Renal Artery Function and Histopathology Linked to Plasma and Fecal Metabolites in Heart Failure Patients

Summary

Here, we present a protocol for developing a multimodal platform for elucidating cardiac metabolite-driven renal vascular dysfunction in cardiorenal syndrome.

Abstract

The gut microbiota and its associated host-microbe co-metabolites are increasingly recognized as key regulators of systemic metabolic balance and the cardiorenal axis, particularly within the context of cardiorenal syndrome. Although clinical evidence indicates that cardiac dysfunction may initiate or exacerbate renal pathological alterations, the key metabolic signaling molecules mediating the cardiorenal axis and their underlying mechanisms remain elusive. This study establishes a novel systematic research platform integrating cardiometabolic signatures with renal vascular function analysis, comprising: (1) Isolation and extraction of plasma/fecal metabolites from heart failure patients; (2) Ex vivo renal vascular isolation and primary culture techniques; (3) A multimodal evaluation framework for cardiorenal metabolic interactions, incorporating vascular functional assays, molecular biochemical tests for renal vascular injury markers, and histopathological analyses. Compared with healthy controls, metabolites from heart failure patients impaired renal vascular function and induced inflammatory responses, highlighting their potential as functional biomarkers in cardiorenal syndrome. This study does not focus on a specific metabolite; therefore, further identification and validation of the specific types of metabolites that exert pathogenic effects will be required in future studies using analytical techniques such as LC-MS/MS and NMR. Application of this platform revealed that cardiac disease-associated metabolites impair renal vascular function and homeostasis. These findings provide mechanistic insight into the metabolic drivers of cardiorenal interactions and offer a translational tool for identifying novel biomarkers and therapeutic targets.

Introduction

Cardiorenal Syndrome (CRS) is a complex pathological condition characterized by bidirectional damage between the heart and kidneys. The intricate interdependence between these two organs was first described by Robert Bright in 1836, who systematically documented significant structural changes in the heart associated with advanced kidney disease¹. The prevalence of CRS is strongly linked to the coexistence of cardiovascular disease (CVD) and chronic kidney disease (CKD). Studies indicate that approximately 30% of heart failure patients also have CKD, while 44%-51% of deaths in CKD patients are directly attributed to cardiovascular events².

The management of CRS presents several significant challenges. First, clinical care remains fragmented, with a lack of interdisciplinary coordination and early warning mechanisms, often leading to delayed interventions during the decompensation phase³. Second, current treatment strategies face a paradoxical dilemma. Conventional therapies, such as diuretics and renin-angiotensin-aldosterone system (RAAS) inhibitors, can alleviate heart failure symptoms⁴; however, their prolonged or high-dose use may activate the RAAS and sympathetic nervous system (SNS), exacerbating renal hypoxia and fibrosis, ultimately contributing to diuretic resistance and worsening renal function⁵. Similarly, while angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) can mitigate cardiorenal damage, their clinical use is often limited due to concerns over elevated serum creatinine or hyperkalemia, with only 30%-40% of patients able to tolerate long-term therapy⁶.

Given these challenges, there is an urgent need to identify effective early biomarkers and achieve a deeper understanding of CRS pathogenesis to facilitate the discovery of novel therapeutic targets. However, current limitations in identifying actionable mediators of cardiorenal crosstalk -- particularly disease-specific metabolites that directly link cardiac dysfunction to renal vascular injury -- hinder progress in resolving these unmet clinical needs. Emerging evidence suggests that cardiac disease-associated metabolites may serve as both diagnostic biomarkers and mechanistic drivers of CRS by reprogramming renal vascular homeostasis, yet their spatiotemporal roles in initiating or amplifying renal injury remain poorly characterized^7,8,9. Recent studies have demonstrated that endogenous metabolites such as ceramides can actively aggravate vascular inflammation and remodeling, particularly under cardiorenal conditions, highlighting the broader relevance of metabolite sensing in vascular pathology¹⁰.

