Fecal Microbiota Transplantation (FMT) in Multiple Sclerosis

• ClinicalTrials.gov Identifier: NCT03975413
• Recruitment Status: Completed
• First Posted: June 5, 2019
• Last Update Posted: October 8, 2020
• Sponsor: Rush University Medical Center
• Information provided by (Responsible Party): Ali Keshavarzian, Rush University Medical Center

Study Description

Brief Summary:

Multiple sclerosis (MS) is a chronic immune central nervous system (CNS) disease of unknown cause. Recent studies suggest that gut microbiota could be a trigger for the neuro-inflammation in MS and abnormal gut microbiota composition has been reported in MS patients. These data provided scientific rationale for microbiota-directed intervention, like stool transplant, for the treatment of MS.

Condition or disease	Intervention/treatment
Multiple Sclerosis, Relapsing-Remitting	Other: Fecal Microbiota Transplantation (FMT)

Detailed Description:

A subject (n-of-1) clinically diagnosed with Relapsing Remitting Multiple Sclerosis (RRMS), by Rush University Neurologists, volunteered and provided written informed consent to participate in this study conducted by Rush University Medical Center's department of Digestive Diseases and Nutrition. The RRMS subject underwent a fecal microbiota transplantation (FMT) administered outside the United States, at Taymount Clinic in the Bahamas, for the treatment of their MS. Being one of the investigators' patients, the subject volunteered to donate their stool samples to the Rush University Medical Center Gastrointestinal (GI) tissue repository for microbiota interrogation at the following time points: before FMT (baseline), 3, 13, 26, 39, 52 weeks (1 year) after FMT, to determine the impact on their microbiota composition and sustainability of the change. The subject also agreed to donate their blood during the above stated time points to see if FMT affected markers of bacteria translocation and systemic inflammation. The subject also agreed to have their GI symptoms, diet, sleep, and MS related symptoms (rating scales or questionnaires), MRI (brain & spine), as well as their gait metric activity objectively assessed to see if the FMT affects these symptoms and whether any observed improvement is sustained, in this proof-of-concept study. Based on this research, the investigators hypothesize that the FMT will significantly altered the overall microbial community structure to promote the growth of short chain fatty acid (SCFA)-producing beneficial bacteria, which in turn could potentially improve the MS subject's health outcomes, neurological symptoms, and walking metrics over time. More clinical trials (larger sample size) will be needed to study the potential of FMT for the treatment of MS and to examine the long term effects. FMT is an emerging treatment approach for MS. The donor selection, the separation of fecal bacteria, the frequency of FMT, the way of infusion, the long-term safety, and efficacy are still uncertain and need to be examined.

Study Design

• Study Type: Observational
• Actual Enrollment: 1 participants
• Observational Model: Case-Only
• Time Perspective: Prospective
• Official Title: Single-Arm, Non-Randomized, Time Series, Single-Subject Study: Fecal Microbiota Transplantation (FMT) in Multiple Sclerosis
• Actual Study Start Date: September 25, 2018
• Actual Primary Completion Date: April 1, 2020
• Actual Study Completion Date: May 1, 2020

Groups and Cohorts

Group/Cohort

Intervention/treatment

N=1 MS patient; Single-Arm, Non-Randomized, Time Series, Single-Subject Study. Observational study of the FMT intervention. Single subject studies are based on repeated observations within an individual over time and are acknowledged as an important research method for generating scientific evidence about the health or behavior of an individual. This design is desirable when the available patient pool is limited and thus it is not optimal to randomize participants to a control arm. The subject serves as his/her own control, rather than using another individual/group.These designs are used primarily to evaluate the effect of a variety of interventions in early stage clinical research development.

Other: Fecal Microbiota Transplantation (FMT); Longitudinal FMT study: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week; Other Name: Taymount Clinic

Outcome Measures

Primary Outcome Measures :

1. Fecal microbial community structure and functional changes over six time frames for phylum, genus and species taxonomic level bacteria, virus, fungi, and archaea. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
   Shotgun Metagenomics
2. Walking and balance changes over four time frames for stride time (seconds). [ Time Frame: Baseline, 3 week, 13 week, 52 week ]
   Orthopedic gait task, side gaze gait, and alternating gaze gait metrics.
3. Walking and balance changes over four time frames for stride distance (meters). [ Time Frame: Baseline, 3 week, 13 week, 52 week ]
   Orthopedic gait task, side gaze gait, and alternating gaze gait metrics.
4. Walking and balance changes over four time frames for cadence (total number of steps per minute). [ Time Frame: Baseline, 3 week, 13 week, 52 week ]
   Orthopedic gait task, side gaze gait, and alternating gaze gait metrics.
5. Walking and balance changes over four time frames for step width (meters). [ Time Frame: Baseline, 3 week, 13 week, 52 week ]
   Orthopedic gait task, side gaze gait, and alternating gaze gait metrics.
6. Walking and balance changes over four time frames for average pelvis forward velocity (meters per second). [ Time Frame: Baseline, 3 week, 13 week, 52 week ]
   Orthopedic gait task, side gaze gait, and alternating gaze gait metrics.
7. Walking and balance changes over four time frames for pelvis smoothness (pelvis horizontal speed). [ Time Frame: Baseline, 3 week, 13 week, 52 week ]
   Orthopedic gait task, side gaze gait, and alternating gaze gait metrics.

