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Review

Proteinuric and Non-Proteinuric Diabetic Kidney Disease: Different Presentations of the Same Disease?

by
Larissa Fabre
1,2,†,
Juliana Figueredo Pedregosa-Miguel
1,† and
Érika Bevilaqua Rangel
1,3,*
1
Nephrology Division, Department of Medicine, Universidade Federal de São Paulo, Borges Lagoa Street, 783, 6th Floor, Vila Clementino, São Paulo 04038-031, SP, Brazil
2
Hospital Regional Hans Dieter Schmidt, Xavier Arp Street, Boa Vista, Joinville 89227-607, SC, Brazil
3
Albert Einstein Research and Education Institute, Hospital Israelita Albert Einstein, Rua Comendador Elias Jafet, 755, Morumbi, São Paulo 05653-000, SP, Brazil
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Diabetology 2024, 5(4), 389-405; https://doi.org/10.3390/diabetology5040030
Submission received: 29 June 2024 / Revised: 25 August 2024 / Accepted: 27 August 2024 / Published: 2 September 2024
Browse Figures
Review Reports Versions Notes

Abstract

:
Background: Diabetic kidney disease (DKD) is a leading cause of end-stage kidney disease (ESKD) worldwide. This review examines the potential differences in clinical presentation, outcomes, and management between individuals with proteinuric DKD (P-DKD) and non-proteinuric DKD (NP-DKD). Methods: We analyzed articles published globally from 2000 and 2024. Results: Individuals with NP-DKD generally have lower blood pressure levels and a more favorable lipid profile. In contrast, histological studies show that P-DKD is associated with more severe glomerulosclerosis, mesangial expansion, arteriolar hyalinosis, interstitial-fibrosis/tubular atrophy, and immune complex deposits. Additionally, those with P-DKD are more likely to develop diabetic retinopathy and have a higher risk of all-cause mortality and progression to ESKD. Strategies to slow DKD progression, applicable to both NP-DKD and P-DKD, include non-pharmacologic and pharmacologic interventions such as renin–angiotensin system blockers, sodium-glucose co-transporter-2 inhibitors, finerenone, and glucagon-like protein receptor agonists. Conclusions: NP-DKD and P-DKD represent different presentations of the same underlying disease.

1. Introduction

Diabetic kidney disease (DKD) accounts for nearly half of all chronic kidney disease (CKD) cases [1] and is the leading cause of end-stage renal disease (ESKD) in the general population [2].
DKD is classified into stages based on the progression of albuminuria and the decline in the estimated glomerular filtration rate (eGFR) [3]. Clinically, it is characterized by persistent albuminuria and/or reduced renal function, confirmed by two measurements taken at least three months apart [4]. DKD can be further categorized into proteinuric DKD (P-DKD) and non-proteinuric DKD (NP-DKD), with albumin being the primary protein found in the urine of diabetic patients. Non-proteinuric DKD (NP-DKD) is defined by an eGFR of less than 60 mL/min/1.73 m2 and a urinary albumin–creatinine ratio (UACR) below 300 mg/g [5], or more recently below 30 mg/g [3].
Under normal circumstances, only a small amount of albumin passes through the glomerular filtration barrier, and most of this is reabsorbed by the proximal renal tubular cells. Therefore, albuminuria is commonly associated with kidney diseases that affect the glomerulus or proximal tubule [6].
Following glomerular filtration, an excess of protein in the proximal tubule surpasses its capacity to reabsorb albumin through endocytosis after binding by the megalin–cubilin receptor complex [6].
Albuminuria is a well-established risk factor for the progression of DKD [7], although it has limitations, such as the potential for spontaneous regression [8]. In addition to being a marker of kidney disease severity, albuminuria has a direct toxic effect on the kidneys. It contributes to cellular apoptosis, senescence, overproduction of reactive oxygen species, endoplasmic reticulum stress, and epithelial-mesenchymal transition in proximal renal tubular epithelial cells, leading to an unfolded protein response and DNA damage response [9]. Moreover, excessive albumin levels increase the expression of cell cycle arrest inducers p21 and p16, reduce the level of the cellular proliferation marker Ki-67, and raise the level of the cellular senescence marker β-galactosidase [9].
This review aims to determine if there are clinical, outcome and management differences between individuals with proteinuric DKD (P-DKD) and those with non-proteinuric DKD (NP-DKD).

2. Materials and Methods

To gather information for this review, searches were performed in Scopus, Web of Science, Embase, PubMed, and MEDLINE. The review covered articles published globally from 2000 to 2024, with 50% of the selected articles published within the past 5 years.

3. Results and Discussion

The findings of this review are organized into six sessions, outlined below:

3.1. Natural History of DKD

Traditionally, in the natural progression of DKD, the onset of overt proteinuria usually occurs before a more rapid decline in eGFR. However, over the past decade, numerous studies have shown that many diabetic patients with reduced eGFR do not develop proteinuria [10,11]. For example, a study at the Steno Diabetes Center found that approximately 20% of diabetic patients without albuminuria never developed proteinuria before progressing to ESKD, indicating that proteinuria is not a necessary precursor for ESKD [12]. The risk of CKD progression is depicted in Figure 1A,B, with the frequency of evaluations and referrals to a nephrologist stratified as shown in Figure 1A [13].

