Progressive renal decline as the major feature of diabetic nephropathy in type 1 diabetes
Despite almost universal implementation of renoprotective therapies over the past 25 years, the risk of end-stage renal disease (ESRD) in type 1 diabetes (T1D) is not decreasing, and ESRD remains the major cause of excess morbidity and premature mortality . Such a state of affairs prompts a call to action. In this review we re-evaluated the proteinuria-centric model of diabetic nephropathy and showed its deficiencies. On the basis of extensive studies that we have been conducting on the patients attending the Joslin Clinic, we propose that progressive renal decline, not abnormalities in urinary albumin excretion, should be considered as the major feature of disease processes leading to ESRD in T1D. The etiology of diabetic nephropathy should be reconsidered in light of our new findings so our perspective can be broadened regarding new therapeutic targets available for interrupting the progressive renal decline in T1D. Reduction in the loss of glomerular filtration rate, not reduction of albumin excretion rate, should become the measure for evaluating the effectiveness of new therapeutic interventions. We need new accurate methods for early diagnosis of patients at risk of progressive renal decline or, better still, for detecting in advance which patients will have rapid, moderate or minimal rate of progression to ESRD.
KeywordsType 1 diabetes Kidney complications Proteinuria Progressive renal decline
Since there is no animal model that mimics progressive diabetic nephropathy in humans, there is a great need to understand the etiology of this devastating complication through clinical, epidemiological and genetic studies.
Prof. Hirofumi Makino introducing Dr. Krolewski as the speaker at the 2013 JSN meeting.
Proteinuria-centric model of diabetic nephropathy
As long ago as 1836, Bright  postulated that proteinuria could reflect a serious renal disease specific to diabetes. Almost 100 years later Kimmelstiel and Wilson observed nodular glomerular intercapillary lesions in autopsy reports of long-standing patients with diabetes and heavy proteinuria which they considered to be morphological lesions specific to diabetic nephropathy . In the 1970s radioimmunoassay techniques were developed that permitted the quantitative measurement of the minutely elevated urinary albumin levels that distinguished microalbuminuria (MA) (typically albumin excretion rate [AER] between 30 and 299 μg/min), from the elevations of albumin detectable by urinary dipstick method that define proteinuria (typically AER ≥300 μg/min) . During the 1980s longitudinal studies were conducted in patients with type 1 diabetes (T1D) which used the new method of measuring urinary albumin. These studies found a 60–85 % risk of progression of MA to proteinuria/impaired renal function within 6–14 years of follow-up [5, 6, 7]. These findings together with the previous observations provided a foundation for the so-called proteinuria-centric model of the natural history of diabetic nephropathy.
This model developed in 1990s postulated that in diabetes an increase in urinary AER that reflects glomerular abnormalities precedes the development of impaired renal function and end-stage renal disease (ESRD). In this model, the onset of MA can be considered a manifestation of an initiating disease process that leads to proteinuria, and the latter is followed by glomerular filtration rate (GFR) loss that eventually results in ESRD . The sequential occurrence of the above stages has been referred to as progressive diabetic nephropathy.
Shortcomings of the proteinuria model
Clinical and epidemiological studies conducted during the past decade have shown that the development of elevated urinary excretion of albumin leading to proteinuria and GFR loss or renal decline are two separable manifestations of diabetic nephropathy, rather than two successive stages of one disease process. Abnormal urinary albumin excretion waxes and wanes (progresses and regresses), and renal decline is usually progressive and leads to ESRD. While the two manifestations can progress in parallel, changes in one are not well-correlated with changes in the other. As a result, some patients have abnormal urinary albumin excretion that progresses, regresses or simply persists, even though their renal function remains stable. On the other hand, renal decline is initiated in patients with normoalbuminuria (NA) or MA and it is progressive (we refer to it as progressive renal decline) regardless of the variation in urinary albumin excretion. Following is a summary of the above studies.
