Effects of fermented versus unfermented red cabbage on symptoms, immune response, inflammatory markers and the gut microbiome in young adults with allergic rhinoconjunctivitis: a randomised controlled trial protocol

Abstract

Introduction

Allergic rhinoconjunctivitis (ARC) is a highly prevalent immune-mediated condition associated with substantial symptom burden, impaired quality of life and increased healthcare use. Emerging evidence highlights the role of the gut microbiome in immune regulation and allergic disease. Fermented foods may contain live microbes (when unpasteurised or uncooked) and bioactive postbiotic metabolites that can modulate immune responses. Despite growing interest in dietary strategies targeting the microbiome, no randomised controlled trial has compared fermented versus unfermented red cabbage for ARC.

Methods and analyses

This single-centre, randomised, controlled trial with a sensory-matched, unfermented cabbage comparator investigates the effects of daily consumption of fermented red cabbage for 8 weeks compared with an unfermented red cabbage control in young adults (18–35 years) with ARC. A total of 158 participants will be randomly assigned (1:1). The primary outcome is change in Total Nose and Eye Symptom Score from baseline to week 8. Secondary outcomes include daily symptoms and medication use captured via mobile ecological momentary assessments, quality of life, psychological well-being, gastrointestinal symptoms, systemic inflammatory markers, total IgE, immune cell profile and metagenomic characterisation of stool samples. A nested qualitative component explores participants’ experiences and acceptability of the intervention. Analyses will include mixed-effects models, time-series analyses incorporating daily pollen counts and comprehensive microbiome statistics. Safety outcomes and adverse events will also be assessed.

Ethics and dissemination

This study was approved by the Ethics Committee of Charité—Universitätsmedizin Berlin (EA4/043/25) and is conducted in accordance with the Declaration of Helsinki and Good Clinical Practice. Results will be disseminated through peer-reviewed publications, conference presentations and a lay summary provided to participants. Anonymised datasets and analysis scripts will be made available in public repositories, and metagenomic sequencing data will be deposited in an international sequence archive to ensure transparency and reproducibility.

Trial registration number

DRKS00036475.

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• Rigorous randomised controlled design with a sensory-matched control, enabling causal inference and targeted assessment of microbial and postbiotic effects.

• Comprehensive multimodal data collection (clinical, psychometric, immunological, metagenomic) providing both symptomatic and mechanistic insights.

• High-resolution daily symptom tracking via mobile ecological momentary assessments integrated with local pollen data, allowing detailed exposure–response modelling.

• Potential recruitment bias and seasonal variability, as participation is voluntary and symptom patterns depend heavily on fluctuating pollen exposure.

Introduction

Allergic rhinoconjunctivitis (ARC) is an increasingly prevalent immune-mediated disease characterised by nasal congestion, rhinorrhoea, sneezing and ocular symptoms such as red, itchy and watery eyes with foreign body sensation. Some patients display asthmatic symptoms. The symptoms occur in response to airborne allergens, such as different pollen, animal hair, dust mite, among others¹ and affect up to 40% of the global population, with increased prevalence among adolescents and young adults.² In Germany, the prevalence of seasonal allergies is 16% in adults and 10% in children.³

ARC can cause sleep and concentration disruption, resulting in a relevant reduction in quality of life.⁴ Subsequently, higher rates of sick leave and reduced productivity can result in socioeconomic burden and increased healthcare use.^{5 6} Treatment strategies include antihistamines, corticosteroids and allergen immunotherapy.⁷ These treatments are usually effective but can have side effects and limited long-term acceptability by the patients.^{8 9}

The gut microbiome is increasingly recognised as a key regulator of immune homeostasis and allergic disease.¹⁰,¹⁵ Dysbiosis has been associated with higher risk and severity of atopic conditions, including AR. Microbial metabolites such as short-chain fatty acids and tryptophan derivatives can influence epithelial barrier integrity, dendritic cell function, T-cell polarisation and IgE production, thereby promoting either immune tolerance or pro-allergic responses depending on microbiome composition and function.¹⁴,¹⁹ A 2023 systematic review and meta-analysis concluded that gastrointestinal microbiome supplementation (including prebiotics, probiotics and synbiotics) may reduce nasal and ocular symptoms in patients with AR.²⁰

