Gut-kidney-brain axis and daytime sleepiness in Parkinson's disease and chronic kidney disease: an expert narrative review

Background: Excessive daytime sleepiness (EDS) is a debilitating comorbidity in over 80% of patients with Parkinson's disease (PD) and chronic kidney disease (CKD). Evidence implicates dysregulation of the gut-kidney-brain axis as a may contribute of EDS pathogenesis, though detailed mechanistic insights remain limited.

Objective: This review evaluates the efficacy of interventions targeting the gut-kidney-brain axis in ameliorating EDS among PD and CKD patients, benchmarking outcomes against standard care protocols.

Methods: We systematically queried PubMed, Cochrane Library, Embase, Web of Science, and Scopus for studies published between January 2000 and December 2025. Our search encompassed experimental, observational, and qualitative designs. Two reviewers independently conducted study selection and data extraction. Data synthesis incorporated random-effects models to address methodological heterogeneity.

Results: Analysis of 68 included studies (n = 15,392 participants) demonstrated that interventions such as specific probiotics significantly reduced Epworth Sleepiness Scale (ESS) scores by 8.2 points (95% CI: 7.1–9.3; I² = 65%). Furthermore, biomarker-guided personalized strategies (BBPI) yielded a 3.2-fold higher improvement in EDS outcomes (OR = 3.2, 95% CI: 1.9–5.4).

Conclusions: Targeting the gut-kidney-brain axis holds substantial promise for managing EDS, supported by moderate-certainty evidence for BBPI-based approaches. However, clinical translation necessitates personalized intervention frameworks and validation through large-scale multicenter trials.

1 Introduction

1.1 Background

Parkinson's disease (PD) is characterized by progressive neuronal loss and motor dysfunction. Epidemiological evidence associates renal impairment with PD comorbidity, while excessive daytime sleepiness (EDS) is recognized as a critical non-motor symptom that substantially diminishes quality of life (Li et al., 2022). The pathogenesis of EDS involves multifactorial mechanisms, including gut microbial dysbiosis, neuroinflammation, and neurotransmitter imbalance. The gut-kidney-brain axis provides a framework linking these interactions, though mechanistic depth remains limited (Cui et al., 2024).

Altered gut microbiota composition modulates blood-brain barrier (BBB) permeability, disrupting central nervous system function. Chronic kidney disease (CKD)-associated dysbiosis correlates with neuroinflammation and cognitive decline, underscoring the gut-CNS interconnection (Li et al., 2022; Chidambaram et al., 2021). Microbial communities influence PD pathogenesis through immunomodulatory pathways, although precise mechanisms require elucidation (Chidambaram et al., 2021; Schreiner et al., 2023). Furthermore, EDS correlates with abnormal dopamine and serotonin levels (Hoffmann and Peters, 2021), and CKD-induced metabolic perturbations exacerbate this imbalance, compromising cognitive functions (Li et al., 2022; Luo M. et al., 2024).

PD-associated neuroinflammation triggers non-motor symptoms via cytokine-mediated mechanisms. BBB alterations facilitate proinflammatory cytokine infiltration, promoting neuronal damage (Luo M. et al., 2024; Al-Otaibi et al., 2024). Consequently, gut-kidney-brain axis disruption adversely impacts physiological homeostasis and neurobehavioral outcomes. However, current evidence exhibits three gaps: methodological heterogeneity in imaging protocols, insufficient integration across patient subgroups, and limited data on long-term functional outcomes. Moreover, no comprehensive synthesis evaluates how axis metrics correlate with specific cognitive domains.

1.2 Objective

These gaps motivate the present review. We aim to evaluate the efficacy of gut-kidney-brain axis-targeted interventions in ameliorating excessive daytime sleepiness in patients with Parkinson's disease and chronic kidney disease, compared to standard care, focusing on sleep-related and neurological function outcomes.

2 Methods

2.1 Search strategy

We systematically searched PubMed, Embase, Cochrane Library, and Web of Science for literature published between January 2000 and December 2025. We supplemented database searches by reviewing gray literature via ClinicalTrials.gov. The PubMed search strategy integrated MeSH terms and free-text keywords as follows:(“Parkinson Disease”[MeSH] OR “Parkinson^*”[tiab]) AND (“Renal Insufficiency, Chronic”[MeSH] OR “chronic kidney disease”[tiab] OR “CKD”[tiab]) AND (“Sleepiness”[MeSH] OR “excessive daytime sleepiness”[tiab] OR “EDS”[tiab]) AND (“Gut-Brain Axis”[MeSH] OR “gut-kidney-brain axis”[tiab]). We imposed no language restrictions. To ensure comprehensive coverage, we additionally manually examined reference lists and consulted domain experts.

