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Abstract

Background

Emerging evidence has indicated gut dysbiosis as a potential modifiable contributor to the pathogenesis of Parkinson’s disease (PD). Fecal microbiota transplantation (FMT), a microbiome-centric model aimed at modulating the intestinal microbial taxa, represents a novel therapeutic approach. However, its safety and efficacy profile in improving PD symptoms remains inadequately researched.

Methods

PubMed, ScienceDirect, and the Cochrane Central Registry were searched to retrieve relevant articles from inception till February 2025. Risk ratios (RR) and Mean differences (MD), along with 95% confidence intervals (CI), were pooled under the random-effect model for dichotomous and continuous outcomes, respectively. The primary outcomes of interest were change in Movement Disorder Society Unified Parkinson’s Disease Rating Scale part 1 (MDS-UPDRS 1), change in MDS-UPDRS 2. Secondary endpoints of interest were change in MDS-UPDRS 3 (on medication), change in MDS-UPDRS 3 (off medication), change in MDS-UPDRS 4, change in Irritable Bowel Severity Scoring System (IBS-SSS), change in Montreal Cognitive Assessment (MoCA), change in Parkinson Disease Questionnaire Summary Index (PDQ-39 SI), and GI adverse events. The Cochrane Risk of Bias 2.0 (RoB 2.0) tool was used for the quality assessment of the included randomized controlled trials (RCTs). A Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) assessment was done for the certainty of evidence.

Results

This systematic review and meta-analysis included 145 patients across 3 RCTs. FMT and placebo were comparable regarding the primary outcomes that include MDS-UPDRS Part I (MD = −0.36; 95% CI:[-2.18,1.45]; P = .70; I² = 33%), Part II (MD = −0.46; 95% CI:[-1.91,0.99]; P = .53; I² = 0%). The secondary outcomes, involving MDS-UPDRS Part III on-medication (MD = 1.41; 95% CI:[-2.14,4.42]; P = .50; I² = 17%), Part III off-medication (MD = 1.26; 95% CI:[-2.27,4.79]; P = .48; I² = 0%), and Part IV (MD = −0.39; 95% CI:[-1.63,0.85]; P = .54; I² = 24%) were also comparable between the two groups. No significant changes were observed in IBS-SSS (MD = −15.91; 95% CI:[-63.17,31.89]; P = .51; I² = 76%), PDQ-39 SI (MD = −2.13, 95% CI:[-5.62,1.36]; P = .23; I² = 0%), and MOCA scores (MD = 0.11; 95% CI:[-1.34,1.57]; P = .88; I² = 68%). However, the FMT group had more frequent adverse gastrointestinal events (RR = 3.32; 95% CI: [1.01,10.87]; P = .05; I² = 39%).

Conclusion

FMT shows no evidence of superiority compared to placebo. Variations in the findings of existing studies suggest that donor fecal composition, host-microbiota interactions, and methodological heterogeneity may determine outcomes. Further RCTs employing tailored microbiota and standardized endpoint metrics are required to establish a correlation between FMT and PD.

Keywords

Parkinson disease fecal microbiota transplantation lewy body Parkinson disease systematic review meta-analysis

Introduction

Parkinson’s disease (PD) is a chronic, progressive neurodegenerative disorder that primarily affects movement due to the deterioration of the nervous system wherein there is a loss of dopamine-producing neurons. PD is characterized by both motor symptoms like tremors, rigidity, and bradykinesia and non-motor symptoms like constipation, sleep disorders, cognitive decline, depression, and other mental illnesses.^1-4 The Global Burden of Disease (GBD) study estimated that PD cases increased from 6.1 million in 2016 to 8.5 million in 2019.⁵ World Health Organization (WHO) data from 2023 reported an 81% rise in PD-related Disability-Adjusted Life Years (DALYs) since 2000, with deaths more than doubling.⁴

The symptomatic spectrum of PD extends beyond its motor and non-motor clinical manifestations, with the gastrointestinal tract being the principal locus of pathological perturbations.^6,7 A cornerstone element of this broader disease paradigm is the bidirectional microbiota-gut-brain axis or “second brain”, an intricate bidirectional network through which the gut microbial taxa communicate with the central nervous system via neural, hormonal, and immune pathways⁸. This axis features significant perturbations in PD, with gut dysbiosis delineated by contraction in butyrate and short-chain fatty acid (SCFA) producing strains, including Prevotellaceae, Lachnospiraceae, and Faecalibacterium and a concurrent increase in proinflammatory taxa such as Ralstonia.^9,10 Evidence indicates that gut dysbiosis might exacerbate the progression of PD^11-14 as it's linked to disrupting the integrity of the intestinal epithelial barrier and blood-brain barrier (BBB), exacerbating neuroinflammation, in conjunction to prompting alterations in the metabolism of serotonin, kynurenine, dopamine and alpha-synuclein aggregation.^6,15