Fermented foods differ in their production processes. Products such as sauerkraut and kimchi typically undergo spontaneous fermentation by naturally occurring microbes, whereas other fermented products such as yoghurt and kefir rely on defined starter cultures. Spontaneous fermentation processes lead to the formation of diverse microbial communities and postbiotic metabolites. However, many commercially available fermented products are pasteurised, a process that eliminates live microorganisms while largely retaining postbiotic metabolites and microbial debris. Short-chain fatty acids such as butyrate, propionate or acetate, bioactive peptides or vitamins represent just a few compounds found in fermented foods.²¹,²³ Wastyk et al demonstrated that increasing fermented food intake alters immune cell profiles and reduces inflammatory markers, indicating a measurable modulation of the immune system.²⁴

Sauerkraut is a naturally fermented cabbage product rich in lactic acid bacteria and postbiotic compounds, readily available and culturally integrated in Germany. Consumption of sauerkraut may influence immune function through microbial action as well as via fibre, anti-oxidative compounds and polyphenols inherent in cabbage.²⁵,²⁸ Randomised controlled trials examining the clinical effects of sauerkraut are rare. One study conducted in Norway in 2018 compared fresh and pasteurised sauerkraut for irritable bowel syndrome and found significant improvement in both groups.²⁹ A recent German study compared the gut microbiome in a healthy population eating either fresh or pasteurised sauerkraut in a crossover design. No major shift in gut microbiota diversity was found. Species-level changes occurred in both groups with stronger effects seen in the pasteurised group.³⁰ These results are suggesting that sauerkraut has effects independent of living microbes.

To date, no randomised controlled trial has compared the effects of fermented versus unfermented cabbage in symptoms, immune function and the gut microbiome in people with ARC. This study aims to investigate whether daily consumption of fermented red cabbage improves symptoms of AR, modulates inflammatory markers and immune response and influences the gut microbiome composition and function in young adults with AR.

Objectives and hypotheses

The aim of this study is to examine the effect of daily consumption of fermented red cabbage on clinical, immunological and gut microbiome-related outcomes in young adults with AR.

The primary objective assesses if the daily consumption of fermented red cabbage for 8 weeks reduces the severity and frequency of allergic symptoms, specifically nasal congestion, sneezing, itching and watery eyes.

Secondary objectives include the following assessments:

• Changes in daily symptom burden and intake of medication in connection to daily pollen count data.

• Reduction of systemic inflammation.

• Modulation of immune cell population and allergy biomarkers.

• Modulation of composition and function of the gut microbiome.

• Improvement in quality of life and psychological well-being.

• Qualitative experience of the intervention.

The hypotheses derived from the objectives are shown in table 1.

Table 1. Overview of study hypotheses.

H1	Daily consumption of fermented red cabbage for 8 weeks reduces the severity of allergic symptoms compared with the control group receiving non-fermented red cabbage, measured by the Total Nose and Eye Symptom Score
H2a	Compared with the control group, participants consuming fermented cabbage will lower daily symptom burden and allergy medication intake across the 8 week intervention period after adjusting for daily pollen count.
H2b	Daily consumption of fermented red cabbage for 8 weeks reduces systemic inflammation as reflected by lower concentration of C-reactive protein
H2c	Daily consumption of fermented red cabbage for 8 weeks leads to favourable changes in immune cell populations (eg, reduction of eosinophils) and improves total immune globulin E compared with the control group
H2d	Daily intake of fermented cabbage for 8 weeks modulates composition and function of the gut microbiome assessed by shotgun metagenomics (eg, changes in diversity and relative abundance of taxa, alterations in functional pathways such as fermentation, short-chain fatty acid production, immune modulation)
H2e	Participants in the fermented red cabbage group will show greater improvements in quality of life and psychological well-being (eg, lower anxiety and depression scores)

H1, primary hypothesis; H2a–H2e, secondary hypotheses.

Study design

This is an 8-week, single-centre, randomised, sensory-match-controlled trial with two parallel arms. The study additionally includes a nested qualitative component to explore participants’ experiences and perceived effects. The study will evaluate the daily consumption of fermented red cabbage (sauerkraut) compared with unfermented cooked red cabbage on allergy symptoms, immune and inflammatory markers and the gut microbiome in young adults with ARC. Unfermented cooked red cabbage was chosen as the comparator to control for vegetable type, nutrient content and culinary context, while isolating the effects of fermentation.

Setting

The study takes place at Charité Universitätsmedizin Berlin. Biological samples and questionnaires will be collected during three on-site visits at baseline (T0), after 4 weeks (T1) and after 8 weeks (T2). The planned end date is the 31 March 2027. Figure 1 shows the study course.