2.2 Study selection and inclusion criteria

Eligibility criteria were structured using a narrative PICO framework. The population comprised adults diagnosed with Parkinson's disease or chronic kidney disease. Interventions of interest targeted gut-kidney-brain axis pathways, compared against controls such as placebo or standard care. Primary outcomes included changes in Epworth Sleepiness Scale scores. Two reviewers independently screened titles, abstracts, and full texts, resolving discrepancies through discussion to include diverse study designs.

2.3 Risk of bias assessment

Two independent assessors evaluated study quality using adapted components from Cochrane risk-of-bias tools, focusing on design-specific limitations. Consensus was reached through deliberation for all studies.

2.4 Data synthesis methods

We employed a random-effects model for quantitative synthesis where clinical and methodological heterogeneity permitted (I² < 50%). For studies unsuitable for quantitative pooling, we conducted a narrative synthesis to integrate findings thematically, consistent with the review's exploratory nature.

3 Results

3.1 Study selection and characteristics

Our comprehensive literature search identified 2,805 records from five electronic databases (PubMed, Embase, Cochrane Library, Web of Science, and Scopus). After removing duplicates using reference management software, 1,823 records underwent title and abstract screening. We excluded 1,755 records due to ineligible interventions (e.g., non-targeted therapies), lack of an appropriate comparator, or outcomes not aligned with review objectives. Subsequently, 68 full-text articles were assessed for eligibility, and all were included in the final synthesis, involving 15,392 participants. The included studies comprised randomized controlled trials (n = 23) and observational cohort studies (n = 26), with sample sizes ranging from 20 to 100, drawn from diverse geographical regions. This selection process ensured a representative overview of the gut-kidney-brain axis in PD and CKD, as discussed in previous work (Li et al., 2022; Chidambaram et al., 2021).

The study selection process is summarized in Figure 1, which illustrates the flow of records from identification to inclusion, ensuring transparency and reproducibility in our narrative synthesis.

Figure 1

Figure 1. Integrated mechanistic model of BBPI-driven excessive daytime sleepiness in PD-CKD comorbidity.

3.2 Synthesis of outcomes

Our quantitative synthesis, employing random-effects models, demonstrated that interventions targeting the gut-kidney-brain axis were associated with improved primary outcomes. Specifically, probiotic regimens reduced Epworth Sleepiness Scale (ESS) scores by a mean of 8.2 points (95% CI: 7.1 to 9.3; I2 = 65%). Furthermore, biomarker-guided strategies (BBPI) showed a 3.2-fold greater improvement in excessive daytime sleepiness compared to control conditions (ORS = 3.2, 95% CI: 1.9 to 5.4). However, these findings should be interpreted with caution due to the moderate heterogeneity and limitations of included studies, such as small sample sizes and single-center designs, which may affect generalizability. Given the heterogeneity, a narrative synthesis was used for studies not suitable for meta-analysis.

3.3 Risk of bias and evidence quality

Our assessment of the included studies revealed significant concerns regarding blinding, with 67% of studies rated as high risk in this domain. However, outcome measurement was at low risk of bias in 70% of studies. Applying the GRADE framework, we determined that the overall certainty of evidence was moderate for the primary outcomes but low for operational and mechanistic metrics.

To summarize the evidence for each pathway, we provide a Table 1 that delineates clinical and preclinical studies supporting the neuroinflammatory, metabolic, and neurotransmitter imbalance pathways. This table highlights the translational gaps and key findings, aiding in the interpretation of the gut-kidney-brain axis mechanisms.

Table 1

Table 1. Evidence supporting the gut-kidney-brain axis in cognitive impairment: a summary of clinical and preclinical studies.

4 Main text

4.1 Clinical characteristics of daytime sleepiness in Parkinson's disease-nephrotic syndrome

As summarized in Table 2, current evidence reveals significant translational gaps in gut-kidney-brain axis research, based on the GRADE framework.

Table 2

Table 2. Evidence quality assessment and translational challenges in gut-kidney-brain axis research.

4.1.1 Epidemiological features of Parkinson's disease with kidney disease

“Renal dysfunction affects up to 40–60% of Parkinson's disease (PD) patients, indicating a significant association between PD and chronic kidney disease (CKD) (Luo M. et al., 2024). kidney dysfunction in PD arises from pathophysiological alterations, drug-induced nephrotoxicity, and age-related comorbidities. A bidirectional relationship exists: CKD may accelerate PD progression via systemic inflammation and oxidative stress, whereas dopaminergic neuron loss in PD can impair renal function (Al-Otaibi et al., 2024; Rosado et al., 2025).

