The Integrative Human Microbiome Project

,

doi:10.1038/s41586-019-1238-8

Cited by 906 publications

(410 citation statements)

References 91 publications

(89 reference statements)

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“…The Human Microbiota Project was launched in 2008 to deepen our understanding of how the microbiome (the whole set of microorganisms, their genomes and the environmental conditions) influences human health and diseases. 16S ribosomal RNA (16S rRNA) sequencing allows characterizing the complexity of the microbial population to study whether there is an "healthy microbiota" and potential implications of different patterns (1).…”

Section: Introductionmentioning

confidence: 99%

Gut and Lung Microbiota in Preterm Infants: Immunological Modulation and Implication in Neonatal Outcomes

et al. 2019

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In recent years, an aberrant gastrointestinal colonization has been found to be associated with an higher risk for postnatal sepsis, necrotizing enterocolitis (NEC) and growth impairment in preterm infants. As a consequence, the reasons of intestinal dysbiosis in this population of newborns have increasingly become an object of interest. The presence of a link between the gut and lung microbiome's development (gut-lung axis) is emerging, and more data show as a gut-brain cross talking mediated by an inflammatory milieu, may affect the immunity system and influence neonatal outcomes. A revision of the studies which examined gut and lung microbiota in preterm infants and a qualitative analysis of data about characteristic patterns and related outcomes in terms of risk of growing impairment, Necrotizing Enterocolitis (NEC), Bronchopulmonary Dysplasia (BPD), and sepsis have been performed. Microbiota take part in the establishment of the gut barrier and many data suggest its immune-modulator role. Furthermore, the development of the gut and lung microbiome (gut-lung axis) appear to be connected and able to lead to abnormal inflammatory responses which have a key role in the pathogenesis of BPD. Dysbiosis and the gut predominance of facultative anaerobes appear to be crucial to the pathogenesis and subsequently to the prevention of such diseases.

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Section: Introductionmentioning

confidence: 99%

Gut and Lung Microbiota in Preterm Infants: Immunological Modulation and Implication in Neonatal Outcomes

et al. 2019

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“…The etiology of ASD remains unknown and likely involves a wide range of environmental factors that affect many physiological processes in genetically sensitive individuals( 3 ). Recently, lines of evidence showed possible contributions of intestinal microbiomes to the pathogenesis of ASD as in many other diseases( 4 ). First, gastrointestinal co-morbidity is common in ASD children( 5 ).…”

Section: Introductionmentioning

confidence: 99%

A quasi-paired cohort strategy reveals the impaired detoxifying function of microbes in the gut of autistic children

Zhang

Chu

Meng

et al. 2020

Preprint

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30Growing evidence suggests that autism spectrum disorder (ASD) is highly associated with 31 dysbiosis in the gut microbiome. However, results of metagenome-based microbiome 32 studies are not always consistent due to great individual diversity that overwhelms 33 disease-associated alterations. Here, we proposed a novel analysis strategy-quasi-paired 34 cohort and applied it to a metagenomic study of ASD microbiomes. By comparing the 35 paired samples of ASD and neurotypical subjects, we identified significant deficiencies in 36 ASD children in detoxifying enzymes and pathways, which showed strong correlations to 37 mitochondrial damage. Diagnostic models with these detoxifying enzymes accurately 38 discriminated ASD individuals from controls, and the dysfunction score inferred from the 39 model increased with the clinical rating scores of ASD. Conclusively, our findings suggest 40 a previously undiscovered mechanism in which impaired microbial detoxification leads to 41 toxicant accumulation and mitochondrion damage contributes to the pathogenesis of ASD. 42 This novel mechanism points to future therapeutic strategies of rebuilding microbial 43 detoxification for ASD. 44 45 MAIN TEXT 46 47 131 Hs37 human genomes by BWA (mem module with default parameters) (http://bio-132

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“…retinoblastoma [8]), there is increasing 48 evidence for cases in which multiple distinct patterns can be associated with (and 49 potentially causing) the same high-level phenotype [9,10]. A particular example we will 50 explore in this work is the multiplicity of distinct microbial presence/absence patterns 51 which may be associated with Crohn's disease [11]. Crohn's disease has five clinically 52 defined sub-types [12] but studies of the associated microbiome do not usually indicate 53 which form of Crohn's disease a donor has been diagnosed with.…”

Section: Introduction 23mentioning

confidence: 99%

“…We first demonstrate that BowSaw can recover true rules by applying the 109 algorithms to simulated data sets of varying complexity. We then apply BowSaw to a 110 study on the role of the gut microbiome on Crohn's disease [11], and show that it can find 111 a previously unreported combination of microbial taxa that is broadly and precisely 112 associated with Crohn's disease instances in the data set. In its current implementation 113…”

Section: Introduction 23mentioning

confidence: 99%

“…Despite their demonstrated 409 effectiveness as good classifiers of Crohn's disease, studies that look to discover 410 associations with disease status typically focus on individual OTUs while specific 411 microbial association rules found by RF are not discussed, as a result it is uncertain how 412 heterogeneous study cohorts are. To investigate potential rule heterogeneity in a human 413 microbiome cohort we downloaded processed files from the Human Microbiome Project 414 for inflammatory bowel disease (IBD) [11] which contain information on the taxonomic 415 profiles of 982 OTUs in 178 patients -86 of which have been diagnosed with Crohn's 416 disease, 46 diagnosed with ulcerative colitis, and 46 diagnosed as non-IBD. We were 417 specifically interested in finding rules that separate the Crohn's disease samples from 418 ulcerative colitis and non-IBD, so we framed the problem as a binary classification task 419…”

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confidence: 99%

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BowSaw: inferring higher-order trait interactions associated with complex biological phenotypes

DiMucci

Kon

Segrè

2019

Preprint

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1Machine learning is helping the interpretation of biological complexity by enabling the 2 inference and classification of cellular, organismal and ecological phenotypes based on 3 large datasets, e.g. from genomic, transcriptomic and metagenomic analyses. A number 4 of available algorithms can help search these datasets to uncover patterns associated with 5 specific traits, including disease-related attributes. While, in many instances, treating an 6 algorithm as a black box is sufficient, it is interesting to pursue an enhanced 7 understanding of how system variables end up contributing to a specific output, as an 8 avenue towards new mechanistic insight. Here we address this challenge through a suite 9 of algorithms, named BowSaw, which takes advantage of the structure of a trained 10 random forest algorithm to identify combinations of variables ("rules") frequently used 11 for classification. We first apply BowSaw to a simulated dataset, and show that the 12 algorithm can accurately recover the sets of variables used to generate the phenotypes 13 through complex Boolean rules, even under challenging noise levels. We next apply our 14 method to data from the integrative Human Microbiome Project and find previously 15 unreported high-order combinations of microbial taxa putatively associated with Crohn's 16 disease. By leveraging the structure of trees within a random forest, BowSaw provides a 17 new way of using decision trees to generate testable biological hypotheses. 18 19 20 21 22

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The Integrative Human Microbiome Project

Cited by 906 publications

References 91 publications

Gut and Lung Microbiota in Preterm Infants: Immunological Modulation and Implication in Neonatal Outcomes

Gut and Lung Microbiota in Preterm Infants: Immunological Modulation and Implication in Neonatal Outcomes

A quasi-paired cohort strategy reveals the impaired detoxifying function of microbes in the gut of autistic children

BowSaw: inferring higher-order trait interactions associated with complex biological phenotypes

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