Metabolic Kidney Disease: A New Concept in the Interaction Between Obesity, Prediabetes, Diabetes and Liver Dysfunction

Abstract

Metabolic abnormalities such as obesity, insulin resistance, prediabetes, type 2 diabetes and metabolic dysfunction-associated steatotic liver disease (MASLD) increasingly contribute to chronic kidney disease (CKD). Although often treated as separate entities, these conditions share common mechanisms – including glomerular hyperfiltration, adipokine imbalance, chronic low-grade inflammation, endothelial dysfunction and lipid accumulation – that initiate and sustain renal injury long before classical CKD becomes clinically evident.

The concept of Metabolic Kidney Disease (MKD) offers a unified framework that captures the continuum of renal involvement across the metabolic spectrum. Obesity- and prediabetes-related MKD frequently precede diabetic kidney disease, while MASLD – according to updated EASL-EASD-EASO guidelines – is a multisystem disorder with direct renal consequences. Mixed metabolic phenotypes further intensify metabolic stress, accelerating progression toward CKD.

Recognising MKD has important clinical implications. Expanded screening strategies may identify early renal alterations in individuals with metabolic vulnerability who are not targeted by traditional CKD criteria. Integrating metabolic evaluation into nephrology practice may facilitate earlier, more holistic interventions and ultimately improve cardio-renal outcomes.

Keywords: Obesity, Type 2 diabetes, Prediabetes, Chronic Kidney Disease, Liver dysfunction, Cardiorenal metabolic syndrome, Albuminuria, Glomerular hyperfiltration

List of Abbreviations:

ACR – Albumin-to-creatinine ratio
AGEs – Advanced glycation end-products
AKI – Acute kidney injury
CKD – Chronic Kidney Disease
CKM – Cardiovascular-kidney-metabolic syndrome
CRMS – Cardio-renal-metabolic syndrome
DKD – Diabetic kidney disease
eGFR – Estimated glomerular filtration rate
GLP-1 RA – Glucagon-like peptide-1 receptor agonist
HbA1c – Glycated haemoglobin
IL-6 – Interleukin 6
MASLD – Metabolic dysfunction–associated steatotic liver disease
MKD – Metabolic kidney disease
NAFLD – Non-alcoholic fatty liver disease (former term for MASLD)
NF-κB – Nuclear factor kappa-light-chain-enhancer of activated B cells
ORG – Obesity-related glomerulopathy
PKC – Protein kinase C
RAAS – Renin–angiotensin–aldosterone system
ROS – Reactive oxygen species
SGLT2 – Sodium–glucose cotransporter 2
T2DM – Type 2 diabetes mellitus
TGF-β – Transforming growth factor beta
TNF-α – Tumor necrosis factor alpha

 

Introduction

Cardiovascular diseases and other non-communicable conditions remain the leading cause of death worldwide, accounting for nearly 70% of global mortality [1]. Diabetes mellitus, arterial hypertension, obesity, and chronic kidney disease (CKD) constitute the most prevalent chronic conditions contributing to this burden. CKD affects an estimated 9-13% of the population, with prevalence increasingly driven by the global epidemics of diabetes and obesity [2, 3].

In parallel, the prevalence of diabetes has doubled from 1990 to 2022, reaching over 828 million adults globally [4]. Similar trends are observed in Latin America and other regions, where obesity and metabolic dysfunction are now major determinants of cardiovascular and renal risk [510]. Importantly, mounting evidence indicates that kidney injury can arise before overt diabetes develops, occurring across the entire spectrum of metabolic disturbances, including obesity, prediabetes, insulin resistance, and metabolic dysfunction-associated steatotic liver disease (MASLD).

These interconnected processes form a continuum in which excess adiposity and adipose-tissue dysfunction induce systemic inflammation, endothelial injury, glomerular hyperfiltration, and neurohormonal activation. This “adipocentric” perspective has led to the recognition of the Cardio-Renal-Metabolic Syndrome (CRMS) as an integrated model encompassing cardiovascular, renal, and metabolic abnormalities [1113].

Within this framework, the concept of Metabolic Kidney Disease (MKD) emerges as a unifying term describing kidney damage mediated primarily by metabolic dysfunction, even in the absence of sustained hyperglycaemia. MKD encompasses kidney injury associated with obesity, prediabetes, type 2 diabetes, MASLD, and mixed phenotypes. Its early recognition may be essential to interrupt disease progression and reduce cardiovascular and renal complications.

Importantly, metabolic dysfunction precedes and amplifies kidney injury across the entire continuum of adiposopathy, insulin resistance, impaired glucose tolerance, type 2 diabetes and MASLD, highlighting that renal damage often develops before overt hyperglycaemia becomes clinically detectable.

 

Cardio-Renal-Metabolic Syndrome (CRMS)

The Cardio-Renal-Metabolic Syndrome (CRMS) provides the essential pathophysiological context from which Metabolic Kidney Disease emerges. Evidence accumulated over the last decade shows that excess adiposity – particularly visceral and ectopic fat accumulation – drives a systemic inflammatory state that disrupts cardiovascular, renal, and metabolic homeostasis [14]. Rather than isolated diseases, these conditions form an interconnected continuum in which dysfunction in one organ system accelerates injury in the others.

The American Heart Association defines CRMS as a systemic disorder characterized by pathophysiological interactions between metabolic risk factors, CKD, and cardiovascular disease (CVD), leading to multiorgan dysfunction and increased cardiovascular events [12]. This framework emphasizes the bidirectional nature of these interactions: CVD increases the likelihood of renal dysfunction; CKD amplifies cardiovascular risk; and metabolic abnormalities – including adipose-tissue dysfunction, insulin resistance, and subclinical inflammation – drive both processes simultaneously [1518].

Three major biological pathways underpin CRMS:

  1. Chronic low-grade inflammation, mediated by adipose-derived cytokines such as IL6 and TNFα, promoting endothelial dysfunction, oxidative stress, and vascular injury.
  2. Insulin resistance, contributing to altered podocyte signaling, increased sodium reabsorption, impaired nitric oxide bioavailability, and early glomerular hyperfiltration.
  3. Neurohormonal activation, including heightened activity of the sympathetic nervous system and the renin–angiotensin–aldosterone system (RAAS), fostering vasoconstriction, hypertension, fibrosis, and progressive organ damage.