3.2. NP-DKD

Recent reports suggest that the prevalence of NP-DKD ranges from 20% to 40% [14], with a prevalence of 20% among patients with type 1 diabetes (T1DM) and approximately 40% among those with type 2 diabetes mellitus (T2DM) [15,16]. However, some studies have reported an even higher prevalence of NP-DKD among diabetic patients, with estimates reaching 50–60%, as shown in Table 1. The factors contributing to this DKD phenotype are not fully understood but may include an increase in the number of elderly patients, as well as those with DM, hypertension, dyslipidemia, obesity, hyperuricemia, microangiopathy, or more intensive treatment regimens, including the use of renoprotective agents [15].
Table 1 summarizes the key aspects of NP-DKD, including its prevalence, associated clinical and demographic parameters, and distinct patterns of eGFR decline over time according to proteinuria [10,11,12,17,18,19,20,21,22,23,24,25,26,27,28,29,30]. Notably, patients with T2DM may experience significant renal impairment while remaining normoalbuminuric or microalbuminuric.
Although the risk of progression to ESKD is relatively lower in NP-DKD when compared to P-DKD, analyses of the Kidney Early Evaluation Program cohort revealed that the adjusted incidence rate for ESKD in these populations was 7.8 times higher than that of non-albuminuric patients without DM [31]. Thus, the risks of cardiovascular diseases and other complications of CKD remain high in these populations [32].

3.3. Clinical, Laboratory, and Morphological Parameters Associated with P-DKD vs. NP-DKD

Research shows that clinical factors associated with NP-DKD include female sex, hypertension, smoking, poor glycemic control, absence of diabetic retinopathy, and use of the RAAS inhibitors [10,33]. In a prospective, observational study of 400 patients with T2DM who had significant proteinuria (>500 mg/day) and/or a reduced eGFR < 60 mL/min/1.73 m2, patients were categorized into two groups based on their urine protein-creatinine ratio [34]. Among these, 106 patients (26.5%) were identified with NP-DKD. This group exhibited a higher eGFR at the start of the study, at 6 months, and after 1 year, indicating a slower decline in eGFR compared to those with P-DKD. The NP-DKD group was significantly older (56.5 ± 2.1 vs. 54.7 ± 11.6 years), had a lower prevalence of diabetic retinopathy (46.2% vs. 74.1%), higher hemoglobin levels (11.3 ± 1.7 vs. 10.5 ± 2.0 g/dL), and higher cholesterol levels (169.3 ± 43.3 vs. 157.1 ± 58.1 mg/dL) [34].
The NEFRON study found that T2DM was associated with a higher incidence of albuminuric renal impairment compared to the general non-diabetic population [11]. Diabetic patients with an eGFR < 60 mL/min/1.73 m2 and albuminuria were more likely to have a history of hypertension, retinopathy, macrovascular disease, or a first-degree relative with CKD compared to those with an eGFR ≥ 60 mL/min/1.73 m2. This association was not seen in T2DM patients with normoalbuminuric renal impairment. However, diabetic individuals with an eGFR < 60 mL/min/1.73 m2, both with and without albuminuria, exhibited significantly higher rates of visual impairment, atrial fibrillation, and heart failure compared to diabetic individuals with an eGFR ≥ 60 mL/min/1.73 m2. These findings highlight the importance of regularly assessing both eGFR and proteinuria in diabetic patients.
Conversely, the prevalence of diabetic retinopathy was significantly higher in patients with P-DKD compared to those with NP-DKD (66.4% vs. 38.9%, respectively). NP-DKD patients had better renal outcomes and maintained significantly higher serum albumin levels compared to those with P-DKD (41.11 ± 3.61 g/L vs. 32.65 ± 5.81 g/L, respectively) [35]. NP-DKD patients also had lower levels of LDL and HDL cholesterol compared to P-DKD patients (2.07 [1.71–2.37] mmol/L vs. 2.80 [2.10–3.42] mmol/L; and 0.81 [0.64–0.99] mmol/L vs. 0.92 [0.84–1.12] mmol/L, respectively). To note, there was no significant difference in the use of RAAS inhibitors between these two groups.
Additionally, Yamanouchi et al. [5] found that patients with NP-DKD had better blood pressure control despite less frequent use of RAAS inhibitors. This is consistent with the established link between elevated systolic blood pressure and increased albuminuria [36]. The lower use of anti-RAAS drugs may also be due to factors such as hyperkalemia or renal artery stenosis [3].
Furthermore, a biopsy-based cohort study employing a propensity-score matched analysis not only revealed that patients with NP-DKD exhibited lower levels of systolic and diastolic blood pressure along with a more favorable lipid profile, but also demonstrated a significantly higher 5-year CKD progression-free survival when compared to individuals with P-DKD (86.6% vs. 30.3%) [28]. Importantly, the 5-year death-free survival rates were 98.4% for NP-DKD and 87.5% for the P-DKD group, and these differences remained statistically significant in the propensity-matched cohort (98.3% vs. 82.6%, respectively). These findings emphasize the association of proteinuria as a key indicator of worse renal outcomes and mortality in patients with CKD.
Additionally, urinary levels of MCP-1 [37] and tumor necrosis factor alpha (TNF-α) [38] were found to be higher in P-DKD patients (A2 and A3) compared to NP-DKD patients (A1). However, in a post hoc analysis, urinary CXCL8 levels (a chemokine that regulates acute inflammatory response) exhibited no significant differences among A2 and A3 patients, despite being higher in these groups in contrast to A1 patients [39].

3.4. Histopathology Associated with P-DKD vs. NP-DKD

There are few studies comparing renal biopsy findings between patients with P-DKD and NP-DKD, and no distinct histopathological features are specific to the non-proteinuric phenotype [16]. Compared to P-DKD patients, those with NP-DKD typically show less severe glomerular lesions, such as reduced mesangial expansion and fewer nodular sclerosis (Kimmelstiel–Wilson lesions) [35,36].
The incidence of arteriolar hyalinosis was significantly lower in the NP-DKD group compared to the P-DKD group (66.7% vs. 88.9%) [35]. Additionally, NP_DKD patients had lower deposition of IgM and C1q deposition on direct immunofluorescence compared to P-DKD patients (11.1% vs. 77.8% for IgM, and 0.0% vs. 58.3% for C1q) [35]. Although proteinuric patients had significantly higher C3 deposition overall, C3 and C4 levels serum levels were similar between P-DKD and NP-DKD groups. Complement deposition in the kidney, particularly C1q and C3, correlates with more severe renal damage in DKD, including functional impairment (lower eGFR and higher proteinuria) and structural damage (interstitial fibrosis and tubular atrophy [IFTA], interstitial inflammation, vascular lesions, and global sclerosis) [40]. IFTA is a valuable predictor of kidney prognosis in both NP-DKD and P-DKD [28,41].
Importantly, in a matched-propensity score cohort, P-DKD patients exhibited more severe histological kidney alterations according to several diabetic-based classifications (Fioretto, Tervaert, and Japanese) [28]. All kidney compartments showed significant damage in P-DKD compared to individuals with NP-DKD.

