Understanding uremic cardiomyopathy: from pathogenesis to diagnosis and the horizon of therapeutic innovations

Uremic toxins accumulation

The accumulation of uremic toxins results from progressive renal function decline, leading to the inefficient elimination of toxins and waste substances from the body. Examples of these toxins include urea, creatinine, phenols, and indoxyl sulfate (IS).

Elevated uremic toxin levels significantly contribute to endothelial dysfunction, which plays a role in cardiovascular diseases such as atherosclerosis and thrombotic events. The accumulation of these toxins can trigger apoptosis in cardiac muscle cells, leading to metabolic abnormalities, oxidative stress, and inflammation, ultimately resulting in myocardial damage (Wojtaszek et al., 2021).

Substances like phosphate and urea are closely linked to cardiovascular events. Phosphate has a multifaceted impact, directly influencing vascular smooth muscle cells (VSMCs) through complex calcium/phosphate interactions, and indirectly through the fibroblast growth factor 23 (FGF23)/Klotho axis and hyperparathyroidism (PTH) pathways (Disthabanchong, 2018).

These toxins also contribute to other cardiac conditions such as fibrosis, arrhythmias, and hypertrophy. IS is linked to atrial fibrillation, intensifying fibrosis and hypertrophy through increased oxidative stress (Pieniazek et al., 2022). Elevated levels of phosphate and urea are also associated with cardiac hypertrophy and fibrosis. High urea levels contribute to systemic inflammation, thickening subepicardial arteries, and collectively exacerbating diastolic dysfunction (Carmona et al., 2011).

Abnormal metabolism of cardiomyocytes

Metabolic dysregulation within cardiac muscle cells plays a crucial role in the pathogenesis of UC, involving impaired mitochondrial function, altered myocardial substrate utilization, and changes in the function and expression of metabolic transport proteins (Nguyen & Schulze, 2023). The accumulation of uremic toxins has been found to hinder mitochondrial function in cardiac muscle cells, leading to oxidative stress and inflammatory responses, both contributing significantly to the advancement of myocardial damage (Sun et al., 2017). This metabolic disruption, involving glucose, lipid, and amino acid metabolism, contributes to myocardial damage progression, leading to cellular injury and apoptosis.

In a study, endothelial dysfunction and recurrent reductions in myocardial blood flow during hemodialysis may contribute to the development of metabolic abnormalities, potentially with regional variations (Kawano, Kudo & Maemura, 2021).

Furthermore, metabolic irregularities in cardiac muscle cells may impact cardiac neuroendocrine function, potentially leading to a spectrum of disorders, including arrhythmias, myocardial hypertrophy, and impaired cardiac diastolic function (Nguyen & Schulze, 2023).

Inflammation and oxidative stress

Oxidative stress (OS), defined as the disequilibrium between excessive prooxidant activities and the defense mechanisms of antioxidants, induces metabolic dysregulation, leading to the oxidation of lipids, proteins, and nucleic acids. Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are responsible for oxidative damage to cells, tissues, and organs (Di Meo et al., 2016).

In the early phases of renal disease, OS is evidently heightened, characterized by an imbalance in ROS production and degradation, including uncoupling of nitric oxide production. This imbalance contributes to endothelial damage, serving as a risk factor for congestive heart failure (CHF) by affecting cardiac microcirculation and inducing endothelial dysfunction (Sárközy et al., 2018).

CKD creates a persistent low-grade inflammatory state, involving cytokines such as C-reactive protein (CRP), interleukin-6 (IL-6), pentraxin-3, tumor necrosis factor-alpha (TNF-alpha), adhesion molecules, and fibrinogen (Filiopoulos & Vlassopoulos, 2009).

Uremic toxins, including IS, p-cresol (PC), and p-cresol sulfate (PCS), are implicated in cardiovascular diseases among CKD patients, primarily inducing endothelial dysfunction and vascular calcification through OS and inflammation (Ribeiro et al., 2023). Uremic toxins are also implicated in neurodegenerative disorders associated with CKD, escalating oxidative stress in glial cells and downregulating the transcription factor Nrf2, leading to decreased expression of cytoprotective and antioxidant enzymes. Meanwhile, dialysis contributes to increased OS through various mechanisms, including the use of bioincompatible membranes and fluids, dialysate contamination with bacterial endotoxins, and occult infections (Rodríguez-Ribera et al., 2017).

