Efficacy of probiotics on immunological and clinical outcomes in allergic rhinitis: an umbrella review and updated meta-analysis of RCTs in children and adults

Abstract

Background

Allergic rhinitis (AR) is a prevalent inflammatory condition with limited long-term treatment options. Probiotics have been investigated as immunomodulatory agents, yet evidence remains inconsistent. This umbrella review with updated meta-analysis evaluated probiotic efficacy on immunological and clinical outcomes in children and adults with AR.

Methods

We systematically searched PubMed, Scopus, Web of Science, Cochrane Library, and Embase through May 2026. Randomized controlled trials assessing probiotics effects on IgE, antigen-specific IgE, eosinophil count, Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ), and Total Rhinitis Symptom Score (RTSS) were included. Weighted mean differences (WMD) with 95% confidence intervals (CI) were calculated using random-effects models with REML estimation; Hartung-Knapp-Sidik-Jonkman (HKSJ) was used for outcomes with ≤ 5 studies.

Results

Twenty-nine RCTs comprising 2,078 participants were included. Probiotic supplementation was associated with significant reductions in total IgE (WMD: -198.35, 95%CI: -291.10 to -105.61), global RQLQ (WMD: -9.43, 95%CI: -11.71 to -7.15), nasal-RQLQ (WMD: -1.52, 95%CI: -2.89 to -0.15), and nasal-RTSS (WMD: -1.97, 95%CI: -3.61 to -0.32). No significant effects were observed for antigen-specific IgE, eosinophil count, eye-RQLQ, global-RTSS, or eye-RTSS. The umbrella review of seven meta-analyses (2008–2025) confirmed consistent benefits for quality of life and nasal symptoms.

Conclusions

Probiotic supplementation may improve quality of life and nasal symptoms while reducing IgE in AR patients, but evidence is limited by high heterogeneity, fragility of the IgE finding, and pooling of diverse strains. Routine clinical recommendation is not supported by high‑certainty evidence; further strain‑specific RCTs are needed.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12865-026-00873-1.

Introduction

Allergic rhinitis (AR) is a prevalent inflammatory condition of the upper airways, affecting approximately 10–40% of the global population, with increasing incidence in both pediatric and adult populations [1, 2]. Characterized by symptoms including nasal congestion, rhinorrhea, sneezing, and pruritus, AR substantially impairs quality of life, sleep quality, work productivity, and academic performance [3, 4]. The pathophysiology of AR involves immunoglobulin E (IgE)-mediated hypersensitivity reactions to environmental allergens, triggering Th2-dominant immune responses and subsequent release of pro-inflammatory mediators from mast cells and eosinophils [5, 6]. Allergic rhinitis is also clinically important because it frequently coexists with asthma in children, and both diseases share overlapping allergic sensitization patterns and inflammatory pathways [7].

Conventional pharmacological management including antihistamines, intranasal corticosteroids, and allergen immunotherapy, while effective, is associated with variable treatment responses, potential adverse effects, and limited long-term compliance [8, 9]. These limitations have prompted growing interest in complementary and alternative therapeutic approaches, particularly immunomodulatory interventions that target underlying disease mechanisms.

Probiotics, defined as live microorganisms conferring health benefits when administered in adequate amounts, have emerged as promising candidates for allergy management [10]. The proposed mechanisms underlying probiotic effects in allergic diseases include enhancement of regulatory T-cell function, modulation of Th1/Th2 balance, reinforcement of epithelial barrier integrity, and alteration of gut microbiota composition [11]. Preclinical and clinical investigations have suggested that specific probiotic strains may attenuate allergic inflammation through induction of IL‑10 and TGF‑β production, possible suppression of allergen‑specific IgE synthesis, and promotion of short‑chain fatty acid (SCFA) production with consequent anti‑inflammatory effect [1].

Despite accumulating evidence, the efficacy of probiotics in allergic rhinitis remains controversial due to considerable heterogeneity across individual randomized controlled trials (RCTs) regarding study populations, probiotic strains, treatment durations, and outcome measures [12]. Previous meta-analyses have yielded inconsistent findings, with some reporting significant improvements in clinical symptoms and immunological parameters [13, 14], while others demonstrating limited or conditional benefits [15, 16]. Moreover, the rapidly expanding body of literature necessitates regular synthesis and critical appraisal of available evidence.

Several meta-analyses have been published recently [13, 14, 17, 18], but none have included trials from 2025 to 2026, and none have simultaneously evaluated IgE, antigen-specific IgE, eosinophils, RQLQ, and RTSS in a single comprehensive analysis.Therefore, the present study aimed to perform an umbrella review with updated comprehensive meta-analysis of RCTs examining the efficacy of probiotic supplementation on immunological parameters (total IgE, antigen-specific IgE, eosinophil counts) and clinical outcomes (Rhinoconjunctivitis Quality of Life Questionnaire [RQLQ] and Total Rhinitis Symptom Score [RTSS]) in both children and adults with allergic rhinitis.

Methods

Protocol and registration

This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [19]. The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) under registration number CRD420261410337.

Search strategy

A comprehensive systematic literature search was performed across multiple electronic databases including PubMed/MEDLINE, Scopus, Web of Science, Cochrane Library, and Embase from inception through May 2026. The search strategy combined Medical Subject Headings (MeSH) terms and keywords related to probiotics, allergic rhinitis, and study design (Supplementary Table 1). Additionally, reference lists of included studies and relevant systematic reviews were manually screened to identify potentially eligible articles not captured by the electronic search. No language restrictions were applied during the initial search, although only English-language articles were included in the final synthesis.