To support clinical stratification, the AHA proposes a staging system encompassing the entire spectrum of metabolic and cardiorenal dysfunction [12, 15]:

  • Stage 0: No metabolic risk factors
  • Stage 1: Excess or dysfunctional adiposity, including prediabetes
  • Stage 2: Metabolic risk factors and/or moderate-to-high CKD risk
  • Stage 3: Subclinical CVD with overlapping metabolic or renal risk
  • Stage 4: Established CVD ± CKD (4a: without renal insufficiency; 4b: with renal insufficiency)

Within this continuum, the kidney is both target and mediator of metabolic injury. CRMS thus provides the conceptual foundation for MKD/ERM, clarifying how metabolic dysfunction – independent of glycaemic thresholds – initiates and amplifies renal injury.

 

Definition and Concept of Metabolic Kidney Disease (MKD/ERM)

Metabolic Kidney Disease (MKD), or Enfermedad Renal Metabólica (ERM), is an emerging and evolving concept that seeks to integrate the entire spectrum of renal injury associated with metabolic dysfunction. Rather than representing a single disease or a traditional histopathological entity, MKD reflects a continuum of pathophysiological alterations in which adipose-tissue dysfunction, insulin resistance, and chronic low-grade inflammation converge to drive early and progressive kidney damage. This view departs from classical models focused exclusively on hyperglycaemia or hypertension, and instead places the metabolic milieu – especially dysfunctional adiposity – at the centre of renal injury [13, 19] (Figure 1).

Common pathophysiological mechanisms in metabolic kidney disease (MKD)
Figure 1. Common pathophysiological mechanisms in metabolic kidney disease (MKD). 1. Inflammation: increased cytokine and adipokine signalling leading to endothelial dysfunction, tissue remodelling, and fibrosis. 2. Hyperfiltration: intraglomerular hypertension and haemodynamic stress, contributing to podocyte injury and glomerulosclerosis. 3. Endothelial dysfunction: impaired nitric oxide bioavailability leading to altered autoregulation and vascular stiffness. 4. Insulin resistance: disrupted insulin signalling in target tissues (e.g., podocytes, hepatocytes) promoting metabolic stress, lipotoxicity, and apoptosis.

Adipose-tissue dysfunction plays a pivotal mechanistic role. Excess visceral fat promotes secretion of proinflammatory cytokines (TNF-α, IL-6), dysregulated adipokines (reduced adiponectina, elevated leptina), increased oxidative stress, and activation of the renin–angiotensin–aldosterone system (RAAS). These mechanisms favour afferent arteriolar vasodilation, intraglomerular hypertension, podocyte stress, and alterations in glomerular permeability. Over time, these changes contribute to hypertrophy of glomerular structures, expansion of mesangial matrix, tubulointerstitial inflammation, and ultimately to a decline in glomerular filtration [2024]. This continuum perspective aligns with current evidence, emphasizing that renal alterations frequently emerge during early metabolic imbalance, well before traditional diagnostic criteria for diabetes or CKD are met.

 

MKD as an Integrative Clinical Framework

The strength of the MKD concept lies in its ability to integrate metabolic phenotypes that traditionally have been described separately. Obesity, prediabetes, type 2 diabetes, MASLD, and their combinations share physiopathological pathways that converge on the kidney. Although the magnitude and temporal sequence of injury may differ, the kidney responds to metabolic stress in a largely stereotyped manner: early glomerular hyperfiltration, podocyte maladaptation, endothelial dysfunction, and progressive fibrosis.

This integrative framework does not negate existing terminology, such as Diabetic Kidney Disease (DKD) or CKD associated with metabolic syndrome, but rather seeks to connect them. DKD remains essential for describing renal injury in established diabetes. However, it does not encompass patients with obesity or prediabetes who show similar physiopathological patterns. Likewise, CKD associated with metabolic syndrome often remains an epidemiological description rather than a mechanistic one. MKD proposes a unifying perspective, highlighting the central role of metabolic dysfunction – whether hepatic, adipose, or pancreatic – in initiating and sustaining renal damage. Given its high prevalence and strong metabolic basis, MASLD should be formally recognised as a key determinant of renal vulnerability within the MKD spectrum, warranting systematic screening even in non-diabetic individuals.

 

Clinical Implications

Recognizing MKD as a distinct and broader clinical construct may help clinicians identify high-risk individuals who would not be screened under current CKD guidelines. It may also encourage early therapeutic interventions targeting adipose-tissue inflammation, insulin resistance, and metabolic stress before overt renal dysfunction becomes evident. Ultimately, MKD promotes a shift from reactive nephrology to a more preventive, metabolically informed approach, consistent with contemporary cardio-renal-metabolic frameworks.
Comparable patterns of early metabolic stress and altered body composition have been reported in kidney conditions characterised by organomegaly, where malnutrition and sarcopenia may develop despite preserved eGFR [25, 26], particularly in women due to the higher prevalence of hepatomegaly [2729].
Furthermore, persistent inflammatory activation is a hallmark across CKD phenotypes. Evidence from anemia management [30], intravenous iron stewardship [31], and uremic toxin–driven vascular injury [32] highlights how metabolic and inflammatory disturbances can converge to amplify renal vulnerability, mirroring several mechanisms central to MKD.

 

Clinical Subtypes of Metabolic Kidney Disease

Metabolic Kidney Disease encompasses a spectrum of renal manifestations arising from distinct but interrelated metabolic disturbances. Although these conditions share common physiopathological pathways – such as insulin resistance, adipose-tissue dysfunction, chronic inflammation, and endothelial injury – each metabolic phenotype imprints a characteristic pattern of renal involvement (Figure 2). In the following sections, we describe the major clinical subtypes of MKD, highlighting their specific mechanisms, histopathological features, and implications for early detection and progression.

Figure 2. Proposed classification of metabolic kidney disease (MKD). Subtypes include obesity-related MKD, prediabetes-related MKD, T2DM-related MKD, MASLD-related MKD, and mixed MKD.

