EPIGUT: EPILEPSY AND GASTROINTESTINAL MICROBIOTA: UNDERSTANDING THERAPY RESPONSE (EpiGUT)

The goal of this observational study is to learn how the bacteria in the gut and mouth (called the microbiota) are linked to different types of epilepsy and how they may affect how well seizure medicines work.

Researchers want to answer two main questions:

Are certain types of epilepsy linked to changes in the gut or mouth microbiota? Do the bacteria in the gut change how seizure medicines work for each person?

Epilepsy is a brain condition that causes seizures. Even though there are many medicines for epilepsy, some people still have seizures or side effects. Studies in animals show that gut bacteria can raise or lower the chance of seizures. Smaller studies in people suggest the same thing, but they have been limited in size and scope.

In this study, researchers will collect biological samples from people who have newly diagnosed epilepsy and from people without epilepsy (called healthy controls). The samples will be tested to learn which bacteria are present. The researchers will then look for patterns that may explain which types of epilepsy are linked to changes in the microbiota.

The study will also look at whether the bacteria in the gut and mouth affect how well anti-seizure medicines (ASMs) work. For example, the researchers will explore if certain bacteria make medicines work better or worse.

Patients will provide blood, stool and saliva samples. If collected for medical reasons, cerebrospinal fluid (CSF) - the clear liquid that surrounds the brain and spinal cord -will also be used.

Healthy controls will provide stool and saliva samples only

All participants will be asked to fill an online questionnaire to share health and lifestyle information.

Patients also allow researchers to confidentially access data from medical records related to diagnosis and treatment.

By comparing data from many participants across Sweden, researchers hope to understand how gut and mouth bacteria influence epilepsy and seizure control.

This research may help doctors in the future to use a person's microbiota profile to choose the best seizure medicine. The long-term goal is to improve seizure control, reduce side effects, and raise the quality of life for people living with epilepsy.

Study Overview

• Status: Recruiting
• Conditions: Epilepsy; Microbiota; Metabolomics; Proteomics; Biomarker Discovery

Detailed Description

Background:

Clinical studies in humans on the role of the microbiota in promoting seizures and epilepsy are sparse and limited to small, heterogenous cohorts of epileptic patients already treated with ASMs. Larger, treatment-naïve cohorts followed longitudinally are needed to investigate the role of the microbiota in seizures and anti-seizure drug therapy. EpiGUT is building such a cohort in order to study both the oral and gut microbiota by analysis of saliva and fecal samples (primary outcomes). Blood and CSF samples for metabolic and inflammation profiling are collected to analyze how the microbiota may influence systemic and central inflammation and metabolism (secondary outcomes).

In vitro, non-antibiotic drugs can inhibit growth of gut microbes and microbes can metabolize drugs to produce active or toxic metabolites. In vivo, almost nothing is known about the interactions of the microbes and ASMs. Yet these interactions can profoundly influence treatment outcome, as demonstrated for anti-PD1 therapy of patients with cancer as well as for many other treatments of various diseases. It is thus plausible that individual differences in the gut microbiota may be part of the reason why some individuals respond to certain ASMs, and others do not. By confirming this hypothesis and further in vitro validation of specific drug-microbe interactions we can create valuable clinical guidelines for personalizing anti-seizure treatments based on the composition of the gut microbiota, thus increasing the probability of a positive treatment response of the individual patient.

Study design:

EpiGUT studies individuals with newly diagnosed epilepsy and their microbiota in response to different ASMs both on an individual level and in comparison to healthy controls. We will analyze the gut and oral microbial composition and function at baseline, i.e., time of diagnosis and study associations with specific subtypes of epilepsies. Building a unique sample collection of blood and CSF enables mechanistic studies on how specific microbes may modulate seizures through metabolites or inflammatory signaling. We will also study correlations between components of the microbiota and ASM treatment efficacy, as well as drug therapy-associated alterations in the gut microbiota.

In the initial part, we have two sampling time points, at baseline, i.e., time of diagnosis and at follow-up at the time of evaluation of monotherapeutic outcome at three months (or before start of additional ASM, if earlier). About 30% of patients will present with drug-resistent epilepsy. Those will be asked to provide additional samples and quetionnaire answers before and after alternative treatment which may include the ketogenic diet, vagus nerve stimulation or surgery.