Frequent remission of microalbuminuria to normoalbuminuria
Reviewing and analyzing studies on the natural history of MA, Caramori et al.  noticed a frequent remission of MA to NA. However, it remained uncertain whether such remissions occurred simply because of short-term changes in urinary albumin excretion or it was a biological process which takes several or more years [9, 10]. We investigated this issue in the First Joslin Study of the Natural History of Microalbuminuria. In that study, 386 patients with persistent MA were observed for the occurrence of remission to NA during a 6-year follow-up . Analysis of the trends in urinary AER revealed that values of albumin excretion during repeated measurements were not random—rather, a clear pattern of remission over several years was observed. This remission was independent from treatment with angiotensin-converting-enzyme (ACE) inhibitors. Our findings proved that remission of MA was a real biological phenomenon and not a consequence of short-term random changes in urinary albumin excretion. In the first Joslin study, the 6-year cumulative incidence of remission to NA was remarkably high (cumulative incidence 59 %; 95 CI 54–64 %) . In a large proportion of patients this remission to NA persisted for ≥4 years .
Frequency of microalbuminuria remission and progression in three recent observational studies
Study and reference
Number of patients with microalbuminuria
Cumulative incidence of remission to normoalbuminuria
Cumulative incidence of progression to proteinuria
First Joslin Study (2003) 
59 % (54–64)
27 % (22–32)a
EURODIAB (2005) 
DCCT/EDIC (2011) 
40 % (36–48)b
28 % (23–33)b
Infrequent progression of microalbuminuria to proteinuria
Further support for the concept that MA is a functional abnormality, rather than a critical step in the disease process leading to ESRD is its infrequent progression to proteinuria. Rather than being in the range of 60–85 % as originally reported [5, 6, 7], studies published in the 1990s showed 10-year cumulative risks of progression to proteinuria in the range of 25–30 % [9, 14, 15]. In the first Joslin study the cumulative risk of progression from MA to proteinuria during 6 and 12 years of follow-up was 15 and 27 %, respectively (see Table 1) [12, 16].
Multiple clinical trials demonstrated the effectiveness of ACE inhibitors both in reducing urinary albumin excretion and in delaying the progression of MA to overt proteinuria [17, 18, 19, 20, 21, 22]. However, those effects were small and not all studies showed them . The question arises whether the introduction of the renoprotective drugs during the 1990s into the care of patients with diabetes might have changed the natural history of MA and could account for the strikingly different results obtained in the three landmark studies from the 1980s which included a total of 30 patients [5, 6, 7] and the more contemporary studies that comprised over a thousand MA patients [11, 12, 13]. Interestingly, in the first Joslin study only a limited number of patients with MA were treated with ACE inhibitors and the effect of these drugs had minimal or no impact on frequency of remission of MA to NA or its progression to proteinuria [11, 16].
Progressive renal decline in patients with normo- and microalbuminuria
Characteristics of the study groups included in the Second Joslin Study of the Natural History of Microalbuminuria in T1D (data adapted from Ref. )
N = 286
N = 248
Duration of diabetes mellitus (years)
20 (14, 29)
24 (15, 30)
41 (30, 48)
42 (34, 49)
HbA1c in %
8.0 (7.4, 8.8)
8.3 (7.5, 9.3)
Systolic blood pressure
118 (110, 127)
122 (114, 130)
ACE and ARBs Rx
16 (12, 22)
65 (44, 116)
Baseline serum markers
Uric acid (mg/dL)
4.2 (3.7, 5.0)
4.9 (4.2, 5.9)
1300 (1094, 1516)
1536 (1291, 1870)
2073 (1717, 2525)
2374 (1997, 2988)
Baseline renal function
Serum cystatin C (mg/L)
0.65 (0.58, 0.72)
0.66 (0.60, 0.78)
Serum creatinine (mg/dL)
0.76 (0.65, 0.86)
0.79 (0.69, 0.90)
eGFRcr-cys (ml/min/1.73 m2)
113 (102, 123)
112 (96, 122)
Duration of follow-up (years)
8.0 (6.0, 8.7)
7.9 (5.5, 9.2)
No. of serum samples
5 (4, 7)
7 (5, 9)
eGFRcr-cys loss (%/year)
−1.5 (−2.4, −0.8)
−2.2 (−4.1, −1.2)
Renal decline (eGFRcr-cys loss ≥3.3 %/year)
10 % (28 decliners)
35 % (86 decliners)
8-year cumulative risk of CKD ≥3