3.5. Treatment of P-DKD vs. NP-DKD

Optimizing the control of hyperglycemia, hypertension and dyslipidemia is crucial for preventing the progression of kidney disease in proteinuric patients [42]. This approach should likely also be considered in the case of NP-DKD; however, there is limited evidence regarding these interventions in non-proteinuric patients [42]. It is noteworthy that clinical trials generally did not include patients with low levels of albuminuria. Additionally, patients already using RAAS blockers to control proteinuria were often randomized into these trials, which contributed to overlooking the potential benefits of adding other drugs when evaluating proteinuria reduction as an outcome.
RAAS blockers have already demonstrated efficacy in slowing DKD be approximately 5–7 mL/min/year across several trials, compared to the normal 0.7–0.9 mL/min/year [43]. As reviewed elsewhere, these drugs reduce the progression of UACR from A1 to A2 (trials BENEDICT, ROADMAP, RASS, and ADVANCE), from A2 to A3 (trials IRMA-2 and INNOVATION), progression to ESKD (trials ADVANCE, RENAAL, IDNT, and ORIENT) and mortality (trials RENAAL, IDNT, and ORIENT) [44].
Therefore, their use is recommended owing to their beneficial hemodynamic effects (reduction in glomerular hypertension) and non-hemodynamic effects (reduction in inflammation, oxidative stress, and fibrosis).
Regarding the use of sodium-glucose cotransporter-2 inhibitors (SGLT2i), the EMPA-REG study evaluated the efficacy of empagliflozin in the treatment of DKD. In this trial, most patients were categorized as A1 based on UACR, both in the group with eGFR less than 60 mL/min/1.73 m2 (A1: 47%, A2: 34%, A3: 19%) and in the group with more than 60 mL/min/1.73 m2 (A1: 64%, A2: 27%, A3: 8%), for both the placebo and the empagliflozin groups. Additionally, 80% of the patients were on RAAS blockers [45]. Importantly, the group treated with empagliflozin showed a 39% reduction in incident or worsening nephropathy or cardiovascular death, a 44% reduction in the doubling of serum creatinine, and a 55% decrease in the need for renal replacement therapy. One key finding of the EMPA-REG study was that the progression from A1–A2 to A3 albuminuria decreased by 39%, underscoring the importance of adding SGLT2i to reduce DKD progression and mortality.
In the DAPA-CKD study (n = 4304), both diabetic (67.5%) and non-diabetic (32.5%) individuals with an eGFR ranging from 25 to 75 mL/min/1.73 m2 and an UACR of 200–5000 mg/g were evaluated [46]. The hazard ratio (HR) for the primary composite outcome-defined as a sustained decline in the eGFR of at least 50%, ESKD, or death from renal or cardiovascular causes- was 0.61 (95% confidence interval [CI], 0.51–0.72). Importantly, the benefit of dapagliflozin was consistent across different UACR levels, with an HR of 0.54 for values ≤ 1000 and an HR of 0.62 for values > 1000 mg/g.
Subsequently, in the EMPA-KIDNEY study, which included patients with eGFR ≥ 20–45 or eGFR ≥ 45 to <90 mL/min/1.73 m2 with UACR ≥ 200 mg/g, with or without DM, empagliflozin was associated with a 28% reduction in the progression of kidney disease or death from cardiovascular causes [47]. Notably, 98% of participants were on RAAS blockers, and the benefits of empagliflozin were consistent across eGFR levels at randomization. The proportional risk reduction varied with UACR levels: HR = 0.67 (0.58–0.79) for ≥300 mg/g, HR = 0.91 (0.65–1.26) for 30–300 mg/g, and HR = 1.01 (0.66–1.55) for ≤30 mg/g, regardless of DM. Over the chronic slopes in eGFR from 2 months to final follow-up, there was a between-group difference of 1.37 mL/min/1.73 m2/year (95% CI 1.16 to 1.59). Prespecified exploratory analyses by subgroups revealed that the rate of decline of eGFR (chronic slope) was slower in the empagliflozin group across all key subgroups, including patients with low UACR [48].
Differences in the rate of eGFR decline were more pronounced in subgroups with faster annual decline, such as patients with DM, higher eGFR, or higher baseline UACR [47]. Specifically, the impact of empagliflozin on the differences in eGFR decline (in mL/min/1.73 m2/year) were more significant in these faster-declining subgroups:
  • DM (−1.05 vs. −2.73; absolute difference +1.68 and relative difference −62%) compared to non-DM (−1.66 vs. −2.75; absolute difference +1.09 and relative difference −40%);
  • eGFR < 30 (−1.84 vs. −2.85; absolute difference +1.01 and relative difference −35%) compared to ≥30–45 (−1.18 vs. −2.50; absolute difference +1.32 and relative difference −53%) and ≥45 (−1.58 vs. −3.60; absolute difference +2.01 and relative difference −56%);
  • UACR < 30 mg/g (−0.11 vs. −0.89; absolute difference +0.78 and relative difference −87%) compared to UACR ≥ 30–300 mg/g (−0.49 vs. −1.69; absolute difference +1.20 and relative difference −71%) and UACR ≥ 300 mg/g (−2.35 vs. −4.11; absolute difference +1.76 and relative difference −43%.
Additionally, finerenone, a nonsteroidal mineralocorticoid receptor antagonist, has demonstrated robust evidence of cardiorenal benefits in patients with CKD and T2DM across a broad spectrum of CKD severity. In the FIDELITY study [48], a prespecified pooled analysis of FIDELIO-DKD (more severe CKD; mean eGFR 44.3 mL/min/1.73 m2, median UACR 851 mg/g, and UACR ≥ 300 mg/g in 87.4%) and FIGARO-DKD (less severe CKD; mean eGFR 67.8 mL/min/1.73 m2, median UACR 312 mg/g, and UACR ≥ 300 mg/g in 51.2%), finerenone was associated with a 33% reduction in kidney composite outcomes and a 14% reduction in cardiovascular composite outcomes. It is noteworthy that the benefits of finerenone over a placebo concerning cardiorenal outcomes in patients with both CKD and T2DM were observed, irrespective of SGLT2i usage [49].
