the macula densa is subsequently decreased, and perceived as low effective circulating volume by the juxtaglomerular apparatus, which causes vasodilation of the afferent renal arteriole, renal hyperperfusion and an increase in GFR (73). Figure 2 illustrates these proposed mechanisms.

Figure 2. Acute Hyperglycemia Increases GFR.

The figure illustrates the effect of hyperglycemia on glomerular filtration. Acute glycemia is associated with (1) increase glucose reabsorption at SGLT2 with decreased delivery of NaCl to macula densa and subsequent afferent arteriolar vasodilation, and (2) RAAS activation and efferent arteriolar vasoconstriction.

Despite these observations, the effect of blood glucose on renal function is generally not accounted for when measuring GFR in people with type 1 diabetes (65, 74–76). Therefore, failure to maintain euglycemia, or possibly account for hyperglycemia, could potentially result in differential misclassification and bias in measurement (and estimation) of GFR, thereby hindering the ability to determine early changes in GFR within an individual (46, 58, 77). Accounting for ambient blood glucose could improve intra-individual precision in GFR measurement, as well as changes in renal function over time in people diabetes.

New methods to evaluate GFR

Similar to clinical practice, a significant barrier in diabetic kidney research is a clinically easy and accurate method to measure GFR in adolescents and adults with diabetes (78). Improved methods should be less cumbersome and time consuming than current methods to measure GFR and provide more accurate and precise assessment of GFR than estimates from equations.

i. Beta-trace protein

Beta-trace protein (BTP), a low molecular weight protein, is a promising endogenous marker used to estimate GFR. It shares many of the features of cystatin C as a marker for GFR (79, 80). In contrast to cystatin C which is strongly positively charged, BTP is more isoelectric (85). Recent data support the use of BTP to estimate GFR in newborns (81), in children who have had a renal transplant and in pregnancy (82, 83). Equations have been developed and validated in children and adults. For example, Witzel et al recently presented sex-specific equations to estimate GFR with BTP in children, which demonstrated better accuracy estimating GFR than previous equations at GFR levels ≥60mL/min/1.73m² (84). To our knowledge these equations have not been validated in children or adults with diabetes.

ii. GFR measured by magnetic resonance imaging (MRI)

Blood-oxygen-level dependent functional MRI (BOLD-MRI) is a promising method to non-invasively assess renal function without contrast media, but recent data have been inconsistent. Inoue et al. demonstrated a relationship between BOLD-MRI values and eGFR in non-diabetic nephropathy, but these associations were not significant in diabetic nephropathy (85). Furthermore, recent data demonstrated the failure of BOLD-MRI to distinguish between patients with different stages of chronic kidney disease (86). Additional studies are needed to evaluate the utility of BOLD-MRI in diabetic nephropathy.

iii. GFR measured by iohexol clearance on dried blood spots

Recently, a practical method of measuring GFR by iohexol clearance using dried capillary blood spots (DBS) was developed in non-diabetic patients (87, 88). In 2006 Niculescu-Duvaz et al. demonstrated that iohexol clearance measured on dried blood spots (DBS) on filter paper provided GFR measurements comparable to the iohexol plasma clearance, but at a significantly reduced time and cost (87). This method is ideally suited for patients with type 1 diabetes who routinely prick their fingers to obtain glucose measurements. We recently demonstrated that GFR by iohexol clearance using dried capillary blood spots on filter paper measured GFR accurately in adults with type 1 diabetes (89). This method could be translated to screening for early kidney disease in people with type 1 diabetes (89). This method was piloted for feasibility in adolescents and adults with type 1 diabetes (89, 90). GFR measured in DBS was comparable to the gold standard method of GFR plasma iohexol and more accurate, precise and less biased than GFR estimated by CKD-EPI creatinine, CKD-EPI cystatin C and CKD-EPI both in adults with type 1 diabetes (89). Furthermore, GFR-DBS offers a more convenient approach to quantify GFR, as the bias in the GFR-DBS measurements (2 or 5-spots) compared to GFR plasma iohexol was minimal and very similar to that previously reported in non-diabetic subjects (− 1.17, 95% CI: − 16.12–13.78) (87, 88). In addition, in adolescents with type 1 diabetes, there appeared to be less variability of GFR calculated by iohexol clearance on DBS than the estimated GFR methods (Bouvet and Schwartz) (90), and using 2 spots at 120 and 240 minutes was comparable to using 5 spots (89). All of the adolescent participants also agreed or strongly agreed that the iohexol injection and DBS collection was preferable to an overnight urine sample (90).