Among the renal compartments affected in CRS, the vasculature is increasingly recognized as a primary and early target of injury. Endothelial dysfunction in the renal microcirculation -- marked by impaired nitric oxide bioavailability, oxidative stress, and elevated expression of pro-inflammatory and pro-thrombotic mediators -- contributes to microvascular rarefaction, increased vascular permeability, and regional hypoxia¹¹. In parallel, vascular smooth muscle cells (VSMCs), which are essential for regulating arterial tone and compliance, are also vulnerable to metabolic dysregulation in CRS. Accumulating evidence indicates that disease-associated metabolites can disrupt VSMC contractility, promote maladaptive remodeling, and contribute to increased vascular stiffness and impaired renal perfusion. Despite their fundamental role, smooth muscle-driven mechanisms of vascular dysfunction remain underexplored in current CRS models^8,12. These pathophysiological changes not only exacerbate renal damage but also promote maladaptive neurohormonal activation and systemic hemodynamic disturbances, further impairing cardiac function and perpetuating CRS progression¹³. Thus, targeting renal vascular injury offers a mechanistically informative window into the early pathogenesis of CRS and provides a rational focus for investigating heart-kidney metabolic interactions.

To address these gaps, our study prioritizes the systematic identification and functional validation of heart failure-associated metabolites as central regulators of CRS progression. This work bridges the critical disconnect between observational biomarker discovery and mechanistic pathogenesis research by delineating how these metabolites induce renal vascular dysfunction, activate inflammatory cascades, and compromise tissue repair mechanisms. Traditional models used to study CRS -- including animal models, in vitro cell cultures, and induced pluripotent stem cell (iPSC)-derived organoids -- each have limitations¹⁴. Animal models suffer from interspecies differences that limit clinical relevance. In vitro cultures lack organ-level integration, while iPSC-derived organoids-although capable of modeling cardiomyocyte-tubular epithelial cell interactions-remain functionally immature and are limited to early developmental stages¹⁵. Furthermore, current vascular organoid systems primarily consist of endothelial monolayers or primitive microvessels, lacking the contractile smooth muscle layer and functional readouts necessary to assess vessel-level responses to metabolic injury¹⁶.

In contrast, our platform employs human-derived cardiac metabolites and ex vivo human renal vasculature, allowing physiologically relevant and structurally intact ex vivo human renal arteries, enabling physiologically relevant and mechanistically informative analysis of cardiorenal metabolic interactions at the vascular interface. This provides a unique advantage in modeling the inter-organ metabolic communication that underlies cardiorenal syndrome progression. Our pioneering integrated cardiorenal research platform synergizes three core innovations: metabolomic profiling of heart failure-derived plasma/fecal metabolites, ex vivo renovascular isolation/culture systems, and multimodal functional-molecular-histopathological evaluation. Each component of this platform was optimized for reproducibility and translational relevance, including the use of 200 µL of plasma or 0.1 g of fecal material per sample, incubation of 2 mm human renal artery segments at 37 °C with 5% CO₂ for up to 24 h, and quantitative real-time polymerase chain reaction (qRT-PCR)-based detection of vascular injury markers. This system not only deciphers the diagnostic potential of metabolite signatures but also directly links their causal contributions to CRS pathology, enabling therapeutic target identification through molecular-level mapping of inter-organ metabolic dysregulation. By bridging mechanistic discovery with clinical translation, this dual-focused paradigm shifts CRS management from reactive symptom control to proactive biomarker-driven interventions.

Protocol

The experimental protocols and case methodologies employed in this study were ethically approved by the Urology Department at Peking University First Hospital (Ethical Review Code: 2023yan500-002) and Peking Union Medical College Hospital (approval No. I-23PJ585), with strict adherence to the principles outlined in the Declaration of Helsinki. For this study, we recruited male or female patients hospitalized in Peking Union Medical College Hospital (PUMCH) from July 2019, diagnosed with heart failure (HF) by at least two experienced cardiologists. A total of four HF patients (HF1-HF4) were included for plasma and fecal metabolite extraction. Written informed consent was obtained from all subjects before their inclusion in the research. The experimental apparatus and reagents are shown in the Table of Materials.