Insulin resistance and metabolic abnormality

Insulin resistance, a common occurrence in patients with CKD, stands as an independent risk factor for cardiac disease in this population (Sebastian, Padda & Johal, 2024). Factors contributing to this disruption include increased angiotensin II, inflammation, metabolic acidosis, and uremic toxins (Thomas, Zhang & Mitch, 2015).

Underlying insulin resistance in patients with uremia disrupts the balance of insulin’s pleiotropic effects. Metabolic acidosis in CKD contributes to uremic insulin resistance, as correcting pH has been shown to improve the insulin sensitivity of glucose metabolism (Spoto, Pisano & Zoccali, 2016).

Insulin resistance affects the heart through various mechanisms, by downregulating sodium-calcium exchange, decreasing myosin ATPase activity, and upregulating angiotensin II, ultimately resulting in reduced cardiac efficiency (Singh et al., 2008).

In uremia, insulin resistance may exacerbate metabolic remodeling in the heart by limiting the uptake and metabolism of glucose, predisposing the uremic heart to progress into chronic energy deficiency and eventually heart failure.

Cardiac structure abnormality

UC is characterized by a combination of LVH, diastolic dysfunction, capillary rarefaction, endothelial dysfunction, and cardiac fibrosis. These factors collectively contribute to the development of heart failure (HF) (Sárközy et al., 2018). These findings highlight the significance of the underlying fibrotic process and myocardial edema as fundamental mechanisms in the pathophysiology of UC. Initially viewed as a beneficial adaptive response in the early phases of UC, LVH becomes maladaptive as progressive LV overload induces detrimental changes in cardiomyocytes, ultimately leading to cell death (Garikapati et al., 2021).

UC-associated LV hypertrophy results from complex pressure overload, volume overload, and the uremic state itself. Some authors suggest a higher proportion of deaths in these patients attributed to LVH and congestive heart failure, surpassing those caused by coronary artery disease (Alhaj et al., 2013). Within the uremic heart, elevated expression of profibrosis mediators such as transforming growth factor beta (TGFβ) and connective tissue growth factor (CTGF) leads to increased collagen levels, contributing to interstitial fibrosis. This, in turn, contributes to diastolic dysfunction, ventricular stiffness, and cardiac dysrhythmias (Lekawanvijit et al., 2012).

CKD-MBD

Chronic kidney disease-mineral and bone disorder (CKD-MBD) is a significant contributor to UC. A comprehensive understanding of CKD-MBD’s role in cardiomyopathy development necessitates the analysis of key factors such as PTH, phosphate, fibroblast growth factor-23 (FGF-23), and Klotho. The crucial role of phosphate in CKD-MBD is notable, and its toxicity is implicated in contributing to cardiovascular mortality (Ritter & Slatopolsky, 2016).

CKD patients often experience deficiencies in renal excretory capacity, leading to significant upsurges in FGF-23 levels as a compensatory response to preserve phosphate levels. These elevated FGF-23 levels have been associated with cardiovascular disease (CVD) and mortality in a dose-dependent fashion (Vergaro et al., 2018). The kidney-expressed transmembrane protein, Klotho, acts as a co-receptor for FGF-23, playing a role in mediating phosphate regulation. Emerging data suggests that FGF-23 and Klotho collaboratively contribute to UC in a coadjutant manner (Memmos & Papagianni, 2021).

The mechanism underlying myocardial dysfunction in hyperparathyroidism is believed to involve the uncoupling of oxidative phosphorylation, resulting in reduced cellular ATP concentrations and impaired calcium extrusion. This, in turn, leads to calcium overload in cardiomyocytes (Ahmadmehrabi & Tang, 2018).

MicroRNAs and molecular regulation

Specific microRNAs (miRNAs) have been identified as significant roles in the development and progression of UC (Table 1). UC is characterized by myocardial remodeling, fibrosis, and impaired response to injury. Among the miRNAs, miR-26a is decreased in CKD mouse hearts and helps alleviate cardiac fibrosis and improve cardiac function when administered (Wang et al., 2019).

The miR-30 family plays a role in modulating autophagy, apoptosis, and oxidative stress in cardiomyocytes, with lower expression linked to renal damage and CKD-induced cardiac hypertrophy (Bao et al., 2021). miR-29b-3p has an antifibrotic effect via the Na/K-ATPase signaling pathway, where its downregulation leads to increased cardiac fibrosis (Drummond et al., 2016). miR-212/132 promotes LVH and heart failure by repressing FoxO3 under pressure overload conditions, with increased levels observed in CKD (Ucar et al., 2012).