Microbiome-based treatments, including probiotics, prebiotics, and fecal microbiota transplantation (FMT), are emerging as potential therapeutic options for patients with PD.¹⁶ Probiotics and prebiotics support gut bacteria, reduce inflammation, and improve motor function.^17-20 FMT is a novel, promising therapeutic approach to address gut microbiome dysregulation in PD patients, potentially affecting neuromuscular symptoms and GI motility.²¹ FMT involves the transfer of fecal material via colonoscopy, esophagogastroduodenoscopy, or oral capsules.^22,23 Proven effective for conditions like Clostridioides difficile infection and Inflammatory bowel disease (IBD), FMT may help modify PD-related gut dysbiosis.^24,25 However, its role in PD remains unexplored, mainly lacking a standardized protocol.²⁶

Some studies suggest FMT may improve symptoms in PD. Huang et al.²⁷ reported rapid improvements in tremors, reduced defecation time, and enhanced Unified Parkinson’s Disease Rating Scale (UPDRS) scores. In an open-label case series, Segal et al.²⁸ observed motor, non-motor, and constipation symptoms relief in five of six patients, lasting up to 24 weeks. Sciscio et al.²⁹ found no significant improvement in motor symptoms; however, transient improvements in OFF time, quality of life, and non-motor symptoms were observed in 12 patients, though these were not sustained. A systematic review by Nabil et al.³⁰ showed mixed results with some reporting benefits, particularly with colonic FMT. FMT was generally well-tolerated across all studies, with only mild gastrointestinal side effects. To our knowledge, no similar meta-analysis has been conducted previously to evaluate the efficacy and safety of FMT in PD. Therefore, this meta-analysis aims to address this gap by examining its effects on neurological and gastrointestinal symptoms. We intend to offer initial evidence that supports FMT’s potential role in managing Parkinson’s disease.

Methods

Data Sources and Search Strategy

This study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.³¹ The protocol for this systematic review was registered on PROSPERO under the ID CRD420251026602.³² A comprehensive literature search was conducted from inception up to February 2025. We thoroughly searched electronic databases such as PubMed, ScienceDirect and the Cochrane Central Library for studies comparing the two treatment modalities: FMT vs usual care/placebo for treating PD. Additionally, we checked clinicaltrials.gov for any unpublished trials. Following MeSH headings and keywords were utilized for the screening process “Parkinson Disease”, “Fecal Microbiota Transplantation”, and “Donor Feces Infusion”. A comprehensive search strategy for each database is summarized in Supplemental Table 1.

Study Selection and Criteria

The relevant articles identified using specific keywords were imported into Rayyan.ai for screening, where duplicates were flagged and removed.³³ Studies were initially filtered via the title and abstract, followed by full-text screening. There was no restriction on the study timeline, and only English-language articles were considered. Additionally, the bibliographies of included articles were checked for any additional relevant studies. Two authors (BS and NR) assessed the studies against the eligibility criteria, with any disagreements resolved by the third author (MHW). The criteria for inclusion were participants with a clinical diagnosis of PD, no recent gastrointestinal infection, and no use of probiotics for a few months before the trial. Participants with severe comorbidities such as malignancies, gastrointestinal dysfunctions not related to PD, and medications that could alter the gut microbiota before the trial were excluded. Study types considered for inclusion included only the randomized controlled trials (RCTs), while the case-control studies, cohort studies, case reports, systematic reviews, protocols, editorials, abstracts, conference papers, and other unpublished studies were excluded. A summary of the screening process is illustrated in the PRISMA Flowchart Figure 1.

Figure 1.

PRISMA Flowchart of the Study Selection Process

Data Extraction and Quality Assessment

The relevant data was extracted and recorded in a standardized extraction form on Google Sheets. The baseline characteristics extracted included study ID, location, study design, sample size, age in years, BMI, duration of PD, Levodopa-equivalent daily dose (LEDD) and Montreal Cognitive Assessment (MoCA) score. The primary outcomes of interest were change in Movement Disorder Society Unified Parkinson’s Disease Rating Scale part 1 (MDS-UPDRS 1), change in MDS-UPDRS 2. Secondary endpoints of interest were change in MDS-UPDRS 3 (on medication), change in MDS-UPDRS 3 (off medication), change in MDS-UPDRS 4, change in Irritable Bowel Severity Scoring System (IBS-SSS), change in Montreal Cognitive Assessment (MoCA), change in Parkinson Disease Questionnaire Summary Index (PDQ-39 SI), and GI adverse events. Two authors (ZUA and AS) performed data extraction, with disparities being resolved by a third author (MHW). To assess the quality of the included trials, the Cochrane Risk of Bias tool (RoB 2.0) was employed.³⁴ The RoB 2.0 tool focuses on five main areas: (1) bias during the randomization process, (2) bias due to deviations from intended interventions, (3) bias due to missing outcome data, (4) bias in the measurement of the outcome, and (5) bias in the selection of the reported results. The risk of publication bias in the included studies was assessed visually through funnel plots. We also performed the GRADE assessment using GRADEpro GDT to determine the certainty of evidence.³⁵

Statistical Analysis

Forest plots were constructed utilizing the Review Manager software (version 5.4.1). Risk ratios (RR) and Mean differences (MD), along with 95 % Confidence intervals (CI), were pooled under the random effects model. A P-value of <0.05 was deemed statistically significant. Heterogeneity was determined using Higgins I² statistics and the Cochrane Q test. Studies reporting I² of more than 50% were further evaluated by performing the sensitivity analysis (leave one-out method).³⁶

Results

Search Results

The literature searches initially retrieved 1154 articles. After removing 807 duplicates, 347 articles remained. The title and abstract screening excluded 319 articles, leaving 28 studies for full-text screening against the eligibility criteria. Eventually, 3 RCTs were included in this meta-analysis. The selection of studies is summarized in Figure 1.