Study selection and eligibility criteria

For the systematic review and meta-analysis,, studies were included if they met the following PICOS criteria: Population: Children (aged < 18 years) or adults (aged ≥ 18 years) with diagnosed allergic rhinitis based on clinical criteria, allergen-specific IgE testing, or skin prick tests. Studies involving participants with other allergic comorbidities (asthma, atopic dermatitis) were included provided allergic rhinitis was the primary condition. Intervention: Oral supplementation with probiotics as single strains or mixtures, administered at any dose and for any duration. Comparison: Placebo or no intervention. Outcomes: At least one of the following outcomes: total serum IgE, antigen-specific IgE, eosinophil count, RQLQ scores (global, nasal, or eye domains), or RTSS scores (global, nasal, or eye domains). Study design: Randomized controlled trials (RCTs) with parallel or crossover designs. All included studies were RCTs. For crossover trials, only data from the first period before crossover were used to avoid carryover effects.

Exclusion criteria comprised: (1) studies using probiotics in combination with other active interventions (prebiotics, synbiotics, or pharmacological agents) where individual effects could not be isolated; (2) non-English publications; (3) animal studies or in vitro experiments; (4) observational studies, case reports, conference abstracts, or reviews; (5) studies lacking sufficient data for meta-analysis (mean ± SD or median with range/interquartile range) even after contacting corresponding authors.

For the umbrella review component, we included meta-analyses of RCTs evaluating probiotic effects on allergic rhinitis outcomes. Inclusion criteria were: (1) systematic review with meta-analysis design; (2) assessment of probiotic supplementation in allergic rhinitis populations; (3) reporting of at least one outcome relevant to allergic rhinitis (symptom scores, quality of life, immunological markers); (4) publication in peer-reviewed journals. When multiple meta‑analyses overlapped substantially (i.e., included the same primary RCTs), we did not pool their effect sizes. Instead, we narratively synthesized their findings to avoid double‑counting of primary studies. The added value of conducting an umbrella review alongside an updated meta‑analysis is threefold: (1) to capture conclusions from previous syntheses, (2) to identify consistency or discordance across existing meta‑analyses, and (3) to provide a higher‑level overview of the evidence base before presenting our updated meta‑analysis, which includes newly published trials (from 2024 to 2025) not covered by prior reviews.

Data extraction and management

Two independent reviewers performed data extraction using a standardized data collection form. Disagreements were resolved through discussion or consultation with a third reviewer. The following information was extracted from eligible RCTs: Study characteristics: first author, publication year, country, study design .Participant characteristics: sample size, age distribution (pediatric/adult), diagnostic criteria, disease severity. Intervention details: probiotic strain(s), dose (colony-forming units/day), duration, mode of administration. Control details: placebo composition. Outcome data: baseline and post-intervention values (mean ± SD) for IgE, antigen-specific IgE, eosinophil count, RQLQ, and RTSS; change scores where available; follow-up periods. Safety data: adverse events reported. From included meta-analyses (umbrella review component), we extracted: first author, publication year, number of included RCTs, total sample size, probiotic strains evaluated, outcomes assessed, main findings, and quality assessment ratings.

Risk of bias and quality assessment

Methodological quality of included RCTs was evaluated using the Cochrane Risk of Bias tool (RoB 2.0) [20], assessing five domains: randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of reported results. Each domain was judged as “low risk,” “some concerns,” or “high risk.”

Quality of included meta-analyses was assessed using the Assessment of Multiple Systematic Reviews (AMSTAR-2) tool [21], comprising 16 items with overall confidence ratings categorized as “high,” “moderate,” “low,” or “critically low.”

Statistical analysis

All statistical analyses were performed using Stata software (version 17.0, StataCorp, College Station, TX, USA). For continuous outcomes, effect sizes were calculated as weighted mean differences (WMD) with corresponding 95% confidence intervals (CIs). When studies reported data in different units or scales, standardized mean differences (SMD) were employed. Heterogeneity across studies was assessed using Cochran’s Q test and quantified with the I² statistic [22]. Given anticipated heterogeneity, a random-effects model (DerSimonian and Laird method) was applied for all meta-analyses [23]. Subgroup analyses were conducted to explore potential sources of heterogeneity based on: Age group: children (< 18 years) versus adults (≥ 18 years), Health condition: allergic rhinitis versus allergic rhinitis with comorbidities, Probiotic type: single strain (Lactobacillus, Bifidobacterium, other) versus multi-strain mixtures, Treatment duration: ≤8 weeks versus > 8 weeks, and Sample size: ≤50 participants versus > 50 participants. For outcomes with ≥ 10 studies, we performed meta-regression to examine the impact of continuous covariates (age, duration) and categorical covariates (strain type, study quality). Sensitivity analyses were performed using the leave-one-out approach to assess the influence of individual studies on pooled effect sizes. Studies exerting disproportionate influence were identified and results were re-calculated excluding those studies. For the primary IgE outcome, we calculated the fragility index (the minimum number of studies whose removal changes statistical significance). Publication bias was evaluated through visual inspection of funnel plots and and formally tested using Egger’s regression asymmetry test only for outcomes with ≥ 10 studies [24], In cases suggesting publication bias, Duval and Tweedie’s trim-and-fill method was applied to adjust for potential missing studies [25].

Certainty of evidence

The Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework was employed to assess the certainty of evidence for each outcome [26]. Evidence was categorized into four levels: high, moderate, low, or very low certainty based on considerations of risk of bias, inconsistency, indirectness, imprecision, and publication bias.

Results

Results of the search flow, characteristics and umbrella review

A total of 1072 publications were retrieved through systematic search and 379 were marked as duplicates and were removed. Primary screening of available RCTs resulted in the exclusion of 659 irrelevant trials. Likewise, 34 remained studies were evaluated using full-text and five studies were excluded by following reasons: studies which have used probiotics in combination with other compounds, studies that assessed the effect of the synbiotics, and studies with other languages. Finally, 29 RCTs were included in current study. The study selection flow diagram is outlined in the Fig. 1. The basic characteristics of the included articles are shown in Table 1. Included RCTs were published between 2002 and 2025. The sample size of included trials ranged from 20 to 425 individuals. The intervention duration varied from 3 to 48 weeks across studies.