Methods:

Our primary outcome variable is the composition of the oral and intestinal microbiota, both on a taxonomic as well as functional level. This will be measured by high throughput whole-metagenomic sequencing of saliva and fecal samples with a minimum of 10 million reads per sample which provides a detailed microbial profile. The role of the microbiota for both research questions will be analyzed using advanced metagenomics-specific bioinformatics tools as well as state-of-the-art machine learning algorithms to identify microbial predictors of seizures and/or ASM therapy outcome. Blood levels of ASMs are measured routinely during follow-up and will be correlated to prescribed dose and components of the gut microbiota to identify potential candidates of ASM metabolizing intestinal microbes. Clinical data such as patient history, epilepsy classification, etiology, seizure burden and current medications will be entered in an anonymized Redcap database. In addition, patients/caregivers will be asked to answer a questionnaire with standard questions relevant to microbiota studies including other diagnoses, dietary habits, oral health, birth mode, physical activity etc. PERMANOVA analysis will identify significant factors contributing to our main outcome, the microbial composition. Regression analysis will take these significant factors into account when analyzing the contribution of microbes to the diagnosis or ASM therapeutic outcome.

In addition, we biobank blood samples collected at both time points and CSF at baseline (only if taken as part of the clinical workup) to analyze inflammatory and metabolomic profiles of the patients using the Olink® inflammation panel and untargeted metabolomics. These profiles will be analyzed both independently and in relation to the microbial profiles to identify host and microbiota-mediated disease- and therapy-relevant factors as secondary outcomes.

Selection of participants:

1,000 patients will be recruited, 300 children and 700 adults from university and regional hospitals across Sweden A healthy control group will be recruited in a 1:2 ratio and matched by age.

Data analysis and statistics:

Data analysis will be performed using advanced metagenomics-specific bioinformatics tools. The diversity of the resulting baseline taxonomic and functional profiles will be analyzed for confounding and other influencing clinical and lifestyle factors and ranked by effect size (R2) and statistical significance (p) in relation to our variables of interest (e.g. epilepsy type, seizure burden and refractoriness, etiology) using Permutational Multivariate Analysis of Variance (PERMANOVA). We will apply state-of-the-art machine learning algorithms to identify microbial predictors of seizures and/or AMS therapy outcome. The most important microbial features of the best model will be extracted and tested in silico as potential biomarkers for diagnosis and/or therapeutic outcome.

• Study Type: Observational
• Enrollment (Estimated): 1500

Contacts and Locations

• Study Contact: Name: Ronny Wickström, MD, PhD; Phone Number: +46 70 68 38 182; Email: ronny.wickstrom@ki.se
• Study Contact Backup: Name: Stefanie Prast-Nielsen, PhD; Phone Number: +46 76 21 67 781; Email: stefanie.prast-nielsen@ki.se

Study Locations

• Sweden
  • Gothenburg, Sweden
    • Recruiting
    • Drottning Silvias barnsjukhus
    • Contact: Ann-Louise Esserlind, MD; Phone Number: +46 31 343 63 00; Email: ann-louise.esserlind@vgregion.se
  • Linköping, Sweden
    • Recruiting
    • Universitetssjukhuset i Linköping
    • Contact: Helena Gauffin, MD; Phone Number: +46 10 103 00 00; Email: Helena.Gauffin@regionostergotland.se
  • Lund, Sweden
    • Recruiting
    • Skanes universitetssjukhus
    • Contact: Erik Eklund, MD; Phone Number: +46 46 17 85 00; Email: Erik.Eklund@skane.se
  • Stockholm, Sweden
    • Recruiting
    • Karolinska Universitetssjukhus
    • Contact: Sigrid Bjuresäter, Registered nurse; Phone Number: +46 8 123 774 61; Email: sigrid.bjuresater@ki.se
    • Contact: Ronny Wickström, MD; Phone Number: +46 8 123 706 27; Email: ronny.wickstrom@ki.se
    • Principal Investigator: Ronny Wickström, MD
  • Umeå, Sweden
    • Recruiting
    • Norrlands Universitetssjukhus
    • Contact: Måns Berglund, MD; Phone Number: +46 90 785 91 40; Email: mans.berglund@regionvasterbotten.se
  • Uppsala, Sweden
    • Recruiting
    • Akademiska Sjukhuset
    • Contact: Christian Wentzel, MD; Phone Number: +46 18 611 58 48; Email: christian.wentzel@uu.se