Study Characteristics

This meta-analysis encompassed three RCTs that fulfilled the eligibility criteria. Of these, one was conducted in Belgium, another in Finland, and the last in China. The publication years ranged from 2023 to 2024. The total number of patients across these studies was 145 (79 FMT, 66 Placebo). The participants’ ages ranged from 60.50 to 66 years. The BMI values varied between 22.33 and 26.29 kg/m², and the duration of PD ranged from 4.2 to 6.96 years. MoCA scores were between 19.30 and 28.2. Table 1 summarizes the baseline characteristics of the included studies.

Table 1.

Baseline Characteristics of the Included Studies

Study ID	Location	Study design	Sample size		Age (years)		BMI (kg/m²)		PD duration (years)		LEDD (mg)		MoCA score
Study ID	Location	Study design	FMT	Placebo	FMT	Placebo	FMT	Placebo	FMT	Placebo	FMT	Placebo	FMT	Placebo
Bruggeman 2024	Belgium	RCT	22	24	61	60.5	24.6	24.3	4.2	4.4	383	431	27.6	28.2
Scheperjans 2024	Finland	RCT	30*	15*	66*	65*	26.16*	26.29*	5.91*	6.96*	670*	712*	26*	25*
Cheng 2023	China	RCT	27	27	60.52	62.63	22.33	22.43	6.74	5.85	N/A	N/A	19.41	19.3

Note. RCT: Randomized Controlled Trial; FMT: Fecal Microbiota Transplantation; PD: Parkinson Disease; LEDD: Levodopa-equivalent daily dose; MoCA: Montreal Cognitive Assessment; all the data is reported as mean; * values are reported as median.

Bias Assessment

The Cochrane RoB 2.0 tool was used to evaluate the risk of bias in the included RCTs.³⁴ Two independent reviewers (MO and MWA) assessed the quality of the included RCTs. Any disagreements were addressed through consultation with a third reviewer (MHW). Some concerns were observed in two of the included studies. These concerns were related mainly to randomization, deviation from the intended intervention, and outcome measurement. The other study was judged to be at a low risk of bias. The RoB 2.0 traffic plot is shown in Figure 2.

Figure 2.

RoB 2.0 (Risk of Bias) Traffic Light Plot

Analysis of Primary Outcome

Change in MDS-UPDRS Part I

The analysis included three studies involving 145 patients (79 FMT vs 66 Placebo). Moderate certainty evidence suggested that FMT and placebo are comparable regarding change in MDS-UPDRS Part I (MD = − 0.36; 95% CI: −2.18,1.45, P = 0.70, I² = 33%) (Figure 3) and (Table 2).

Figure 3.

Forest Plot for Change in Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Part I

Change in MDS-UPDRS Part II

This outcome was reported by three studies involving 145 patients (79 FMT vs 66 Placebo). Moderate certainty evidence revealed that FMT and placebo showed no significant difference regarding change in MDS-UPDRS Part II (MD = −0.46; 95% CI: [-1.91,0.99]; P = 0.53; I² = 0%) (Figure 4).

Figure 4.

Forest Plot for Change in Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Part II

Meta-Analysis of Secondary Outcomes

Change in MDS-UPDRS Part III (on Medication)

The analysis included two studies involving 99 patients (57 FMT vs 42 Placebo). Moderate certainty evidence suggested that FMT and placebo are comparable regarding change in MDS-UPDRS Part III on medications (MD = 1.41; 95% CI: [-2.14,4.42]; P = .50; I² = 17%) (Figure 5).

Figure 5.

Forest Plot for Change in Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Part III (on Medication)

Change in MDS-UPDRS Part III (off Medication)

The analysis encompassed two studies involving 91 patients, 52 in the FMT group and 39 in the placebo group. Moderate certainty evidence suggested no significant difference between the two groups regarding change in MDS-UPDRS Part III on medication (MD = 1.26; 95% CI: [-2.27, 4.79]; P = .48; I² = 0%) (Figure 6).

Figure 6.

Forest Plot for Change in Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Part III (off Medication)

Change in MDS-UPDRS Parts IV

The analysis comprised two studies involving 100 patients, with 49 in the FMT group and 51 in the placebo group. Moderate certainty evidence showed that both the groups are comparable regarding change in MDS-UPDRS Part IV (MD = −0.39; 95% CI: [-1.63, 0.85]; P = .54; I² = 24%) (Supplemental Figure 1) (Table 2).

Table 2.