In this study, 24 (30 %) patients developed progressive renal decline (defined as eGFRcys loss ≥3.3 % per year). Their trajectories are shown in Fig. 2a . Renal decline was present at the time or soon after development of MA and the significant rate of eGFRcys loss continued to be constant during the subsequent follow-up. Similar to decliners with NA (Fig. 1), the decline within individuals in this group of decliners was linear and could be well represented by a simple regression slope. Furthermore, the rates of eGFR loss per year varied widely among individuals. Within 10 years of follow-up, almost half (10 patients) reached CKD stage ≥3 and in 5 patients the eGFRcys decline was so rapid that they progressed to ESRD. The rest of the decliners will most likely reach CKD stage 3 during the next 10 years of follow-up, assuming their trajectories of eGFR decline remain linear. For comparison, Fig. 2b shows eGFRcys trajectories in non-decliners. Most of the trajectories were linear and horizontal. A few patients had variation in eGFRcys over time but renal function at the end of follow-up was the same as at baseline.
It is interesting that the distribution of AER abnormalities during the 2-year interval when new-onset MA occurred was not different among patients who subsequently had renal decline and those in whom renal function remained stable . During follow-up, one can see un-coupling of changes in AER and changes in eGFRcys. Only half of the decliners developed proteinuria. In contrast, among non-decliners half had either persistent MA or progressed to proteinuria.
Progressive renal decline in patients with proteinuria
Progressive renal decline as the major feature of diabetic nephropathy
The data presented in Figs. 1, 2 and 3 unequivocally demonstrated that progressive renal decline is the primary manifestation of diabetic nephropathy and best represents the disease process underlying the development of ESRD in T1D. These observations do not support the proteinuria-centric model of diabetic nephropathy in which renal decline is a late consequence of proteinuria .
Mechanisms of progressive renal decline
Presently, the putative mechanisms underlying progressive renal decline in T1D are not known. To advance our understanding of these mechanisms and taking into account the salient features of progressive renal decline, several questions must be answered. First, we need to know in which kidney compartment/tissue/cells the disease process that underlies progressive renal decline seen in patients with NA or MA (see Figs. 1, 2a) is initiated. Theoretically, this process may take place in glomerula, tubules, interstitium, or in vasculature. Second, the nature of the putative mechanisms that are responsible for the progressive GFR loss is unclear. It is possible that early GFR loss (in the range of normal renal function) is due to some (yet unknown) functional changes and the late GFR loss (CKD stage 3–5) is due to morphological lesions in some putative kidney compartments/tissues/cells. However, the rates of GFR loss during the early and late phases of progressive renal decline are similar. This suggests that the mechanisms may also be similar. Third, since trajectories of GFR loss over time seems to be linear (stable) within individuals but variable among individuals, one may postulate a role of genetic factors as determinants of progressive renal decline . A search for these factors may unravel pathways involved in the etiology of progressive renal decline.
Lack of an animal model that would mimic progressive renal decline in human diabetes and the lack of kidney biopsy specimens leave us with clinical and epidemiological studies to investigate the above questions. Identifying systemic risk factors, genetic markers or biomarkers specifically associated with risk of progressive renal decline should help us understand the mechanisms of progressive renal decline in T1D.
Systemic factors and serum markers and progressive renal decline
The risk of renal decline according to quartiles of baseline AER (top graph in panel a) was flat (around 10 %) across quartiles in the NA group. In MA, the risk of renal decline was significantly higher than in NA and increased from 23 % in the lowest quartile to 55 % in the highest. For HbA1c, the increase risk was moderate in the NA group but strong in the MA group (panel a). The risk of decline increased with age in both groups (panel a) and increased similarly with duration of T1D because of its co-linearity with age (data not shown). Risk of decline also increased with systolic blood pressure in both groups (panel a) and increased as the number of prescribed reno-protecting treatments increased (panel b).