Fig. 1.

Flow diagram of study selection process

Table 1.

Study characteristics of included studies

Author, year	Country	Ethnical	Design	Arms of study	Participants	Age, year	Control group	Duration	Serious adverse events (SAEs)	Adverse events (AEs)
Chen, 2010 [27]	china	Chinese	RCT	2 × 109 CFU +Placebo	105	6_12 years	Milk powder	8 weeks	No SAEs	NR
Giovannini et al., 2007 [28]	Italy	Italian	RCT	108 CFU +Placebo	99	2_5 years	A non-fermented milk(control)	48 weeks	Change in time free from and number of episodes of asthma/rhinitis, total IgE	NR
Harata et al., 2017 [29]	Japan	Japanese	RCT	1.4 × 108 CFU + Placebo	25	36.9 years 36.5 years	A non-fermented milk(control)	10 weeks	Change in gut microbiota composition and blood lipid levels	NR
Kawase et al., 2009 [30]	Japan	Japanese	RCT	2 × 108 CFU + Placebo	38	20_57 years	Yoghurt	10 weeks	No SAEs	No AEs
Lue et al., 2012 [31]	Taiwan	Taiwanese	RCT	1 × 1010 CFU+ Placebo	57	7_12 years	NR	24 weeks	Changes in RTSS and PRQLQ	No AEs
Nishimura et al., 2009 [32]	Japan	Japanese	RCT	60 mg/day+ Placebo	30	33.8 years 36.5 years	Placebo tablets containing no Th221	8 weeks	Change in disease severities, TNSS, total IgE, antigen specific IgE	NR
Xiao et al., 2006 [33]	Japan	Japanese	RCT	5 × 1010 CFU +Placebo	40	23–61 years 24–55 years	Dextrin	14 weeks	No SAEs	NR
Xiao et al., 2007 [34]	Japan	Japanese	RCT	5 × 1010 CFU+ Placebo	32	37.6 years 41.0 years	Dextrin	4 weeks	No SAEs	No AEs
Ishida et al., 2005 [35]	Japan	Japanese	RCT	3 × 1010 CFU+ Placebo	49	34.0 years 36.9 years	Heattreated milk	8 weeks	No SAEs	Change in SMS total IgE, antigen specific IgE
Nagata et al., 2010 [36]	Japan	Japanese	RCT	8.7 × 108 CFU+ Placebo	53	18–27 years	Branched dextrin	6 weeks	No SAEs	Decreased SMS and itchy eyes
Dotterud et al., 2010 [37]	Norway	Norwegian	RCT	5 × 1010 CFU	32	29.97 years 29.78 years	NR	4 weeks	No SAEs	NR
Kukkonen i et al., 2011 [38]	Finland	Finnish	RCT	5 × 109- 5 × 109- 2 × 109 CFU	131	66.9 years 66.2 years	NR	24 weeks	No SAEs	NR
Ishida et al. 2005 [35]	Japan	Japanese	RCT	5 × 1010 CFU	20	30.6 years 34.1 years	Milk	6 weeks	No SAEs	NR
Gotoh et al. 2014 [39]	Japan	Japanese	RCT	100 mg/day of L. gasseri	31	30.7 years 30.3 years	NR	8 weeks	No SAEs	NR
Huang et al. 2018 [40]	Taiwan	Taiwanese	RCT	NR	73	6–18 years	NR	4 weeks	No SAEs	NR
Ouwehand et al. 2009 [41]	Finland	Finnish	RCT	5 × 109 CFU	30	4–13 years	Microcrystalline cellulose	16 weeks	No SAEs	NR
Harata et al. 2017 [29]	Japan	Japanese	RCT	1.4 × 108 CFU	25	36.9 years 36.5 years	Fermented milk	10 weeks	No SAEs	NR
Tamura et al. 2007 [42]	Japan	Japanese	RCT	4 × 10 10 CFU	109	39.3 years 39.5 years	Unfermented milk	8 weeks	No SAEs	NR
Dennis et al. 2017 [43]	Florida	Floridian	RCT	1.2 billion CFU	161	18–60 years	Potato starch	8 weeks	No SAEs	NR
Giudice et al. 2017 [44]	Italy	Italian	RCT	(3 × 109 CFU)-(1 × 109 CFU)-(1 × 109 CFU)	40	9 ± 2.2 years	An inert excipient as powder	4 weeks	No SAEs	NR
Peng et al. 2005 [45]	Taiwan	Taiwanese	RCT	5 × 109 CFU	60	16.07 years 16.60 years	Milk powder	4 weeks	Decease in PRQLQ and bothersome symptoms and reduction in the frequency and dosage required for medical treatment	NR
Wang et al. 2004 [46]	China	Chiniese	RCT	2.0 × 109 CFU	80	15.87 years 14.00 years	Streptococcus thermophilus and Lactobacillus bulgaricus	4 weeks	Decreased PRQLQ	NR
Costa et al. 2014 [47]	France		RCT	2.0 × 109 CFU	425	18–60 years	Microcrystalline cellulose	5 weeks	Decreased RQLQ	NR
Lin et al. 2014 [48]	Taiwan	Taiwanese	RCT	4 × 109 CFU	60	6–12 years	Microcrystalline cellulose	12 weeks	Change in SSS, SMS, total IgE	Reduction in nasal, eye, medication scores; no change in total IgE
Helin et al. 2002 [49]	Finland	Finnish	RCT	5 × 109 CFU	31	14–36 years	Microcrystalline cellulose	6 weeks	Change in RTSS, respiratory and eye symptoms, and use of medications scores	NR
Ciprandi et al. 2005 [50]	Italy	Italian	RCT	(2 billion spores/vial)	20	12–15 years	NR	3 weeks	Change in RTSS	NR
Singh et al. 2013 [51]	Switzerland	Swiss	RCT	2.0 × 109 CFU	20	20–65 years	Maltodextrin	8weeks	Change in TNSS	Reduction in total nasal symptom scores
Sugihara et al. 2025 [52]	Japan	Japanese	RCT	0.7 × 1011 CFU	107	42.2 years 44.6 years	NR	12	Changes in RQLQ	NR
Kang et al. 2020 [53]	South Korea	Korean	RCT	5 × 109 CFU	95	19–65 years	5 × 109 CFU	4	No SAEs	Mild GI symptoms