Secondary Outcome Measures :

1. Fecal targeted short-chain-fatty-acid metabolomics concentration changes over six time frames for acetate (mM/kg), propionate (mM/kg), butyrate (mM/kg), and total SCFA (mM/kg). [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
   Targeted metabolomics of short-chain-fatty-acids (SCFA).
2. Measurement of blood serum biomarker brain-derived neurotrophic factor (BDNF) (ng/ml) changes over six time frames. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
   ELISA (enzyme-linked immunosorbent assay)
3. Sleep changes over six time frames. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
   Munich ChronoType Questionnaire (MCTQ). Questions about work day and free day sleep schedules, work details, and lifestyle provide data to aid in the understanding of how biological clocks work in social life, such as Roenneberg's conclusions of social jetlag. The MCTQ categorizes each participant into one of seven chronotype groups, and utilizes data on participants' midsleep phase and sleep debt to survey what "type" of sleeper each person is.
4. Food timing changes over six time frames. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
   Food Timing Screener (FTS) questionnaire. A structured food demographics questionnaire was therefore developed to access food timing. The questionnaire consists of eight questions asking subjects' eating habits on work days and non-work days. Questions include the time of the main meal during work and non-work days, time of last meal before bed, consistency of dinner within work and non-work days, and consistency of breakfast, lunch, and dinner between work and non-work days.
5. Gastrointestinal symptoms changes over six time frames (t-scores, mean, standard deviations). [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
   Patient-Reported Outcomes Measurements Information System (PROMIS) gastrointestinal questionnaire for Belly Pain (6 questions), Bowel Incontinence (4 questions), Constipation (9 questions), and Gas & Bloating (12 questions). Higher score denoted more GI symptoms. Lower score denotes less GI symptoms. Scores range from 20 (low) to 80 (high). A score of 50 is denoted as the general population.
6. Walking changes over six time frames. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
   Multiple sclerosis walking scale questionnaire. Higher scores indicate a greater impact from MS on walking than lower scores. Scale range from 1 (no impact) to 5 (high impact). 12 questions in total.
7. Lesions changes over three time frames. [ Time Frame: Baseline, 26 week and 52 week ]
   MRI of brain and spine
8. Food and frequency of consumption changes over six time frames. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
   Food Time Questionnaire (FTQ) consists of a list of foods and the frequency in which these foods are consumed in at each time frame.
9. Single day food recall changes over six time frames. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
   Automated Self-Administered 24-Hour Recall (ASA24) Dietary Assessment. Total nutrients from all supplements reported in a given day.
10. Diet changes over six time frames. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
    Vioscreen Food Frequency Questionnaire (FFQ). Total of 19 measured food components collected for each time frame. Vioscreen captures comprehensive dietary behaviors in just 30 minutes. VioScreen is a unique online dietary questionnaire, management and analysis system that efficiently gathers and manages data, that immediately identify dietary "habits" and counsel for lifestyle changes.
11. Measurement of blood serum biomarker Interleukin-6 (IL-6) (pg/ml) changes over six time frames. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
    ELISA (enzyme-linked immunosorbent assay)
12. Measurement of blood serum biomarker Interleukin-* (IL-8) (pg/ml) changes over six time frames. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
    ELISA (enzyme-linked immunosorbent assay)
13. Measurement of blood serum biomarker Tumor necrosis factor alpha (TNFα) (pg/ml) changes over six time frames. [ Time Frame: Baseline, 3 week, 13 week, 26 week, 39 week, 52 week ]
    ELISA (enzyme-linked immunosorbent assay)

Biospecimen Retention:   Samples With DNA

Whole Fecal Collection; Fecal DNA Extraction; Blood: frozen serum, plasma & buffy coat.