Other notable miRNAs include miR-208, which modulates α-myosin heavy chain (α-MHC) and myocardial fibrosis, crucial for heart remodeling and regulated by thyroid hormones (Prado-Uribe et al., 2013). These miRNAs are promising biomarkers for diagnosis, prognosis, and therapeutic targets in UC, with ongoing research aimed at understanding their complex molecular mechanisms to improve care for CKD and ESRD patients.

Potential applications and challenges of AI in the diagnosis and biomarker discovery of uremic cardiomyopathy

AI-based image recognition is transforming the diagnosis of UC, enabling faster and more accurate analysis of cardiac imaging data than traditional methods. Deep learning models, trained on extensive datasets of UC cases, can minimize human error and accelerate diagnosis, especially in clinical settings where early detection is vital for treatment planning (Elias et al., 2024; Glass et al., 2022). This section explores the potential group designs, data categories for AI analysis for identifying early biomarkers, and challenges that may arise during implementation.

Control group design for early biomarkers

To identify early biomarkers, appropriate control group design is crucial. The design should consider the disease’s early characteristics and potential confounders. Some options include:

• Healthy control vs. patient groups: Age-, sex-, and clinical feature-matched healthy volunteers serve as a baseline, while patient groups can be divided into early-stage CKD patients (without significant cardiac symptoms) and end-stage patients (with obvious uremic cardiomyopathy symptoms).

• CKD control group: CKD patients without cardiac abnormalities can be used to distinguish kidney-specific effects from cardiomyopathy-related changes. A normal kidney function group can further isolate kidney and heart health factors.

• Disease progression groups: Patients with UC can be grouped by acute and chronic phases to identify biomarkers relevant to early vs. advanced stages.

• Clinical and laboratory-based groups: Clinical risk stratification groups can focus on high-risk patients based on factors like blood pressure or proteinuria. Biochemical marker-based groups can be stratified by kidney and cardiac markers to identify early cardiac damage.

• Dynamic monitoring vs. cross-sectional groups: A dynamic monitoring group can track longitudinal changes in biomarkers, while a cross-sectional group provides a snapshot for quick identification of early biomarkers.

Data for AI-based disease recognition in uremic cardiomyopathy

AI-based disease recognition can benefit from various data types:

1. Blood biomarkers: Uremic toxins, inflammatory markers, and cardiac biomarkers help assess disease severity and progression.

2. Fluid biomarkers: Data from body fluids (e.g., urine, peritoneal fluid) can provide insights into systemic effects of uremic toxins.

3. Cardiac imaging: MRI, CT, and PET scans offer comprehensive data on heart structure and function.

4. Genetic testing: AI can use genetic data to identify at-risk patients before symptoms arise.

5. Myocardial biopsy: Histological data from myocardial biopsies can enhance AI models by revealing cellular changes in the heart muscle.

Challenges and solutions

Several challenges need to be addressed to optimize AI in diagnosing UC:

1. Data quality and variability: AI models require high-quality, consistent data. Variability in imaging, demographics, and disease stages can limit generalizability. Larger, more diverse datasets and standardized protocols are needed to improve consistency.

2. Interpretability and clinical integration: Deep learning models are often “black-box,” making predictions difficult to interpret. Developing explainable AI models will enhance clinician trust and usage.

3. Regulatory and ethical issues: Data privacy, validation, and regulatory concerns must be addressed to ensure AI systems are safe, reliable, and compliant with clinical standards.

Angiotensin-converting-enzyme inhibitors and angiotensin II receptor blockers

At present, angiotensin-converting-enzyme inhibitors (ACEi) and angiotensin II receptor blockers (ARBs) are the primary therapeutic drugs for UC, serving to counteract the effects of the renin-angiotensin-aldosterone system (RAAS). ACEi/ARBs contribute to improved vascular endothelial function, enhanced fibrinolysis, and the antagonism of vascular smooth-muscle cell proliferation and plaque rupture (Poskurica & Petrović, 2014).