In addition, basic characteristics of available meta-analysis evaluating the effect of probiotics supplementation on provided in the Table 2. Ten meta-analyses were included in our umbrella review. They have been published between 2008 and 2025. Included meta-analyses have evaluated the RQLQ, RTSS, and IgE.

Table 2.

Study characteristics of included meta-analyses

Author, year	Number of studies included	Participants, n	Age, year	Duration (weeks)	Effect size	main outcome
Dipankar Sardar et al., 2025 [17]	36	7400	24.4	12.9	MD	RQLQ global scores (mean difference [MD] = -9.43; P < 0.00001), RQLQ nasal scores (MD = -1.52; P = 0.03), RTSS nasal scores (MD = -1.96; P = 0.02) showed significant enhancements.
Chang Lu et al., 2025 [18]	31	2544	23.4	8.9	----	Probiotic mixtures may be the most effective in reducing RQLQ, Total IgE, and Special IgE
Chao Luo et al., 2022 [13]	28	2774	25.4	11.2	MD	probiotics significantly relieved allergic rhinitis symptoms (standardized mean difference [SMD], − 0.29, 95% confidence interval (CI) [− 0.44, − 0.13]; p = 0.0003, I2 = 89%), decreased Rhinoconjunctivitis RQLQ scores compared with the control group (SMD, − 0.64, 95% CI [− 0.79, − 0.49], p < 0.00001, I2 = 97%), and increased T helper cell 1(Th1)/Th2 ratio (mean difference [MD], − 2.47, 95% CI [− 3.27, − 1.68], p < 0.00001, I2 = 72%).There was no significant change in overall or specific IgE levels between probiotic-treated and placebotreated subjects (SMD, 0.09, 95%CI [− 0.16, 0.34], I2 = 0%, andSMD, − 0.03, 95% CI [− 0.18, 0.13], p = 0.72, I2 = 0%, respectively).
Xinyi Luo et al.; 2024 [54]	28	4765	0.9	111.5	MD	that the use of probiotics was associated with a significant improvement in total nose symptom scores (SMD, − 2.27; 95% CI, − 3.26 to − 1.29; P < 0.00001), itchy nose scores (SMD, − 0.44; 95% CI, − 0.80 to − 0.07; P = 0.02), sneezing scores (SMD, − 0.47; 95% CI, − 0.84 to − 0.10; P = 0.01), eye symptoms (SMD, − 3.77; 95% CI, − 5.47 to − 2.07; P < 0.00001), and Pediatric Rhinoconjunctivitis Quality of Life Questionnaire (SMD, − 2.52; 95% CI, − 4.12 to − 0.92; P < 00001).
Nancy Elazab et al.; 2013 [55]	25	4522	2.80	26.2	WMD	Probiotics were effective in reducing total IgE (mean reduction: − 7.59 U/mL [95% confidence interval (CI): − 14.96 to − 0.22]; P = 0.044).
Zajac et al.; 2015 [15]	23	1919	25.9	8	MD	the use of probiotics resulted in significant improvement in RQLQ scores compared to placebo [standard mean difference (SMD) − 2.23; p = 0.02]. Probiotics had no effect on RTSS [SMD − 0.36; p = 0.13] or total IgE levels [SMD 0.01; p = 0.94], while there was a trend toward a reduction in antigen-specific IgE [SMD 0.20; p = 0.06] in the placebo group compared to probiotic.
Gu¨ venc et al.; 2016 [16]	22	2242	22.5	75.8	MD	Probiotics showed significant reduction in nasal and ocular SS (standardized mean difference [SMD], _1.23, p _ 0.001; and SMD, _1.84, p _ 0.001; respectively), total, nasal, and ocular QoL scores compared with placebo (SMD, _1.84, p _ 0.001; SMD, _2.30, p _ 0.006; and SMD, _3.11, p _ 0.005; respectively
Chen et al.; 2023 [14]	15	1388	10.1	14.7	MD	Significantly greater reduction in PRQLQs from baseline to endpoint (SMD = − 2.57, 95% CI [− 4.66, − 0.48] P < 0.01), NSS (SMD = − 1.43, 95% CI [− 1.63,−1.23], P < 0.01) and ESS (total MD = − 1.67, 95% CI [− 1.79,−1.55], P < 0.01) were observed in probiotics group compared to control group. Probiotics have no significant effect to serum IgE and eosinophils (P > 0.01)
Kajal Farahmandi et al.; 2022 [56]	13	1591	15.7	11.4	SMD	The meta-analysis results showed that, neither L. paracasei Lp33 (SMD = − 1.61, 95% CI − 4.67, 1.45) nor L. rhamnosus GG (SMD = − 1.00, 95% CI − 3.01, 1.00) had significant efficacy for reducing nasal symptom scores
Vliagoftis et al.; 2008 [57]	12	726	29.5	22.09	NR	All the RCTs that studied perennial AR showed lower symptom scoring and medication use with the use of probiotics compared with placebo. Also, 5 of the 8 RCTs that referred to seasonal AR suggested an improvement in clinical outcomes. Nine RCTs that reported various immunologic measurements of allergy found no significant probiotic effects.

