Deciphering the Role of the Gut Microbiota in Multiple Sclerosis

NCT02580435 | Unknown

• 1 other identifier: 2356-15-SMC
• Study Type: observational
• Target: 520
• Locations: 0 countries
• Sites: N/A

Brief Summary

Multiple sclerosis (MS) is an inflammatory disease that affects the nervous system and results in a wide range of signs and symptoms including physical and cognitive problems. Recent evidence demonstrates that interactions between the host immune system and the commensal gut microbiota have a key role in the development of the disease. However, the natures of these interactions are poorly studied, and the set of bacteria with pathogenic or protective potential are unknown. Here, the investigators propose a multi-pronged approach to deciphering the role of the microbiota in MS, by developing microbiome-based machine learning algorithms aimed at: (1) distinguishing healthy individuals from MS patients; (2) predicting the time since the onset of MS in relation to disease activity by predicting next relapse and neurological progression; (3) identifying microbiome signatures that characterize the relapse state; (4) distinguishing various MS phenotypes in relation to blood and microbiome transcriptome signatures; (5) predicting response to various immunomodulatory treatments in relation to blood and microbiome transcriptome signatures. Overall, these studies should establish the role of the microbiome in multiple sclerosis, resulting in a set of non-invasive tools for characterization of the disease; identification of the kinetics of MS using microbiome as a readout; and allowing the prediction of individuals prone to MS based on their microbiome and in relation to their protein expression. These new set of diagnostic and predictive tools may thus add a novel and unexplored dimension to the study of the disease that may lead in the future to new therapeutic avenues based on designing microbiome-targeted interventions.

Conditions

Multiple Sclerosis

Keywords

multiple sclerosis; microbiome; prediction; outcome

Outcome Measures

Primary Outcomes (2)

• 1. Change in expression of intestinal microbiome composition between MS patients and healthy controls.

  Intestinal microbiome composition and function of a cohort of 50 untreated early MS patients, up to 12 months from onset, untreated with immunomodulatory drugs or steroids for at least 3 months, as well as 50 age-, sex-, and diet-matched healthy controls (obtained from the Weizmann DataBank) will be performed.

  5 years

• Change in microbiome expression intestinal microbiome composition between MS patients phenotypes.

  Intestinal microbiome composition and function and blood profiling of 100 patients with different disease phenotypes (RIS=20; CIS=30; RRMS=30; PPMS=20) will be performed.

  5 years

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

The Multiple Sclerosis Center at Sheba Medical Center is currently following and treating 3710 out of \~5000 MS patients in Israel and as such represents a unique opportunity to unravel the role of the microbiome in MS, since it offers the possibility to identify multiple subgroups of patients in an attempt to detect microbiome signatures. A total of 520 subjects will be included in the study as is further specified. The data for 100 healthy control subjects will be obtained from the Weizmann DataBank by Prof Eran Segal.

You may qualify if:

• Diagnosis of RIS, CIS, RRMS, PPMS.
• Signed written informed consent.

You may not qualify if:

• Pregnancy
• Lactation
• Severe cognitive decline.

Sponsors & Collaborators

• Sheba Medical Center: lead
• Weizmann Institute of Science: collaborator

Related Publications (8)

• Maslowski KM, Vieira AT, Ng A, Kranich J, Sierro F, Yu D, Schilter HC, Rolph MS, Mackay F, Artis D, Xavier RJ, Teixeira MM, Mackay CR. Regulation of inflammatory responses by gut microbiota and chemoattractant receptor GPR43. Nature. 2009 Oct 29;461(7268):1282-6. doi: 10.1038/nature08530.

  PMID: 19865172 BACKGROUND

• Slack E, Hapfelmeier S, Stecher B, Velykoredko Y, Stoel M, Lawson MA, Geuking MB, Beutler B, Tedder TF, Hardt WD, Bercik P, Verdu EF, McCoy KD, Macpherson AJ. Innate and adaptive immunity cooperate flexibly to maintain host-microbiota mutualism. Science. 2009 Jul 31;325(5940):617-20. doi: 10.1126/science.1172747.