Sacubitril/valsartan functions as an angiotensin-receptor neprilysin inhibitor. By acting as an antagonist to angiotensin II receptors, sacubitril/valsartan can impede the activation of the RAAS, thereby reducing vasoconstriction and cardiomyocyte fibrosis. Additionally, neprilysin inhibition prevents the breakdown of natriuretic peptides, thus enhancing their activity. This leads to vasodilation, increased natriuresis, and decreased cardiac workload (Vaduganathan et al., 2020). A post hoc analysis of the PARAGON-HF trial revealed that serum levels of NT-proBNP and cardiac troponin T were notably reduced in the sacubitril/valsartan group compared to the valsartan group. This suggests that sacubitril/valsartan is more effective in reducing ventricular hemodynamic stress and safeguarding against cardiomyocyte damage (Chandra et al., 2019). Furthermore, sacubitril/valsartan significantly elevates circulating cGMP levels, suppresses the expression of gene programs associated with cardiac fibroblasts, diminishes fibroblast activation and proliferation, enhances myocardial flexibility, and slows down cardiac hypertrophy and remodeling (Mochel et al., 2019).

Vericiguat

Medications targeting the nitric oxide (NO), soluble guanylate cyclase (sGC), and cyclic guanosine monophosphate (cGMP) pathway for treating heart failure are gaining increasing attention. As a secondary messenger, cGMP functions include vasodilation, inhibition of platelet aggregation, suppression of smooth muscle proliferation, and anti-cardiac remodeling, anti-proliferative, and anti-inflammatory effects (Murad, 2006). Vericiguat, an sGC stimulator, serves as a novel targeted therapy for heart failure. It operates by activating the NO-sGC-cGMP pathway, resulting in vasodilation and amelioration of cardiac remodeling (Armstrong et al., 2020). However, additional research is needed to explore the feasibility of adding vericiguat to standard heart failure treatment in patients with an eGFR < 30 mL min⁻¹ (1.73 m²)⁻¹.

Vitamin D

Furthermore, the significance of vitamin D is becoming increasingly recognized. Supplementing vitamin D in hemodialysis patients led to a notable decrease in PTH levels, an elevation in LV fiber fraction shortening, and an increase in the mean velocity of LV fiber shortening (D’Amore et al., 2017).

Insulin sensitizers

Recent data suggests that insulin sensitizers, such as PPAR-gamma agonists like rosiglitazone and pioglitazone, may partially restore lost insulin-mediated protection in the uremic population. These drugs offer multifaceted benefits, including anti-inflammatory, antihypertensive, anti-proteinuric, and insulin-sensitizing effects (Hung & Ikizler, 2011).

Renal replacement therapy

Regardless of pharmacotherapy, the ultimate treatment for UC typically involves renal replacement therapy, including hemodialysis, peritoneal dialysis, or renal transplantation. Conventional hemodialysis is the most common treatment for UC. Numerous studies have shown that hemodialysis enhances reverse cardiac remodeling and reverses certain clinical consequences of UC, making it a crucial treatment (Adhyapak & Iyengar, 2011). Indeed, the strikingly elevated incidence of cardiovascular events and the severity of LVH have shown a significant reduction following successful kidney transplantations (Diakos et al., 2016).

Other candidate drug targets

Neuregulin-1β (NRG-1β) is a stress-induced paracrine transmembrane growth factor released by endothelial cells. It plays a crucial role in embryonic cardiac development. Dysregulation of NRG-1β expression has also been associated with various cardiovascular diseases, including myocardial infarction and HF (Geissler, Ryzhov & Sawyer, 2020). The administration of recombinant human NRG-1β (rhNRG-1β) protein has been shown to protect against myocardial ischemia/reperfusion injury and cardiac fibrosis, as well as to promote cardiac repair following myocardial infarction (Liu et al., 2006). Sárközy et al. (2023) conducted the first study demonstrating that treatment with rhNRG-1β can prevent the progression of renal dysfunction and UC, and also reduce circulating levels of uremic toxins in a rat model of chronic kidney disease (CKD). Therefore, rhNRG-1β may represent a novel and promising therapeutic strategy in translational studies aimed at treating UC.

Clinicaltrials

Through consulting relevant databases (https://clinicaltrials.gov), we have identified several clinical trials on pharmacological treatment for UC. One completed single-center, randomized controlled trial investigated the impact of intravenous L-carnitine (1,000 mg per dialysis session) on myocardial fatty acid metabolism in hemodialysis patients over the course of one year before and after administration. Additionally, a recruitment is currently underway to explore the efficacy and safety of colchicine as an anti-inflammatory treatment for UC.

Shortcoming

Currently, the efficacy of available drug treatments for UC is limited, and there are few clinical trials for these drugs. We aim to explore potential drug targets and drug discovery strategies to address this issue.