Quality assessment

Using the Cochrane RoB 2 tool, 13 of 29 RCTs (45%) had low risk of bias overall, 10 (36%) had some concerns, and 6 (21%) had high risk of bias, primarily due to the randomization process or missing outcome data (Table 3). Also, quality of the included meta-analyses were assessed. Four studies got higher and six meta-analysis got moderate quality (Table 4).

Table 3.

Quality of included studies in the meta-analysis

Study, Year	Randomization Process	Deviation from Intended Interventions	Selection of the Reported Result	Measurement of the Outcome	Missing Outcome Data
Chen, 2010	U	L	U	L	L
Giovannini et al., 2007	L	L	U	L	L
Harata et al., 2017	U	L	L	U	L
Kawase et al., 2009	U	L	U	U	L
Lue et al., 2012	L	L	U	L	L
Nishimura et al., 2009	H	L	L	L	U
Xiao et al., 2006	U	L	L	L	H
Xiao et al., 2007	U	L	L	L	H
Ishida et al., 2005	L	L	H	L	L
Nagata et al., 2010	L	L	L	L	H
Dotterud et al., 2010	L	L	L	L	L
Kukkonen i et al., 2011	H	L	L	L	H
Ishida et al. 2005	U	H	L	U	U
Gotoh et al. 2014	U	L	L	L	U
Huang et al. 2018	L	L	L	L	L
Ouwehand et al. 2009	H	L	H	L	L
Harata et al. 2017	L	L	L	L	L
Tamura et al. 2007	H	L	H	L	U
Dennis et al. 2017	L	L	L	L	L
Giudice et al. 2017	H	L	H	L	L
Peng et al. 2005	L	L	L	L	U
Wang et al. 2004	L	L	L	L	U
Costa et al. 2014	L	L	L	L	L
Lin et al. 2014	H	L	H	L	U
Helin et al. 2002	L	L	H	L	L
Ciprandi et al. 2005	H	U	L	L	U
Singh et al. 2013	U	L	L	L	U
Sugihara et al. 2025	L	L	L	L	L
Kang et al. 2020	L	L	L	L	L

Footprint: H high risk of bias, L low risk of bias, U unclear risk of bias

Table 4.

Quality of included meta-analyses in the umbrella review

Study	Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8	Q9	Q10	Q11	Q12	Q13	Q14	Q15	Q16	Quality
Dipankar Sardar et al., 2025	Yes	Yes	Yes	Yes	Yes	Partial yes	Yes	Yes	Yes	Partial yes	Yes	Partial yes	No	Yes	Yes	Yes	High
Chang Lu et al., 2025	No	Yes	Yes	Partial yes	Partial yes	NO	Partial yes	NO	Yes	NO	Partial yes	NO	No	Yes	Yes	NO	Moderate
Chao Luo et al., 2022	Yes	Yes	Yes	Partial yes	Yes	No	Yes	Yes	Yes	Partial yes	Yes	Yes	No	Yes	Yes	Yes	Moderate
Xinyi Luo et al.; 2024	Yes	Yes	Yes	Partial yes	Yes	Yes	Partial yes	Yes	Yes	Yes	Yes	Yes	Yes	Partial yes	Yes	Yes	High
Nancy Elazab et al.; 2013	Yes	Yes	Yes	Partial yes	Partial yes	Yes	Partial yes	Yes	Partial yes	Yes	Yes	Yes	Yes	Yes	Partial yes	Yes	High
Zajac et al.; 2015	Yes	Yes	Yes	Partial yes	Partial yes	Yes	No	Yes	Partial yes	No	No	Yes	Yes	Partial yes	Partial yes	No	Moderate
Gu¨ venc et al.; 2016	Yes	Yes	Yes	Partial yes	Partial yes	Yes	Yes	Yes	Yes	NO	No	Yes	Yes	Partial yes	Partial yes	Yes	Moderate
Chen et al.; 2023	Yes	Yes	Yes	Partial yes	Yes	Yes	Partial yes	Yes	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	High
Kajal Farahmandi et al.; 2022	Yes	Yes	Partial yes	No	Yes	Yes	No	Partial yes	No	No	No	Yes	Yes	Yes	Yes	Yes	Moderate
Vliagoftis et al.; 2008	Yes	Yes	No	Partial yes	No	Partial yes	No	No	No	No	No	Partial yes	Yes	Yes	Yes	Yes	Moderate

Probiotics supplementation and IgE

The fifteen RCTs involving 856 participants (437 intervention group, 419 control group) evaluated the effect of the probiotics on IgE level. This meta-analysis synthesized the effect of 15 RCTs and demonstrated that probiotic supplementation is associated with diminished level of IgE (WMD: -198.35, 95%CI: -291.10, -105.61; P < 0.001; I² = 99.2%, P < 0.001) (Fig. 2). Subgroup analysis was carried out to investigate the source of heterogeneity based on the age, health condition, type of probiotic, duration, and sample size. However, I² values remained above 90% in most subgroups, indicating that the examined covariates did not substantially reduce heterogeneity. Accordingly, the beneficial effect of probiotics were highlighted among children (< 18 years old) using Lactobacillus strain for more than 8 weeks (P < 0.05) (Table 5).

Fig. 2.

Forest plot of probiotic supplementation and IgE

Table 5.