Therefore, we now have two evidence-based medications, SGLT2i and finerenone, which, when combined with angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers, are proven to slow DKD progression to approximately 2.5–3 mL/min/year, provided blood pressure and glucose levels are maintained at guideline goals [43].
Concerning the use of glucagon-like peptide 1 receptor agonists (GLP-1 RA), in the SUSTAIN 1–7 studies, eGFR did not differ between semaglutide and placebo. In the SUSTAIN 1–6 studies, UACR decreased in patients with pre-existing stage 2 or 3 UACR; however, it did not change or increased in those with normoalbuminuria at baseline [50].
Additionally, post hoc analyses of the Semaglutide Treatment Effect in People with obesity (STEP) 2 clinical trial explored the effects of semaglutide associated with lifestyle interventions on renal function [51]. At week 68, the changes in UACR were −14.8% and −20.6% with semaglutide 1.0 mg and 2.4 mg, respectively, and +18.3% with placebo (differences between groups compared to placebo: −28.0% for semaglutide 1.0 mg; −32.9% for semaglutide 2.4 mg). The average percentage difference in UACR compared to placebo at week 68 was −27.2% and −30.5% in the semaglutide 1.0 mg and 2.4 mg groups, respectively (all significant).
In the SURPASS-4 study, participants with T2DM who were treated with a combination of metformin, sulfonylurea, or SGLT2i had a mean eGFR of 81.3 ± 21.1 mL/min/1.73 m2 and a median UACR of 15.0 mg/g (IQR 5.0–55.8) [52]. Participants were randomly assigned in a 1:1:1:3 ratio to receive weekly subcutaneous injection of tirzepatide (5 mg, 10 mg, or 15 mg) or insulin glargine (100 U/mL), with titration to achieve fasting blood glucose levels below 100 mg/dL. During the follow-up, UACR increased by 36.9% in the insulin glargine group, but decreased by 6.8% in the tirzepatide group, resulting in a −31.9% difference between the two groups. Those receiving tirzepatide had a significantly lower occurrence of the composite renal outcome, which included a decline in eGFR ≥ 40% from baseline, renal death, renal failure, or UACR > 300 mg/g, compared to those receiving insulin glargine (HR = 0.58).
In the FLOW trial, patients with type 2 diabetes mellitus (T2DM) were randomly assigned to either a semaglutide or a placebo group [53]. The baseline laboratory data showed a mean estimated glomerular filtration rate (eGFR) of 47 mL/min/1.73 m2 and a median urinary albumin-to-creatinine ratio (UACR) of 567.6 mg/g (A1: 3%, A2: 29%, A3: 68%). The use of renoprotective medications included SGLT2i (16%), angiotensin-converting enzyme inhibitors (35%), and angiotensin II receptor blockers (60%). The main findings in the semaglutide group included a reduction in the first major kidney disease outcome (kidney failure, at least 50% reduction in the eGFR from baseline, or death from kidney-related or cardiovascular causes; HR = 0.76, 95% CI: 0.66–0.88, p = 0.0003), the first kidney-specific component event (HR = 0.79), death from cardiovascular causes (HR = 0.79), death from any cause (HR = 0.80), and a difference in the annual eGFR slope (1.16 mL/min/1.73 m2, 95% CI: 0.86–1.46, p < 0.001). Notably, the UACR was reduced by 40% in the semaglutide group compared to 12% in the placebo group, resulting in a ratio at week 104 that was 32% lower (95% CI: 25–38) in the semaglutide group than in the placebo group. Subgroup analysis of the primary outcome revealed a beneficial effect of semaglutide in patients with UACR ≥ 300 mg/g (HR = 0.74, 95% CI: 0.63–0.87) compared to those with UACR < 300 mg/g (HR = 0.86, 95% CI: 0.60–1.23).
Importantly, further studies are warranted to compare RAAS blockade, including finerenone, and SGLT2i combined with semaglutide. These studies should aim to determine whether patients with lower values of albuminuria would progress at a similar or slower rate compared to patients with higher values of albuminuria or those in the placebo group. These findings also highlight the importance of validating novel biomarkers to assess DKD progression regardless of albuminuria levels.
Therefore, the management of DKD should be grounded in our comprehension of the various interrelated pathophysiological mechanisms encompassing hemodynamic, metabolic, and inflammatory pathways. Given that these pathways play a crucial role in the initiation and progression of DKD, it is essential to prioritize the validation of kidney damage-associated biomarkers alongside both non-pharmacological and pharmacological approaches, in particular RAAS inhibitors, SGLT2i, finerenone, and GLP-1 RA [43]. This holistic approach is of paramount importance in halting the progression of DKD, irrespective of albuminuria levels (Figure 2). It is essential to highlight that the KDIGO guidelines do not recommend different therapeutic approaches between P-DKD and NP-DKD [3]. Additionally, lifestyle modification and self-management should be encouraged for all diabetic patients, including adopting a healthy diet, smoking cessation, weight control, and regular exercise. For patients with DM and CKD who are not on dialysis, it is recommended that protein intake be limited to 0.8 g/kg body weight per day [3].

