A practical method to measure GFR in people with type 1 diabetes
Introduction
Although effective treatment exists to prevent or slow decline in renal function (de Boer, Sun, et al., 2011, Marshall, 2012), diabetic kidney disease continues to cause morbidity and mortality in type 1 diabetes (de Boer, Rue, et al., 2011, Maahs and Rewers, 2006, Rosolowsky et al., 2011). Improved early diagnostic methods are needed to better identify those at risk to progress to diabetic nephropathy (Cherney and Maahs, 2013, Maahs, 2012). One barrier in renal research is a clinically easy and accurate method to assess glomerular filtration rate (GFR), especially when GFR is > 60 ml/min/1.73 m2 (Hsu, Chertow, & Curhan, 2002) and estimating equations are inaccurate (Stevens, Coresh, Greene, & Levey, 2006). A recent DCCT-EDIC paper states that changes in eGFR over a clinically relevant period may not reflect changes in measured GFR (de Boer et al., 2014). Improved methods should be less cumbersome than current methods to measure GFR and provide more accurate and precise assessment of GFR than estimates from equations (eGFR), especially when GFR is > 60 ml/min/1.73 m2. Ideally, such a method could be applied to detect early change in GFR when therapeutic intervention could have the greatest impact (Bjornstad, Cherney and Maahs, 2014, Maahs et al., 2013).
Multiple factors can influence GFR measurements. In people with type 1 diabetes, an additional challenge in measuring GFR is the acute effect of blood glucose. Hyperglycemia is known to affect renal hemodynamics and increase GFR by up to 20 ml/min/1.73 m2 (Cherney et al., 2010, Christiansen et al., 1981, De et al., 1993, Dullaart et al., 1990, Jones et al., 1992, Skott et al., 1991, Wiseman et al., 1985, Wiseman et al., 1987). However, the effect of blood glucose is not generally accounted for when measuring GFR in people with type 1 diabetes (Amin et al., 2005, Caramori et al., 1999, Chiarelli et al., 1995, Dahlquist et al., 2001, Lervang et al., 1988, Lervang et al., 1992, Magee et al., 2009, Mogensen, 1986, Steinke et al., 2005, Yip et al., 1996, Zerbini et al., 2006). Potentially, failure to maintain euglycemia, or possibly account for hyperglycemia, could result in differential misclassification and bias in measurement (and estimation) of GFR hindering the ability to determine early changes in GFR within an individual (Bjornstad, McQueen, et al., 2014, Cherney and Maahs, 2013, Maahs, 2012).
In this study, we adapt a simple approach to measure GFR, requiring an injection of iohexol with samples obtained by finger prick (Mafham et al., 2007, Niculescu-Duvaz et al., 2006). We compare measures of GFR by iohexol clearance using dried blood spots (DBS) on filter paper to plasma (gold-standard) in adults with type 1 diabetes. We hypothesized that GFR measured by iohexol clearance using DBS would be comparable to plasma and superior to GFR estimated by serum creatinine and cystatin C based GFR equations (eGFR) (Inker et al., 2012). Second, we hypothesized that accounting for hyperglycemia would improve precision and accuracy of GFR measurement (when compared to GFR measured during euglycemia) by iohexol clearance in plasma and DBS and as estimated by the CKD-EPI equations.
