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Microbiota stratification identifies disease-specific alterations in neuro-Behçet’s disease and multiple sclerosis

1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11

 

  1. Baylor College of Medicine, Department of Pathology & Immunology, and Texas Children's Microbiome Center, Houston TX, USA. oezguen@bcm.edu
  2. Baylor College of Medicine, Department of Pathology & Immunology, and Texas Children's Microbiome Center, Houston TX, USA.
  3. Istanbul University, Department of Neuroscience, Institute for Experimental Medical Research, Istanbul, Turkey.
  4. Baylor College of Medicine, Department of Pathology & Immunology, and Texas Children's Microbiome Center, Houston TX, USA.
  5. Diversigen, Inc., Houston, TX, USA.
  6. Baylor College of Medicine, Department of Pathology & Immunology, and Texas Children's Microbiome Center, Houston TX, USA.
  7. Haydarpasa Numune Training and Research Hospital, Department of Neurology, Istanbul, Turkey.
  8. Istanbul University, Department of Neuroscience, Institute for Experimental Medical Research, Istanbul, Turkey.
  9. Istanbul University, Istanbul School of Medicine, Department of Neurology, Istanbul, Turkey.
  10. Baylor College of Medicine, Department of Pathology & Immunology, and Texas Children's Microbiome Center, Houston TX, USA.
  11. Istanbul University, Department of Neuroscience, Institute for Experimental Medical Research, Istanbul, Turkey.

CER11936
2019 Vol.37, N°6 ,Suppl.121
PI 0058, PF 0066
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PMID: 31172918 [PubMed]

Received: 25/11/2018
Accepted : 28/03/2019
In Press: 30/05/2019
Published: 09/12/2019

Abstract

OBJECTIVES:
Altered gut microbiota community dynamics are implicated in diverse human diseases including inflammatory disorders such as neuro-Behçet’s disease (NBD) and multiple sclerosis (MS). Traditionally, microbiota communities are analysed uniformly across control and disease groups, but recent reports of subsample clustering indicate a potential need for analytical stratification. The objectives of this study are to analyse and compare faecal microbiota community signatures of ethno-geographical, age and gender matched adult healthy controls (HC), MS and NBD individuals.
METHODS:
Faecal microbiota community compositions in adult HC (n=14), NBD patients (n=13) and MS (n=13) were analysed by 16S rRNA gene sequencing and standard bioinformatics pipelines. Bipartite networks were then used to identify and re-analyse dominant compositional clusters in respective groups.
RESULTS:
We identified Prevotella and Bacteroides dominated subsample clusters in HC, MS, and NBD cohorts. Our study confirmed previous reports that Prevotella is a major dysbiotic target in these diseases. We demonstrate that subsample stratification is required to identify significant disease-associated microbiota community shifts with increased Clostridiales evident in Prevotella-stratified NBD and Bacteroides-stratified MS patients.
CONCLUSIONS:
Patient cohort stratification may be needed to facilitate identification of common microbiota community shifts for causation testing in disease.

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