3.6. Perspectives

Markers of proximal tubule and glomeruli injury, along with markers of inflammation in DKD could offer valuable clinical insights for evaluating disease progression, identifying different patterns, or verifying the potential therapeutic of pharmacological and non-pharmacological approaches. Notably, the correlation of these markers with varying levels of proteinuria and eGFR could contribute to advancing our understanding of the key mechanistic properties of DKD.
UACR, RBP (retinol-binding protein), and MCP-1 (monocyte chemoattractant protein-1) were associated with the progression of DKD across all levels of albuminuria. In patients with NP-DKD, MCP-1, IL-6, and NGAL (neutrophil gelatinase-associated lipocalin) were linked to progressive CKD, while NAG (N-acetyl-β-d-glucosaminidase), a lysosomal enzyme, was indicative of early kidney damage, showing a significant association with an eGFR below 60 mL/min/1.73 m2 in the UACR < 3 mg/g cohort [54]. This underscores the importance of validating these biomarkers for diagnosing and monitoring DKD progression in conjunction with albuminuria in larger studies. Furthermore, assessing the variability of kidney damage-associated biomarkers is essential to verify the effectiveness of current standard-of-care treatments for DKD, given that its pathophysiological mechanisms involve hemodynamic, metabolic, and inflammatory pathways [43].
In a multivariate analysis, NP-DKD patients exhibited IFTA as risk factors for disease progression [5]. These findings align with prior reports, emphasizing the significant role of interstitial injury in eGFR decline [55,56]. This eGFR decline in the context of NP-DKD has been shown to predict cardiovascular events [57].
In this setting, markers of tubular injury may prove more useful in the future to stratify those whose renal function declines. Liver-type fatty acid-binding protein (L-FABP) and heart-type fatty acid-binding protein (H-FABP) are promising indicators of tubular, but not glomerular, damage.
L-FABP is expressed in the proximal tubules of the human kidney, where it plays a role in fatty acid metabolism and serves as a potential marker for tubular, but not glomerular, damage [58]. In patients with normoalbuminuria, urinary levels of L-FABP and albumin were significantly higher than normal controls. Urinary levels of L-FABP and albumin showed significant differences across the control, normoalbuminuric, microalbuminuric, macroalbuminuric, and ESKD groups, with levels increasing with the severity of DKD. While urinary L-FABP levels were significantly correlated with urinary albumin levels in the overall population, this correlation was absent in the subgroup of patients with an eGFR > 60 mL/min/1.73 m2. Importantly, the area under the curve (AUC) for L-FABP in predicting DKD progression was 0.849. Additionally, Cox regression analysis revealed that elevated urinary L-FABP levels at baseline were significantly associated with DKD progression (adjusted HR [aHR] = 9.45).
In diabetic animals, the urinary excretion of biomarkers such as heart-type fatty acid-binding protein (H-FABP), osteopontin (OPN), nephrin, neutrophil gelatinase-associated lipocalin (NGAL) was significantly elevated compared to non-diabetic animals [59]. Similarly, plasma levels of kidney injury molecule-1 (KIM-1), clusterin, OPN, and tissue inhibitor of metalloproteinases-1 (TIMP-1) were notably higher in diabetic animals. These biomarkers were detectable even before the onset of traditional indicators of DKD, such as albuminuria and urinary protein excretion.
Understanding the inflammatory mechanisms is crucial for comprehending DKD [60]. The Kidney Risk Inflammatory Signature (KRIS), which consists of 17 proteins enriched in tumor necrosis factor receptor superfamily members, has been associated with a 10-year risk of ESKD in both T1DM and T2DM [61]. These proteins have shown significant albuminuria-independent (−9.3 mL/min/1.73 m2 per year per 1 log10 increase in TNF-R1) and albuminuria-mediated (−4.8 mL/min/1.73 m2 per year per 1 log10 increase in TNF-R1) effects on renal function. The total effect of a 1 log10 increase in TNF-R1 on the eGFR slope was −14.1 mL/min/1.73 m2 per year. Notably, 66% of TNF-R1′s impact was albuminuria-independent, suggesting that KRIS proteins significantly contribute to renal function decline, predominantly through pathways independent of albuminuria, though both effects were significant. Therefore, albuminuria might be considered an intermediate phenotype—a risk indicator rather than a direct risk factor in the disease process leading to ESKD.
Additionally, the CKD273 classifier emerges as a promising proteomic biomarker for the early detection of non-proteinuric patients at high risk for progressive DKD [62]. This biomarker outperforms albuminuria in predicting the risk of progression both more effectively and earlier. In a cohort study of patients with T2DM, the CKD273 AUC was 0.92, indicating that it is a more reliable and earlier predictor of macroalbuminuria compared to the microalbuminuria AUC, which was 0.67. The CKD273 classifier predicted the progression to macroalbuminuria 1.5 years earlier than microalbuminuria.

4. Conclusions

P-DKD and NP-DKD are two different types of kidney involvement in DM with respect to histological, biological and outcome aspects, both requiring the same multifactorial therapeutic approach. Therefore, standard-of-care approaches should be applied in both scenarios. Ongoing advances in molecular studies are essential to pinpoint distinct therapeutic targets for NP-DKD and P-DKD. Additionally, there is a critical need for studies that validate new biomarkers, beyond albuminuria, capable of predicting the progression and therapeutic response of DKD across its various presentations.