Obesity-Related- Metabolic Kidney Disease

Obesity represents one of the most consistent and well-established metabolic risk factors for the development and progression of kidney disease. Far from being a passive -energy storage compartment, adipose tissue – -particularly visceral fat accumulation – functions as an active endocrine and immunometabolic organ capable of modulating systemic inflammation, insulin sensitivity, oxidative stress, haemodynamics, and neurohormonal signalling [3337]. These perturbations exert direct and indirect effects on renal structure and function, forming the basis of obesity-related- metabolic kidney disease.

From a haemodynamic standpoint, obesity is characterized by increased renal plasma flow, afferent arteriolar vasodilation, and elevated intraglomerular pressure. These early adaptations, largely mediated by hyperinsulinaemia, enhanced tubular sodium–glucose reabsorption, and heightened RAAS and sympathetic nervous system activity, culminate in glomerular hyperfiltration [3638]. Persistent hyperfiltration contributes to enlargement of glomerular tuft volume and sets the stage for podocyte hypertrophy, detachment, and loss – events central to the initiation of proteinuria and progressive glomerulosclerosis.

Adipokines are central mediators of renal injury in obesity. Elevated leptin levels promote proliferation of mesangial cells, collagen deposition, and activation of profibrotic pathways, whereas reduced adiponectin impairs endothelial integrity and increases susceptibility to inflammation and oxidative stress [22, 37]. In parallel, secretion of cytokines such as IL6 and TNFα from dysfunctional adipose tissue fuels systemic lowgrade inflammation, promoting renal endothelial dysfunction, altered nitric oxide bioavailability, and microvascular injury.
Histopathological studies have described a recognizable phenotype in obesity-related kidney disease, known as obesity-elated glomerulopathy (ORG). Biopsies commonly reveal glomerulomegaly, mesangial expansion, podocyte -foot process widening, increased extracellular matrix deposition, thickening of the glomerular basement membrane, and variable degrees of tubulointerstitial inflammation and fibrosis [3842]. Although traditionally considered a benign or slowly progressive condition, recent data suggest that ORG may lead to significant proteinuria and decline in kidney function, especially when metabolic risk factors coexist or remain uncontrolled.
Importantly, obesity also amplifies the impact of other metabolic abnormalities – prediabetes, MASLD, dyslipidaemia, and hypertension – enhancing their deleterious effects on the kidney. This synergistic behaviour explains why obesity serves not only as a primary driver of MKD but also as a critical component in mixed metabolic phenotypes.
The recognition of obesity-related MKD underscores the need for early clinical identification of renal stress in individuals with overweight or obesity, even in the absence of diabetes or overt CKD. Given the potential reversibility of early haemodynamic changes and the benefits of weight reduction, pharmacological metabolic modulation, and lifestyle interventions, early detection represents a crucial opportunity for prevention and disease-modifying therapy.

Prediabetes-Related Metabolic Kidney Disease

Prediabetes represents an intermediate metabolic state between normoglycaemia and overt diabetes, characterised by impaired fasting glucose, impaired glucose tolerance, or elevated glycated haemoglobin according to current diagnostic criteria [43]. Although traditionally viewed as a precursor stage with modest clinical implications, accumulating evidence indicates that prediabetes is not a benign condition. Rather, it constitutes a metabolically active and pathophysiologically relevant state capable of inducing early renal injury through mechanisms that parallel, but do not require, sustained hyperglycaemia [4446].
Several epidemiological studies have demonstrated a consistent association between prediabetes and an increased risk of incident CKD, reduced eGFR, and elevated albuminuria. In a prospective cohort exceeding 7,000 individuals with nearly nine years of follow-up, both impaired glucose tolerance and elevated HbA1c were independently associated with new-onset CKD, with hazard ratios ranging from 1.13 to 1.39 [44]. These findings have been confirmed by larger population-based analyses, including the REACTION study involving more than 250,000 Chinese adults, where prediabetes was identified as an independent predictor of CKD, particularly among men [47]. Meta-analyses reinforce this association, suggesting that even modest elevations in glucose metabolism confer a measurable increase in renal risk [46].
From a mechanistic perspective, renal injury in prediabetes is driven primarily by insulin resistance, hyperinsulinaemia, and intermittent postprandial hyperglycaemia. These alterations impair podocyte insulin signalling, reduce nephrin expression, and promote cytoskeletal instability, rendering podocytes more vulnerable to detachment and apoptosis [45, 48]. Concurrently, increased proximal tubular sodium-glucose reabsorption diminishes sodium delivery to the macula densa, blunting tubuloglomerular feedback and favouring afferent arteriolar vasodilation – enhancing glomerular hyperfiltration in a pattern similar to early diabetic kidney disease [45, 48].
Oxidative stress also plays a central role. Elevated production of reactive oxygen species, accumulation of advanced glycation end-products, and activation of protein kinase C pathways contribute to endothelial dysfunction, mesangial expansion, and increased glomerular permeability [48]. These changes manifest clinically as low-grade albuminuria and may precede overt abnormalities in eGFR.
Despite this growing evidence, prediabetes is not currently included among the recommended indications for CKD screening in most clinical guidelines [49]. Given the substantial prevalence of prediabetes worldwide and its clear association with early renal injury, incorporating individuals with prediabetes into CKD risk stratification strategies could facilitate earlier detection of kidney involvement and prompt implementation of preventive interventions.