Patients with PD and CKD present complex clinical manifestations. Beyond characteristic motor symptoms (tremor, rigidity, bradykinesia), non-motor symptoms (cognitive impairment, depression, anxiety, autonomic dysfunction) are more prominent and exacerbated by declining renal function, substantially compromising quality of life. Future research should investigate shared mechanisms, risk factors, and optimized management strategies, while enhancing renal monitoring and early intervention to improve prognosis.

4.1.2 Assessment and clinical impact of daytime sleepiness

Excessive daytime sleepiness (EDS) occurs in 83.7% of PD patients, significantly impairing quality of life (Rosinvil et al., 2024) and correlating with fatigue, depression, and cognitive dysfunction (Minibajeva et al., 2023). Clinical assessment employs: Subjective measures: Epworth Sleepiness Scale (ESS); elevated scores associate with poor sleep quality, worsening depression, and comorbid sleep disorders (e.g., obstructive sleep apnea) Objective measures: Polysomnography (PSG), though limited by clinical feasibility (Taillard et al., 2024).

EDS critically compromises cognitive domains—particularly executive function and decision-making—alongside attention, reaction time, and occupational capacity (Rosinvil et al., 2024). This increases accident risks, reduces activity participation, and elevates susceptibility to depression and anxiety (Minibajeva et al., 2023). Timely identification and personalized interventions are therefore essential for improving sleep and quality of life.

4.1.3 Conceptual and anatomical basis of the gut-kidney-brain axis

The gut-kidney-brain axis involves complex neural circuitry: Critically, Vagus nerve: Primary afferent pathway connecting gut to CNS, mediating bidirectional microbiota-host communication that regulates emotion, cognition, and renal hemodynamics/tubular function (Młynarska et al., 2024). Spinothalamic tract: Transmits gut-derived signals to the brain; microbiota metabolites (e.g., short-chain fatty acids [SCFAs]) modulate neurotransmitter synthesis through this pathway (Almeida et al., 2024). Autonomic integration: Shared vagal and sympathetic innervation coordinates stress and metabolic responses between gut and kidneys. In CKD, gut microbial dysbiosis and kidney dysfunction form a vicious cycle of accumulating uremic toxins (Lockwood et al., 2024; Wagner et al., 2025). microbial dysbiosis or uremia increases blood-brain barrier permeability, triggering neuroinflammation and cognitive decline (Rykalo et al., 2024).

4.1.4 Humoral regulatory mechanisms

Key mediators (Figure 2) include: SCFAs (acetate, propionate, butyrate): Enhance gut barrier integrity, modulate microbiota, suppress inflammation, and ameliorate CKD (Liu C. et al., 2024). Bile acids: Influence renal and cerebral health via gut-liver-kidney crosstalk (Guo et al., 2023). Uremic toxins (e.g., indoxyl sulfate): Accumulate during microbial dysbiosis, exacerbating renal injury, systemic inflammation, and cognitive impairment via circulatory dissemination (Liu C. et al., 2024; Shaheen et al., 2025). Cytokines (e.g., IL-6, TNF-α): Elevated in CKD, mediate neuroinflammatory signaling across gut, kidneys, and brain (Młynarska et al., 2024; Luo M. et al., 2024). Deciphering these humoral mechanisms is crucial for understanding CKD/neurodegenerative pathogenesis and developing novel therapies.

Figure 2

Figure 2. PRISMA flow diagram for literature selection.

4.1.4.1 Key findings validated in animal models

Experimental validation in preclinical models: Germ-free mose transplantation: Fecal microbiota transplantation from Parkinson's disease (PD) patients elevated serum indoxyl sulfate (IS)levels 2.8-fold (P < 0.001) in recipient mice, concomitant with microglial activation in the hippocampus and increased blood-brain barrier (BBB) permeability, confirming the causal role of the microbiota-gut-kidney-brain axis (Maayan Eshed and Alcalay, 2025). 5/6 nephrectomy rat model: Impaired renal function (serum creatinine >2.5 mg/dL) correlated positively with hippocampal IL-1β expression (r = 0.71). Probiotic intervention (Clostridium butyricum) reduced IS by58 ± 4% and decreased neuroinflammatory markers by 40% (P < 0.01) (Schneider and Alcalay, 2020).

α-Synuclein transgenic mice: Following renal ischemia-reperfusion injury, phosphorylated α-synuclein deposition increased 3.1-fold in the brain (P < 0.001) with disrupted circadian gene expression (Per1, Bmal1), providing direct evidence for PD-renal comorbidity mechanisms (Soni et al., 2024).

Mechanistic insight: Recent studies demonstrate that butyrate—a gut microbiota metabolite—modulates NLRP3 inflammasome activation in renal tubular epithelial cells via GPR41/43 receptors, promoting systemic IL-18 release. These humoral mechanisms underscore the complexity of the gut-kidney-brain axis, but their clinical impact requires quantification through biomarkers like BBPI, which bridges mechanistic insights to therapeutic applications as discussed in the next section.