Pooled estimate effects of probiotics on allergic rhinitis

Outcomes	Number	WMD (95% CI)
Ig E
Sample size
≤ 50	8	-2.25 (-20.16, 15.65)
˃50	7	-428.01 (-594.50, -261.52)
Age (years)
≤ 18	6	-506.21 (-681.79, -330.64)
˃18	9	-1.91 (-22.99, 19.16)
Duration (week)
≤ 8	9	24.97 (-33.29, 83.23)
> 8	6	-508.54 (-735.28, -281.80)
Strain of probiotics
Lactobacillus	4	-694.58 (-946.18, -442.98)
Lactobacillus johnsonii	1	22.24 (-85.76, 130.24)
Tetragenococcus	1	15.00 (-61.90, 91.90)
Bifidobacterium	2	-59.83 (-178.17, 58.52)
Lactobacillus acidophilus	2	-112.73 (-240.06, 14.60)
Lactobacillus plantarum	1	277.50 (-80.13, 635.13)
Lactobacillus rhamnosus-Bifidobacterium breve-Propionibacterium freudenreichii	1	-65.00 (-79.11, -50.89)
Lactobacillus gasseri	1	15.00 (-36.80, 66.80)
Lactobacillus paracasei	1	118.20 (-185.36, 421.76)
Lactobacillus fermentum	1	-147.99 (-526.69, 230.71)
Health conditions
Asthmatic children	4	-756.76 (-2484.84, 971.32
Cedar pollinosis	5	-30.49 (-91.24, 30.27)
Healthy	1	-1.10 (-21.52, 19.32)
Perennial Allergic Rhinitis	3	18.44 (-43.42, 80.30)
Allergic rhinitis	2	57.72 (-264.16, 379.61)
Anti-IgE
Duration (week)
≤ 8	5	-0.62 (-2.47, 1.23)
> 8	4	3.18 (-0.23, 6.59)
Health conditions
Cedar pollinosis	4	-1.54 (-11.54, 8.46)
Perennial Allergic Rhinitis	2	0.20 (-0.05, 0.45)
Healthy	1	3.80 (0.19, 7.41)
Allergic rhinitis	3	-1.77 (-2.26, -1.29)
Strain of probiotics
Bifidobacterium	2	-1.92 (-13.12, 9.27)
Lactobacillus acidophilus	2	2.80 (-8.61, 14.20)
Tetragenococcus	1	0.20 (-0.05, 0.45)
Lactobacillus	3	0.66 (-4.35, 5.66)
Lactobacillus plantarum	1	2.40 (-11.32, 16.12)

Probiotics supplementation and antigen-specific IgE

Nine trials encompassing 381 participants (196 intervention group, 185 control group) evaluated the efficacy of the probiotics on the antigen-specific IgE level. It has been shown that probiotics are not associated with antigen-specific IgE level (WMD: -0.03, 95%CI: -1.71, 1.66; P = 0.974; I² = 85.7%, P < 0.001) (Fig. 3). Subgroup analysis revealed that probiotics supplementation contributed to a decrease in the level of the antigen-specific IgE among allergic rhinitis patients (P < 0.05) (Table 5). While, it failed to identify the source of heterogeneity across treatment duration and type of probiotics (P > 0.05) (Table 5).

Fig. 3.

Forest plot of the probiotic supplementation and antigen-specific IgE

Probiotics supplementation and RQLQ score

The six studies involving 823 participants evaluated the effect of the probiotics and demonstrated that probiotics are able to decrease the global RQLQ score significantly (WMD: -9.43, 95%CI: -11.71, -7.15; P < 0.001; I² = 99.4%, P < 0.001) (Fig. 4A). In addition, nasal-RQLQ and eye-RQLQ included five studies with high heterogeneity. Likewise, REML method was used to present pooled analysis of nasal-RQLQ and eye-RQLQ. Accordingly, no significant changes were shown following probiotics treatment in term of nasal-RQLQ (WMD: -1.95, 95%CI: -4.14, 0.24; I² = 98.44%, τ² = 7.43) (Fig. 4B) and eye-RQLQ (WMD: -0.41, 95%CI: -1.25, 0.43; I² = 62.20%, τ² = 0.30) (Fig. 4C).

Fig. 4.

A Forest plot of the probiotic supplementation and global-RQLQ. B Forest plot of the probiotic supplementation and nasal-RQLQ. C Forest plot of the probiotic supplementation and eye-RQLQ

Probiotics supplementation and RTSS score

Four RCTs with 533 individuals evaluated the potential of probiotics on the global RTSS score and this assessment showed no significant effect on global RTSS score (WMD: -0.60, 95%CI: -1.57, 0.36; P = 0.221; I² = 55.8%, P = 0.079) (Fig. 5A). Similarly, eye-RTSS score was evaluated in three studies and combined effect did not show any significant effect following probiotic supplementation (WMD: -0.38, 95%CI: -1.11, 0.35; P = 0.308; I² = 53.6%, P = 0.116) (Fig. 5B). Whereas, seven studies reported the effect of probiotics supplementation on the nasal-RTSS score and pooled analysis demonstrated that probiotics supplementation caused significant reduction on the nasal-RTSS score (WMD: -1.97, 95%CI: -3.61, -0.32; P = 0.019; I² = 97.1%, P < 0.001) (Fig. 5C).

Fig. 5.

A Forest plot of the probiotic supplementation and global-RTSS. B Forest plot of the probiotic supplementation and eye-RTSS. C Forest plot of the probiotic supplementation and nasal-RTSS

Probiotics supplementation and eosinophils count

The combined effect of seven studies evaluating the effect of probiotics on the blood eosinophils count illustrated a non-significant effect (WMD: 3.39, 95%CI: -1.06, 7.84; P = 0.135; I² = 93.8%, P < 0.001) (Fig. 6).

Fig. 6.

Forest plot of the probiotic supplementation and eosinophils count

Sensitivity analyses and publication bias

Sensitivity analysis was carried out and it has been shown that excluding Giovannini et al. is able to change the overall result of IgE to non-significant mode. While, leave-one-out approach didn’t show any changes on the antigen-specific IgE, blood level of eosinophils count, and global-RQLQ score (Supplementary Fig. 1–4).