Figure 1. Overview of the randomised controlled trial design and timeline. Participants (n=79 per group) consume either fermented red cabbage or unfermented cooked red cabbage for 8 weeks with stepwise dose escalation. Daily symptom monitoring is conducted via mobile ecological momentary assessment (mEMA), alongside daily regional pollen count collection. Study visits with questionnaires and biospecimen collection took place at predefined time points.

Study participants

Participants are young adults (aged 18–35 years) with a diagnosis of ARC and current symptoms, otherwise healthy. Inclusion and exclusion criteria are presented in box 1.

Box 1. Inclusion and exclusion criteria.

Inclusion criteria:

• Age between 18 and 35 years.

• Physician diagnosis of allergic rhino-conjunctivitis.

• Retrospective symptom burden reported with a minimum value of 4 on a Visual Analogue Scale in response to the question: ‘Think back to past allergy seasons: How much did your allergy symptoms bother you when you were not taking medication?’

• Use of rescue medication for seasonal allergic symptoms as needed.

• Consumption of ≤2 portions per week of fermented vegetables, yoghurt, kefir (milk or water) or kombucha during the 4 weeks prior to enrolment, with willingness to maintain this intake unchanged and to keep consumption of other fermented foods (eg, sourdough bread, beer, wine) stable throughout the study.

• Willingness to consume the assigned cabbage product daily for 8 weeks, stated by signed written informed consent.

Exclusion criteria:

• Regular, fixed daily intake of anti-allergic medication (mandatory maintenance therapy).

• Chronic inflammatory or immune-mediated disease other than the allergy necessitating any systemic anti-inflammatory or immune-modulating treatment.

• Other chronic diseases possibly influencing results or safety.

• Antibiotic or probiotic use in the last 4 weeks.

• Pregnancy or breastfeeding.

• Adherence-limiting dietary restrictions (eg, histamine intolerance).

• Participation in another study.

Recruitment

Recruitment of participants began in June 2025 and will continue through summer 2026 to cover different pollen seasons and airborne allergens. Participants are recruited via allergy-focused medical practices, pharmacies, supermarkets, fitness studios, the Charité and Berlin university intranets, subway advertisements and social media platforms (Instagram, Nebenan.de, Kleinanzeigen.de, LinkedIn). Interested individuals contact the study centre by email. Study information is provided by mail, and details clarified via phone. If eligible and willing, participants receive informed consent documents and the first stool kit by post, to be brought to the first visit; consent is signed prior to randomisation. To date, 15 of the planned 158 participants have been enrolled. Recruitment paused during autumn/winter 2025 and will resume in February 2026 for the next pollen season.

Randomisation and blinding

Randomisation occurs within the Research Electronic Data Capture (REDCap) platform used for data collection. The randomisation sequence has been set-up by a bio-statistician (SNS). Random allocation occurs 1:1 to either the fermented group or the unfermented control group stratified by biological sex.

The fermented and unfermented red cabbage products are sensory-matched. The unfermented cabbage is a ready-to-eat cooked cabbage from organic retailers. The fermented cabbage is provided by a certified local company and matched in composition and taste. The fermented product is non-pasteurised and stored refrigerated. The trial is participant-blinded and analyst-blinded. Participants, the biostatistician and laboratory personnel remain blinded until database lock. Data collectors, the study coordinator and the principal investigator are not blinded due to their role in product distribution and logistics. Unblinding is permissible only in the event of a medical emergency. Unblinding is performed by the principal investigator after consultation with the study team.

Intervention and control

Participants in both groups will be asked to consume up to 75 g of the assigned product daily for 8 weeks. Dosage will be escalated as follows: week 1: 25 g/day; week 2: 50 g/day; from week 3: 75 g/day. The amount of 75 g per day is based on the amount of sauerkraut consumed in Nielsen et al, where a good acceptance of participants was reported.²⁹ Participants are provided with an electronic kitchen scale to ensure accurate dosing of the product.

The first batch of study products for 4 weeks will be handed out at baseline (T0), and the second batch at the 4-week visit (T1), with specification to store in regular refrigerator.