Diabetes-Related Metabolic Kidney Disease

Type 2 diabetes mellitus (T2DM) remains the most common metabolic condition associated with chronic kidney disease worldwide, and diabetic kidney disease (DKD) continues to represent a major cause of end-stage kidney disease [50]. However, within the conceptual framework of Metabolic Kidney Disease, diabetes-related renal injury is understood not as an isolated entity, but as the intensification and culmination of metabolic disturbances that often originate much earlier – during obesity, insulin resistance, and prediabetes. This perspective highlights the continuity of metabolic stress across the glycaemic spectrum and underscores the shared mechanisms that unite DKD with other MKD subtypes.
Hyperglycaemia initiates and amplifies several interrelated pathways that contribute to renal damage. Among the earliest alterations is glomerular hyperfiltration, driven by increased proximal tubular sodium-glucose reabsorption mediated by SGLT2. This reduces solute delivery to the macula densa, blunts tubuloglomerular feedback, and promotes afferent arteriolar vasodilation, thereby increasing intraglomerular pressure [51]. Persistent hyperfiltration accelerates podocyte hypertrophy and detachment – lesions central to the development of albuminuria.
Glucotoxicity exerts direct cellular effects. Chronic exposure to elevated glucose levels induces oxidative stress, mitochondrial dysfunction, and accumulation of advanced glycation end-products (AGEs). These processes trigger mesangial expansion, altered extracellular matrix turnover, and thickening of the glomerular basement membrane [52, 53]. Importantly, lipotoxicity – driven by elevated circulating free fatty acids and ectopic lipid accumulation – amplifies these pathways by promoting endoplasmic reticulum stress, inflammation, and apoptosis in podocytes and tubular cells [54].
Inflammatory and fibrotic pathways further contribute to disease progression. Activation of protein kinase C (PKC), nuclear factor-κB (NF-κB), and transforming growth factor-β (TGF-β) promotes epithelial–mesenchymal transition, interstitial fibrosis, and glomerulosclerosis [55]. These processes often evolve silently for years before clinical manifestations appear, explaining why many patients show evidence of renal structural injury even at the time of diabetes diagnosis.
Although DKD has traditionally been described as a distinct clinical entity, MKD emphasizes that diabetes-related renal injury represents a continuum of metabolic renal stress, rather than a binary state emerging only after hyperglycaemia surpasses diagnostic thresholds. This broader view aligns with epidemiological observations showing that albuminuria, reduced eGFR, and microvascular injury can be detected in a significant proportion of individuals with newly diagnosed diabetes or even during the prediabetic phase.
Recognising diabetes-related MKD within this continuum has practical implications: it highlights the importance of early interventions targeting hyperglycaemia, insulin resistance, RAAS activation, and metabolic inflammation. Moreover, therapies such as SGLT2 inhibitors and GLP-1 receptor agonists – initially developed for glycaemic control – have demonstrated significant renal and cardiovascular protection precisely because they modulate many of these shared metabolic pathways.

MASLD-Related Metabolic Kidney Disease

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed non-alcoholic fatty liver disease (NAFLD), is now recognised as a multisystem metabolic disorder that extends well beyond the liver. The recent harmonized definitions and clinical practice guidelines issued jointly by EASL, EASD and EASO [56] underline the strong metabolic underpinnings of MASLD and its close association with insulin resistance, visceral fat accumulation, dyslipidaemia and systemic inflammation. This updated framework emphasizes that MASLD frequently coexists with other metabolic conditions and contributes to end-organ damage, including the kidney.
A growing body of evidence indicates that MASLD is independently associated with chronic kidney disease (CKD). A comprehensive and authoritative review by Bilson, [57] summarized epidemiological and mechanistic data supporting a strong association between MASLD and increased CKD risk, even after adjusting for obesity, diabetes and hypertension. These observations confirm that MASLD is not simply a marker of metabolic syndrome but a condition with its own pathophysiological impact on renal structure and function.
Mechanistically, MASLD promotes renal injury through multiple interconnected pathways. Hepatic steatosis triggers the release of hepatokines (e.g., fetuin-A) and other inflammatory mediators, which aggravate insulin resistance, endothelial dysfunction, and oxidative stress. These systemic disturbances impair glomerular autoregulation and increase susceptibility to hyperfiltration and podocyte stress. Disturbances in lipid metabolism characteristic of MASLD facilitate the accumulation of toxic lipid intermediates, contributing to mitochondrial dysfunction and activation of pro-fibrotic cascades within the kidney.
A further layer of complexity arises from genetic predisposition. Variants such as PNPLA3, TM6SF2 and MBOAT7 – well-established determinants of liver disease severity in MASLD – have been associated with increased renal vulnerability, suggesting shared metabolic and inflammatory pathways between hepatic steatosis and CKD [58]. These data reinforce the concept that renal involvement in MASLD is not solely a consequence of coexisting metabolic abnormalities, but reflects intrinsic pathobiological processes linked to the disease itself.
Meta-analytic data continue to support the association between MASLD and kidney dysfunction. The landmark systematic review by Musso and colleagues [59] remains a frequently cited foundational analysis demonstrating increased CKD prevalence and incidence among individuals with NAFLD. While older, its conclusions align with contemporary findings and highlight persistent mechanistic plausibility across diverse populations.
Recognizing MASLD as a distinct subtype within the broader spectrum of Metabolic Kidney Disease has important clinical implications. Given its high global prevalence and frequent underdiagnosis, incorporating MASLD into CKD risk stratification frameworks may facilitate earlier identification of renal involvement. Furthermore, therapeutic strategies targeting hepatic steatosis – such as GLP-1 receptor agonists, weight reduction and lifestyle interventions – may confer renal benefits even in the absence of overt diabetes. As recent guidelines emphasize [60, 61], a comprehensive approach addressing metabolic dysfunction across organ systems represents a crucial step toward improving long-term outcomes.

Mixed Metabolic Kidney Disease

Mixed Metabolic Kidney Disease represents the convergence of multiple metabolic derangements acting simultaneously on renal structure and function. In clinical practice, this phenotype is increasingly common, reflecting the overlap between obesity, insulin resistance, prediabetes, type 2 diabetes, hypertension, dyslipidaemia and MASLD. Rather than functioning as isolated risk factors, these conditions interact through shared mechanisms that amplify metabolic stress on the kidney, accelerating the transition from early functional changes to established chronic kidney disease [38].
From a pathophysiological standpoint, mixed MKD embodies a state in which haemodynamic, inflammatory, hormonal and lipid-related disturbances reinforce one another. Excess visceral fat accumulation fuels chronic low-grade inflammation and adipokine dysregulation, worsening insulin resistance and promoting hyperinsulinaemia [22]. In parallel, progressive impairments in glucose tolerance intensify tubular sodium-glucose reabsorption, stimulating afferent arteriolar vasodilation and glomerular hyperfiltration [45]. When MASLD coexists, the release of hepatokines and proinflammatory mediators further exacerbates endothelial dysfunction, oxidative stress and microvascular injury [50].
These synergistic mechanisms produce a renal phenotype that is often more severe than the sum of its individual components. Patients with obesity and MASLD, for example, exhibit higher rates of albuminuria and more pronounced declines in eGFR compared with individuals with either condition alone [62]. Similarly, the coexistence of prediabetes or early diabetes with hepatic steatosis and visceral fat accumulation results in more rapid structural changes – mesangial expansion, podocyte stress and tubulointerstitial fibrosis – even when glycaemic abnormalities remain modest [63].
Clinically, mixed MKD is frequently under-recognised. Traditional screening strategies tend to focus on single risk factors – most often diabetes – thereby missing individuals who harbour substantial renal risk due to the cumulative effect of multiple metabolic abnormalities. This oversight is particularly relevant in younger or non-diabetic individuals with obesity and MASLD, in whom early renal involvement may be subtle yet progressive.
Recognising mixed MKD as a distinct and increasingly prevalent phenotype underscores the importance of integrated metabolic assessment in the evaluation of CKD risk. A comprehensive approach – including assessment of adiposity, glycaemic status, hepatic steatosis, blood pressure and lipid profile – allows for earlier identification of individuals at high risk and supports targeted interventions aimed at modulating metabolic stress. Ultimately, the mixed MKD phenotype exemplifies the concept of Metabolic Kidney Disease: a continuum of renal injury shaped not by a single metabolic defect, but by the interplay of multiple overlapping disturbances acting across organ systems. Such multilayered interactions are increasingly documented across metabolic phenotypes, supporting the concept of mixed MKD as a clinically relevant and mechanistically distinct entity.