GRADE Summary of Findings

FMT compared to placebo for Parkinson’s disease
Patient or population: Parkinson’s disease
Intervention: FMT
Comparison: Placebo
Outcomes	Anticipated absolute effects^* (95% CI)		Relative effect (95% CI)	№ of participants (studies)	Certainty of the evidence (GRADE)
Outcomes	Risk with placebo	Risk with FMT	Relative effect (95% CI)	№ of participants (studies)	Certainty of the evidence (GRADE)
Change in MDS-UPDRS 1	The mean change in MDS-UPDRS 1 ranged from -2.74 to 0.1	MD 0.36 lower (2.18 lower to 1.45 higher)	-	145 (3 RCTs)	⨁⨁⨁◯
Change in MDS-UPDRS 1	The mean change in MDS-UPDRS 1 ranged from -2.74 to 0.1	MD 0.36 lower (2.18 lower to 1.45 higher)	-	145 (3 RCTs)	Moderate^a
Change in MDS-UPDRS 2	The mean change in MDS-UPDRS 2 ranged from -2 to 0.5	MD 0.46 lower (1.91 lower to 0.99 higher)	-	145 (3 RCTs)	⨁⨁⨁◯
Change in MDS-UPDRS 2	The mean change in MDS-UPDRS 2 ranged from -2 to 0.5	MD 0.46 lower (1.91 lower to 0.99 higher)	-	145 (3 RCTs)	Moderate^a
Change in MDS-UPDRS 3 (On medication)	The mean change in MDS-UPDRS 3 (On medication) ranged from -3.85 to 0.4	MD 1.14 higher (2.14 lower to 4.42 higher)	-	99 (2 RCTs)	⨁⨁⨁◯
Change in MDS-UPDRS 3 (On medication)		MD 1.14 higher (2.14 lower to 4.42 higher)	-	99 (2 RCTs)	Moderate^a
Change in MDS-UPDRS 3 (OFF medication)	The mean change in MDS-UPDRS 3 (OFF medication) ranged from -4.5 to - 2	MD 1.26 higher (2.27 lower to 4.79 higher)	-	91 (2 RCTs)	⨁⨁⨁◯
Change in MDS-UPDRS 3 (OFF medication)		MD 1.26 higher (2.27 lower to 4.79 higher)	-	91 (2 RCTs)	Moderate^a
Change in MDS-UPDRS 4	The mean change in MDS-UPDRS 4 ranged from -0.81 to 0.26	MD 0.39 lower (1.63 lower to 0.85 higher)	-	100 (2 RCTs)	⨁⨁⨁◯
Change in MDS-UPDRS 4	The mean change in MDS-UPDRS 4 ranged from -0.81 to 0.26	MD 0.39 lower (1.63 lower to 0.85 higher)	-	100 (2 RCTs)	Moderate^a
Change in IBS-SSS	The mean change in IBS-SSS ranged from -68.63 to -25.1	MD 15.91 lower (63.71 lower to 31.89 higher)	-	99 (2 RCTs)	⨁⨁◯◯
Change in IBS-SSS	The mean change in IBS-SSS ranged from -68.63 to -25.1	MD 15.91 lower (63.71 lower to 31.89 higher)	-	99 (2 RCTs)	Low^a,b
Change in MOCA	The mean change in MOCA ranged from 0.24 to 3.89	MD 0.11 higher (1.34 lower to 1.57 higher)	-	145 (3 RCTs)	⨁⨁◯◯
Change in MOCA	The mean change in MOCA ranged from 0.24 to 3.89	MD 0.11 higher (1.34 lower to 1.57 higher)	-	145 (3 RCTs)	Low^a,b
Change in PDQ-39 SI	The mean change in PDQ-39 SI ranged from -1.9 to 1.31	MD 2.13 lower (5.62 lower to 1.36 higher)	-	91 (2 RCTs)	⨁⨁⨁◯
Change in PDQ-39 SI	The mean change in PDQ-39 SI ranged from -1.9 to 1.31	MD 2.13 lower (5.62 lower to 1.36 higher)	-	91 (2 RCTs)	Moderate^a
GI adverse events	179 per 1000	596 per 1000 (181 to 1000)	RR 3.32 (1.01 to 10.87)	91 (2 RCTs)	⨁⨁⨁◯
GI adverse events	179 per 1000	596 per 1000 (181 to 1000)	RR 3.32 (1.01 to 10.87)	91 (2 RCTs)	Moderate^c

Note. CI, confidence interval; MD, mean difference; RR, risk ratio; ^a 95 % Confidence Interval (CI) is wide and crossing 0; ^b Heterogeneity (I2) is >50%; ^c Wide 95 % Confidence Interval (CI).

Change in IBS-SSS

The analysis included two studies involving 99 patients (57 FMT vs 42 Placebo). Low certainty evidence revealed that FMT and placebo are comparable regarding change in IBS-SSS at short-term follow-up (MD = −15.91; 95% CI: [-63.17,31.89]; P = .51; I² = 76%) (Supplemental Figure 2).

Change in MoCA Score

A total of 145 individuals from three studies (79 in the FMT group and 66 in the placebo group) were included in the analysis. Low certainty evidence indicated that FMT and placebo showed no significant difference regarding change in MoCA scores (MD = 0.11; 95% CI: [-1.34, 1.57]; P = .88; I² = 68%) (Supplemental Figure 3).

Change in PDQ-39 SI

The analysis included two studies involving 91 patients (52 FMT vs 39 Placebo). Moderate certainty evidence suggested no significant difference regarding change in PDQ-39 SI (MD = −2.13, 95% CI: [-5.62,1.36]; P = .23; I² = 0%) between the two arms (Supplemental Figure 4).