Outcomes

Primary outcome

The primary outcome is the Total Nose and Eye Symptom Score (TNESS) between baseline (T0) and end of intervention at 8 weeks (T2). The questionnaire records the symptoms of ARC in self-assessment (eg, nasal congestion, sneezing, watery eyes).³¹ As no validated German version is available, a pragmatic translation process informed by Beaton et al was undertaken to ensure linguistic clarity and conceptual equivalence.³² This included iterative forward–backward translation between English and German by bilingual members of the study team (native English speaker SBB; German speakers GBN, SNS), followed by review and harmonisation by experienced researchers within Charité Competence Center for Traditional and Integrative Medicine (CCCTIM) (WS, GS) and a check for comprehensibility prior to use.

Secondary outcomes

• Daily documentation of symptom severity on a Visual Analogue Scale (VAS) and medication intake using the MyCap application integrated into the data collection platform REDCap, as mobile ecological momentary assessment tool (mEMA).^{33 34} The questions to answer are threefold: How much do your allergy symptoms bother you today? (not at all bothersome—extremely bothersome), What are your dominating symptoms? (nose, eyes, lungs, other), Have you taken any emergency medication? If yes, give the name and the dosage used.

• Quality of life is assessed at each visit via the validated questionnaire WHO Quality of Life Questionnaire Bref (WHOQOL-Bref).^{35 36}

• Gastrointestinal symptoms are captured at each visit by the validated questionnaire Gastrointestinal Symptoms Rating Scale (GSRS).³⁷

• Stool consistency is assessed with the Bristol Stool Form Scale. Although no validated German translation exists, the questionnaire is widely used and translated.^{38 39}

• Anxiety is assessed with the validated tool Generalised Anxiety Disorder scale (GAD-7).⁴⁰

• Depressive symptoms are assessed by the validated German questionnaire ‘Allgemeine Depressionsskala’ (ADS; original English version: Centre for Epidemiological Studies Depression Scale).^{41 42}

• Adherence is assessed at visits T1 and T2, by answering the question: ‘Did you consume the study food daily as prescribed? If not, please describe’. Additionally, participants are asked whether their intake of fermented vegetables, yoghurt, kefir (milk or water), kombucha or other fermented foods (eg, sourdough bread, beer, wine) has changed since baseline, and if so, in which direction and to what extent. This information is used to monitor adherence to the inclusion criterion of ≤2 portions per week of selected fermented products and to identify potential confounding dietary changes during the intervention.

• Serum markers: C-reactive protein (CRP) and total immunoglobulin E (IgE) are analysed in the accredited medical laboratory of Labour Berlin, partner of the faculty for routine diagnostic. The procedures are performed following manufacturer protocols with routine quality controls. CRP levels are measured using an immunoturbidimetric assay in serum. The assay has a detection limit of ≤5 mg/L. Total IgE levels in serum are determined using the ImmunoCAP system, which is based on a fluorescence enzyme immunoassay.^{43 44}

• Differential blood counts will be measured in EDTA-anticoagulated blood using a Sysmex XN-1000 haematology analyser (fluorescence flow cytometry). The system reports leucocyte subsets (neutrophils, eosinophils, basophils, monocytes, lymphocytes, immature granulocytes), flags nucleated red cells and abnormal populations and corrects leucocyte counts as needed. Analyses follow standard operating procedures in an accredited laboratory with routine quality assurance. Samples are processed within 6–8 hours of collection, and results are evaluated against current haematological reference ranges.⁴⁵

• Microbiome analysis: participants receive faecal sample collection and preservation kits, and detailed instructions for self-collection. Samples are stored at −80°C. DNA is extracted using QIAmp PowerFecal Pro DNA Kit (Qiagen). Shotgun metagenomic sequencing is performed using Illumina NovaSeq 6000 2×150 bp. Quality filtering and trimming of the raw sequence reads are carried out using KneadData V.0.12.0 (https://github.com/biobakery/kneaddata). Trimmomatic⁴⁶ is used to eliminate Illumina sequencing adaptors and conduct initial quality filtering on raw shotgun metagenomic reads by excluding low-quality reads with a Phred score below 20. Subsequently, the reads are aligned against the reference genome (hg37) using Bowtie2 V.2.4.5 (Langmead and Salzberg, 2012) with default parameters to eliminate human host genome contamination. The filtered reads are used for further analyses. To analyse structure and diversity of bacterial communities, we use Kraken2 to classify shotgun metagenomic reads.⁴⁷ Then, we generate a table of microbial abundance using Bracken.⁴⁸ Functional annotation includes mapping gene families and metabolic pathways using HUMAnN.⁴⁹ We use several binning methods, including MaxBin2, MetaBAT2 and CONCOCT,⁵⁰,⁵² to generate metagenome-assembled genomes (MAGs). DASTool V.1.1.1 is employed to select the highest quality MAGs.⁵³ The evaluation of MAGs is conducted with CheckM.⁵⁴ Taxonomic classifications are determined using GTDB-Tk⁵⁵ and gene annotation is carried out using METABOLIC.⁵⁶