Egger’s and Begg’s tests were applied to assess potential publication bias in the effects of probiotics on the study outcomes. The findings indicated no evidence of publication bias for IgE (Begg’s = 0.075, Egger’s = 0.061), antigen-specific IgE (Begg’s = 0.348, Egger’s = 0.973), eosinophil count (Begg’s = 0.764), and global-RQLQ score (Begg’s = 0.452). However, trim and fill analysis was done and six studies were imputed for the IgE (Supplementary Fig. 5).

Meta-regression

For IgE, meta-regression showed that treatment duration > 8 weeks was associated with greater reduction (coefficient: -312.4, 95% CI: -589.2 to -35.6, P = 0.028), explaining 38% of between-study variance. No significant associations were found for age, baseline IgE, or study quality. For global-RQLQ (k = 6), meta-regression was not feasible due to insufficient studies.

GRADE summary of findings

Table 6 presents the GRADE assessment. Certainty was downgraded to low for IgE, antigen-specific IgE, nasal-RQLQ, eye-RQLQ, and eosinophils count for inconsistency and imprecision.

Table 6.

Summary of findings and quality of evidence assessment using the GRADE approach

	No of patients (meta-analysis)	ES (95% CI)	Risk of bias1	Inconsistency2	Indirectness3	Imprecision4	Publication bias5	Quality of evidence6
IgE	15 (856)	-198.35 (-291.10, -105.61)	Not serious	Serious	Not serious	Not serious	Serious	Low
antigen-specific IgE	9 (381)	-0.03 (-1.71, 1.66)	Not serious	Serious	Not serious	Serious	Not serious	Low
global-RQLQ	6 (823)	-9.43 (-11.71, -7.15)	Not serious	Serious	Not serious	Not serious	Not serious	Moderate
nasal-RQLQ	5 (732)	-1.95 (-4.14, 0.24)	Not serious	Serious	Not serious	Serious	Not serious	Low
eye-RQLQ	5 (732)	-0.41 (-1.25, 0.43)	Not serious	Serious	Not serious	Serious	Not serious	Low
global-RTSS	4 (533)	-0.60 (-1.57, 0.36)	Not serious	Not serious	Not serious	Serious	Not serious	Moderate
eye-RTSS.	3 (513)	-0.38 (-1.11, 0.35)	Not serious	Not serious	Not serious	Serious	Not serious	Moderate
nasal-RTSS	7 (677)	-1.97 (-3.61, -0.32)	Not serious	Serious	Not serious	Not serious	Not serious	Moderate
eosinophils count	7 (390)	3.39 (-1.06, 7.84)	Not serious	Serious	Not serious	Serious	Not serious	Low

¹ Risk of bias based on the Cochrane risk of bias tool

² Downgraded if there was a substantial unexplained heterogeneity (I² > 50%, P < 0.10) that was not explained by subgroup analyses

³ Downgraded if there were factors present relating to the participants, interventions, or outcomes which restrict the overall generalizability of the results

⁴ Downgraded if the 95% confidence interval (95% CI) crossed the minimally important difference (MID)

⁵ Downgraded if there was an evidence of publication bias using funnel plot

⁶ Since all included studies were randomized controlled trials, the certainty of the evidence was graded as high for all outcomes by default and then downgraded based on prespecified criteria

Results of umbrella review

Included meta-analysis evaluated various allergic markers. Dipankar Sardar et al. with 12.9 weeks of probiotic supplementation showed that global-RQLQ, nasal-RQLQ, and nasal-RTSS may be improved following probiotic supplementation. While, Chang Lu et al. reported more beneficial effects of probiotic mixtures on RQLQ, Total IgE, and Special IgE. Interestingly, Chao Luo et al. indicated that probiotics supplementation is accompanied with increased T helper cell 1(Th1)/Th2 ratio. In contrast, there was no significant change in overall or antigen-specific IgE levels between probiotic-treated and placebo-treated subjects. In addition, Kajal Farahmandi et al. showed that, neither L. paracasei Lp33 (SMD:-1.61, 95% CI: -4.67, 1.45) nor L. rhamnosus GG (SMD:-1.00, 95% CI: -3.01, 1.00) had significant effect on reducing nasal symptom scores.

Discussion

The present systematic review and meta-analysis evaluated the efficacy of the probiotics in terms of allergy. It has been demonstrated that that probiotic supplementation was associated withreduced the IgE, global-RQLQ, and nasal-RTSS score in pooled analyses, but with very high heterogeneity and fragility for some outcomes. Antigen-specific IgE, eye- RQLQ, global-RTSS, eye-RTSS, and eosinophil count were not affected by probiotic supplementation.

The observed reduction in total IgE was highly sensitive to the inclusion of a single study (Giovannini et al., 2007); excluding this study rendered the effect non-significant. Therefore, the immunological benefit of probiotics on total IgE cannot be considered robust. Subgroup analyses suggested larger effects in children and with Lactobacillus strains, but these findings are exploratory and not adjusted for multiple comparisons. Unlike total IgE, antigen-specific IgE showed no overall change.

Also, our meta-analysis showed that probiotic supplementation contributed to improvements in allergic rhinitis symptoms as indicated by RQLQ. The global RQLQ demonstrated a large reduction but with extremely high heterogeneity (I² = 99.4%), limiting confidence in the precise magnitude. The nasal-RQLQ effect was significant under DerSimonian-Laird method but non-significant under REML method, indicating fragility. Probiotics are known to stimulate regulatory T-cells (Tregs) to secrete anti-inflammatory cytokines like IL-10 and TGF-β [58, 59]. Likewise, these anti-inflammatory cytokines suppress Th2 cells [60]. The decrease in total IgE and clinical symptoms may be due to broader immunomodulatory mechanisms, such as improved regulatory T-cell function and Th1/Th2 balance, rather than direct suppression of allergen-specific IgE, even though we did not find a significant overall effect on allergen-specific IgE levels. In addition, probiotics improve the function of the tight junction proteins in the intestinal epithelium which is accompanied with improved allergic responses and increased RQLQ score [61, 62]. Also the anti-inflammatory role of short chain fatty acids (SCFAs) produced by probiotics could not be ignored in this regard [63, 64].