Plots of the risk of renal decline according to three serum markers are shown in panel b. In both study groups, elevated serum uric acid increased the risk of renal decline, and the effect of increasing serum tumor necrosis factor receptor 1 (TNFR1) or TNFR2 was even more striking. The effects of both TNFRs were very similar and the information in them redundant. The independent effects of all of these variables on risk of renal decline were confirmed in multiple logistic analyses. We did not find any association between risk of progressive renal decline in either study group and baseline serum levels of other markers such as TNFα (free), interleukin (IL)-6, IL-8, interferon inducible protein-10 (IP-10), monocyte chemoattractant protein 1 (MCP-1), vascular cell adhesion molecule (VCAM), intercellular adhesion molecule (ICAM), Fas and FasL .
Recognizing that multiple clinical factors and serum markers contribute in a similar way to renal decline in NA and MA strengthens the hypothesis that progressive renal decline is the primary clinical abnormality of diabetic nephropathy. Although the exact mechanisms through which these factors contribute to early progressive renal decline are not clear at present, we discussed some mechanisms with regard to the three serum markers.
Elevated serum uric acid has pro-inflammatory properties and may act as either a pro-oxidant or anti-oxidant molecule depending on the circumstances . In vivo, rats rendered hyperuricemic by means of a uricase inhibitor develop an afferent arteriolopathy that decreases luminal diameter and produces renal ischemia, leading to glomerulosclerosis and tubulointerstitial fibrosis . Similar histological changes occur in humans with gouty nephropathy . Lowering serum uric acid concentration with allopurinol attenuates these histological and functional changes, although this effect may be due in part to reduced oxidative stress resulting from xanthine oxidase inhibition . It is intriguing to postulate that lowering serum uric acid in patients at risk of renal decline may be an effective intervention to reduce risk of renal decline in T1D . Preparations for such a clinical trial are underway .
Our previous studies described the strong effect of serum concentrations of TNFR1 or TNFR2 on the risk of advanced stages of renal decline such as CKD stage 3 or ESRD [36, 37]. The recent study in NA and MA extends demonstration of their effects to the onset of the process of renal decline itself . We do not know how elevated concentrations of TNFRs may initiate renal decline and lead to renal failure. However, we excluded some hypotheses. For example we showed that serum TNFα is not involved directly or indirectly, through regulation of serum TNFRs, in the development of renal decline. Furthermore, we showed that serum concentration of several chemokines and circulating adhesion molecules (IL-8, IP-10, MCP-1, VCAM, ICAM as potential downstream effectors of TNFRs) were not associated with renal decline either . An intriguing finding of the present study is the negative interaction between serum uric acid and TNFR1 on the risk of renal decline in both NA and MA, meaning that the risk of renal decline for patients with elevated serum uric acid and serum TNFR1 is less than the sum of the individual risks associated with the two predictors. This suggests that the predisposing effects of serum uric acid and TNFR1 converge on some common pathway that cannot be further activated by one factor if it has already been turned on by the other. The nature of this putative pathway is unknown at this time.
Urinary markers of inflammation and progressive renal decline
Although glomerulopathy has been assumed to be the major contributor to the pathogenesis of diabetic nephropathy [8, 38], a growing body of evidence suggests that tubulointerstitial injury mediated through an inflammatory process may also contribute to the development of diabetic nephropathy and particularly to progressive renal decline . In 1991, Bohle et al.  were the first to draw attention to the presence of tubulointerstitial injury in the human diabetic kidney and its strong association with renal failure. Based on a large collection of renal biopsies from humans with diabetic nephropathy, they demonstrated the presence of infiltrates of monocytes, macrophages and T cells in the interstitium similar to those seen in chronic glomerulonephritides. Several subsequent kidney biopsy studies showed cross-sectional associations between severity of diabetic nephropathy measured as GFR and the presence of specific inflammatory markers [41, 42, 43, 44].