Eligibility Criteria

• Ages Eligible for Study: 18 Years and older (Adult, Older Adult)
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes
• Sampling Method: Non-Probability Sample

Study Population

One of the investigators' patients planned to have a fecal microbiota transplant (FMT) for treatment of their MS, at the Taymount Clinic in the Bahamas, volunteered to donate multiple sample collection time points for stool and blood. Additionally, the subject would undergo gait metric activity and MRI (brain & spine), as well as completing MS rating scales and various GI, diet and sleep clinical questionnaires.

Criteria

Inclusion Criteria:

1. Older than 18 years of age.
2. Diagnosis of relapsing-remitting multiple sclerosis (RRMS) by neurology(primary specialist).
3. Presence of active lesions on brain or spinal cord MRI, in the past 1 year prior to baseline.
4. MS disease duration greater than 1 year.
5. Symptomatic (Active RRMS).
6. On MS therapy/medication greater than 4 weeks.

Exclusion Criteria:

1. Newly diagnosed multiple sclerosis.
2. Inactive relapsing-remitting multiple sclerosis (RRMS).
3. Unstable or no MS therapy/medication use.
4. Presence of symptomatically active gastrointestinal diseases such as inflammatory bowel disease or celiac disease (except for hemorrhoids, hiatal hernia, or occasional (˂3 times a week) heartburn)).
5. Pre-existent organ failure or co-morbidities as these may change GI flora: a) liver disease (cirrhosis or persistently abnormal AST or ALT that are 2X˃ normal); b) kidney disease (creatinine ˃ 2.0mg/dL); c) uncontrolled psychiatric illness; d) clinically active lung disease or decompensated heart failure; e) known HIV infection; f) alcoholism; g) transplant recipients (other than FMT); h) diabetes
6. Severe malnutrition or obesity with BMI ˃ 40.
7. Antibiotic and probiotic use (except yogurt) within 4 weeks of enrollment.
8. Chronic use of NSAIDS. A washout period of 3 weeks is needed before the subject could be enrolled into the study. Low dose aspirin is allowed.
9. Pregnant or lactating women or intention of getting pregnant during the trial period.
10. Active infection including untreated latent or active tuberculosis, HIV, hepatitis, syphilis or other major active infection.
11. Active symptomatic C. Difficile infection (colonization is not an exclusion).
12. Active gastrointestinal condition being investigated (i.e. GI bleeding, colon cancer, active GI workup); history of known or suspected toxic megacolon and/or known small bowel ileus, major gastrointestinal surgery (e.g. significant bowel resection) within 3 months before enrollment (note that this does not include appendectomy or cholecystectomy); or history of total colectomy or bariatric surgery.

Contacts and Locations

Locations

United States, Illinois

Rush University Medical Center

Chicago, Illinois, United States, 60612

Sponsors and Collaborators

Rush University Medical Center

Investigators

• Principal Investigator: Ali Keshavarzian, MD; Rush University Medical Center

More Information

Publications:

Cekanaviciute E, Yoo BB, Runia TF, Debelius JW, Singh S, Nelson CA, Kanner R, Bencosme Y, Lee YK, Hauser SL, Crabtree-Hartman E, Sand IK, Gacias M, Zhu Y, Casaccia P, Cree BAC, Knight R, Mazmanian SK, Baranzini SE. Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models. Proc Natl Acad Sci U S A. 2017 Oct 3;114(40):10713-10718. doi: 10.1073/pnas.1711235114. Epub 2017 Sep 11. Erratum In: Proc Natl Acad Sci U S A. 2017 Oct 17;114(42):E8943.

Berer K, Gerdes LA, Cekanaviciute E, Jia X, Xiao L, Xia Z, Liu C, Klotz L, Stauffer U, Baranzini SE, Kumpfel T, Hohlfeld R, Krishnamoorthy G, Wekerle H. Gut microbiota from multiple sclerosis patients enables spontaneous autoimmune encephalomyelitis in mice. Proc Natl Acad Sci U S A. 2017 Oct 3;114(40):10719-10724. doi: 10.1073/pnas.1711233114. Epub 2017 Sep 11.

Kaskow BJ, Baecher-Allan C. Effector T Cells in Multiple Sclerosis. Cold Spring Harb Perspect Med. 2018 Apr 2;8(4):a029025. doi: 10.1101/cshperspect.a029025.

Berer K, Mues M, Koutrolos M, Rasbi ZA, Boziki M, Johner C, Wekerle H, Krishnamoorthy G. Commensal microbiota and myelin autoantigen cooperate to trigger autoimmune demyelination. Nature. 2011 Oct 26;479(7374):538-41. doi: 10.1038/nature10554.