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Residents of Sweden

Description

Inclusion Criteria:

• Patients: Age 2-79 years, newly diagnosed with epilepsy, treatment-naive at time of enrollment
• Controls: Age 2-79 years

Exclusion Criteria:

• Patients: already started ASM treatment (more then one dose), has used antibiotics or probiotics in the last three months, has a gastrointestinal diagnosis, has surgically removed parts of the GIT, obesity (BMI>30), T2D, follows a strict exclusion diet, is pregnant or breastfeeding, has a gastrostomy, PEG or jejunostomy
• Controls: previous epilepsy diagnosis or ASM treatment, has used antibiotics or probiotics in the last three months, has a gastrointestinal diagnosis, has surgically removed parts of the GIT, obesity (BMI>30), T2D, follows a strict exclusion diet, is pregnant or breastfeeding, has a gastrostomy, PEG or jejunostomy

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Patients; Age 2-79 years, newly diagnosed with epilepsy, treatment-naive at time of enrollment. Exclusion criteria: already started ASM treatment (more then one dose), has used antibiotics or probiotics in the last three months, has a gastrointestinal diagnosis, has surgically removed parts of the GIT, obesity (BMI>30), T2D, follows a strict exclusion diet, is pregnant or breastfeeding, has a gastrostomy, PEG or jejunostomy
Controls; Age 2-79 years, exclusion criteria: previous epilepsy diagnosis or ASM treatment, has used antibiotics or probiotics in the last three months, has a gastrointestinal diagnosis, has surgically removed parts of the GIT, obesity (BMI>30), T2D, follows a strict exclusion diet, is pregnant or breastfeeding, has a gastrostomy, PEG or jejunostomy

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Gut and oral microbiota composition in patients vs. controls	metagenomic sequencing of home-collected fecal and saliva samples	two years after completion of sample collection and sequencing
Changes in gut/oral microbiota in epilepsy patients on monotherapy	Metagenomic sequencing of at home-collected fecal and saliva samples before and after single ASM treatment for approx. three months	two years after completion of sample collection and sequencing

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Changes in inflammation markers and metabolites in blood and CSF during monotherapy and in relation to changes in the microbiota	Olink inflammation panel and untargeted metabolomics	three years after completion of sample collection and sequencing
Can the gut/oral microbiota at time of diagnosis predict therapy response?	Metagenomic sequencing of the gut/oral microbiota	three years after completion of sample collection and sequencing

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Changes in the gut/oral microbiota of therapy-resistant epilepsy during alternative treatment	Metagenomic sequencing	four years after completion of sample collection and sequencing

Collaborators and Investigators

• Sponsor: Karolinska Institutet
• Investigators: Study Director: Stefanie Prast-Nielsen, PhD, Karolinska Institutet

Publications and helpful links

Helpful Links

• Karolinska Institutets official site for EpiGUT which includes a link for registration of participation

Study record dates

Study Major Dates

• Study Start (Actual): February 27, 2024
• Primary Completion (Estimated): March 1, 2028
• Study Completion (Estimated): March 1, 2028

Study Registration Dates

• First Submitted: November 19, 2025
• First Submitted That Met QC Criteria: November 19, 2025
• First Posted (Actual): November 28, 2025

Study Record Updates

• Last Update Posted (Actual): November 28, 2025
• Last Update Submitted That Met QC Criteria: November 19, 2025
• Last Verified: November 1, 2025

More Information

Terms related to this study

• Keywords: epilepsy; microbiome; seizures; gut-brain-axis; anti-seizure medication
• Additional Relevant MeSH Terms: Neurologic Manifestations; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Pathological Conditions, Signs and Symptoms; Signs and Symptoms; Epilepsy; Seizures
• Other Study ID Numbers: 2023-04648-01

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: No personal data will be shared according to EU GDPR. For publication, anonymized results from biological samples will be shared with minimal information (Patient/Control, sampling timepoint 1-4, and name of drug treatment) to meet FAIR guidelines and ensure participant anonymity at the same time.
• IPD Sharing Time Frame: At time of publication of research results in a high-quality peer-reviewed scientific journal.
• IPD Sharing Access Criteria: Anyone with access to the journal and the ENA (European Nucleotide Archive) portal (storage of sequencing data)
• IPD Sharing Supporting Information Type: ANALYTIC_CODE

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No