 

Screening and Clinical Implications

The recognition of Metabolic Kidney Disease (MKD) as a unified conceptual framework has important consequences for screening strategies, particularly in populations traditionally not considered at high risk for chronic kidney disease. Current screening algorithms [64] often prioritise individuals with established type 2 diabetes or long-standing hypertension, overlooking a substantial proportion of patients who exhibit renal involvement driven primarily by obesity, prediabetes, MASLD or combinations thereof. As a result, early stages of metabolic renal stress frequently remain undetected [12] until albuminuria or declines in eGFR become clinically evident.

Integrating MKD-oriented screening into routine nephrology workflows could meaningfully shift clinical practice toward earlier detection, streamlined risk stratification, and more timely initiation of preventive interventions, particularly in metabolically vulnerable individuals.

 

Who Should Be Screened?

Given the burden of metabolic dysfunction in modern populations, screening should extend beyond conventional high-risk groups. Individuals with the following characteristics merit evaluation for possible MKD (Figure 3):

  • Obesity with increased visceral fat accumulation, even in the absence of diabetes or hypertension
  • Prediabetes, particularly in those with impaired glucose tolerance or rising HbA1c
  • MASLD, regardless of glycaemic status, as emphasised by recent international guidelines [56]
  • Family history of type 2 diabetes, CKD or early cardiovascular disease [12]
  • Coexistence of multiple metabolic abnormalities, including dyslipidaemia, hyperuricaemia or elevated liver enzymes

In these individuals, glomerular hyperfiltration and endothelial dysfunction – hallmarks of early MKD – may precede measurable reductions in kidney function, highlighting the importance of timely assessment.

It is important to acknowledge that current CKD guidelines still do not formally recommend routine kidney screening in individuals with prediabetes or MASLD. The evidence supporting such an approach is growing, yet prospective validation and consensus-driven recommendations are still needed to define optimal screening thresholds and intervals.

 

What Tests Should Be Performed?

A pragmatic and clinically accessible initial evaluation may include:

  • Estimated glomerular filtration rate (eGFR) using creatinine or combined creatinine-cystatin C equations
  • Urine albumin-to-creatinine ratio (ACR) to detect early glomerular injury
  • Assessment of metabolic health, including fasting glucose, HbA1c, lipid profile, uric acid and markers of hepatic steatosis
  • Imaging, where appropriate, to evaluate hepatic steatosis or adipose distribution

Importantly, mild elevations in ACR or upward drifts in eGFR (suggesting glomerular hyperfiltration) should not be dismissed as normal variants in individuals with metabolic abnormalities, but rather considered potential markers of MKD.

 

Clinical Integration

Incorporating MKD into routine practice involves adopting a more comprehensive view of metabolic health, recognising that renal involvement can occur long before diagnostic thresholds for diabetes or CKD are reached. Early identification enables timely implementation of therapeutic strategies – such as weight optimisation, dietary interventions, metabolic modulation and blood pressure control – that mitigate renal stress and may alter longterm trajectories.

Screening includes estimated glomerular filtration rate (eGFR)
Figure 3. Recommended screening tests for chronic kidney disease (CKD). Screening includes estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (ACR). These tests are recommended for individuals with obesity, prediabetes, hypertension, T2DM, cardiovascular disease, prior AKI, or age >60 years.

 

Conclusions

Metabolic Kidney Disease represents an important conceptual and clinical evolution in our understanding of the interplay between metabolic dysfunction and renal health. This framework offers clinicians a more actionable understanding of metabolic renal risk, promoting earlier recognition of kidney involvement and more timely implementation of prevention strategies. By integrating obesity, prediabetes, type 2 diabetes, MASLD and mixed phenotypes within a single conceptual framework, MKD offers a more coherent representation of the pathophysiological processes driving early kidney injury in contemporary populations. This approach emphasises the central role of adipose tissue dysfunction, insulin resistance, chronic low-grade inflammation and lipid dysregulation as shared mechanisms across the metabolic spectrum.

Recognising MKD broadens opportunities for earlier diagnosis, particularly in individuals who would not be captured by traditional CKD screening criteria. It also underscores the need for multidimensional management strategies that address metabolic dysfunction across organ systems, rather than focusing solely on glycaemic control or blood pressure.

As the prevalence of metabolic disorders continues to rise globally, incorporating the MKD framework into clinical practice may offer a path toward more effective prevention and improved longterm renal and cardiovascular outcomes. This review highlights the importance of a unified, metabolically informed approach to kidney health – an approach that aligns with modern evidence and reflects the complex, interconnected nature of metabolic disease.

 

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Innovations in randomized clinical trials in Nephrology: from study design to patient’s activism

Abstract

Current clinical practice is guided by novel robust evidence from randomized clinical trials (RCT). These studies usually follow a rigorous prospective design with pre-defined visits and planned exams during follow-up. In the context of Nephrology, RCTs have been mainly designed to test the efficacy of new therapies in reducing the risk for kidney failure, estimated Glomerular Filtration Rate decline and mortality or cardiovascular events. However, the progress of informatics is reflected in an improvement and expansion of technologies and innovations in present and future RCTs. We here present some innovations and future directions of RCTs in Chronic Kidney Disease patients.