N = 74
N = 43
N = 28
Concentrations adjusted for urinary creatinine in pg/mg creatinine
0.9 (0.3, 2.0)
1.1 (0.4, 1.8)
1.6 (0.6, 15)
1.0 (0.3, 4.9)
0.8 (0.1, 3.9)
15 (3.1, 79)
5.1 (3.1, 60)
5.3 (2.6, 66)
49 (6.9, 228)
49 (25, 90)
59 (32, 89)
95 (55, 198)
50 (16, 97)
48 (10, 91)
80 (48, 155)
In conclusion, urinary concentrations of inflammatory markers IL-6, IL-8, MCP-1, IP-10 and MIP-1δ are elevated in patients with MA who are at risk of progressive renal decline. Our results are consistent with previous work in experimental models and observational studies in humans that implicated inflammation in the development and progression of renal injury in diabetes [46, 47, 48]. However, we refined the characterization of its role in humans with T1D by demonstrating that elevated levels of markers of low level inflammation in urine are not associated with MA per se but are specific for early progressive renal decline .
None of the covariates available in this study such as age, duration of diabetes, glycemic control, urinary albumin excretion, and treatment with ACE inhibitors accounted for the associations. Therefore, the nature of the factors determining the elevated concentrations of urinary pro-inflammatory chemokines and cytokine in T1D remains unknown.
An explanation for the findings reported by Wolkow et al.  is that kidney cells, primarily tubular, are the source of the elevated urinary concentrations of these markers. Although, the nature of the stimulus to synthesize these chemokines in tubular cells is unknown, it might originate from the glomerular filtrate. We hypothesize that impairment of the glomerular filtration barrier (evidenced by the presence of MA) permits injurious serum proteins or growth factors to leak into the urinary space. These putative factors, which we refer to as toxic urinary proteins (txUPs), may stimulate proximal tubular cells to secrete chemokines/cytokines and other stress proteins indicating tubular damage that leads to tubular atrophy, interstitial fibrosis and early GFR loss. Recently it was demonstrated in animal studies that tubular damage initiates a disease process that leads to inflammation, loss of blood vessels, interstitial fibrosis and glomerulosclerosis .
Toxic urinary proteins and renal decline
Recently Wanic et al.  tested the above hypothesis. Archived baseline urine specimens from patients described in Fig. 2 were used. Urine specimens from five decliners (Fig. 2a) and five non-decliners (Fig. 2b) were pooled and used in in vitro experiments. Human proximal tubular cells (HK-2 cells) were grown in serum-free medium enriched with pooled urines from decliners or non-decliners. Genome-wide expression profiles were determined in extracted mRNA from the two sets of HK-2 cells. We found that pooled urine from decliners induced differential expression of 312 genes. There were 119 up-regulated genes. Their biological processes were enriched for defense response, responses to other organisms, regulation of cellular processes, or response to stress or stimulus, and programmed cell death. There were 195 down-regulated genes. They were disproportionately represented in biological processes for regulation of metabolic processes, nucleic acid metabolic processes, cellular response to stress and macromolecule biosynthesis.
Progressive renal decline: how to diagnose it?
An important message conveyed by Fig. 5 is that the majority of patients with NA and a large proportion of those with MA and proteinuria will never develop ESRD. They have elevated risk of death unrelated to ESRD, but its excess risk is only one-tenth of the excess risk of death seen among those who develop ESRD . On the other hand, among those with renal decline the rate of GFR loss varies widely (Figs. 1, 2, 3, 4). Therefore, physicians face not only the challenge of distinguishing patients who will remain with stable renal function for their lifetime from patients who will have progressive renal decline, but also the challenge within the latter group of identifying rapid, moderate and slow decliners and estimating the time to onset of ESRD (examples in Fig. 3a, b).