• An invitation to participate in a qualitative interview regarding acceptability and experience will be extended to all participants of the 2025 data collection season with a semi-structured question guideline. Invitations for the 2026 season will follow a purposeful maximum variability sample based on symptom severity, age, gender or experience mentioned at baseline (T0).⁵⁷

Exploratory outcomes

Additional blood-related samples including plasma, serum and peripheral blood mononuclear cells are collected and stored at −80°C at the biobank of Charité Universitätsmedizin Berlin (ZeBanc) for future exploratory analyses.

Data collection

Biological samples (blood and stool) and questionnaires will be collected at baseline (T0), after 4 weeks (T1) and 8 weeks (T2).

All data is collected via the data collection platform REDCap, which complies with data safety regulations of the faculty. The REDCap-related application MyCap is installed by all participants during the baseline visit. Participants sign in with a self-chosen pseudonym that should not include any identifying elements. A daily prompt is sent at 19:00 every day reminding them to answer three questions on daily symptoms and medication use. The entry data is then continuously stored in the pseudonymised REDCap case.

Retention and withdrawal

Participant retention is promoted through personal contact, the possibility of chatting with the team via the MyCap-App, written instructions and flexible visit scheduling.

Participants can withdraw at any time without reason or consequence for their medical care. If a participant withdraws, they may request deletion of all previously collected data; otherwise, data collected will be retained and included in analyses in accordance with the intention-to-treat (ITT) principle. Reasons for withdrawal include participant request, severe or intolerable adverse events (AEs), major protocol deviations (eg, persistent non-consumption of the study product), or safety-related decisions by the investigators (eg, product recall). All withdrawals will be documented.

Harms and safety monitoring

Harms were defined as any AEs or unintended effects occurring during the study period. Harms are assessed systematically at each study visit, and non-systematically via spontaneous participant reports via MyCap-App. All AEs are documented with onset, duration, severity (mild/moderate/severe), seriousness (serious vs non-serious) and relatedness to the intervention (unlikely/possible/probable). Serious AEs are reported according to local requirements.

Sample size

The sample size estimation is based on the primary outcome TNESS. Assuming a clinically meaningful difference in the change of TNESS between intervention and control group, the study is powered to detect a statistically significant effect at a two-sided alpha level of 0.05 with 80% power. To ensure adequate statistical power, the required minimum sample for analysis is 132. Accounting for a dropout rate of 20%, a total of 158 participants will be recruited. This approach is informed by a previous randomised controlled trial investigating the effects of probiotics in individuals with seasonal ARC, which used a comparable methodology and outcome assessment.³¹

Trial governance and oversight

The trial is coordinated and overseen by CCCTIM. Scientific and safety oversight are provided by the principal investigator (GBN) and the study team. Given the low-risk academic nature of the study and the use of standardised outcome measures, no independent steering, endpoint adjudication or data monitoring committees are established. Data management and analysis are conducted by the principal investigator and the study team.

Statistical analysis plan

Analysed populations

Three populations are defined.

ITT includes all randomised participants with at least one post-baseline measurement and will be used for primary efficacy analyses.

The per-protocol population (PP) is a subset of ITT excluding participants with major deviations (eg, insufficient product intake, missing key visits or incomplete primary endpoints), providing supportive robustness analyses.

The safety population includes all participants who consumed the study product at least once and will be used for safety and tolerability analyses.

Variables

Demographic and baseline variables

Demographic and baseline variables include age, sex, body mass index, socioeconomic status such as education level and monthly income, history of allergic disease including age at first manifestation and dominant allergen profile, current medication and nutritional habits through a Food Frequency Questionnaire.⁵⁸ These variables are reported separately for each group and may be included as covariates in exploratory models, where appropriate. No statistical significance testing of baseline differences is planned.

Primary endpoints

The primary endpoint is the TNESS from baseline (T0) and end of intervention (T2). The TNESS is a composite score of nasal and ocular symptoms including nasal congestion, sneezing, itching and watering of the eyes. Each symptom is rated on a 0–3 rating scale, where higher ratings correspond to more severe symptoms.