1. Plasma and fecal sample processing-polar metabolite extraction

1. Sample collection
   1. Collect all plasma and fecal samples in sterile, precooled collection tubes and immediately flash-freeze them in liquid nitrogen post collection. Store the samples at -80 °C until processing.
   2. To ensure metabolite stability, process all samples within one freeze-thaw cycle, and do not let the time interval between sample collection and extraction exceed 2 weeks.
      NOTE: These measures were taken to minimize metabolite degradation and ensure reproducibility in downstream metabolomic analyses.
   3. Extract metabolites from fecal and plasma samples following protocol steps 1.3 or 1.4, respectively.
2. Study population
   1. Take baseline blood pressure measurements and record medication histories of all participants.
   2. Collect patient samples before any acute clinical deterioration, excluding individuals with major metabolic comorbidities (e.g., diabetes, primary hypertension) to minimize confounding factors in metabolomic analysis (Supplemental Table S1).
   3. Obtain clinical information for each subject using standard procedures.
3. Plasma extraction
   1. Centrifuge raw serum at 14,000 × g for 10 min (4-8 °C). Collect the supernatant into new 1.5 mL microcentrifuge tubes.
   2. Add chilled (-80 °C) HPLC-grade methanol to achieve 80% (v/v) methanol concentration. Mix gently by inversion and incubate at -80 °C for 6-8 h.
   3. Centrifuge at 14,000 × g for 10 min (4-8 °C). Transfer the methanolic supernatant to fresh tubes for metabolomic profiling.
      ​NOTE: Place the plasma samples after collection in a -80 °C freezer within 2 h, and minimize freeze-thaw cycles to ensure metabolite stability.
4. Fecal extraction
   1. Add 500 µL of HPLC-grade methanol (precooled to -80 °C) to fresh or frozen fecal samples in 1.5 mL microcentrifuge tubes. Homogenize using a micro-pestle/tissue homogenizer on dry ice for 1-2 min, followed by vortexing (1 min at 4-8 °C) and incubation at -80 °C for 4 h.
   2. Centrifuge at 14,000 × g for 10 min (4-8 °C) using a refrigerated centrifuge. Transfer the supernatant to new 1.5 mL microcentrifuge tubes; store at -80 °C until step 1.4.4.
   3. Resuspend the pellet with 400 µL of prechilled (-80 °C) HPLC-grade methanol. Vortex thoroughly (1 min at 4-8 °C) and incubate at -80 °C for 30 min.
   4. Repeat centrifugation (14,000 × g, 10 min, 4-8 °C). Combine the supernatants from both extraction phases.
   5. Perform a final clarification centrifugation (14,000 × g, 10 min, 4-8 °C). Transfer the purified supernatant to sterile 1.5 mL tubes for downstream analysis.
      NOTE: Place the fecal samples after collection in a -80 °C freezer within 2 h, and minimize freeze-thaw cycles to ensure metabolite stability.