Several legacy markers are used to diagnose diabetic nephropathy in T1D, including measurements of levels of hemoglobin A1C (HbA1c, exposure), concentration of urinary albumin excretion (supposedly early disease process) and concentration of serum creatinine (late disease process). The last two markers used cross-sectionally (during one patient visit) indicate presence/absence or extent of diabetic nephropathy. When these markers are used in prospective epidemiological studies, they quantify risk of progression to ESRD or risk of deaths. However, as discussed earlier their utility to predict these outcomes in individual patients is limited. They have some sensitivity to diagnose patients at risk but they are hopelessly unspecific to predict future renal decline and progression to ESRD. The usage of legacy markers will continue until new, more specific markers are discovered and introduced to the clinical practice.
During the last several years, intensive research has been underway to find new markers to more reliably diagnose patients at risk of renal decline and progression to ESRD. Serum concentration of cystatin C emerged as a candidate diagnostic marker that might be a more accurate indicator of impaired renal function than serum creatinine. Only recently we have shown that one determination of serum cystatin C in patients with diabetes and proteinuria provides better risk stratification of subsequent ESRD than determination of serum creatinine obtained at the same time .
Just recently, we showed that serum concentrations of TNFR 1 or TNFR2 are good predictors of future development of CKD stage ≥3 in T1D patients . We reported similar findings regarding the relationship between circulating TNFRs and risk of ESRD during 12 years of follow-up in patients with T2D .
Progressive renal decline and considerations for therapeutic trials
New effective therapies are desperately needed to reduce the risk of ESRD in T1D as discussed in the recent issue of Seminars in Nephrology . In designing therapies for T1D it is important to put aside the previous proteinuria-centric model of diabetic nephropathy and fully appreciate the features of progressive renal decline. We discuss several implications of this switch below.
First, the wide variation in rates of renal decline (between −50 and −5 ml/min/1.73 m2/year) illustrated in Fig. 4 may be determined by multiple mechanisms, which may be identified with the help of modern genetics, proteomics, and metabolomics platforms. Prediction of the rate of progression will not only help in stratification of patients according to risk of ESRD but will also direct development/selection of specific therapies to prevent or delay the onset of ESRD. Such personalized approaches are being developed in other fields [54, 55, 56].
Second, patients with the fastest renal decline (example in Fig. 3a), referred to as rapid progressors, may be suitable for more aggressive therapies that have received little consideration so far. The ability to recognize their imminent risk of ESRD and high post-ESRD mortality could justify taking strong measures such as pancreas transplant , pre-emptive kidney transplant , cellular therapies  or aggressive new pharmacological therapies. The latter approach has been practiced in cancer therapies.
Third, the effectiveness of new therapies against progressive renal decline cannot be evaluated in clinical trials that use changes in urinary albumin excretion as an outcome. A more reliable outcome measure is a change in the rate of renal decline or postponement of the time to events such as CKD stage 3, doubling of serum creatinine or ESRD. The efficiency of a study design based on either of the latter outcomes is significantly reduced (and cost significantly increased) by including patients who are non-decliners or have a slow rate of renal decline. Recruitment of non-decliners or slow decliners like the patients in Fig. 3c would be counterproductive despite their having proteinuria, hypertension or impaired renal function. This shows the importance of having markers/algorithms to determine, on the basis of one or few baseline measurements, which patients are decliners (rapid, moderate, or slow) and which are non-decliners. At this time, measurements of circulating levels of TNFR1 or TNFR2 seem to be the best markers to achieve such a goal [36, 37]. However, to increase the accuracy of prediction, baseline TNFR1 or TNFR2 needs to be combined with baseline levels of AER and eGFR.
This study was supported by the following grants: NIH grants DK-41526 and DK676381 and JDRF grants 1-2008-1018 and 17-2013-8 to A.S. Krolewski; and Diabetes Research Center—Joslin, Pilot and Feasibility Grant, P30DK036836 to M.A. Niewczas.
Conflict of interest
The authors have declared that no conflict of interest exists.
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