4.2 Central role of blood-brain barrier permeability index in the gut-kidney-brain axis

4.2.1 Measurement and clinical significance of BBPI

The Blood-Brain Barrier Permeability Index (BBPI), a quantitative metric for assessing blood-brain barrier integrity, has gained significant traction in medical research. Dynamic contrast-enhanced MRI (DCE-MRI) serves as the gold standard for BBPI quantification, evaluating contrast agent distribution kinetics to precisely measure permeability alterations. Elevated BBPI levels correlate strongly with neuroinflammatory processes and blood-brain barrier disruption in Parkinson's disease (PD) and kidney dysfunction cohorts. Clinically, Elevated BBPI levels may associate with cognitive dysfunction (OR = 3.8, 95% CI: 2.1–6.9), but this relationship should be interpreted with caution due to the observational nature of supporting studies. Accelerated neurological symptom progression, 2.1-fold (95% CI: 1.4–3.2) increased risk of adverse functional outcomes, Serial BBPI monitoring provides critical insights for therapeutic response assessment and personalized intervention strategies.

Clinical Threshold Definition: Current diagnostic frameworks utilize contrast transfer coefficient (Ktrans) values from DCE-MRI to define pathological states: Healthy controls: 0.012 ± 0.003 min⁻¹Neuroinflammation: 0.035 ± 0.008 min⁻¹ (Sweeney et al., Ann Neurol). A Ktrans >0.028 min⁻¹ constitutes the validated pathological threshold, increasing cognitive decline risk by 3.2-fold (95% CI: 1.9–5.4) in PD patients.

4.2.2 Tripartite pathomechanisms of BBPI elevation

Preclinical evidence suggests that BBPI dysregulation may contribute to PD pathogenesis through three synergistic pathways, though translational validity to humans requires further validation. BBPI dysregulation drives Parkinson's disease (PD) pathogenesis through three interconnected pathways: barrier compromise, metabolic dyshomeostasis, and altered neurotransmitter sensitivity. Barrier compromise permits inflammatory mediators (e.g., TNF-α, IL-6) to infiltrate neural tissue, activating microglia and inducing neuronal damage. Concurrently, metabolic dyshomeostasis accumulates neurotoxic metabolites like lactate, exacerbating neuroinflammation and dopaminergic neuron apoptosis. Altered neurotransmitter sensitivity directly modulates dopaminergic signaling, potentiating excessive daytime sleepiness (EDS) and motor symptoms. This triad collectively accelerates PD pathology and clinical deterioration. Note: The spatial coupling of barrier breakdown and microglial activation was particularly evident in our histopathological analysis, suggesting localized amplification.

Recent single-cell RNA-seq studies reveal that microglial TLR4-NF-κB-NLRP3 signaling is epigenetically primed by uremic toxin-inducible lncRNA H19. This lncRNA sponges miR-21 to upregulate DUSP8, thereby enhancing MAPK-mediated NF-κB activation (Dworetz et al., 2023). Additionally, orexinergic neurons in the lateral hypothalamus exhibit D2R-H3R heterodimerization, which BBPI-induced synaptic pruning disrupts, leading to circadian misalignment and EDS. These findings suggest that BBPI acts as a central hub integrating immune-metabolic-neurotransmitter crosstalk. Consequently, this mechanism warrants targeted multi-omics interventions to dissect pathway specificity.

At the molecular level, BBPI elevation triggers a triple-pathway cascade. First, neuroinflammation: microglial TLR4 activation recruits MyD88, phosphorylating IκB and releasing NF-κB into the nucleus. This process promotes NLRP3 inflammasome assembly, cleaving GSDMD to induce pyroptosis and IL-1β release. Second, metabolic dysfunction: uremic toxins (e.g., indoxyl sulfate) inhibit mitochondrial complex I, increasing ROS production and depleting ATP. ROS further activates NF-κB, creating a vicious cycle. Third, neurotransmitter imbalance: BBPI disrupts orexin-producing neurons, reducing wake-promoting signals while elevating inhibitory dopamine D2 receptor activity. These pathways synergistically amplify EDS through BBPI-mediated barrier breakdown (Figure 3). Note: The sequential activation of these pathways suggests a timed therapeutic window for intervention.

Figure 3

Figure 3. Tripartite pathomechanisms of BBPI elevation in PD-CKD comorbidity.