2. Renal artery isolation

1. Participant selection and tissue collection
   1. Screen patients undergoing radical nephrectomy for renal cell carcinoma. Include only those aged ≥ 18 years without metabolic comorbidities (e.g., primary hypertension, diabetes mellitus). During surgery, collect histologically normal renal parenchyma located at least 3 cm from tumor margins.
   2. Immediately immerse the harvested specimens in oxygenated Krebs-Henseleit buffer (4 °C, pH 7.4; composition in mM: 119.0 NaCl, 4.7 KCl, 2.5 CaCl₂, 1.0 MgCl₂, 25.0 NaHCO₃, 1.2 KH₂PO₄, 11.0 glucose). Complete the isolation procedures within 6 h of surgery.
2. Renal tissue preparation
   1. Perform coronal sectioning in 4 °C Krebs buffer to obtain heminephric specimens containing intact hilar structures. Perform microdissection using a stereomicroscopic system (40x magnification) to expose renal arcuate artery branches and identify arcuate arteries.
3. Microvascular dissection
   1. Achieve precise isolation of arterial segments through sequential removal of perivascular adventitial tissue using micro-corneal scissors.
   2. Preserve the arterial segments with a diameter of approximately 500 µm.
   3. Minimize endothelial shear stress through tension-free manipulation with micro-forceps. Carry out the dissection under hypothermic conditions (4 °C) with Krebs buffer renewed every 15 min to preserve physiological pH and ionic homeostasis.
      NOTE: Explicit quantification of arterial dimensions and buffer composition, a thermally regulated workflow from procurement (4 °C) to processing (4 °C), and complete microvascular dissection within 6 h post specimen collection ensure optimal tissue viability and functional integrity.

3. Renal artery incubation with cardiac injury metabolites

1. Vascular tissue preparation: Dissect renal arteries microsurgically under sterile conditions, and meticulously remove the adherent perivascular connective tissue using fine ophthalmic forceps. Section the isolated renal arteries into 2 mm segments using sterile microscissors for subsequent organotypic culture.
2. Antibiotic decontamination: Wash the vascular segments for 3 x 5 min with phosphate-buffered saline (PBS) supplemented with triple antibiotic/antimycotic cocktail to minimize microbial contamination and ensure sterility prior to metabolite exposure.
3. Experimental grouping: Randomly assign vascular segments to four experimental cohorts and transfer to 24-well culture plates containing 500 µL of Dulbecco's Modified Eagle Medium per well.
4. Metabolite intervention
   1. Add metabolites from the following groups: 1) Healthy control plasma-derived metabolites (HC-P); 2) Heart failure patients' plasma-derived metabolites (HF-P); 3) Healthy control feces-derived metabolites (HC-F); 4) Heart failure patients' feces-derived metabolites (HF-F).
   2. Reconstitute metabolite extracts in methanol (HPLC-grade) and administer 10 µL of each extract into the corresponding well of the 24-well culture plate, which contains 500 µL of Dulbecco's Modified Eagle Medium and renal artery segments (final solvent concentration of 2% (v/v)). Add equivalent volumes of vehicle (methanol/PBS mixture) to the control wells.
5. Culture conditions: Incubate the plate assemblies under standard cell culture conditions (37 °C, 5% CO₂, 95% humidity) for 24 h using a humidified incubator.

