Gut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles
Chang D, Gupta V, Hur B, Cobo-López S, Cunningham K, Han N, Lee I, Kronzer V, Teigen L, Karnatovskaia L, Longbrake E, Davis J, Nelson H, Sung J. Gut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles. Nature Communications 2024, 15: 7447. PMID: 39198444, PMCID: PMC11358288, DOI: 10.1038/s41467-024-51651-9.Peer-Reviewed Original ResearchConceptsMicrobiome taxonomic profilingTaxonomic profilesOpen-source command-line toolGut microbiome researchGut microbial compositionGut microbiome signaturesFecal microbiota transplantationCommand-line toolShotgun metagenomicsTaxonomic signalMicrobiome researchMicrobial compositionMicrobiome signaturesGut healthMicrobiota transplantationGutPublished datasetsMultiple diseasesAntibiotic exposureEffects of dietMetagenomicsHigh confidencePhenotypeCross-validated balanced accuracyMeta-analysis identifies common gut microbiota associated with multiple sclerosis
Lin Q, Dorsett Y, Mirza A, Tremlett H, Piccio L, Longbrake E, Choileain S, Hafler D, Cox L, Weiner H, Yamamura T, Chen K, Wu Y, Zhou Y. Meta-analysis identifies common gut microbiota associated with multiple sclerosis. Genome Medicine 2024, 16: 94. PMID: 39085949, PMCID: PMC11293023, DOI: 10.1186/s13073-024-01364-x.Peer-Reviewed Original ResearchConceptsRRNA gene sequence dataGroups of microbial taxaGene sequence dataMicrobiome community structureAbundance of FaecalibacteriumAbundance of PrevotellaAbundance of ActinomycesSequence dataBeta diversityMicrobial taxaGut microbiotaMicrobial compositionCommunity structureNetwork analysisGutBacterial correlationsMicrobiotaAbundanceMultiple sclerosisDiverse groupMeta-analysisDiversityTaxaFaecalibacteriumConclusionsOur meta-analysis