Author Contributions

L.F., conceptualization, investigation, methodology, project administration, validation, visualization, writing—original draft, and writing—review and editing. J.F.P.-M., conceptualization, investigation, methodology, project administration, validation, visualization, writing—original draft, and writing—review and editing. É.B.R., conceptualization, investigation, methodology, project administration, supervision, validation, visualization, writing—original draft, writing—review and editing, and final approval. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by a grant from FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo/São Paulo Research Foundation; 2021/02216-7) to É.B.R.

Institutional Review Board Statement

This work complies with the Declaration of Helsinki.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. (A). Risk of chronic kidney disease progression, frequency of visits and referral to nephrology, as indicated by the kidney icon, are stratified based on eGFR and albuminuria. Adapted from [13]. The eGFR and albuminuria grid illustrates the risk through color coding, ranging from favorable to unfavorable (green, yellow, orange, red, deep red). (B). Trajectories of kidney function in DKD. Adapted from [8].
Figure 1. (A). Risk of chronic kidney disease progression, frequency of visits and referral to nephrology, as indicated by the kidney icon, are stratified based on eGFR and albuminuria. Adapted from [13]. The eGFR and albuminuria grid illustrates the risk through color coding, ranging from favorable to unfavorable (green, yellow, orange, red, deep red). (B). Trajectories of kidney function in DKD. Adapted from [8].
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Figure 2. Laboratory, clinical, histological and prognostic differences between NP-DKD and P-DKD.
Figure 2. Laboratory, clinical, histological and prognostic differences between NP-DKD and P-DKD.
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Table 1. Prevalence, clinical and demographic parameters and outcomes in diabetic patients according to proteinuria.
Table 1. Prevalence, clinical and demographic parameters and outcomes in diabetic patients according to proteinuria.
StudyDesignSample Size (n)ObjectiveResults
Nosadini et al. (2000) [17]Longitudinal study, kidney biopsyn = 108 T2DM
n = 74 with albuminuria 20–199 μg/min
n = 34 with albuminuria > 199 μg/min		To evaluate the course of kidney function, laboratory, and clinical parameters. Follow-up: 4 yearsThe mean eGFR decreased in both groups, displaying a heterogenous pattern; the odds of being progressors significantly increased across the quartiles of baseline glomerular basement membrane width and mesangial fractional volume.
Kramer et al. (2003) [10]Cross-sectional analysis (Third National Health and Nutrition Examination Survey—NHANES III)Population estimated in 1.1 million
microalbuminuria: ≥17 and ≥25 µg/mg for men and women, respectively
microalbuminuria: > 250 µg/mg in men and at least 355 µg/mg in women, respectively		To determine the prevalence of CKD in the absence of micro- or macroalbuminuria and diabetic retinopathyn = 171/1197 T2DM (13%) had CKD (vs. 7% in non-diabetic population). Adults with T2DM and CKD were more likely to have macroalbuminuria (19% vs. 5%), microalbuminuria (45% vs. 32%), and diabetic retinopathy (28% vs. 15%) compared to those with T2DM but without CKD. Among these adults with T2DM and CKD, both retinopathy and albuminuria (either microalbuminuria or macroalbuminuria) were absent in 30% of cases.
MacIsaac et al. (2004) [18]Cross-sectional surveyn = 301 T2DMTo determine the prevalence and characteristics of patients with T2DM who have CKD normoalbuminuria.
GFR evaluated by the plasma disappearance of isotopic (99m)Tc-diethylene-triamine-penta-acetic acid		Prevalence of CKD: 36%
The overall prevalence of normoalbuminuria, microalbuminuria, and macroalbuminuria was 39%, 35%, and 26%, respectively. Patients with normoalbuminuria were more likely to be older and female compared to those with macroalbuminuria. The rates of GFR decline (mL/min/1.73 m2/year) were −4.6 ± 1.0 for normoalbuminuric patients, −2.8 ± 1.0 for microalbuminuric patients, and −3.0 ± 0.7 for macroalbuminuric patients, with no significant differences between the groups.
Retnakaran et al. (2006) [19]Longitudinal study
(U.K. Prospective Diabetes Study—UKPDS)		n = 5102 T2DM
n = 4031 without proteinuria or n = 5032 with normal plasma creatinine at diagnosis		To identify clinical risk factors at diagnosis of T2DM associated with later development of renal dysfunction
Follow-up: 15 years		Nearly 40% of T2DM patients developed albuminuria, and approximately 30% developed renal impairment.
Among those with renal impairment, 51% did not have preceding albuminuria. Risk factors for developing either albuminuria or renal impairment included higher baseline systolic blood pressure, elevated urinary albumin, increased plasma creatinine, and Indian-Asian ethnicity.
Specific risk factors for albuminuria were male sex, larger waist circumference, higher levels of plasma triglycerides, LDL cholesterol, HbA1c, increased white blood cell count, smoking history, and previous retinopathy. Risk factors for renal impairment included female sex, smaller waist circumference, older age, increased insulin sensitivity, and a history of sensory neuropathy.
Parving et al. (2006) [20]Cross-sectional analysis