4. Renal artery ring assay

1. Renal arterial ring suspension and fixation
   1. Wire preparation: Thread two parallel 2 cm stainless steel wires (preequilibrated in Krebs, 95% O₂/5% CO₂) through the arterial lumen under optical microscopy, ensuring equal wire protrusion at both ends.
   2. Myograph mounting: Turn on the heating system and gas to maintain physiological temperature and oxygenation. Secure wires horizontally in a temperature-controlled wire myograph bath (Krebs, 95% O₂/5% CO₂). Adjust screw knobs to maintain natural vessel relaxation.
2. Determination of the optimal initial tension with vessel-specific normalization
   NOTE: Resting tension was adjusted using a normalization procedure to standardize baseline conditions, optimize vessel responsiveness, and ensure reproducibility. Equilibrate for 30 min before proceeding with the normalization.
   1. Select Normalization settings from the DMT menu, using the following parameters: eyepiece calibration: 1 mm/div; target pressure: 13.3 kPa; IC1/IC100 ratio: 0.9 C; online averaging: 3 s; delay time: 60 s.
      NOTE: Additional background and system configuration details are provided in the referenced paper¹⁷.
   2. To normalize a vessel, select the channel of interest and populate the normalization screen with data. Set tissue end points based on the micrometer reading and wire diameter of 40 µm.
   3. Apply passive stretch and wait for 3 min. Administer 60K⁺ to induce a potassium-mediated contraction and wait until the contraction reaches a plateau. Rinse the preparation 3 x 5 min with Krebs solution to wash out the 60K⁺. Calculate the active force by subtracting the passive force at each stretch level from the potassium-induced force recorded on the trace.
   4. Repeat step 4.2.3 until the maximum active force is reached. Define optimal resting tension as the level yielding maximal active tension in each artery, with peak responses to high K⁺ used as reference contractions.
   5. Equilibrate the arterial ring for 10 min before further experiments.
      NOTE: Due to significant inter-individual variability in vessel grades, thicknesses, and origins, normalize each blood vessel individually to ensure reproducibility. Use the normalization module of the wire myograph system to determine the appropriate baseline tension based on each vessel's passive diameter and mechanical properties. Apply the procedure consistently across all samples before functional testing.
3. Reactivity detection of renal artery rings
   1. To investigate the effects of different metabolites on vascular contractility, perform vascular contraction function tests using renal arteries incubated with extracted plasma and fecal metabolites from healthy volunteers and HF patients for 12 h. For specific details, refer to section 3.
   2. Use 60K⁺ to elicit a potassium-mediated contraction. Make sure that each chamber has 5 mL Krebs solution.
   3. To determine phenylephrine (Phe)-induced, concentration-dependent contractions in artery rings, add Phe in half-log increments from 10^-9 to 10^-4 M. Begin with the lowest Phe concentration, introduce it into the chamber, and wait for a steady contraction.
   4. Mark the spot at which a steady contraction is reached (i.e., record the tension value at the plateau), then go on to the next concentration. Repeat until the final concentration has been successfully added.
   5. After finishing the experiment, save the data file and remove the artery rings. Clean the chamber well with an 8% acetic acid solution, then incubate for 3 min.
   6. Turn off the heating system and gas, ensuring all liquid has been removed before turning off the gas.

5. Histopathological examination of renal artery: hematoxylin-eosin staining

NOTE: Dispose of hazardous reagents and biological waste in accordance with institutional biosafety and chemical hygiene protocols. Specifically, xylene and paraformaldehyde should be collected in labeled, sealable chemical waste containers and stored in a designated fume hood area before disposal by certified hazardous waste handlers. Acetic acid used for myograph chamber cleaning must be neutralized and disposed of following standard acid waste disposal procedures. Do not discharge any of these reagents into laboratory sinks.

1. Wash the arteries in cold PBS and fix in 4% paraformaldehyde (pH 7.4) overnight. Cut serial sections at 4 µm and process for histology.
2. Incubate tissue sections mounted on glass slides in a slide dryer at 60 °C for 1 h, then immediately transfer to xylene. Immerse the sections in xylene (3 x 5 min).
3. Subject the sections to graded ethanol hydration: 100% ethanol (2 x 5 min), 95% ethanol (1 x 5 min), 90% ethanol (1 x 5 min), 80% ethanol (1 x 5 min), 70% ethanol (1 x 5 min), rinse with ultrapure water (1 x 5 min).
4. Stain with hematoxylin (0.5% w/v) for 5 min; then rinse under running water.
5. Differentiate with 1% acid alcohol (HCl-ethanol) for 5-10 s and rinse under running water.
6. Blue the sections in 0.6% ammonia water and rinse under running water.
7. Immerse the sections in eosin solution (1% w/v) for 2 min.
8. Dehydrate and clear the sections in 95% ethanol (2 x 5 min), 100% ethanol (2 x 5 min), and xylene (2 x 5 min).
9. Air-dry briefly until optical transparency is achieved, mount in mounting medium, cover with coverslips, and seal the coverslips with a neutral mounting medium.
10. Perform brightfield imaging and histomorphometric evaluation.