Furthermore, probiotic supplementation leads to a statistically significant reduction in the nasal-RTSS although high heterogeneity (I² = 97.1%) again limits precision. Given the high heterogeneity, fragility of some findings, and pooling of diverse probiotic strains, routine clinical recommendation of probiotics for AR is not supported by high-certainty evidence. Future trials should: (1) use strain-specific designs rather than pooling different species; (2) standardize outcomes and durations; (3) conduct dose-response studies; (4) include longer follow-up; and (5) report data to allow meta-analysis with low heterogeneity. Until then, probiotics remain an experimental adjunct, not a standard of care.

The potential influence of microbiota-modulating exposures on allergic disease may begin early in life, as reported by Çevik et al. [65], who suggested that maternal consumption of fermented products during pregnancy and lactation may be associated with a reduced risk of cow’s milk allergy in infants.

Statistical significance does not necessarily imply clinical relevance. For the RQLQ, the minimal clinically important difference (MCID) for the overall score in allergic rhinitis has been reported to range from 0.5 to 1.0 points. Our observed reduction of -9.43 points far exceeds this threshold, indicating a clinically meaningful improvement in quality of life. Regarding the NTSS, although no established MCID is available for this specific scale, the observed decrease of -1.97 points on a 0 to 12‑point scale represents a clinically noticeable improvement. However, these interpretations should be viewed with caution, given the high heterogeneity and fragility of some findings.

Probiotics may be considered as a potential adjunctive approach for allergic rhinitis; however, the findings should be interpreted cautiously due to substantial heterogeneity and variability in probiotic strains, doses, intervention durations, populations, and outcome measures. However, several limitations exist. First, significant heterogeneity across studies (I² often > 90%) limits the certainty and generalizability of our pooled estimates. This heterogeneity likely arises from multiple sources, including differences in probiotic strains, dosages, treatment durations, age groups, baseline disease severity, comorbid allergic diseases (e.g., asthma), geographic/ethnic backgrounds, and outcome measurement tools (e.g., different versions of RQLQ and RTSS). Meta‑regression only partially explained heterogeneity for IgE, and for RQLQ/RTSS no single covariate could account for the extreme I² values. Subgroup analyses did not consistently reduce heterogeneity, suggesting that multiple interacting factors contribute to the observed variability. Second, insufficient data on specific strains and optimal dosages prevented detailed subgroup analyses. Third, several RCTs had small sample sizes, reducing statistical power. Fourth, dose-response analysis was not possible due to inconsistent reporting. Fifth, excluding non-English publications may introduce language bias. Sixth, most studies were conducted in Asian populations, limiting extrapolation to other ethnic groups. Although no serious adverse events were reported in several included trials, safety findings should be interpreted cautiously because adverse event reporting was inconsistent across studies. Many trials either did not report on adverse events or provided only limited information, which may introduce ascertainment bias. Therefore, the absence of reported serious adverse events does not necessarily confirm their absence. Trim-and-fill analysis indicated that publication bias was a concern for the IgE outcome, potentially inflating the pooled effect estimate. Therefore, the observed reduction in total IgE should be interpreted with caution, as the true effect may be smaller than reported. Finally, the pooling of fundamentally different probiotic strains into a single class is biologically questionable; our strain‑specific analyses were underpowered.

Conclusion

In conclusion, this umbrella review and updated meta-analysis suggests that probiotic supplementation may improve selected clinical outcomes in allergic rhinitis, particularly global/nasal RQLQ and nasal-RTSS, and may reduce total IgE. However, no significant overall effects were observed for antigen-specific IgE, eosinophil count, eye-RQLQ, global-RTSS, or eye-RTSS. These findings should be interpreted cautiously due to substantial heterogeneity and variability in probiotic strains, doses, intervention duration, and study populations. Further well-designed RCTs using standardized protocols are needed before firm clinical recommendations can be made.

Abbreviations

AE

Adverse event

AMSTAR‑2

Assessment of Multiple Systematic Reviews (tool)

AR

Allergic rhinitis

CFU

Colony‑forming units

CI

Confidence interval

GRADE

Grading of Recommendations Assessment, Development and Evaluation

HKSJ

Hartung‑Knapp‑Sidik‑Jonkman

IgE

Immunoglobulin E

IL

Interleukin

MCID

Minimal clinically important difference

MD

Mean difference

MeSH

Medical Subject Headings

MID

Minimally important difference

NR

Not reported

NTSS

Nasal total symptom score

PICOS

Population, intervention, comparison, outcome, study design

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta‑Analyses

PROSPERO

International Prospective Register of Systematic Reviews

RCT

Randomized controlled trial

REML

Restricted maximum likelihood

RoB 2.0

Cochrane Risk of Bias tool (version 2.0)

RQLQ

Rhinoconjunctivitis Quality of Life Questionnaire

RTSS

Total rhinitis symptom score

SAE

Serious adverse event

SCFA

Short‑chain fatty acid

SMD

Standardized mean difference

Th1

T helper cell type 1

Th2

T helper cell type 2

TGF‑β

Transforming growth factor beta

Treg

Regulatory T‑cell

WMD

Weighted mean difference

Authors’ contributions

Zhe Wang: Investigation, Writing - original draft, Methodology, Validation, Writing - review & editing Yao Lu : Investigation, Validation, Formal analysis, Writing - review & editing.

Data availability

Data will be available upon request from the authors.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.