Change in GI adverse events

The analysis included two studies involving 91 patients (52 FMT vs 39 Placebo). Moderate certainty evidence revealed that GI adverse events were more frequent in the FMT group at short-term follow-up (RR = 3.32; 95% CI: [1.01,10.87]; P = .05; I² = 39%) (Supplemental Figure 5).

Publication Bias and Sensitivity Analysis

Funnel plots were used to evaluate the risk of publication bias. The symmetrical appearance of the funnel plots suggests a low risk of publication bias (Supplemental Figures 6–14). A leave-one-out sensitivity analysis was conducted to assess the cause of heterogeneity. On removing the study by Scheperjans et al, the heterogeneity changes from 68% to 45% in the case of the MoCA score (Supplemental Figure 15).

Discussion

To our knowledge, this is the first systematic review and meta-analysis comparing the outcomes of PD patients treated with FMT. We found comparable results between the two treatment groups for the motor outcomes assessed by employing MDS-UPDRS II, MDS-UPDRS III (on-medication), MDS-UPDRS III (off-medication), and MDS-UPDRS IV. In terms of non-motor outcomes, including change in MDS-UPDRS 1, change in IBS-SSS scores, change in cognition assessed by the MoCA scale, and change in quality of life evaluated by the PDQ-39 SI scale, demonstrated a nonsignificant trend favouring the FMT group.

With regard to the MDS-UPDRS motor score, our findings were consistent with Scheperjans et al, who illustrated no substantial improvement with the administration of FMT, though its small sample size and crossover design without a washout period might restrict interpretability³⁷. Cheng and Bruggeman reported motor improvements in the FMT group, which were not consistent with our meta-analysis findings.^38,39 This discrepancy could be due to differences in FMT protocols, such as administration methods and donor selection, as well as variations in baseline PD severity across the included trials. Our meta-analysis revealed no significant improvement in motor symptoms, suggesting that factors like gut microbiota, levodopa metabolism, and the progression of neurodegeneration may influence the outcomes.⁴⁰ The microbial taxa, predominantly Enterococcus faecalis, that constitute the levodopa metabolizing TyrDC enzyme activity, alter the pharmacokinetics of levodopa^41,42 and thus reduce its systemic bioavailability.^43-45 The FMT-induced gut remodeling may influence levodopa pharmacokinetics heterogeneously across patients, potentially augmenting or impairing its bioavailability based on the final microbial architecture, which can ultimately yield varying motor responses.^41,46 The standard clinical scales like MDS-UPDRS may not be adequately sensitive to detecting the subtle yet clinically relevant motor improvements in patients whose levodopa pharmacokinetics are favorably impacted by FMT. This underscores the need to leverage AI-based motion analysis and machine learning–based tracking tools owing to their high-resolution, continuous, and objective quantification of motor parameters, enabling detection of subtle yet clinically meaningful changes that may otherwise be obscured by pharmacokinetic heterogeneity.

The nigrostriatal degeneration of PD precedes its clinical manifestation,¹² contracting the potential for FMT-mediated neuromodulation to reverse dopaminergic deficits. The bidirectionality of GBA implies that while gut dysbiosis is a crucial contributing factor to PD, the neurodegenerative alterations may independently disintegrate the gut taxa and architectural integrity of microbiota restoration by FMT¹¹. This might elucidate that microbial shifts in PD are predominantly a consequence of neurodegeneration rather than a cause, hence restricting the therapeutic potential of FMT in advancing PD. The MDS-UPDRS Part III (off-medication) scores, owing to higher within-subject reliability, are a more appropriate measure of baseline motor function.⁴⁷ However, even in this state, we found no improvement post-FMT, projecting concerns regarding reliance on FMT as a standalone intervention.

The improvement of non-motor symptoms after the administration of FMT did not reach statistical significance in our study. Thus, the comparable efficacy of FMT and the control group regarding the mitigation of non-motor manifestations in our meta-analysis reinforces deeper pathophysiological underpinnings of GBA dysfunction, where microbial perturbations might be one element of a broader dysregulation mechanism. Unlike our meta-analysis, Scheperjans and Cheng et al showed marked improvement in the FMT group.^37,38 However, Bruggeman et al. established no superiority of FMT compared with placebo, reinforcing similar findings from our study.³⁹ The unchanged IBS-SSS score in our meta-analysis may be explained by the early degeneration of the enteric nervous system, including the submucosal and myenteric plexus, even before the motor symptoms of PD become apparent.^48-50 This might suggest a neuronal rather than microbial pathogenesis of PD, implying that the host’s gut microbiota reconstruction by FMT does not necessarily translate to enteric neuronal integrity and improvement in clinical symptoms.