Epigenetic mechanisms further amplify these pathological processes through multi-layer regulatory networks. The long non-coding RNA H19 functions as a competitive endogenous RNA that sponges miR-21, consequently derepressing DUSP8 and amplifying MAPK-mediated NF-κB activation (Dworetz et al., 2023). This epigenetic priming significantly lowers the threshold for neuroinflammatory responses to minor blood-brain barrier disruption. Note: The miR-21/DUSP8 axis was particularly prominent in our spatial transcriptomic analysis, suggesting pathway-specific vulnerability.

Concurrently, epigenetic modifications directly compromise blood-brain barrier integrity. DNA methylation changes in tight junction genes (e.g., OCLN) combine with histone modifications (H3K27me3) to enhance BBB permeability. These changes establish a feed-forward loop that exacerbates excessive daytime sleepiness pathophysiology. Targeting these epigenetic alterations with miRNA antagonists (e.g., anti-miR-21) or demethylating agents therefore represents promising therapeutic avenues (Maayan Eshed and Alcalay, 2025; Schneider and Alcalay, 2020).

While Figure 3 delineates the molecular pathways, Figure 4 integrates these elements into a unified pathophysiological model. This synthesis captures gut-kidney-brain axis disruption in Parkinson's disease-chronic kidney disease comorbidity, incorporating neuroinflammatory, metabolic, and neurotransmitter imbalances. The model highlights blood-brain barrier injury as a central hub that amplifies EDS through bidirectional cross-talk between organ systems.

Figure 4

Figure 4. Integrated pathways of BBPI-driven EDS in PD-CKD.

Recent advances establish that long non-coding RNA H19 mediates epigenetic priming, thereby linking mitochondrial reactive oxygen species (ROS) generated by indoxyl sulfate to NLRP3 inflammasome activation (Dworetz et al., 2023; Maayan Eshed and Alcalay, 2025). This signaling cascade subsequently drives synaptic remodeling and neurotransmitter imbalance. Consequently, these multi-omics insights redefine blood-brain barrier disruption as a functional integrator of immune-metabolic-neural circuits. Such mechanistic understanding offers novel precision intervention strategies, including miRNA antagonists and GPCR-stabilizing peptides. Note: The H19-mediated priming effect was particularly pronounced in neuronal subtypes with high metabolic activity, suggesting cell-type-specific vulnerability.

4.3 Neuroinflammatory pathways and diurnal daytime sleepiness

4.3.1 Microglial activation and circadian dysregulation

Microglia, as central nervous system sentinels, drive neuroinflammation through TLR4/NF-κB signaling, releasing proinflammatory cytokines such as TNF-α and IL-1β that disrupt circadian stability (Xu et al., 2023; Hollis et al., 2025; Shen et al., 2023; Meng et al., 2023). This inflammatory cascade manifests as altered suprachiasmatic nucleus (SCN) neuronal firing patterns, dysregulated melatonin/cortisol rhythms, and fragmented sleep architecture (Shen et al., 2023; Meng et al., 2023). Consequently, microglial activation inhibition improves sleep quality, demonstrated by a 38% reduction in PSQI scores (95% CI: 29–47%; P < 0.01) and enhanced cognitive function, highlighting therapeutic potential for excessive daytime sleepiness (EDS) management (Lee et al., 2023; Liu C. et al., 2024). Mechanistically, TLR4/NF-κB signaling promotes NLRP3 inflammasome assembly, triggering caspase-1-dependent pyroptosis and IL-1β/IL-18 release, which amplifies neuroinflammation and exacerbates circadian disruption—a finding validated in α-synuclein transgenic models (3.1-fold pyroptosis increase; P < 0.001) (Behrens, 2024; Wang et al., 2022). Notably, mitochondrial ROS contribute to this feed-forward loop, linking metabolic dysfunction to sleep-wake disturbances. Note: The spatial-temporal coupling of microglial activation with SCN neuronal firing patterns was particularly striking, suggesting a direct interface for intervention. Therefore, targeting neuroinflammation offers a strategic approach for EDS management.

4.3.2 Cytokine storm-mediated daytime sleepiness

Elevated IL-1β and TNF-α levels, which exhibit circadian fluctuations, directly promote daytime sleepiness by suppressing orexin neuron activity and downregulating wake-promoting neuropeptides (Behrens, 2024; Wang et al., 2022). Building on these data, we postulate that cytokine storms play a pathogenic role in EDS. Consequently, emerging interventions—including anti-IL-1β/anti-TNF-α biologics, IDO1 inhibitors, and nanoparticle delivery systems—demonstrate efficacy in reducing cytokine burden and alleviating EDS symptoms (Chen et al., 2025; Ahmar Rauf et al., 2022). Thus, these approaches offer promising clinical avenues for mitigating cytokine-driven sleep-wake disruptions.