6. Detection of renal injury-associated molecular biomarkers

1. Renal artery mRNA extraction
   1. Add the cryopreserved vascular tissue in liquid nitrogen to 1 mL of RNA extraction reagent and transfer to a precooled tissue homogenizer for thorough homogenization.
   2. Add 250 µL of chloroform per 100 µL of the extraction reagent, vortex vigorously for 30 s, and incubate for 10 min at 25 °C.
   3. Centrifuge at 12,000 × g (10 min, 4 °C) and transfer the aqueous phase to a fresh tube.
   4. Add 500 µL of isopropanol to the aqueous phase, mix by inversion, and incubate for 20 min at 25 °C.
   5. Centrifuge at 12,000 × g (10 min, 4 °C) and discard the supernatant.
   6. Wash the pellet with 1 mL of 75% ethanol (2 x 5 min), air-dry the RNA pellet, and resuspend in DEPC-H₂O (0.1% v/v).
      NOTE: Verify RNA purity (OD₂₆₀/OD₂₈₀ = 1.9-2.0) and confirm intact 28S/18S rRNA bands.
2. cDNA synthesis
   1. Mix 2 µg of mRNA + 1 µL of oligo(dT) primer, adjust to 8 µL with DEPC-H₂O (0.1% v/v), heat at 70 °C for 5 min, and snap-cool on ice for 5 min.
   2. Prepare the reverse transcription master mix in 10 µL of 2x TS Reaction Mix, 1 µL of RT/RI Enzyme Mix, and 1 µL of gDNA Remover. Add the 12 µL of master mix to the 8 µL of RNA/primer mixture from Step 6.2.1 to achieve a total reaction volume of 20 µL.
   3. Heat the mixture from step 6.2.2. at 42 °C for 60 min and terminate the process by heating at 85 °C for 5 min.
   4. Dilute the 20 µL of reverse transcription reaction by adding 80 µL of nuclease-free H₂O, resulting in a final volume of 100 µL (4x dilution). Use the diluted cDNA as the template for quantitative PCR.
3. Quantitative PCR analysis
   1. Set up the reaction by mixing 2.0 µL of cDNA template, 0.5 µL of forward primer (10 µM), 0.5 µL of reverse primer (10 µM), 10 µL of SYBR Green master mix (2x), and 7 µL of ddH₂O.
   2. Carry out the PCR using the following settings: initial denaturation: 95 °C/3 min; 40 cycles: 95 °C/30 s; Tm-5 °C/30 s; 72 °C/30 s; melt curve: 65-95 °C (+0.5 °C/5 s).
   3. Analyze gene expression by the 2-ΔΔct method. The primer sequences are shown in Supplemental Table S2.

Results

The cohort consisted of two females and two males, with an age range of 46 to 73 years (mean age: 64.0 years). Baseline blood pressure measurements showed systolic blood pressure ranging from 109 to 168 mmHg and diastolic pressure from 68 to 115 mmHg. All HF patients had recorded medication histories, including common cardioprotective agents such as beta-blockers, statins, and antiplatelet drugs, with individual variations in renin-angiotensin system inhibitors and diuretics. For controls, we recruited four subjects with...

Discussion

Recent research in CRS has identified metabolic reprogramming as a key pathological mechanism, with metabolites regulating renal vascular homeostasis^7,8,9. While VSMCs play a critical role in regulating vascular tone and compliance in CRS, our study provides direct evidence that cardiac injury-associated metabolites impair vascular smooth muscle contractility and structural integrity. Specifically, our findings demonstrate that ...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
DMEM High Glucose	Gibco	Cat# 06-1055-57-1-ACS
PBS	Solarbio	Cat# P1010
Penicillin-Streptomycin-amphotericin B	Thermo Fisher Scientific	Cat# 15240062
Phenylephrine	MCE	Cat#HY-B0769
Reverse transcription system	Promega	Cat# A5001
Stereomicroscopic system	Leica	M80
SYBR Green master mix	Thermo Fisher Scientific	Cat# 4309155
Vascular tension measurement system	DMT	620M