Regarding cognition, the trial by Cheng et al showed worsening MOCA scores in the FMT group, while Bruggeman and Scheperjans et al revealed comparable cognitive outcomes as no significant difference was reported between the MOCA scores of both treatment groups^37-39. In PD, the physiological integrity of cognitive capacities undergoes disruption in equilibrium partially due to the alleviated population of SCFAs-producing bacteria.⁵¹ Consequently, the SCFA’s capacity to enhance gut barrier integrity, along with mitigating inflammation and modulating immune responses, is severely compromised.⁵² Also, studies in rodents have demonstrated that specific microbiota are more selectively neuroprotective, whereas others have a minimal role in cognition.^53,54

Given that gut microbiota is influenced by ethnicity and geographic location, this might imply that standard FMT may not yield favorable outcomes when heterogeneities in the donor’s fecal microbiome fail to restore critical strains, such as SCFA-producing bacteria, that are necessary for modulating neuroinflammatory and dopaminergic pathways.^55,56 The inadequacy of FMT in mitigating non-motor symptoms elucidates the predominant influence of systemic and central neuroinflammation over gut-driven inflammatory cascades, potentially constraining its utility in optimizing quality of life among patients with PD⁵⁷. With neuroimmune dysregulation and microglial activation being the cornerstone of PD progression, gut-targeted interventions may require supplementation with direct central anti-inflammatory therapies. Moreover, as PD advances, progressive dopaminergic neuronal degeneration curtails the relevance of gut modulation, thereby suggesting a time-sensitive window for microbial interventions confined to early or preclinical neuroprotection.^58,59

The results of our analysis demonstrate that the patient population treated with FMT features a higher prevalence of adverse gastrointestinal events, potentially raising concerns over the modality’s safety profiles. Our pooled findings resonate with Scheperjans and Bruggeman et al, who documented adverse gastrointestinal symptoms in the FMT-treated group^37,39. In contrast, Cheng et al. reported improved gastrointestinal symptoms when treated with FMT.³⁸ This divergence may stem from oral capsule administration, shorter follow-up, and varying delivery routes.³⁸ These variations reflect the intervention of patient heterogeneity, timelines of outcome evaluations, study designs, and PD stage pathophysiology. To illustrate our findings, the pronounced incidence of adverse gastrointestinal events may be stemming from the compromised ability of an already dysfunctional enteric nervous system (ENS) to adapt to foreign microbial ecosystems post-FMT⁵⁹, hence prompting a critical appraisal of FMT’s safety profile and long-term consequences. Also, the hampered gut-brain communication in conjunction with heightened intestinal permeability may increase predisposition to translocation of microbial metabolites, exacerbating maladaptive host-donor microbiome interactions that aggravate gastrointestinal dysfunction.^11,60

The diminished correction rate of long-term dysbiosis post-FMT suggests a failure to accomplish consistent microbial homeostasis, which may synthesize chronic gut inflammation to foster gastrointestinal distress and immune hyperactivation.³⁷ FMT may also introduce disruptions in the metabolism of bile acids, which may disintegrate the equilibrium of primary and secondary bile acids, thereby precipitating fat malabsorption, steatorrhea, and diarrhea.⁶¹ In addition, shifts in gut microbiota constituents could expand the ecosystem of bile-acid deconjugation bacteria, potentially facilitating small intestinal bacterial overgrowth (SIBO), which catalyzes bloating, gut permeability, and dysmotility.⁶² This necessitates the induction of precision microbiota restoration strategies that ensure the establishment of a balanced and functionally stable gut ecosystem, instead of introducing transient or maladaptive microbial taxa to mitigate unintended metabolic and gastrointestinal sequelae.

Limitations

Our study has certain limitations. First, the small number of clinical trials assessing the safety and effectiveness of FMT in managing PD may limit the statistical power to identify potentially important clinical insights. Secondly, discrepancies in FMT protocols, including variations in donor and recipient selection, routes of administration, preparatory method of fecal transplant, and application techniques, could have introduced clinical heterogeneity; however, our study demonstrated a low statistical heterogeneity. Variations in outcome measures and definitions of adverse events may have compromised comparability parameters across included studies. Also, funnel plots have limited power to detect publication bias with fewer than 10 studies. Since this meta-analysis includes only 3 RCTs, the funnel plot should be interpreted cautiously.

Conclusion

The employment of FMT is comparable to placebo in terms of motor and non-motor outcomes. However, an amplified association with adverse gastrointestinal events mandates long-term, prospective studies to evaluate the prolonged safety and tolerability of FMT in patients with PD. An extensively pragmatic safety and efficacy profile of FMT is less likely to be established by studying its effects as monotherapy. Future research must incorporate multifaceted therapeutic strategies with targeted adjunctive modalities, including prebiotics, postbiotics, psychobiotics, synbiotics, dietary modifications, and ENS-preserving regimens. Baseline microbiome evaluation coupled with precise microbiome engineering is warranted for optimization engraftment strategies and enhancement of host-microbiota synergy, expanding FMT’s therapeutic paradigm. Further research into the relationship between PD severity, stage, and clinical subtypes with consistent assessment metrics is also imperative.