Section snippets
Materials and methods
Inclusion criteria were age 18–60 years, provider diagnosis of type 1 diabetes, ability to fast for the study and follow dietary advice. Exclusion criteria were non type 1 diabetes, a history of eGFR < 60 ml/min/1.73 m2 or microalbuminuria or greater, allergies to seafood or iodine, hypertension (defined as use of BP lowering medications [including renin angiotensin aldosterone system blockers] or BP > 130/80 mmHg), smoking, and caffeine intake < 8 h prior to study. Fifteen participants completed two
Results
Characteristics of participants were as follows: age 29 ± 12 years, 53% male, 93% non-Hispanic White, diabetes duration 19 ± 9 years, HbA1c = 7.6 ± 1.8%, BP = 116/73 mmHg, ACR 52 ± 85 mg/g. Blood glucose was similarly stabilized during the first 3 h of the study (Supplemental Fig. 1, 8 AM–11 AM) for V1 compared to V2 (median and IQR: 97 (85–130 mg/dl) v. 97 (82–120 mg/dl), p = 0.35) and hours 1 through 3 (Supplemental Fig. 1, 9 AM–11 AM, 92 [79–118 mg/dl] v. 90 [76–109 mg/dl], p = 0.27). In contrast, blood glucose was
Discussion
GFR measured in DBS is comparable to the gold standard method of GFR plasma iohexol and more accurate, precise and less biased than eGFR measures. A major barrier in diabetic kidney disease research is a clinically easy means to accurately and precisely assess GFR, especially when GFR is > 60 ml/min/1.73 m2 and estimating equations are inaccurate (Stevens et al., 2006). By that point half of renal function may already be lost (Maahs, 2012). GFR-DBS offers a more convenient approach to quantify GFR
Author contributions
DMM researched, wrote, contributed to discussion, and reviewed/edited the manuscript; LB researched, contributed to discussion, and reviewed/edited the manuscript; BK researched, contributed to discussion, and reviewed/edited the manuscript; SE researched, contributed to discussion, and reviewed/edited the manuscript; LP researched, contributed to discussion, and reviewed/edited the manuscript; KM researched, contributed to discussion, and reviewed/edited the manuscript; AB researched,
Acknowledgments
Support for this study was provided by an Innovative Grant from the Juvenile Diabetes Research Foundation5-2013-122.
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Determination of iohexol by capillary blood microsampling and UHPLC-MS/MS
2019, Journal of Pharmaceutical AnalysisCitation Excerpt :DBS has been used successfully for GFR calculations using IOH [12]. Good results in terms of the agreement between GFR values calculated using blood spots and GFRs based on venous classical sampling techniques were obtained [13,14]. VAMS consists of a porous hydrophilic tip, capable of collecting small and reproducible amounts of blood (10, 20 or 30 μL).
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2018, Journal of Diabetes and its ComplicationsCitation Excerpt :Eleven subjects completed the study and an additional 5 refused dilation and were therefore excluded from participation in the study. Data were collected as part of a study in which the primary objective was investigating a novel method to determine glomerular filtration rate by measurement of plasma iohexol clearance.18 No formal power calculation for sample size was performed and these pilot data therefore should be considered hypothesis generating.
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2018, Advances in Chronic Kidney DiseaseCitation Excerpt :Another potential limitation is the reliance of accurate recording of time of DBS collection by patients. While all patients wrote down the time of the DBS collection and the concurrent blood glucose values in our local studies, these data were recorded at home and therefore not validated.9,10 Based on our questionnaire, the majority of youth with T1D agreed that the instructions for home testing were easy to understand and preferable to overnight urine collection.10
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2017, Diabetes Research and Clinical PracticeCitation Excerpt :Moreover, cystatin C based eGFR was superior to creatinine based eGFR, in detecting these changes, suggesting that GFR estimated by cystatin C may be preferable in diabetic persons [33]. Subsequently, Maahs et al. demonstrated that correction for eGFR using simultaneous glucose and cystatin C measures significantly improved the accuracy and precision of cystatin C based eGFR methods [34]. Measured GFR was not performed in the SEARCH study and so we cannot conclude whether the association of fasting glucose and cystatin C in T1D was due to differences in GFR.
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2017, Journal of Diabetes and its ComplicationsCitation Excerpt :The cut-off is important to distinguish it from slow changes in GFR associated with aging, and beyond the range of noise expected when estimating GFR (Krolewski et al., 2014). Rapid GFR decline has been shown to precede the onset of microalbuminuria in type 1 diabetes (Bjornstad, Snell-Bergeon, Nadeau, & Maahs, 2015), and predict end-stage renal disease and cardiovascular outcomes (Maahs et al., 2014; Orchard et al., 2010). The mechanisms that initiate renal GFR decline in type 1 diabetes remain controversial, but likely include both renal arteriolar and glomerular functional and structural effects due to hyperglycemia, hypertension, dyslipidemia and smoking.
Disclosure: The authors have no conflicts of interest to disclose.