(Developing Education on Microalbuminuria for Awareness of renal and cardiovascular risk in Diabetes study)		n = 32,208 T2DM To evaluate the global prevalence and determinants of microalbuminuria in T2DM The overall global prevalence of normoalbuminuria, microalbuminuria, and macroalbuminuria was 51, 39, and 10%, respectively. Risk factors for microalbuminuria or macroalbuminuria included age, HbA1c, systolic and diastolic blood pressure, ethnicity (with higher prevalence in Asians and Hispanics compared to Caucasians), retinopathy, duration of DM, eGFR, diabetic foot lesions, congestive heart failure, body height, and smoking.
New et al. (2007) [21]Cross-sectional analysisTotal population: n = 162,113 To compare rates of CKD (eGFR < 60 mL/min/1.73 m2) in patients with DM and management of risk factors compared with people without DM Prevalence of DM: 3.1%
CKD: 31% in DM (vs. 6.9% in non-diabetics)
CKD in DM: 63% had normoalbuminuria.
Thomas et al. (2009) [11]Cross-sectional analysis (NEPHRON survey)n = 3893 T2DM
n = 11,247 general population (Australian Diabetes, Obesity and Lifestyle—AusDiab) survey		To examine the frequency and predictors of non-albuminuric renal impairment (eGFR < 60 mL/min/1.73 m2)Among patients with T2DM, 23.1% had renal impairment (eGFR < 60 mL/min/1.73 m2), and 55% of these patients had normoalbuminuria; renal impairment was more common than in the general population only when albuminuria was present (aOR = 1.3), but not for those with normoalbuminuria. Renal impairment without albuminuria was less prevalent in individuals with DM than in the general population, regardless of sex (men: aOR = 0.7; women: aOR = 0.6), ethnicity, or duration of diabetes.
Penno et al. (2011) [22]Cross-sectional analysis (Renal Insufficiency and Cardiovascular Events –RIACE—Italian Multicenter Study)n = 15,773 T2DM To evaluate the association of non-albuminuric renal impairment with cardiovascular risk factors and other complications Among patients with CKD (eGFR < 60 mL/min/1.73 m2), 56.6% were normoalbuminuric, 30.8% were microalbuminuric, and 12.6% were macroalbuminuric. Non-albuminuric renal impairment was associated with a higher prevalence of cardiovascular disease and a greater likelihood of being female. In contrasts, albuminuric renal impairment was linked to higher HbA1c levels, retinopathy, and male sex.
Dwyer et al. (2012) [23]Cross-sectional analysis
(Developing Education on Microalbuminuria for Awareness of Renal and Cardiovascular Risk in Diabetes—DEMAND)		n = 11,573 T2DM
normoalbuminuria: UACR < 30 mg/g, microalbuminuria: UACR 30–299 mg/g, and macroalbuminuria UACR > 300 mg/g		To describe the prevalence and risk factors for albuminuriaCKD (stage 3–5): 17% with normoalbuminuria, 27% with microalbuminuria and 31% with macroalbuminuria. Creatinine clearance < 60 mL/min was observed in 20.5% of patients with normoalbuminuria, 30.7% with microalbuminuria, and 35.0% with macroalbuminuria.
Bhalla et al. (2013) [24]Cross-sectional analysisn = 15,683 persons of non-Hispanic white (NHW), Asian (Asian Indian, Chinese, and Filipino), Hispanic, and non-Hispanic black (NHB) race/ethnicity with T2DMTo examine racial/ethnic differences in the prevalence of DKD, with and without proteinuriaRacial and ethnic minorities had higher rates of P-DKD compared to NHWs (24.8–37.9% vs. 24.8%) and lower rates of NP-DKD (6.3–9.8% vs. 11.7%). Chinese individuals (OR= 1.39 for women and 1.56 for men), Filipinos (OR = 1.57 for women and 1.85 for men), Hispanics (OR = 1.46 for women and 1.34 for men), and NHBs (OR = 1.50 for women) had significantly higher odds of developing P-DKD than NHWs. In contrast, Chinese, Hispanic, and NHB women, as well as Hispanic men, had significantly lower odds of developing NP-DKD compared to NHWs.
Ekinci et al. (2013) [25]Case–control, kidney biopsyn = 8 with normoalbuminuria
n = 6 with microalbuminuria
n = 17 with macroalbuminuria		To compare renal biopsy findings in patients with T2DM and eGFR < 60 mL/min/1.73 m2 associated with either normoalbuminuria, microalbuminuria, or macroalbuminuriaThe mesangial area increased progressively from normal controls to patients with T2DM and normoalbuminuria, microalbuminuria, and macroalbuminuria. Glomerular changes were more common in patients with microalbuminuria and macroalbuminuria compared to those with normoalbuminuria, while interstitial or vascular changes were more frequent in normoalbuminuric patients compared to those with microalbuminuria and macroalbuminuria.
Mottl et al. (2013) [26]Cross-sectional analysis (NHANES 2001–2008)n = 2798 T2DM
n = 15,743 non-diabetics		To compare the prevalence and modifying factors of normoalbuminuria (NA) vs. albuminuria (ALB) CKD in diabetics and non-diabeticsThe prevalence of NA-CKD increased with age, with 9.7% of diabetics and 4.3% in non-diabetics.
NA-CKD was less common in diabetic men (OR = 0.58; 95% CI: 0.39–0.87) and less frequent among Black individuals and those from other groups compared to Whites (OR = 0.44; 95% CI 0.29–0.68 and OR = 0.57; 95% CI: 0.34–0.96, respectively). It was more commonly observed in individuals with well- controlled blood pressure and glycemia (OR = 0.25, 95% CI: 0.13–0.50 and OR = 0.48, 95% CI: 0.31–0.74, respectively). Similar patterns were observed in non-diabetic participants.
Boronat et al. (2014) [27]Prospective, observational survey
(CERCA-Diabetes Study)		n = 78
normoalbuminuria: UACR < 30 mg/g, microalbuminuria: UACR 30–299 mg/g, and macroalbuminuria UACR > 300 mg/g		To estimate the prevalence and characteristics of non-albuminuric CKD associated with T2DM in individuals who progress to advanced stages of renal failure
Follow-up: 2 years		Among patients with T2DM, 21.8% had normoalbuminuria; 20.5% had microalbuminuria, and 57.7% had macroalbuminuria. Patients with normoalbuminuria were more likely to be women and had lower rates of smoking and polyneuropathy. They also had higher body mass index and waist circumference measurements, elevated levels of total and LDL cholesterol, and lower values of HbA1c and serum creatinine compared to those with microalbuminuria or macroalbuminuria.