Supplemental Material

Supplemental Material - Fecal Microbiota Transplantation for Treatment of Parkinson’s Disease: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Supplemental Material for Fecal Microbiota Transplantation for Treatment of Parkinson’s Disease: A Systematic Review and Meta-Analysis of Randomized Controlled Trials by Muhammad Hassan Waseem, Zain ul Abideen, Areeba Shoaib, Nohela Rehman, Muhammad Osama, Barka Sajid, Rowaid Ahmad, Zara Fahim, Muhammad Wajih Ansari, Sania Aimen, Ameer Haider Cheema, Pawan Kumar Thada in Journal of Central Nervous System Disease

Footnotes

ORCID iD

Pawan Kumar Thada

Authors’ Contributions

Study concept and design: MHW and ZUA; acquisition of data: ZUA and AS; analysis and interpretation of data: AS, NR,SA and MO; drafting of the manuscript: RA, ZF, WA and ZUA; critical revision of the manuscript: MHW and AHC.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data will be made available upon reasonable request to the authors.*

Supplemental Material

Supplemental material for this article is available online.

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Organization

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Ray

Alexis

Emma

Nooshin

Foad

A-A

Ahmed

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Sampson

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Thron

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Sun

Shen

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Carabotti

Scirocco

Maselli

Severi

. The gut-brain axis: interactions between enteric microbiota, central and enteric nervous systems. Ann Gastroenterol. 2015;28(2):203-209.

Huang

Liu

, et al. Leveraging sequence-based faecal microbial community survey data to identify alterations in gut microbiota among patients with Parkinson's disease. Eur J Neurosci. 2021;53(2):687-696.

10.

Aho

VTE

Pereira

PAB

Voutilainen

, et al. Gut microbiota in Parkinson's disease: temporal stability and relations to disease progression. EBioMedicine. 2019;44:691-707.

11.

Cryan

O'Riordan

Sandhu

Peterson

Dinan

. The gut microbiome in neurological disorders. Lancet Neurol. 2020;19(2):179-194.

12.

Hirayama

Ohno

. Parkinson's disease and gut microbiota. Ann Nutr Metab. 2021;77(Suppl 2):28-35.

13.

Qian

Yang

, et al. Alteration of the fecal microbiota in Chinese patients with Parkinson's disease. Brain Behav Immun. 2018;70:194-202.

14.

Bhattarai

, et al. Role of gut microbiota in regulating gastrointestinal dysfunction and motor symptoms in a mouse model of Parkinson's disease. Gut Microbes. 2021;13(1):1866974.

15.

Takahashi

Nishiwaki

Ito

, et al. Altered gut microbiota in Parkinson's disease patients with motor complications. Parkinsonism Relat Disord. 2022;95:11-17.

16.

Alam

Abbas

Mustafa

Usmani

Habib

. Microbiome-based therapies for Parkinson’s disease. Front Nutr. 2024;11:1496616.

17.

Goya

Xue

Sampedro-Torres-Quevedo

, et al. Probiotic Bacillus subtilis protects against α-Synuclein aggregation in C. elegans. Cell Rep. 2020;30(2):367-380.e7.

18.

Ojha

Patil

Jain

Kole

Kaushik

. Probiotics for neurodegenerative diseases: a systemic review. Microorganisms. 2023;11(4):1083.

19.

Davani-Davari

Negahdaripour

Karimzadeh

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20.

Brüssow

. Probiotics and prebiotics in clinical tests: an update. F1000Res. 2019;8:F1000 Faculty Rev-1157.

21.

Biazzo

Deidda

. Fecal microbiota transplantation as new therapeutic avenue for human diseases. J Clin Med. 2022;11(14):4119.

22.

Zikou

Koliaki

Makrilakis

. The role of Fecal microbiota transplantation (FMT) in the management of metabolic diseases in humans: a narrative review. Biomedicines. 2024;12(8):1871.

23.

Chen

Zaman

Ramakrishna

Olesen

. Stool banking for fecal microbiota transplantation: methods and operations at a large stool bank. Front Cell Infect Microbiol. 2021;11:622949.

24.

Merrick

. The role of faecal microbiota transplantation: looking beyond Clostridioides difficile infection. Ther Adv Infect Dis. 2021;8:2049936120981526.

25.

Wortelboer

Nieuwdorp

Herrema

. Fecal microbiota transplantation beyond Clostridioides difficile infections. EBioMedicine. 2019;44:716-729.

26.

Kim

Gluck

. Fecal microbiota transplantation: an update on clinical practice. Clin Endosc. 2019;52(2):137-143.

27.

Huang

Luo

, et al. Fecal microbiota transplantation to treat Parkinson's disease with constipation: a case report. Medicine (Baltim). 2019;98(26):e16163.

28.

Segal

Zlotnik

Moyal-Atias

Abuhasira

Ifergane

. Fecal microbiota transplant as a potential treatment for Parkinson's disease – a case series. Clin Neurol Neurosurg. 2021;207:106791.

29.

De Sciscio

Bryant

Haylock-Jacobs

, et al. Faecal microbiota transplant in Parkinson’s disease: pilot study to establish safety & tolerability. npj Parkinson's Dis. 2025;11(1):203.

30.

Nabil

Helal

Qutob

, et al. Efficacy and safety of fecal microbiota transplantation in the management of Parkinson'S disease: a systematic review. BMC Neurol. 2025;25(1):291.

31.

Moher

Liberati

Tetzlaff

Altman

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32.

Schiavo

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33.

Ouzzani

Hammady

Fedorowicz

Elmagarmid

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34.

Sterne

JAC

Savović

Page

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35.

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36.

Higgins

Thompson

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37.