  PMID: 19644121 BACKGROUND

• Hapfelmeier S, Lawson MA, Slack E, Kirundi JK, Stoel M, Heikenwalder M, Cahenzli J, Velykoredko Y, Balmer ML, Endt K, Geuking MB, Curtiss R 3rd, McCoy KD, Macpherson AJ. Reversible microbial colonization of germ-free mice reveals the dynamics of IgA immune responses. Science. 2010 Jun 25;328(5986):1705-9. doi: 10.1126/science.1188454.

  PMID: 20576892 BACKGROUND

• Geuking MB, Cahenzli J, Lawson MA, Ng DC, Slack E, Hapfelmeier S, McCoy KD, Macpherson AJ. Intestinal bacterial colonization induces mutualistic regulatory T cell responses. Immunity. 2011 May 27;34(5):794-806. doi: 10.1016/j.immuni.2011.03.021. Epub 2011 May 19.

  PMID: 21596591 BACKGROUND

• 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.

  PMID: 22031325 BACKGROUND

• Achiron A, Gurevich M, Snir Y, Segal E, Mandel M. Zinc-ion binding and cytokine activity regulation pathways predicts outcome in relapsing-remitting multiple sclerosis. Clin Exp Immunol. 2007 Aug;149(2):235-42. doi: 10.1111/j.1365-2249.2007.03405.x. Epub 2007 May 4.

  PMID: 17488294 BACKGROUND

• Suez J, Korem T, Zeevi D, Zilberman-Schapira G, Thaiss CA, Maza O, Israeli D, Zmora N, Gilad S, Weinberger A, Kuperman Y, Harmelin A, Kolodkin-Gal I, Shapiro H, Halpern Z, Segal E, Elinav E. Artificial sweeteners induce glucose intolerance by altering the gut microbiota. Nature. 2014 Oct 9;514(7521):181-6. doi: 10.1038/nature13793. Epub 2014 Sep 17.

  PMID: 25231862 BACKGROUND

• Thaiss CA, Zeevi D, Levy M, Zilberman-Schapira G, Suez J, Tengeler AC, Abramson L, Katz MN, Korem T, Zmora N, Kuperman Y, Biton I, Gilad S, Harmelin A, Shapiro H, Halpern Z, Segal E, Elinav E. Transkingdom control of microbiota diurnal oscillations promotes metabolic homeostasis. Cell. 2014 Oct 23;159(3):514-29. doi: 10.1016/j.cell.2014.09.048. Epub 2014 Oct 16.

  PMID: 25417104 BACKGROUND

Biospecimen

Retention: SAMPLES WITHOUT DNA

From each patient, the investigarors will obtain 1. Clinical metadata, including: Consent form; Medications; annual relapse rate; 2. Blood tests, including a complete blood count, complete biochemistry, lipid profile, cholesterol profile; 3. Gut microbiota profile obtained from stool samples will be processed for shotgun metagenomic sequencing and 16S rRNA profiling. Gut microbiota profiling will be done from stool samples that will be immediately flash-frozen in liquid nitrogen and preserved at a minimum of -80oC until further processing.

MeSH Terms

Conditions

Multiple Sclerosis

Condition Hierarchy (Ancestors)

Demyelinating Autoimmune Diseases, CNS; Autoimmune Diseases of the Nervous System; Nervous System Diseases; Demyelinating Diseases; Autoimmune Diseases; Immune System Diseases

Study Officials

• Anat Achiron, MD, PhD

  Sheba Medical Center

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Anat Achiron, MD, PhD

CONTACT

97235303932; anat.achiron@sheba.health.gov.il

Eran Segal, PhD

CONTACT

972542239989; Eran.Segal@weizmann.ac.il

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER GOV
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director & Chair, Multiple Sclerosis Center

Study Record Dates

• First Submitted: October 18, 2015
• First Posted: October 20, 2015
• Study Start: December 1, 2015
• Primary Completion: December 1, 2020
• Study Completion: December 1, 2021
• Last Updated: October 29, 2015

Record last verified: 2015-10