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The role of the gut microbiota in multiple sclerosis

Nature reviews. Neurology, 2022-09, Vol.18 (9), p.544-558

2022

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Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes

PLoS computational biology, 2015-07, Vol.11 (7), p.e1004259-e1004259

2015

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Gut microbiota from multiple sclerosis patients enables spontaneous autoimmune encephalomyelitis in mice

Proceedings of the National Academy of Sciences - PNAS, 2017-10, Vol.114 (40), p.10719-10724

2017

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Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings

Nature communications, 2019-07, Vol.10 (1), p.3045-10, Article 3045

2019

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Systematic integration of biomedical knowledge prioritizes drugs for repurposing

eLife, 2017-09, Vol.6

2017

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microRNA and exosome profiling in multiple sclerosis

Multiple sclerosis, 2020-04, Vol.26 (5), p.599-604

2020

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The Role of the Gut Microbiome in Multiple Sclerosis Risk and Progression: Towards Characterization of the “MS Microbiome”

Neurotherapeutics, 2018-01, Vol.15 (1), p.126-134

2018

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The genetics of multiple sclerosis: an up-to-date review

Immunological reviews, 2012-07, Vol.248 (1), p.87-103

2012

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The genetics of autoimmune diseases: a networked perspective

Current opinion in immunology, 2009-12, Vol.21 (6), p.596-605

Baranzini, Sergio E

2009

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Aberrant oligodendroglial-vascular interactions disrupt the blood-brain barrier, triggering CNS inflammation

Nature neuroscience, 2019-05, Vol.22 (5), p.709-718

2019

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Differential micro RNA expression in PBMC from multiple sclerosis patients

PloS one, 2009-07, Vol.4 (7), p.e6309-e6309

2009

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Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models

Proceedings of the National Academy of Sciences - PNAS, 2017-10, Vol.114 (40), p.10713-10718

2017

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Gut microbiome analysis in neuromyelitis optica reveals overabundance of Clostridium perfringens

Annals of neurology, 2016-09, Vol.80 (3), p.443-447

2016

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Embedding electronic health records onto a knowledge network recognizes prodromal features of multiple sclerosis and predicts diagnosis

Journal of the American Medical Informatics Association : JAMIA, 2022-01, Vol.29 (3), p.424-434

2022

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Insights into microbiome research 6: The role of consortia in studying the role of microbes in health and disease

Multiple sclerosis, 2019-03, Vol.25 (3), p.336-337

Baranzini, Sergio E

2019

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Insights into microbiome research 2: Experimental design, sample collection, and shipment

Multiple sclerosis, 2018-10, Vol.24 (11), p.1419-1420

Baranzini, Sergio E

2018

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Genetics of multiple sclerosis severity: The importance of statistical power in replication studies

Multiple sclerosis, 2024-08, Vol.30 (9), p.1232-1233

2024

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Age- and Sex-Dependent Patterns of Gut Microbial Diversity in Human Adults

mSystems, 2019-07, Vol.4 (4)

2019

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Insights into microbiome research 1: How to choose appropriate controls for a microbiome study in MS?

Multiple sclerosis, 2018-09, Vol.24 (10), p.1278-1279

Baranzini, Sergio E

2018

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What doesn’t kill you makes you stronger . . . or does it?

Multiple sclerosis, 2024-03, Vol.30 (3), p.292-294

2024

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Insights into microbiome research 5: Mapping is first but function must come next

Multiple sclerosis, 2019-02, Vol.25 (2), p.193-195

Baranzini, Sergio E

2019

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Insights into microbiome research 4: The computational analysis

Multiple sclerosis, 2019-01, Vol.25 (1), p.21-22

Baranzini, Sergio E

2019

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The genetics of multiple sclerosis: SNPs to pathways to pathogenesis

Nature reviews. Genetics, 2008-07, Vol.9 (7), p.516-526

2008

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Insights into microbiome research 3: Who’s there versus what are they doing?

Multiple sclerosis, 2018-10, Vol.24 (12), p.1541-1542

Baranzini, Sergio E

2018

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Dysregulation of the Wnt pathway inhibits timely myelination and remyelination in the mammalian CNS

Genes & development, 2009-07, Vol.23 (13), p.1571-1585

2009

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The role of the gut microbiota in multiple sclerosis

Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes

Gut microbiota from multiple sclerosis patients enables spontaneous autoimmune encephalomyelitis in mice

Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings

Systematic integration of biomedical knowledge prioritizes drugs for repurposing

microRNA and exosome profiling in multiple sclerosis

The Role of the Gut Microbiome in Multiple Sclerosis Risk and Progression: Towards Characterization of the “MS Microbiome”

The genetics of multiple sclerosis: an up-to-date review

The genetics of autoimmune diseases: a networked perspective

Aberrant oligodendroglial-vascular interactions disrupt the blood-brain barrier, triggering CNS inflammation

Differential micro RNA expression in PBMC from multiple sclerosis patients

Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models

Gut microbiome analysis in neuromyelitis optica reveals overabundance of Clostridium perfringens

Embedding electronic health records onto a knowledge network recognizes prodromal features of multiple sclerosis and predicts diagnosis

Insights into microbiome research 6: The role of consortia in studying the role of microbes in health and disease

Insights into microbiome research 2: Experimental design, sample collection, and shipment

Genetics of multiple sclerosis severity: The importance of statistical power in replication studies

Age- and Sex-Dependent Patterns of Gut Microbial Diversity in Human Adults

Insights into microbiome research 1: How to choose appropriate controls for a microbiome study in MS?

What doesn’t kill you makes you stronger . . . or does it?

Insights into microbiome research 5: Mapping is first but function must come next

Insights into microbiome research 4: The computational analysis

The genetics of multiple sclerosis: SNPs to pathways to pathogenesis

Insights into microbiome research 3: Who’s there versus what are they doing?

Dysregulation of the Wnt pathway inhibits timely myelination and remyelination in the mammalian CNS

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