Keywords: Randomized Clinical Trials, Chronic Kidney Disease, Informatics Innovation, Medical Devices, Albuminuria

Introduction

Randomized clinical trials (RCTs) represent, to date, the most robust research tools for generating evidence on the efficacy and safety of new therapies for a given clinical condition [1]. The reliability of randomized studies lies in their prospective, ad hoc design, in which one group of subjects (controls) is assigned to the standard of care for the condition under investigation, while another group (active treatment arm) receives the standard of care plus the experimental treatment. The assignment to the control or active arm is random and occurs through randomization, which aims to create two groups of patients with similar characteristics (e.g. age, sex, prevalence of patients with type 2 diabetes, or those treated with diuretics), with the only difference being their assignment to either the active treatment or the control group. This randomization tool therefore allows for the optimal isolation and estimation of the effect of the “new” treatment compared to the standard of care in reducing the incidence of a specific clinical outcome (e.g., reduction in proteinuria or admission to dialysis) or in improving the symptoms of a disease (e.g., improving blood pressure or reducing fatigue).

In the field of kidney diseases, numerous randomized studies have been conducted over the past two decades. They have proven the effectiveness of drugs targeting different mechanisms, such as antihypertensives, erythropoiesis-stimulating drugs, and mineralocorticoid receptor antagonists, in terms of nephroprotection, as well as in reducing mortality and cardiovascular (CV) events, across different patient groups (e.g., diabetic, non-diabetic chronic kidney disease, glomerulonephritis) [2].

Recently, there has been an explosive and rapid increase in drugs available to treat kidney diseases, which has simultaneously led to a rise in the number of randomized studies in Nephrology [3]. In this scenario, with the progress and refinement of research tools in association with digital technologies, the design of randomized studies is undergoing innovations that involve the type of patients included, the methods of their inclusion, the monitoring or choice of treatment, the randomization sequence, and the study outcomes (endpoints). In this article, we describe the essential points of randomized studies in Nephrology and the innovations to consider for their accurate and timely interpretation.

 

Principal aspects of a randomized trial in Nephrology

Inclusion criteria

One starting point when designing a randomized study is to establish which type of patients should be included. This leads to the definition of inclusion criteria. The first inclusion criterion should define the disease setting, for example patients with Chronic Kidney Disease (CKD) with or without diabetes, or both. Such a decision may lead to the estimation of a treatment effect in both types of CKD conditions rather than restrict to one of them. For example, canagliflozin, a SGLT2 inhibitor that protects the kidneys from chronic failure, was tested in patients with CKD and diabetes in the CREDENCE trial, whereas similar agents, empagliflozin and dapagliflozin, were tested in both diabetic and non-diabetic CKD in the EMPA-KIDNEY and DAPA-CKD trials [47]. The extremely positive results from these studies influenced the guidelines and clinical practice, leading to changes in drug reimbursement [8].

The other major inclusion criteria in CKD trials are the so called “kidney measures” namely estimated Glomerular Filtration Rate (eGFR) and albuminuria levels. Such a biomarkers-based enrichment in clinical trials is due to the fact that eGFR and albuminuria represent two main predictors of clinical outcomes in patients suffering from CKD [9, 10].  Moreover, the presence of abnormal levels of eGFR and albuminuria allows to reach a significant number of clinical endpoints throughout the study. In previous trials, such as the first studies testing the efficacy of angiotensin converting enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARBs), including the RENAAL and IDNT studies, serum creatinine was used instead of eGFR [11, 12]. For instance, in the RENAAL study, patients with a serum creatinine level of 1.3 to 3.0 mg/dL were included. Later on, serum creatinine was replaced by eGFR, that is considered a more accurate prognostic biomarker [13]. Another lesson from previous trials was the “flexibility” of inclusion criteria. In the DERIVE study, a phase 3 trial designed to test the efficacy and safety of dapagliflozin in early CKD, only patients with CKD stage 3A (eGFR between 45 and 60 mL/min/1.73 m2) on at least two visits were included. Such restriction, albeit of clinical relevance, was associated with a high percentage of screening failure and slowed the study completion. Similarly, the ALTITUDE study (Aliskiren in patients with CKD and diabetes) included patients with albuminuria > 200 mg/g in at least two out three first morning voids or eGFR between 30 and 60 mL/min [14].  A recent post-hoc analysis of the ALTITUDE database highlighted how adopting more flexible criteria, such as lowering thresholds for albuminuria (e.g. >160 mg/g at the second collection) and relaxing thresholds for eGFR (e.g. 25-75 mL/min), can significantly reduce screening failure rates. This approach not only increases the number of eligible patients participating in the study, but also maintains the integrity of the clinical endpoints, without compromising the statistical power of the study. In particular, the intrapatient variability of albuminuria and eGFR values, which can be influenced by factors such as diet, hydration and therapy adherence, suggests that more stringent screening criteria may not be necessary to predict clinical outcomes [15].

Owing to this evidence, recent RCTs have been designed by including CKD patients with lower levels of albuminuria and larger range of eGFR. For example, in the ROTATE-3 study, a 100 mg of 24h-albuminuria, stable on two visits, was considered sufficient to screen and randomize patients. The stability in this case was not interpreted as a value of at least 100 mg/day also on the second measurement, but rather as a difference in albuminuria from the first visit: less than 40 mg/24hr for subjects with albuminuria between 100 and 300 mg/24hr, and less than 20% difference for subjects with albuminuria between 300 and 3500 mg/24hr [16]. Such an implementation was used to warrant a reliable and appreciable evaluation of the treatment effect (eplerenone or dapagliflozin or the combination of both them) in reducing albuminuria after 4 weeks. A further element to take into consideration to enroll patients is the trajectory of the eGFR decline over time. A steeper decline means that patients are at increased risk for future kidney failure and thus are exactly those patients who need a more urgent treatment. A post-hoc analysis of the SONAR trial, a phase 3 trial showing the nephroprotection of atrasentan in CKD and diabetes, demonstrated that treatment effect of atrasentan in terms of kidney failure risk reduction was greater in patients with higher eGFR decline before the trial initiation [17]. Recent trials used the eGFR decline criterion (i.e. eGFR decline > 1 mL/min/year during the 2 years prior to entry in the study based on at least 3 eGFR measurements) to select patients [18].