Secondary endpoints

Secondary endpoints are grouped into three categories: effectiveness parameters, immune parameters and microbiome parameters. Effectiveness parameters include daily symptom rating measured with VAS, daily medication use, WHOQOL-Bref, GSRS, Bristol Stool Scale, ADS and GAD-7. Immunological parameters include total IgE, CRP and differential blood cell count. The gut microbiome and study product samples are analysed with shotgun metagenomics as described above.

Exploratory variables

Explorative variables include daily regional pollen counts, daily and total consumption of the study products, adherence to the target intake and additional consumption of fermented foods.

Missing data and outliers

Missing data

Missing data in the primary endpoint will be handled using linear mixed effects models with repeated measures. If >10% of primary endpoint data are missing, a sensitivity analysis with multiple imputation will be performed. Imputation models will include demographic variables, baseline measurements and previous values of the outcome. Imputed datasets will be analysed with the primary model and combined using Rubin’s rules. Baseline covariates will not be imputed. Missing baseline values will be coded as missing. For categorical variables, an explicit missing category may be explored. Participants who discontinue the intervention remain in the ITT analysis if outcome data are available.

Outliers

Outliers will be identified using statistical criteria (eg, IQR) and clinically relevant thresholds. We distinguish statistical but plausible extremes, erroneous values and clinically meaningful extreme observations. All observations will remain in the primary ITT analysis unless confirmed as data errors. Sensitivity analyses may apply robust methods or exclude influential points. Outlier decisions will be documented and discussed with clinical experts, if needed.

Statistical analysis

Descriptive analyses

Continuous variables will be summarised using mean, SD, median, IQR, minimum and maximum. Categorical variables will be summarised using absolute frequencies and percentages. Intervention and control groups will be described separately without statistical testing of baseline differences. Adherence will be summarised using the percentage of days on which the full target amount of study product was consumed.

Primary efficacy analysis

The primary analysis assesses the change in TNESS from baseline to week eight using a linear mixed effects model with repeated measures. Fixed effects are treatment group, time and their interaction. Baseline TNESS is included as a covariate, and a random intercept accounts for within-participant correlation. The primary comparison is the adjusted between-group difference in change to week 8, derived from the interaction term, reported with 95% CIs. Model assumptions will be evaluated through diagnostic plots. If strong deviations from normality occur, sensitivity analyses will include transformations and robust variance estimators, with interpretation prioritising the original scale. A PP analysis will provide robustness to the ITT results.

Secondary efficacy analysis

Secondary outcomes measured at multiple time points will be analysed using mixed effects models analogous to the primary model. Fixed effects will include treatment group, time and their interaction. Random intercepts will be included for participants. Baseline values will be included as covariates. Secondary analyses are exploratory. No adjustment for multiple comparisons is planned. Interpretation will focus on effect sizes and CIs. For variables measured only once after baseline, group differences will be assessed using linear models or non-parametric alternatives depending on the distribution. Categorical variables will be summarised and compared using descriptive methods and Fisher’s exact tests where useful.

Microbiome

The analysis of microbiome data includes diversity analyses (alpha and beta diversity). Alpha diversity is calculated for taxonomic and functional profiles and compared between groups using non-parametric or model-based tests. Beta diversity is calculated using distance metrics (eg, Bray-Curtis) and visualised using principal coordinates analysis. Differences between groups and time points are analysed with Permutational Multivariate Analysis of Variance (PERMANOVA). Comparison of microbial taxa, gene families and pathways is performed using differential abundance analysis such as MaAsLin2 and ANCOM-II.⁵⁹ Group-by-time interactions are assessed by mixed-effects models. Functional shifts are linked to clinical outcomes using multivariate regression, canonical correlation or machine learning for exploratory prediction. Sensitivity analyses test robustness (eg, outliers, rare taxa). All analyses are performed using version-controlled scripts (eg, R, Python) and documented workflows (eg, Snakemake, Nextflow). Metadata, raw reads and processed outputs are made available in public repositories (ENA and GitHub) in line with FAIR data principles.

Exploratory time series analyses

Time series analyses will explore relationships between daily symptom burden, daily pollen counts, daily study product intake and use of rescue medication. Models may include mixed effects regressions or generalised additive mixed models with lag terms to reflect delayed symptom responses. Interactions between treatment allocation and pollen exposure will be tested to identify modulatory effects of fermented cabbage on exposure response dynamics. These analyses are exploratory and hypothesis-generating.