Tremlett H, Fadrosh DW, Faruqi AA, Hart J, Roalstad S, Graves J, Lynch S, Waubant E; US Network of Pediatric MS Centers. Gut microbiota composition and relapse risk in pediatric MS: A pilot study. J Neurol Sci. 2016 Apr 15;363:153-7. doi: 10.1016/j.jns.2016.02.042. Epub 2016 Feb 20.

Ochoa-Reparaz J, Magori K, Kasper LH. The chicken or the egg dilemma: intestinal dysbiosis in multiple sclerosis. Ann Transl Med. 2017 Mar;5(6):145. doi: 10.21037/atm.2017.01.18.

Kirby TO, Ochoa-Reparaz J. The Gut Microbiome in Multiple Sclerosis: A Potential Therapeutic Avenue. Med Sci (Basel). 2018 Aug 24;6(3):69. doi: 10.3390/medsci6030069.

Adamczyk-Sowa M, Medrek A, Madej P, Michlicka W, Dobrakowski P. Does the Gut Microbiota Influence Immunity and Inflammation in Multiple Sclerosis Pathophysiology? J Immunol Res. 2017;2017:7904821. doi: 10.1155/2017/7904821. Epub 2017 Feb 20.

Camara-Lemarroy CR, Metz LM, Yong VW. Focus on the gut-brain axis: Multiple sclerosis, the intestinal barrier and the microbiome. World J Gastroenterol. 2018 Oct 7;24(37):4217-4223. doi: 10.3748/wjg.v24.i37.4217.

Makkawi S, Camara-Lemarroy C, Metz L. Fecal microbiota transplantation associated with 10 years of stability in a patient with SPMS. Neurol Neuroimmunol Neuroinflamm. 2018 Apr 3;5(4):e459. doi: 10.1212/NXI.0000000000000459. eCollection 2018 Jul. No abstract available.

Quintana FJ, Prinz M. A gut feeling about multiple sclerosis. Proc Natl Acad Sci U S A. 2017 Oct 3;114(40):10528-10529. doi: 10.1073/pnas.1714260114. Epub 2017 Sep 25. No abstract available.

Smits LP, Bouter KE, de Vos WM, Borody TJ, Nieuwdorp M. Therapeutic potential of fecal microbiota transplantation. Gastroenterology. 2013 Nov;145(5):946-53. doi: 10.1053/j.gastro.2013.08.058. Epub 2013 Sep 7.

Chu F, Shi M, Lang Y, Shen D, Jin T, Zhu J, Cui L. Gut Microbiota in Multiple Sclerosis and Experimental Autoimmune Encephalomyelitis: Current Applications and Future Perspectives. Mediators Inflamm. 2018 Apr 2;2018:8168717. doi: 10.1155/2018/8168717. eCollection 2018.

Jangi S, Gandhi R, Cox LM, Li N, von Glehn F, Yan R, Patel B, Mazzola MA, Liu S, Glanz BL, Cook S, Tankou S, Stuart F, Melo K, Nejad P, Smith K, Topcuolu BD, Holden J, Kivisakk P, Chitnis T, De Jager PL, Quintana FJ, Gerber GK, Bry L, Weiner HL. Alterations of the human gut microbiome in multiple sclerosis. Nat Commun. 2016 Jun 28;7:12015. doi: 10.1038/ncomms12015.

Hooper LV, Littman DR, Macpherson AJ. Interactions between the microbiota and the immune system. Science. 2012 Jun 8;336(6086):1268-73. doi: 10.1126/science.1223490. Epub 2012 Jun 6.

• Responsible Party: Ali Keshavarzian, Professor and Director of Digestive Diseases & Nutrition, Rush University Medical Center
• ClinicalTrials.gov Identifier: NCT03975413
• Other Study ID Numbers: 18082009
• First Posted: June 5, 2019
• Last Update Posted: October 8, 2020
• Last Verified: October 2020

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: Undecided
• Plan Description: It is not yet known if there will be a plan to make IPD available. This pilot study of FMT in a patient with multiple sclerosis (MS) could suggest a potential effective treatment. More clinical trials (larger sample size) will be needed to study the potential of FMT for the treatment of MS and it's long term effects in the future.

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Ali Keshavarzian, Rush University Medical Center:

FMT; Microbiome; Gait; Longitudinal; Multiple Sclerosis

Additional relevant MeSH terms:

Multiple Sclerosis; Multiple Sclerosis, Relapsing-Remitting; Sclerosis; Pathologic Processes; Demyelinating Autoimmune Diseases, CNS; Autoimmune Diseases of the Nervous System; Nervous System Diseases; Demyelinating Diseases; Autoimmune Diseases; Immune System Diseases