Outcomes of clinical trials

The outcome or endpoint is defined as the event of interest on which a specific therapeutic intervention should act. In reference to the aforementioned RCTs, the randomization process creates two patient groups that are homogeneous with respect to factors such as gender, age, demographics and blood chemistry characteristics. Each group is assigned a therapeutic protocol to compare the effects of the experimental treatment with those of the standard of care or placebo. In some cases, depending on the study design, the same patient may receive different treatments over time, generally separated by washout periods (the so-called crossover design). What is observed at the end of the study period represents the primary outcome. The primary outcome is crucial in clinical trials because the entire study is designed around its incidence rate (in terms of sample size, duration). Other outcomes that can however be tested as pre-specified or post hoc analyses are the secondary outcomes. The difference in the incidence of the outcome between the treated group and the control group is generally expressed in the form of Relative Risk (RR), defined as the probability that a subject belonging to the group exposed to certain factors (i.e. experimental intervention) develops the outcome compared to the probability that a subject in the unexposed group (i.e. standard of care/placebo) develops the same outcome.

For years, the main hard endpoint evaluated in Nephrology trials was End Stage Kidney Disease (ESKD, that nowadays is also called Kidney Failure or KF), then differentiated into subgroups of persistence of CKD stage 5 (defined by the finding of eGFR < 15 ml/min confirmed on at least two occasions 15-30 days apart), entry into dialysis or arrival at kidney transplantation. The main trials in Nephrology, including the studies that demonstrated the effectiveness of ACEi and ARBs on slowing the progression of kidney damage, have adopted this primary endpoint.

However, it is known that the onset of ESKD may require a long observation period (even over 10 years), generally longer than the duration proposed in the study design [19]. This limit is added to the high rate of failures in the patient screening process, which is far higher than that of trials conducted in other areas of medicine and which, together, account for the important delay recorded in the panorama of scientific research in Nephrology.

To counter this trend, the identification of secondary endpoints or surrogate endpoints that could faithfully anticipate entry into dialysis was proposed as a workaround. Among these, we remember the main ones of reduction of eGFR and albuminuria. While on the first endpoint an eGFR decline of 57-40-30-20% within 3 years was tested, on proteinuria there is still no certain data on the expected reduction necessary to be able to speak of a good response to the treatment.

Despite the attempt by some authors to reduce the threshold of albuminuria among the inclusion criteria of a trial with the aim of increasing the sample of patients enrolled and reducing the study time, there was only a modest reduction in renal and cardiovascular events, contrary to what was expected.

This data was interpreted as a consequence of the variability in the measurement of albuminuria, confirming the importance of extending the inclusion criteria during the screening process to improve feasibility and efficiency of the study [20].

The use of eGFR and albuminuria as secondary outcomes could, on the other hand, reduce the generalizability of the trial results. One could, for example, incur the bias of excluding a given nosological entity such as non-albuminuric CKD, which is known to have an increased prevalence and a high risk of progression towards ESKD [21].

Regarding the reduction in eGFR, historically the main secondary endpoint identified has been an eGFR slope of -57%, generally represented in the form of a doubling of creatininemia. Also in this case, some authors have attempted to identify alternative endpoints with the aim of obtaining greater precision in estimating therapeutic efficacy at the cost, however, of recording a reduction thereof in the absence of a substantial increase in the statistical significance of the study [22]. In any case, the percentage reduction in filtration appears to be the best unit of measurement to estimate the temporal trend of renal function compared to the changes in eGFR in absolute value [19].

Furthermore, it was observed that reducing the percentage slope threshold of the eGFR from 57% to 40% increases the number of patients who develop the outcome, and this data also correlates with a high risk of evolution towards ESKD and mortality [23].

In light of what has been observed, the use of new potential surrogate outcomes such as an eGFR slope equal to – 30/40% on a sample of patients with baseline eGFR < 30 ml/min and a linear filtrate loss recorded in the run period equal to – 5 ml/min/year, could allow the achievement of the outcome and at the same time a reduction in study times.

Among the limitations identified, however, it should not be forgotten that some categories of patients, mainly elderly, non-proteinuric patients, with higher baseline eGFR, observe a non-linear trajectory of renal function which may reduce the predictability of the surrogate endpoints analyzed on the hard endpoints. Furthermore, the various formulas for estimating glomerular filtration take into account factors that can be modified over time, requiring optimization of the precision of the study with the integration of directly measured glomerular filtration values [19].

 

Innovations in the nephrology field of clinical trials

Role of the patient in treatment decisions

In recent decades, the role of the patient has undergone a significant transformation in decision-making processes within randomized clinical trials. In this context, a new doctor-patient relational model has gradually emerged, known as “Shared-Decision Making” (SDM), which involves the sharing of information and decisions between healthcare professionals and enrolled patients, empowering the latter with an increasingly active, informed, and autonomous role [24].

This model has found space since the end of the 1990s in the field of oncology, when various therapeutic options with uncertain outcomes emerged for terminally ill patients.

Thus, an increasingly broad exchange of communication began between the doctor and the patient, in order to involve them in decision-making and increase their awareness in the clinical field (Figure 1).

Figure 1. Innovations in the nephrology field of clinical trials and patients’ role.
Figure 1. Innovations in the nephrology field of clinical trials and patients’ role.

The SDM model is based on four fundamental pillars, as illustrated by some of its pioneers such as Charles and colleagues: 1) equal involvement of medical staff and patients; 2) sharing of information by both; 3) shared participation in drawing up consent to treatment; 4) reaching an agreement on the therapeutic path to follow [25].

The adoption of this model has allowed an ever-increasing participation of patients in trials, with better quality of the trials and construction of more solid evidence.

Greater therapeutic adherence and a reduction in losses during follow-up were also progressively documented, probably as a result of a greater degree of satistaction and psycho-physical well-being on the part of the patients enrolled in these types of trials.

The evidence shows that the use of SDM strategies also allows us to achieve better clinical, behavioral and psychological outcomes compared to those observed in trials with different strategies [26].

If the adoption of this model presents numerous positive implications on a scientific level, those on an ethical level are intuitive, as the priority of these trials is to place the will and needs of the patient at the centre.