Strategies for developing therapeutic drugs for UC

Developing effective therapies for UC is challenging due to the disease’s complexity and multifactorial nature. UC is driven by uremic toxin accumulation, chronic inflammation, oxidative stress, calcium-phosphate disturbances, and immune dysfunction. Targeting these mechanisms offers potential, but the lack of specific drugs highlights the need for new strategies. Below, we discuss approaches for UC drug development, focusing on neutralizing uremic toxins, identifying targets, and exploring new drug strategies:

(1) Neutralizing uremic toxins: Uremic toxins contribute to UC by inducing oxidative stress, inflammation, and endothelial dysfunction. Neutralizing or removing these toxins is a promising approach.

• Targeting specific toxins: Certain uremic toxins, like indoxyl sulfate and AGEs, accelerate UC. Developing inhibitors or binders to neutralize these toxins could mitigate their effects. Adsorbents, such as activated charcoal or resins, may be used during dialysis to remove these toxins from the bloodstream.

• Enzyme-based detoxification: Enzyme therapies and gut microbiota modulation via probiotics could degrade toxins like indoles and phenols, reducing their absorption and accumulation.

• Dialysis enhancements: Improving dialysis techniques, like high-flux hemodialysis, could enhance toxin removal, especially for larger molecules or toxins that affect the heart.

(2) Target identification for UC: Identifying molecular targets involved in UC is essential for developing specific therapies. Key targets include:

• Inflammatory pathways: Inflammation plays a critical role in UC. Targeting inflammatory cytokines (e.g TNF-α, IL-6) or their receptors could reduce myocardial injury (Yamaguchi et al., 2022). Anti-inflammatory agents, such as monoclonal antibodies, are being explored.

• Oxidative stress regulators: Targeting the Nrf2 pathway or sirtuins may reduce oxidative stress and improve heart function, offering potential for UC treatment (Liu et al., 2022).

• Calcium-phosphate disturbances: Targeting the FGF23-Klotho pathway or phosphate transporters could restore calcium-phosphate balance and prevent vascular calcification, improving cardiac function (Grabner & Faul, 2016).

• Fibrosis and remodeling: Targeting fibroblast activation and collagen deposition may prevent myocardial stiffening. Drugs inhibiting TGF-β or the SMAD pathway could reduce fibrosis and enhance myocardial compliance.

(3) Repurposing existing drugs: Repurposing FDA-approved drugs for other conditions offers a promising strategy for UC treatment. Drugs targeting inflammation, oxidative stress, or fibrosis—like statins, ACEi and ARBs—may be effective in UC. Machine learning and big data analysis of existing drug libraries could accelerate the repurposing process for UC.

Enhancing practical value for clinicians in managing chronic kidney disease and uremic cardiomyopathy patients

Managing CKD and UC is challenging due to the interplay of uremic toxins, cardiovascular complications, and comorbidities. A clearer framework for patient management can improve outcomes through informed treatment decisions, early intervention, and enhanced monitoring.

Early diagnosis, prognosis, and monitoring

Early detection of UC in CKD patients is difficult due to a lack of specific biomarkers and guidelines. Integrating multi-omics data, machine learning, and imaging can aid early diagnosis, allowing timely interventions to slow UC progression. Nephrologists monitor renal function, cardiologists assess cardiac involvement, and diagnostic specialists use advanced imaging to detect abnormalities. Real-time biomarkers and monitoring technologies will enable proactive care and reduce complications.

Targeted therapeutic strategies and interdisciplinary collaboration

Developing novel drugs and repurposing existing ones will offer specific treatment options targeting inflammation, oxidative stress, fibrosis, and toxin neutralization. Clear treatment algorithms will assist nephrologists and cardiologists in managing UC alongside CKD. Pharmacologists assess drug efficacy and safety, while a multidisciplinary approach involving nephrologists, cardiologists, endocrinologists, and pharmacologists will improve patient care by addressing renal, cardiac, and metabolic aspects.

Personalized medicine and optimized treatment plans

Personalized medicine allows treatment plans based on genetic, molecular, and clinical data. Endocrinologists manage metabolic disturbances, while nephrologists and cardiologists focus on kidney and heart care. Personalized approaches help optimize interventions like dialysis and adjust dietary regimens. These strategies improve drug efficacy and reduce adverse effects.

Education, training, and continued research

Clinicians must stay updated on the latest research, therapies, and technologies related to UC and CKD. Incorporating innovations into clinical practice guidelines and continuous training programs ensures that healthcare providers are equipped with the necessary tools to manage these conditions effectively.