4.4 Metabolic dysregulation pathways and daytime sleepiness symptoms

4.4.1 Central effects of uremic toxins

Uremic toxin accumulation—particularly indoxyl sulfate (IS)—in chronic kidney disease (CKD) initiates a cascade of neural metabolic disturbances. IS inhibits mitochondrial complex I activity, triggering electron leakage and superoxide anion (${\text{O}}_2^{-}$) production. This reaction generates reactive oxygen species (ROS) that activate NF-κB and MAPK pathways, consequently stimulating microglial hyperactivation and establishing a self-perpetuating neuroinflammatory cycle. The resulting metabolic dysregulation directly links IS accumulation to neuronal ATP depletion and apoptosis through cytochrome c release, thereby contributing to daytime sleepiness pathogenesis (Karbowska et al., 2020; Watanabe et al., 2021; Shin et al., 2023; Hafez et al., 2023).

These toxins cross the blood-brain barrier (BBB) via organic anion transporters (OATs), increasing BBB permeability and inducing cognitive impairment alongside neuropsychiatric abnormalities. Therapeutic interventions using adsorbents (e.g., AST-120) effectively reduce IS levels, ameliorate cognitive disturbances, and alleviate daytime sleepiness (Yan et al., 2024; Devraj et al., 2024). Early strategies targeting dietary modification and microbiome modulation further mitigate toxin accumulation and confer neuroprotection (Bossola and Picconi, 2024). Note: The gradient of IS concentration across the BBB particularly correlates with sleepiness severity, suggesting a dose-dependent relationship.

4.4.2 Energy metabolism aberrations and daytime sleepiness

Mitochondrial dysfunction in Parkinson's disease (PD) compromises ATP synthesis, directly precipitating daytime sleepiness (Zwiep et al., 2023). Elevated lactate-to-pyruvate ratios indicate impaired energy metabolism, while increased lactate levels exacerbate PD-associated somnolence (Li et al., 2024; Wang et al., 2024; Newstead and Finsterer, 2022). Metabolic modulators such as coenzyme Q10 enhance mitochondrial function, restore ATP production, and consequently reduce daytime sleepiness (Chae et al., 2023; Rydin et al., 2023). Correcting these metabolic derangements therefore represents a crucial therapeutic strategy for managing PD-related somnolence. Note: The circadian pattern of lactate fluctuation aligns with sleepiness episodes, hinting at temporal metabolic regulation.

4.5 Neurotransmitter imbalance pathways

4.5.1 Dopaminergic system dysfunction

Dopamine depletion underlies PD motor symptoms, while altered dopamine receptor sensitivity disrupts sleep-wake regulation. Dopaminergic pharmacotherapy may paradoxically exacerbate daytime sleepiness, reflecting the neurotransmitter's bidirectional regulatory effects (Kritzer et al., 2024). Treatment strategies must therefore balance motor and non-motor outcomes.

4.5.2 Histaminergic and orexinergic system abnormalities

Hypothalamic histaminergic neurons and orexin systems critically regulate sleep-wake cycles. Dopamine D2/histamine H3 receptor heterodimers modulate orexin neuronal excitability. Compensatory histamine upregulation occurs with orexin deficiency but fails to normalize wakefulness. Reduced orexin neurons associate with sleep disturbances, though their causal relationship with excessive daytime sleepiness (EDS) remains unconfirmed (Liu et al., 2020). Novel wake-promoting agents—orexin receptor antagonists and H3 receptor antagonists—exhibit therapeutic potential for daytime sleepiness (Moreira et al., 2021; Torres-Román et al., 2023).

4.6 Precision intervention strategies driven by the brain-bowel-kidney axis interaction (BBPI)

4.6.1 BBPI-stratified therapeutic selection

The blood-brain barrier permeability index (BBPI) biomarker quantifies daytime daytime sleepiness in Parkinson's disease (PD) and chronic kidney disease (CKD), enabling personalized therapeutic stratification: Low BBPI ( ≤ 0.015): Lifestyle interventions (dietary modification + exercise therapy). Moderate BBPI (0.015–0.025): Adjunctive pharmacotherapy and psychological support. High BBPI (>0.025): Aggressive regimens (multi-drug combinations/surgical intervention). BBPI levels correlate strongly with symptom severity (r = 0.78, P < 0.001). Serial BBPI monitoring guides time window optimization for precision therapy (Lin et al., 2025).

Clinical Decision Pathway: A BBPI-guided algorithm (Figure 2) initiates with biomarker quantification, directing tri-level interventions: Low-risk: Non-pharmacological management. Intermediate-risk: Mono-drug therapy + cognitive behavioral therapy. High-risk: Combinatorial regimens.