Scheperjans

Levo

Bosch

, et al. Fecal microbiota transplantation for treatment of parkinson disease: a randomized clinical trial. JAMA Neurol. 2024;81(9):925-938.

38.

Cheng

Tan

Zhu

, et al. Efficacy of fecal microbiota transplantation in patients with Parkinson's disease: clinical trial results from a randomized, placebo-controlled design. Gut Microbes. 2023;15(2):2284247.

39.

Bruggeman

Vandendriessche

Hamerlinck

, et al. Safety and efficacy of faecal microbiota transplantation in patients with mild to moderate Parkinson's disease (GUT-PARFECT): a double-blind, placebo-controlled, randomised, phase 2 trial. eClinicalMedicine. 2024;71:102563.

40.

Felice

Quigley

Sullivan

O'Keeffe

O'Mahony

. Microbiota-gut-brain signalling in Parkinson's disease: implications for non-motor symptoms. Parkinsonism Relat Disord. 2016;27:1-8.

41.

Cheng

Hardy

Hillard

Feix

Kalyanaraman

. Mitigating gut microbial degradation of levodopa and enhancing brain dopamine: implications in Parkinson’s disease. Commun Biol. 2024;7(1):668.

42.

Reunanen

Ghemtio

Patel

, et al. Targeting bacterial and human levodopa decarboxylases for improved drug treatment of Parkinson's disease: discovery and characterization of new inhibitors. Eur J Pharm Sci. 2025;211:107133.

43.

Miyaue

Yamamoto

Liu

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44.

van Kessel

Frye

El-Gendy

, et al. Gut bacterial tyrosine decarboxylases restrict levels of levodopa in the treatment of Parkinson’s disease. Nat Commun. 2019;10(1):310.

45.

Maini Rekdal

Bess

Bisanz

Turnbaugh

Balskus

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46.

Brüssow

. Parkinson disease, levodopa and the gut microbiota-when microbiology meets pharmacology. Environ Microbiol. 2020;22(3):808-812.

47.

Evers

LJW

Krijthe

Meinders

Bloem

Heskes

. Measuring Parkinson's disease over time: the real-world within-subject reliability of the MDS-UPDRS. Mov Disord. 2019;34(10):1480-1487.

48.

Yin

Wang

, et al. Prevalence of Parkinson's disease: a community-based study in China. Mov Disord. 2021;36(12):2940-2944.

49.

Braak

de Vos

RAI

Bohl

Del Tredici

. Gastric alpha-synuclein immunoreactive inclusions in Meissner's and Auerbach's plexuses in cases staged for Parkinson's disease-related brain pathology. Neurosci Lett. 2006;396(1):67-72.

50.

Schemann

Neunlist

. The human enteric nervous system. Neuro Gastroenterol Motil. 2004;16(Suppl 1):55-59.

51.

Tan

Chong

Lim

, et al. Gut microbial ecosystem in parkinson disease: new clinicobiological insights from multi-omics. Ann Neurol. 2021;89(3):546-559.

52.

Parada Venegas

De la Fuente

Landskron

, et al. Short chain fatty acids (SCFAs)-Mediated gut epithelial and immune regulation and its relevance for inflammatory bowel diseases. Front Immunol. 2019;10:277.

53.

Kang

Cha

Kwon

, et al. Akkermansia muciniphila improve cognitive dysfunction by regulating BDNF and serotonin pathway in gut-liver-brain axis. Microbiome. 2024;12(1):181.

54.

Lei

Cheng

Gao

, et al.

Akkermansia muciniphila in neuropsychiatric disorders: friend or foe?

Front Cell Infect Microbiol. 2023;13:1224155.

55.

Porras

Shi

Zhou

, et al. Geographic differences in gut microbiota composition impact susceptibility to enteric infection. Cell Rep. 2021;36(4):109457.

56.

Gupta

Paul

Dutta

. Geography, ethnicity or subsistence-specific variations in human microbiome composition and diversity. Front Microbiol. 2017;8:1162.

57.

Hussein

Guevara

Del Valle

Gupta

Benson

Huntley

. Non-motor symptoms of Parkinson's disease: the neurobiology of early psychiatric and cognitive dysfunction. Neuroscientist. 2023;29(1):97-116.

58.

Hamamah

Aghazarian

Nazaryan

Hajnal

Covasa

. Role of microbiota-gut-brain axis in regulating dopaminergic signaling. Biomedicines. 2022;10(2):436.

59.

Zhang

Tang

Guo

. Parkinson’s disease and gut microbiota: from clinical to mechanistic and therapeutic studies. Transl Neurodegener. 2023;12(1):59.

60.

Chen

Liao

, et al. Alteration of gut microbial metabolites in the systemic circulation of patients with Parkinson's disease. J Parkinsons Dis. 2022;12(4):1219-1230.

61.

Bustamante

Dawson

Loeffler

, et al. Impact of fecal microbiota transplantation on gut bacterial bile acid metabolism in humans. Nutrients. 2022;14(24):5200.

62.

Tan

Chuah

Beh

Schee

Mahadeva

Lim

. Gastrointestinal dysfunction in Parkinson's disease: neuro-Gastroenterology perspectives on a multifaceted problem. J Mov Disord. 2023;16(2):138-151.

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