Fast renal decline to end-stage renal disease: an unrecognized feature of nephropathy in diabetes

Abstract

A new model of diabetic nephropathy in type 1 diabetes emerged from our studies of Joslin Clinic patients. The dominant feature is progressive renal decline, not albuminuria. This decline is a unidirectional process commencing while patients have normal renal function and, in the majority, progressing steadily (linearly) to end-stage renal disease (ESRD). While an individual's rate of renal decline is constant, the estimated glomerular filtration rate (eGFR) slope varies widely among individuals from -72 to -3.0 ml/min/year. Kidney Disease: Improving Global Outcomes guidelines define rapid progression as rate of eGFR declines > 5 ml/min/year, a value exceeded by 80% of patients in Joslin's type 1 diabetes ESRD cohort. The extraordinary range of slopes within the rapid progression category prompted us to partition it into "very fast," "fast" and "moderate" decline. We showed, for the first time, that very fast and fast decline from normal eGFR to ESRD within 2 to 10 years constitutes 50% of the Joslin cohort. In this review we present data about frequency of fast decliners in both diabetes types, survey some mechanisms underlying fast renal decline, discuss methods of identifying patients at risk and comment on the need for effective therapeutic interventions. Whether the initiating mechanism of fast renal decline affects glomerulus, tubule, interstitium or vasculature is unknown. Since no animal model mimics progressive renal decline, studies in humans are needed. Prospective studies searching for markers predictive of the rate of renal decline yield findings that may make detection of fast decliners feasible. Identifying such patients will be the foundation for developing effective individualized methods to prevent or delay onset of ESRD in diabetes.

Keywords: chronic kidney disease; diabetic nephropathy; end-stage renal disease; renal decline.

Figure 1

Number of new cases of ESRD in the white US population attributed to diabetes between 1990–2006 according to age of onset of ESRD. In these patients, T1DM is the predominant diabetes and the almost exclusive type in those with sufficient diabetes duration to develop diabetes-associated ESRD. The data were obtained from the US Renal Data System (http://www.usrds.org/). Figure adapted from Rosolowsky et al. JASN 2012. Using data presented in Table 1, one may interpret that patients with ESRD onset between aged 20–39 years were enriched for fast decliners and those 40–49 years for moderate and slow decliners.

Figure 2

Examples and frequencies of trajectories of eGFR decline in the Joslin ESRD cohort, classified as linear or non-linear by a linear spline approach. Trajectories were classified by comparing linear (solid gray line) and spline (solid black line) regression models. Dots represent eGFR observations, horizontal gridlines are boundaries of CKD stages, and vertical interrupted line indicates onset of ESRD. Grey area distinguishes late from early progressive renal decline. Figure adapted from Skupien et al. Diabetes Care 2016.

Figure 3

Distribution of eGFR slopes in 364 patients in the Joslin ESRD cohort Panel A: Histogram of the distribution of slopes of eGFR; insert – a trajectory of renal decline in a patient with the steepest slope(indicated with the arrow). Panel B: Proposed categories for the slopes in Panel A Re-analyzed data from Skupien et al. Diabete Care 2016.

Figure 4

eGFR trajectories in T1D patients with normoalbuminuria who developed progressive renal decline during 6–10 years of follow-up, plotted according to whether baseline eGFR was above (Panel A) or below (Panel B) the median (105 mL/min). Onset of early progressive renal decline was observed only in patients with eGFR above 105 mL/min. Lines in red indicate patients with very fast renal decline. Proteinuria developed in them after the onset of early renal decline. Microalbuminuria developed in half of the decliners in both panels by the end of follow-up. Adapted from Krolewski et al. Diabetes Care 2014.

Figure 5

Cumulative risk of ESRD during 10 year follow-up in the two Joslin cohorts with chronic kidney disease according to value of multi-marker criterion at entry into the follow-up. The following markers at baseline were considered: ACR, eGFR, TNFR1 and TNFR2 to develop the multi-marker criterion to identify patients (fast decliners) at risk of ESRD during the first 3 year of follow-up using data from T1D cohort. The performance of the criterion was replicated in the data from T2D cohort. Positive criterion: at baseline serum TNFR1 >4.3 ng/ml disregarding the other markers, or serum TNFR1 between 2.9 and 4.3 ng/ml and ACR >1.9 g albumin/g creatinine in urine. Negative criterion: at baseline serum TNFR1 <4.3 ng/ml and ACR <1.9 g/albumin/1 g creatinine in urine, or serum TNFR1 <2.9 ng/ml disregarding values of other markers. It was extraordinary that the multi-marker criterion that was developed in the T1D cohort produced almost identical stratification according to ESRD risk in T2D cohort. The T2D cohort had very different clinical characteristics than the T1D cohort. Re-analyzed data from Yamanouchi M et al. Kidney Int 2016 (under review).

Figure 6

Schematic representation of eGFR trajectories in fast decliners and their modifications in response to different interventions to reduce the rate of decline and postpone the risk of ESRD. Intervention with a treatment that effectively reduces the rate of decline will postpone the onset of ESRD by a longer interval depending on how soon after the onset of decline the intervention occurs (dashed red and blue lines). Evidence of an effective treatment may not be visible until after a lag interval (as described by Skupien et al. JASN 2014). That effect will not be realized, however, if the treatment is initiated too late (dotted red and blue lines). In moderate and slow decliners, the effects of the treatments illustrated above, will be more pronounced. An immediate treatment effect (straight lines) would result in a greater delay in ESRD, and a lagged treatment effect (curves) would result in a higher residual eGFR. However, demonstrating these effects would require clinical trials longer than 3 years and different definition of end-point measures, e.g. deceleration of eGFR slopes or other more sensitive surrogates.