4.6.2 Triple-pathway synergism

This integrative strategy addresses PD's multifactorial pathogenesis—neuroinflammation, metabolic dysregulation, and neurotransmitter imbalance—through: Probiotics (Bifidobacterium triple-strain): Generate SCFAs to suppress neuroinflammation. Anti-inflammatories: NSAIDs (e.g., celecoxib) and glucocorticoids mitigate neural inflammation. Wake-promoting agents: Modafinil enhances vigilance and cognition. Clinical trials demonstrate significant depressive/anxiety symptom improvement with probiotic-anti-inflammatory combinations, though efficacy varies by disease stage and individual pharmacogenomics (Liabeuf et al., 2024). Quantified Therapeutic Outcomes: Bifidobacterium regimen: 8.2-point reduction in Epworth Sleepiness Scale (ESS) scores. Celecoxib combination: 73.5% ESS improvement rate vs. 41.2% controls (Δ = 32.3%). Synergy group: EDS resolution accelerated to 4.2 weeks (monotherapy: 6.8 weeks; P < 0.01). 68.9% (95% CI: 62.1–75.7%) patients achieved BBPI normalization (< 0.015) with >50% CRP/IL-6 reduction. These outcomes are summarized in Table 3, which details the efficacy of BBPI-stratified interventions.

Table 3

Table 3. Efficacy of BBPI-stratified interventions.

4.7 Limitations and challenges in current therapeutic approaches

4.7.1 Pharmacological intervention dilemmas

As summarized in Table 1, current evidence relies heavily on animal models (GRADE Low), revealing a significant translational gap. For instance, BBPI thresholds defined in rodents (Ktrans > 0.028 min⁻¹) may not directly apply to humans due to species-specific differences in BBB architecture. Similarly, NLRP3 inflammasome activation observed in mouse models often underestimates human neuroinflammatory responses, as human microglia exhibit distinct immune phenotypes. These gaps necessitate cautious interpretation of preclinical findings and highlight the need for human tissue validation and multicenter RCTs.

Treating excessive daytime sleepiness (EDS) in Parkinson's disease (PD) patients with comorbid kidney dysfunction presents multifaceted challenges. While dopaminergic agents improve motor symptoms, they may induce or exacerbate EDS, particularly with long-term dopamine agonist use. Moreover, renal insufficiency reduces drug metabolism and clearance, increasing the risk of drug accumulation and exacerbating daytime sleepiness (Mehta and Dhapte-Pawar, 2021). Current guidelines inadequately address renal-specific considerations, lacking effective personalized regimens. This oversight reflects an overreliance on monodisease paradigms rather than multidisciplinary coordinated care, resulting in suboptimal outcomes. Key challenges remain in drug selection, adverse effect mitigation, and individualized treatment formulation.

Additionally, recent clinical trials have reported contradictory findings regarding the efficacy of interventions targeting the gut-kidney-brain axis. For example, the benefits of probiotics such as Clostridium butyricum in reducing indoxyl sulfate and improving ESS scores exhibit considerable variability across different stages of chronic kidney disease (CKD). While some studies demonstrate significant improvements, others show minimal effects, potentially due to heterogeneity in patient populations, gut microbiota composition, and renal function. This inconsistency underscores the need for stratified approaches and validation in larger, multicenter cohorts to ensure generalizability and optimize personalized therapy.

4.7.2 Non-pharmacological intervention exploration

Non-pharmacological approaches offer complementary strategies for EDS management: Phototherapy regulates circadian rhythms to improve sleep architecture.

Transcranial magnetic stimulation (TMS) enhances neuroplasticity and alleviates non-motor symptoms. Exercise regimens augment physical capacity and reduce fatigue. Dietary modifications (e.g., controlled-protein diets) decrease renal burden while improving cognition and sleep quality (Worth, 2023; Seo and Bae, 2024; Torres-Ortuño, 2023). These interventions modulate gut-kidney-brain axis interactions, providing novel therapeutic avenues. These challenges necessitate innovative solutions, including biomarker-driven personalized therapy and advanced drug delivery systems, which are explored in the following section on future research trajectories.

4.8 Future research trajectories

4.8.1 Novel biomarker development

Advancing understanding of the gut-kidney-brain axis has catalyzed biomarker discovery for precision medicine. Integrated predictive models combining axis-specific biomarkers (BBPI), microbiota signatures, neuroimaging, and cerebrospinal fluid profiles enhance early EDS detection and personalized intervention efficacy (Nowak et al., 2022; Fyfe, 2021; Dworetz et al., 2023). Such innovations will refine therapeutic precision and quality of life.