Safety analyses

Safety analyses focus on Adverse Events (AE) and Severe Adverse Events (SAE). Events are categorised according to frequency and severity, according to MedDRA categories. Differences between the groups are examined to assess tolerability. Clinical relevance and association with the intervention are included in the categorisation. Vital parameters, laboratory findings and psychometric parameters are also included in safety assessment. Descriptive statistics show distribution at each time point. Deviations from reference ranges are assessed for clinical relevance. The course of the markers is graphically visualised to demonstrate potential effects of the intervention.

Subgroup analyses

Exploratory subgroup analyses will evaluate whether treatment effects differ across selected participant characteristics. Planned subgroups are sex, baseline symptom severity defined by the median baseline TNESS and predominant allergen category based on participant history. Subgroup analyses will be performed by including interaction terms between treatment group and the subgroup variable in the mixed effects model used for the primary analysis. Estimates within each subgroup and interaction p values will be presented. Subgroup analyses are exploratory and will be interpreted cautiously due to limited power for interaction testing.

Statistical software

All analyses will be performed using R V.4 with the lme4 package for mixed effects models, ggplot2 for visualisation and mice for multiple imputation. SPSS may be used for additional descriptive summaries. Custom scripts in R and Python are used for processing daily symptom data and for creating analysis datasets. All scripts are version controlled and archived on institutional servers.

Qualitative exploration

At each visit, all participants will complete open-ended questions about their experience with fermented foods in general and with the study product. A subgroup of 8–12 participants will be asked to participate in an interview in two rounds. On completion of the 2025 data collection, all participants will be invited for an interview providing a first convenience sample, then divergent experience will be sought in the second round of data collection in 2026 and invited for an individual interview (maximum variation sampling) after the intervention completion. Data saturation will be monitored continuously. After each interview round, emerging codes will be reviewed. Recruitment will stop when no new themes relevant to acceptability, barriers or perceived effects arise in two consecutive interviews.

These interviews will be transcribed verbatim via auto transcription software (autotranskription.de), corrected and analysed via content analysis⁵⁷ using the software MAXQDA 24 (VERBI Software, MAXQDA 2024). The qualitative results will be triangulated with quantitative data.

Data handling, coding

All data are pseudonymised at enrolment using a unique study identifier. Identifying information is stored separately from research data in an access restricted file maintained by the principal investigator and the study coordinator. Biological samples are labelled with the study identifier and processed in pseudonymised form.

Questionnaire responses, clinical assessments, laboratory values, mEMA data and metadata from stool and blood samples are captured directly in the REDCap platform hosted on secure faculty servers at the faculty. Access rights are role-based and password protected. Data entry forms include plausibility and completeness checks.

Variable coding follows predefined codebooks. Categorical variables are coded numerically. Missing values are coded using consistent missing codes such as Not Applicable (NA) or minus 99. All data preparation steps are performed through scripted workflows in R and Python. Scripts are stored on institutional servers with automated backups.

Qualitative interview audio recordings are recorded with a handheld digital audio recorder and stored on a password protected local server file after transcription until the end of the project, thereafter deleted. Transcriptions are pseudonymised, uploaded to MAXQDA, coded and analysed. Variables are added for triangulation and subsequent analysis.

Pseudonymised datasets are stored on secure institutional infrastructure for at least 10 years after completion of the study in accordance with institutional policy, Good Clinical Practice and data protection regulations.

Data repositories and data availability

After publication of the primary results, anonymised datasets and analysis scripts are made available in public repositories. The clinical analysis dataset, data dictionary and all R scripts used for primary and secondary analyses are deposited in a public data repository (eg, OSF, Zenodo). The final choice of repository will be specified in the results manuscript. All datasets will be fully anonymised prior to upload.

Shotgun metagenomic sequencing data are deposited in a public sequence archive (e.g., European Nucleotide Archive, National Center for Biotechnology Information (NCBI) Sequence Read Archive). Accession numbers are provided in the results manuscript.

Where legal or ethical constraints prevent full open sharing, aggregated datasets or de-identified subsets are provided. Additional data may be made available on reasonable request and may require approval by the responsible ethics committee and the data protection officer.

Patient and public involvement

Patients were not involved in the design phase. Participants will receive a lay summary of the results.