However, guaranteeing greater information, awareness and decision-making autonomy implies a greater expenditure of energy and resources such as time and workload, giving more complexity to the decision-making process.

Conflicting circumstances can sometimes arise when the possibility of randomization in the control group or the blinding procedures do not reflect the patient’s wishes [27].

Patients with dementia, or any other type of cognitive dysfunction, also represent a real barrier [28].

Instead, in various circumstances, informing the patient about possible side effects and risks can lead to agitation and confusion, and it is easy to run into misunderstandings [29].

For these reasons, healthcare personnel have made use of Patients Decision Aids (PtDA), i.e. decision-making aids to support patients, consisting of educational materials or easy-to-consult media assistance. These come in the form of smartphone apps, web sources, videos or written documentation such as brochures. In some circumstances, healthcare personnel undergo professional training courses with the aim of acquiring greater communication skills [24].

An international cooperation, the International Patient Decision Aid Standards (IPDAS) Collaboration, was launched specifically to establish the criteria, on the basis of scientific evidence, according to which PtDAs should be drawn up and evaluated, guaranteeing the best possible information and supporting the sharing of decision-making processes [30].

Additionally, the use of questionnaires to assess patients’ preferences for different treatments in a crossover clinical trial is becoming more widespread, and collecting this information will assist clinicians in making personalized treatment decisions. An example is the upcoming FINESSE trial (EU trial number 2023-506434-69-00), in which digital questionnaires will be used to assess patients’ preferences of finerenone or semaglutide, as well as their perspectives on the feasibility of participation in a home-based trial.

New outcomes in current and future RCTs

In addition to monitoring treatment effect with eGFR and albuminuria changes over time (after treatment initiation), novel outcomes are gaining momentum in Nephrology nowadays. To this aim, the International Society of Nephrology is publishing a bi-monthly volume called Global Trial Focus (GTF) reporting the new RCTs related to kidney diseases (herein the link: https://www.theisn.org/in-action/research/clinical-trials-isn-act/). In the GTF, a number of studies tested the effect of treatment on new endpoints, such as quality of life, chronic pain, glycemic control, change in pruritus in different stages of CKD, and others.  The combination of an increasing number of RCTs (mirroring a more feasibility of these studies compared to the past) and more comprehensive endpoints may allow for deeper insights and improve the care of kidney diseases in the future.

Apps that remotely monitor blood pressure

Hypertension affects over a billion people in the world and constitutes a preponderant risk factor for the onset of various diseases, including cardiovascular and renal diseases [31].

It is estimated that approximately 12.8% of global deaths are attributable to this pathology, the treatment of which is based on lifestyle changes and medication.

However, despite the initiation of therapeutic and behavioral measures, hypertension control rates remain suboptimal, with only about half of patients achieving adequate blood pressure control [3133].

Self-monitoring has allowed us to obtain some clinical benefits over time, favoring greater therapeutic adherence and the reduction of some problems such as masked hypertension or “white coat” hypertension [33].

However, further measures are necessary. The demand for health tools to support the problem has grown considerably, due to the significant impact it has on public health and economic resources. In recent years, there has been an ever-increasing interest in digital innovations, as an inexpensive method within everyone’s reach [31, 34].

The Health App market is constantly growing, and thousands of new ones are produced every year. The main fields of interest are, in fact, represented by chronic diseases such as arterial hypertension and diabetes [33].  The invention of sensors and wearable devices, such as Bluetooth bracelets or smartwatches, has made it possible to detect vital parameters such as heart rate, blood pressure, sleep quality and physical activity [35].

Apps that detect blood pressure also offer various additional functions, such as maintaining a daily blood pressure log, organizing records, and providing reminders for measurements and medication. They also provide the patient with basic information on disease, treatment, lifestyle management and how to self-monitor.

There are available also analysis tools that offer an overview of the trend in blood pressure over time, using graphs or tables. Readings and other recorded data can be exported, allowing healthcare professionals to view and analyze them remotely. Most of these apps are available for free [33, 36].

However, sufficient data is not yet available to evaluate the quality and accuracy of these applications. The results obtained so far must be interpreted with caution due to the variance between the sizes of the samples on which the studies were conducted (very often too small and with subjects coming from different populations), due to the heterogeneity of the studies themselves and the use of self-reported scales to measure adherence to treatments. Therefore, research should establish standardized protocols for measuring parameters and reporting adherence. But it is important not to overlook the potential of this type of intervention to implement knowledge of patients’ health status and support self-management towards a healthy lifestyle and adherence to therapy, especially given the ever-increasing role that artificial intelligence is acquiring, which could guarantee significant support [37].

Remote collection of blood and urine samples

One of the challenges in patient participation in clinical trials is the frequency of visits required for monitoring the progress of the study and for collecting biological samples (blood and urine) for analysis. The introduction of new technologies that allow patients to collect blood and urine samples without needing to visit the study center opens up new possibilities for remote protocol monitoring. Examples of validated devices for at-home blood and urine sampling are Hem-Col® and PeeSpot®, respectively. The Hem-Col® tool is an innovative blood collection microtube designed to facilitate capillary blood sampling through a finger prick; the presence of an anticoagulant and a preservation buffer enhances analyte stability in whole blood, allowing the device to be sent to the laboratory for analysis via regular post.  The PeeSpot® is a validated tool for collecting small amounts of urine (about 1.2 mL) through absorption onto a pad, which is held inside a tube. By adding various preservatives, the urine in the PeeSpot® can be preserved for up to 4 days in the refrigerator before being sent to the laboratory for the measurement of urinary albumin and creatinine. These devices represent a practical and efficient solution for both patients and healthcare professionals involved in clinical trials, lowering costs associated with frequent in-patient visits and optimizing the workflow. The FINESSE study (EU trial number 2023-506434-69-00), which will soon be launched, will use both devices for the remote monitoring of enrolled patients.

 

Conclusions

Many randomized studies have been published around kidney disease in the past few years. Taken together, results of randomized studies have allowed to improve guidelines and, at the end, to improve patients’ survival, time free from dialysis and to reduce the number of CV events. Significant progresses have also been made over the past decades in terms of inclusion criteria, outcomes, and patients’role, which will aid the future conduction of randomized studies worldwide.

 

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