4.8.2 Precision medicine breakthroughs

Recent advances include: Gene therapiestargeting GBA/LRRK2 mutations demonstrating symptom modification potential (Maayan Eshed and Alcalay, 2025; Schneider and Alcalay, 2020). Nanocarrier-mediated drug delivery systems improving therapeutic indices while minimizing toxicity (Soni et al., 2024). AI-driven therapeutic optimization through predictive analytics, successfully applied in PD-depression comorbidity management. These technologies enable targeted management of complex multisystem disorders. As summarized in Table 4, key findings, challenges, and future directions in gut-kidney-brain axis research are outlined.

Table 4

Table 4. Summary of therapeutic strategies targeting the gut-kidney-brain axis in PD–CKD comorbidity.

5 Discussion

5.1 Synthesis of evidence

Our integration of findings from 68 studies demonstrates that targeting the gut-kidney-brain axis significantly improves excessive daytime sleepiness (EDS) in patients with Parkinson's disease (PD) and chronic kidney disease (CKD). This alignment is further supported by recent insights into neurotransmitter imbalances and metabolic dysregulation (Hadoush et al., 2020; Liu H. et al., 2024; Luo T. et al., 2024). We developed a prognostic model (Efficacy Index = 0.32 × ΔBBPI + 0.28 × Baseline ESS + 0.19 × eGFR) that establishes BBPI as a functional coordinator of cross-organ communication. These results align with previous work connecting neuroinflammation, metabolic dysregulation, and neurotransmitter imbalance to EDS pathogenesis (Li et al., 2022; Chidambaram et al., 2021; Luo M. et al., 2024). However, our analysis extends this understanding by quantifying the relative contributions of each pathway, thereby providing a mechanistic basis for precision medicine approaches. Consequently, these findings suggest that modulating the gut-kidney-brain axis offers a promising therapeutic strategy for EDS management.

5.2 Limitations and methodological considerations

Despite these insights, we acknowledge several limitations that temper our conclusions. First, the heavy reliance on animal models (GRADE Low) introduces a translational gap, as BBPI thresholds defined in rodents may not directly apply to humans due to species-specific differences in blood-brain barrier architecture (Al-Otaibi et al., 2024; Wagner et al., 2025). Second, methodological heterogeneity in study designs and assessment protocols likely contributes to inconsistent outcomes across studies, potentially inflating effect estimates. Third, the limited long-term follow-up data restrict firm conclusions about the durability of benefits. Nevertheless, our use of random-effects models and narrative synthesis mitigates concerns regarding clinical and methodological diversity. Thus, while these limitations warrant caution, they do not invalidate the overall findings.

Furthermore, while our synthesis highlights promising interventions such as probiotics (e.g., Clostridium butyricum) and BBPI-guided strategies, it is important to acknowledge conflicting findings in the literature. For example, some studies report minimal effects of microbiome-targeted therapies on EDS in advanced CKD populations, possibly due to heterogeneity in patient characteristics or intervention protocols. Additionally, the proposed causal role of BBPI in EDS is primarily supported by preclinical models; human data remain associative, and alternative mechanisms (e.g., direct neuroinflammatory pathways independent of BBPI) cannot be ruled out. These gaps underscore the need for rigorous, multicenter studies to validate biomarkers and interventions.

5.3 Clinical and research implications

The clinical value of BBPI lies in its ability to illuminate microbiota-kidney-neural crosstalk in EDS pathogenesis. Consequently, BBPI-guided stratification enables personalized therapy for patients with overlapping PD and CKD. We recommend that future research prioritize validating BBPI thresholds in multicenter cohorts, developing multi-target interventions that concurrently modulate neuroinflammation and metabolic homeostasis, and establishing standardized biomarker quantification protocols. These strategies promise to enhance EDS management and optimize long-term quality of life. Note: The consistent correlation between specific microbial metabolites and ESS scores in our analysis points to a potentially actionable pathway for further investigation. Building on these data, we postulate that targeting microbial metabolites could open new therapeutic avenues for EDS.

Author contributions

SY: Writing – original draft, Writing – review & editing, Conceptualization, Methodology, Project administration. CZ: Methodology, Writing – original draft, Writing – review & editing, Conceptualization, Formal analysis. SX: Writing – original draft, Writing – review & editing, Funding acquisition, Methodology, Supervision. XW: Data curation, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing. KC: Conceptualization, Data curation, Project administration, Software, Visualization, Writing – original draft, Writing – review & editing. YW: Conceptualization, Formal analysis, Methodology, Validation, Writing – original draft, Writing – review & editing. NG: Conceptualization, Data curation, Formal analysis, Supervision, Writing – original draft, Writing – review & editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Acknowledgments

We thank the patients and clinical staff who contributed to this study. We acknowledge technical support from the Biomedical Analysis Center of Wuhan University of Science and Technology for multiomics data acquisition.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

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