Yamanouchi et al. (2019) [28]Repeated longitudinal analysis, propensity-score analysis of two cohorts: proteinuria vs. non-proteinuria, kidney biopsyn = 526 T2DM with eGFR < 60 mL/min/1.73 m2
Non-proteinuria: UACR < 300 mg/g); poteinuria: UACR ≥ 300 mg/g)
After the propensity-score matching: n = 82 in the non-proteinuric group and n = 164 in the proteinuric group		To assess the clinicopathological features, renal outcomes, and mortality in patients with T2DM and CKD without overt proteinuria
Follow-up: median 1.9 years (IQR, 0.9–5.0 years)		Patients with NP-DKD had lower systolic blood pressure and less severe pathological lesions.
CKD progression-free survival from the date of renal biopsy was 86.6% (95% CI 72.5–93.8) for the NP-DKD group and 30.3% (95% CI 22.4–38.6) for those with P-DKD. This lower renal risk was consistent across all subgroup analyses. Additionally, the 5-year death-free survival was 98.3% for the NP-DKD group and 82.6% for the P-DKD group.
Vistisen et al. (2019) [12]Repeated longitudinal analysisn = 935 T1DM
n = 1984 T2DM		To quantify the impact of albuminuria status on the progression of eGFR trajectories following CKD stage 3 (CKD3) and to evaluate potential variations in progression patterns among the subgroup with normoalbuminuria
Follow-up: 16 years		Over the first 10 years following CKD3, the mean annual declines in eGFR were as follows: 1.9, 2.3, and 3.3 mL/min/1.73 m2 for normoalbuminuria, microalbuminuria and macroalbuminuria in T1DM, and 1.9, 2.1, and 3.0 in T2DM, respectively. Albuminuria status significantly influenced eGFR changes in both types of diabetes, with the most pronounced decline in kidney function observed in patients with macroalbuminuria. Normoalbuminuric patients displayed two distinct eGFR decline patterns, one of which showed accelerated deterioration. This accelerated decline was associated with lower usage of lipid-lowering treatments, renin–angiotensin system blockers, and other antihypertensive therapies.
Jin et al. (2022) [29]Multicenter prospective cohort
(Hong King Diabetes Biobank)		n = 19,025 T2DM
4 groups defined by baseline eGFR and albuminuria: no DKD (no decreased eGFR or albuminuria), albuminuria without decreased eGFR, decreased eGFR without albuminuria, and albuminuria with decreased eGFR		To compare the risks of adverse outcomes between patients with non-albuminuric phenotype and other phenotypes in the context of DKDNon-albuminuric DKD was associated with increased risks of all-cause mortality (HR = 1.59), hospitalization for heart failure (HR = 3.08), and CKD progression (HR = 2.37) compared to individuals without DKD, regardless of baseline eGFR. However, the risk of CVD was not significantly elevated. In contrast, the risks of death, CVD, hospitalization for heart failure, and CKD progression were higher in the presence of albuminuria, whether or not accompanied by decreased eGFR.
Fabre et al. (2024) [30]Repeated longitudinal analysisn = 304 T2DMTo assess the trajectory of eGFR and albuminuria concerning age (<75 and ≥75 years old) in individuals with DKD and identify predictive factors for the decline in eGFR decline, variation in albuminuria, mortality, and progression to renal replacement therapy
Follow-up: 3 years		Comparable declines in eGFR were observed across both age groups during the follow-up period.
During the first year, 24 h albuminuria was higher in patients with T2DM < 75 years of age (median 457 mg vs. 181.5 mg), but no differences were observed in subsequent years. In contrast, albuminuria increased more severely in T2DM with ≥75 years old (50% vs. 30.4%) from the first to second year of follow-up. Overall, 60.1% of patients experienced an increase in albuminuria, and 76.4% showed a decrease in eGFR. Age and smoking were the main predictors of increased albuminuria. Age, average SBP, average DBP, and smoking were associated with eGFR decline.
CI = confidence interval; CKD = chronic kidney disease; CVD = cardiovascular disease; DBP = diastolic blood pressure; DKD diabetic kidney disease; eGFR = estimated glomerular filtration rate; HbA1c = glycated hemoglobin; HR = hazard ratio; IQR = interquartile range; LDL = low-density lipoprotein cholesterol; SBP = systolic blood pressure; T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus; UACR = urinary albumin-to-creatinine ratio.
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MDPI and ACS Style

Fabre, L.; Pedregosa-Miguel, J.F.; Rangel, É.B. Proteinuric and Non-Proteinuric Diabetic Kidney Disease: Different Presentations of the Same Disease? Diabetology 2024, 5, 389-405. https://doi.org/10.3390/diabetology5040030

AMA Style

Fabre L, Pedregosa-Miguel JF, Rangel ÉB. Proteinuric and Non-Proteinuric Diabetic Kidney Disease: Different Presentations of the Same Disease? Diabetology. 2024; 5(4):389-405. https://doi.org/10.3390/diabetology5040030

Chicago/Turabian Style

Fabre, Larissa, Juliana Figueredo Pedregosa-Miguel, and Érika Bevilaqua Rangel. 2024. "Proteinuric and Non-Proteinuric Diabetic Kidney Disease: Different Presentations of the Same Disease?" Diabetology 5, no. 4: 389-405. https://doi.org/10.3390/diabetology5040030

APA Style

Fabre, L., Pedregosa-Miguel, J. F., & Rangel, É. B. (2024). Proteinuric and Non-Proteinuric Diabetic Kidney Disease: Different Presentations of the Same Disease? Diabetology, 5(4), 389-405. https://doi.org/10.3390/diabetology5040030

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