Measuring GFR by iohexol clearance on DBS could be incorporated into current clinical research or annual screening tests by placement of a peripheral IV for blood sampling followed by injection of iohexol and removal of the IV prior to a regularly scheduled clinic visit. This would significantly reduce the time required for a standard iohexol GFR study from 4–5 hours. Self-collection of DBS could be performed as an outpatient, since finger-pricks are a common task for patients with type 1 diabetes, and the filter paper could then be mailed back to the lab (88, 90). The relative simplicity of the DBS method and better results compared to eGFR suggest that this or similar methodology may improve upon current practices used to assess GFR, which are either not feasible or effective in ascertaining early renal function loss clinically. Adapting this methodology to an out-patient setting by measuring iohexol clearance, as was also recently reported in a Kenyan population (91), to assess GFR in youth with type 1 diabetes requires further study to determine if it addresses the current need to better screen for early diabetic kidney disease. Given the current variability with estimation of GFR at levels >60 mL/min/1.73m², which encompasses the majority of patients with diabetes, particularly adolescents and young adults, better methods are required to fulfill the promise of reducing diabetic nephropathy by annual GFR screening in people with diabetes.

Therapies for diabetic nephropathy

While there is solid evidence showing benefit of glycemic and blood pressure control in preventing microvascular complications in type 1 diabetes (12, 92, 93), optimal control does not abolish the risk. Newer therapies, including sodium glucose co-transporter 2 (SGLT2) inhibitors and allopurinol hold promise as therapeutic targets to further prevent progression of diabetic nephropathy. The SGLT2 inhibitor, empagliflozin, was shown to reduce HbA1c and signficantly attenuate renal hyperfiltration in patients with uncomplicated type 1 diabetes and had no significant effect on GFR in those without hyperfiltration (73). This class of agents has also been shown to subacutely lower eGFR in large clinical trials by 5–10 mL/min/1.73m², a modest effect that likely reflects expected changes in afferent arteriole tone in response to natriuresis caused by this drug class, and which may be responsible for lowering albuminuria (94). An additional hypothesis that lowering serum uric acid with allopurinol will prevent GFR decline in people with type 1 diabetes is being tested in the multi-center double-blind randomized clinical trial “Preventing Early Renal Function Loss – PERL” (95). Improved methods to detect GFR changes would allow us to implement therapies at an earlier stage when renal injury may be reversible or at least more responsive to interventions that either slow or arrest the progression of disease.

Conclusion

A major challenge in preventing diabetic kidney disease relates to the accurate and early identification of high risk patients. The American Diabetes Association now recommends annual assessment of glomerular filtration rate (GFR) in adolescents, in addition to adults, with diabetes to screen for early diabetic nephropathy. Assessment of GFR is essential to accurately diagnose diabetic kidney disease early in the disease process. GFR is, however, difficult and impractical to measure directly with current methodologies. Unfortunately, GFR estimates using serum creatinine and/or cystatin C based equations are only accurate when GFR is <60 ml/min/1.73 m² (78), a point at which half of renal function may already be lost. Improved methods to measure or estimate GFR will lead to a better ability to accurately identify early changes in GFR and track GFR changes over time. One such method is GFR measured by iohexol clearance on DBS which offers promise as a more convenient approach to accurately quantify GFR in patients with diabetes in clinical practice and research.