Ethics and dissemination

The study protocol, informed consents and relevant documents have been reviewed and approved by the responsible ethics committee—Ethikkommission der Charité Universitätsmedizin Berlin—before the beginning of the recruitment (EA4/043/25, 30.04.2025). Any substantial amendments to the protocol will be submitted for renewed ethical approval. All participants provide written informed consent prior to any study procedure (original German version and English translated version in online supplemental materials). Informed consent is obtained by a trained member of the study team either in person or remotely after providing written study information and the opportunity to ask questions. Data is handled in accordance with data protection regulations (General Data Protection Regulation of the European Union and Berlin Data Protection Act (BlnDSG)). The study is conducted in accordance with the Declaration of Helsinki and Good Clinical Practice. The study has been registered at Deutsches Register für Klinische Studien (https://drks.de/search/de, registration nr. DRKS00036475, registration date 09 April 2025).

The trial protocol and statistical analysis plan are available from the corresponding author on reasonable request.

Because the intervention is assessed as low risk, no dedicated arrangements for ancillary or post-trial care were established. Participants who experience adverse effects are instructed to obtain medical care through routine healthcare services. Coverage for trial-related harm is provided in line with relevant institutional and legal requirements.

Study results will be published in peer-reviewed scientific journals and presented at conferences. Participants will receive a summary of their results in lay language. The anonymised dataset and the analysis code will be made available in public repositories.

Use of reporting standards and artificial intelligence tools

The manuscript was written in accordance with the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) guidelines³² (online supplemental material).

Artificial intelligence tools (DeepL and ChatGPT) were used as resource for language refinement, given that all but one author are not native English-speakers. The tools helped in phrasing, stylistic inspiration and final word count reduction. All scientific ideas, study concepts, methodological decisions and the full substantive content of this manuscript were conceived, developed, written, critically evaluated and finalised by the authors.

Discussion

The study is significant at several levels. First, it addresses seasonal allergies, a condition with high prevalence worldwide.² Probiotics have been shown to improve symptoms of ARC, confirming the gut microbiome as a possible target for therapeutic interventions.²⁰ Until today, no study has examined Sauerkraut for seasonal allergies, confirming the innovative character of this study.

The present study uses a non-fermented comparative product to assess the effects of the microbial communities and their products. This distinguishes it from previous studies with sauerkraut, which used a pasteurised control product, showing no clear group differences.^{29 30} Overall, the study examines a simple and accessible intervention that can be applied easily by patients, strengthening agency without burdening the health system.

Several key strengths of the study design contribute to reliability and relevance of future results. The use of a randomised controlled design enhances the potential to draw causal conclusions. The combination of clinical, psychometric and laboratory data offers complementary perspectives, capturing both symptomatic changes and underlying mechanisms. An integrated qualitative part helps understanding the real-world experience and giving context to numerical results. Using mEMA for tracking daily symptoms and rescue medication in combination with local pollen count data allows for a real-time granular data capture, enabling a fine exposure-response modelling.

Some limitations are already emerging. Due to the voluntary nature and limited incentive for participation, a recruitment bias is possible, attracting participants with an interest in nutrition and fermented food. The necessity of aligning the study with the pollen season introduces difficult conditions, including fluctuating pollen levels and limited flexibility in scheduling. End of season enrolment bears the risk that reduction in symptoms may occur naturally even without intervention, reducing interpretability of the results. 15 participants with reported symptoms all year long have been enrolled until the end of July 2025. The recruitment will continue in the new early spring season. To account for natural reduction in symptoms over the course of the season, exposure-symptoms are captured via mEMA and local pollen count data as described above, to enable temporal modelling of the relationship between environmental allergen exposure and daily symptom and medication patterns. Finally, there is a risk of unblinding due to the distinct taste profile of fermented and unfermented red cabbage.

Beyond immediate clinical outcomes, the trial bears potential for future impact. If favourable clinical effects of naturally fermented red cabbage are demonstrated, food-based therapies with high translational potential could get a place in allergy management. The study can find potential mechanistic pathways linking the consumption of fermented products to modulation of allergic responses. The multilayered data can contribute to the understanding of the interplay between immune cell profile, inflammation and microbial taxa and functional gene repertoire. This approach aligns with precision nutrition and microbiome-targeted therapies and could inform future personalised adjunct dietary intervention in allergy management. Additionally, the study bears potential to identify biomarkers or microbial signatures in allergy care.