Cited by 1,381Gut microbiota and healthOral microbiology and periodontitis researchMicrobial Community Ecology and Physiology

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The Integrative Human Microbiome Project

Open access

Abstract

The NIH Human Microbiome Project (HMP) has been carried out over ten years and two phases to provide resources, methods, and discoveries that link interactions between humans and their microbiomes to health-related outcomes. The recently completed second phase, the Integrative Human Microbiome Project, comprised studies of dynamic changes in the microbiome and host under three conditions: pregnancy and preterm birth; inflammatory bowel diseases; and stressors that affect individuals with prediabetes. The associated research begins to elucidate mechanisms of host–microbiome interactions under these conditions, provides unique data resources (at the HMP Data Coordination Center), and represents a paradigm for future multi-omic studies of the human microbiome.

Overview

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TL;DR

The Integrative Human Microbiome Project (iHMP/HMP2) reports three longitudinal multi-omic cohort studies linking host and microbial dynamics to pregnancy/preterm birth, inflammatory bowel disease, and prediabetes. It also describes the resulting data resources and argues that longitudinal, multi-omic profiling is needed to capture personalized host–microbiome interactions.

Key findings

  • In pregnancy/preterm birth (MOMS-PI), 1,527 women were followed and 206,437 specimens collected; analysis of 12,039 samples from 597 pregnancies found that women who had spontaneous preterm birth were less likely to have *Lactobacillus crispatus*-dominated vaginal microbiota and more likely to have increased *Sneathia amnii*, *Prevotella*-related clades, BVAB1, and TM7-H1, with prediction most sensitive/specific using samples before 24 weeks.
  • In IBD (IBDMDB), 132 individuals from five clinical centres were followed for one year each, with 1,785 stool samples, 651 intestinal biopsies, and 529 quarterly blood samples; longitudinal changes were larger than cross-sectional differences among clinical phenotypes, and a network of more than 2,900 significant host and microbial interactors was constructed.
  • In prediabetes (IPOP), 106 healthy/prediabetic individuals were followed over about four years across 1,092 collections; insulin-resistant and insulin-sensitive participants differed at baseline and in response to respiratory viral infection or weight change, with insulin-resistant participants showing decreased/delayed inflammatory responses and altered gut microbial changes.
  • Across HMP1 and HMP2, 42 terabytes of multi-omic data were produced and archived at the HMP Data Coordination Center, which receives 9,000–12,000 user sessions each month; shotgun metagenomics, untargeted metabolomics, and immunoprofiling were particularly effective, whereas genetic variants were generally difficult to link to the microbiome in these small deeply profiled populations.

Methods

  • HMP2 comprised three longitudinal, multi-omic cohort studies: MOMS-PI for pregnancy and preterm birth, IBDMDB for inflammatory bowel diseases, and IPOP for prediabetes.
  • MOMS-PI followed 1,527 pregnancies and collected 206,437 specimens, with subsets analyzed by 16S rRNA gene sequencing, metagenomics, metatranscriptomics, cytokine profiling, lipidomics, and bacterial genome analysis; 12,039 samples from 597 pregnancies were analyzed in depth.
  • IBDMDB followed 132 individuals for one year each with stool, biopsy, and blood multi-omics; IPOP followed 106 individuals quarterly over about four years, profiling host exomes, transcriptomes, metabolomes, proteomes, cytokines, clinical labs, and microbial 16S profiles, including a 23-person weight gain/loss subset.

Limitations

  • Stated: the HMP2 raised more questions than it answered; the aetiologies of baseline inter-individual microbiome differences and dynamic changes were not apparent, it remains unclear whether specific strains are sufficient or necessary for disease phenotypes, and the small molecules or immune cell subsets transmitting gut signals to systemic conditions were not identified.
  • Stated: each HMP2 study was carried out within a geographically and genetically constrained population, and global differences in early life events, infectious disease exposure, or diet may change how microbiome dynamics contribute to disease.
  • Evident: the three studies are separate condition-specific cohorts rather than one unified population, and the findings are largely longitudinal associations rather than direct causal demonstrations.

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Integrity signals

Registry

Crossref · 10.1038/s41586-019-1238-8

Cites

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Statistics

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Figures

Fig. 1 The first and second phases of the NIH Human Microbiome Project. The ten-year NIH Human Microbiome Project (HMP) program, organized into two phases (HMP1 and HMP2), developed reference sequences, multi-omic data sets, computational and statistical tools, and analytical and clinical protocols as resources for the broader research community. The HMP1 focused on the characterization of microbial communities from numerous body sites (oral, nasal, vaginal, gut, and skin) in a baseline study of healthy adult subjects, and included a set of demonstration projects that focused on specific diseases or disorders. The HMP2 expanded the repertoire of biological properties analysed for both host and microbiome in three longitudinal cohort studies of representative microbiome-associated conditions: pregnancy and preterm birth (vaginal microbiomes of pregnant women), inflammatory bowel diseases (gut microbiome) and prediabetes (gut and nasal microbiomes). These studies followed the dynamics of these conditions through multi-omic analyses of multiple measurement types over time, including changes in microbial community composition, viromics, metabolomic profiles, gene expression and protein profiles from both host and microbiome, and host-specific properties such as genetic, epigenomic, antibody, and cytokine profiles, along with other study-specific features. All sequences and multi-omic data, clinical information, and tools from both HMP1 and HMP2 are housed in the HMP Data Coordination Center (DCC) or referenced public or controlled-access repositories to serve as a central resource for the research community.
Fig. 1 The first and second phases of the NIH Human Microbiome Project. The ten-year NIH Human Microbiome Project (HMP) program, organized into two phases (HMP1 and HMP2), developed reference sequences, multi-omic data sets, computational and statistical tools, and analytical and clinical protocols as resources for the broader research community. The HMP1 focused on the characterization of microbial communities from numerous body sites (oral, nasal, vaginal, gut, and skin) in a baseline study of healthy adult subjects, and included a set of demonstration projects that focused on specific diseases or disorders. The HMP2 expanded the repertoire of biological properties analysed for both host and microbiome in three longitudinal cohort studies of representative microbiome-associated conditions: pregnancy and preterm birth (vaginal microbiomes of pregnant women), inflammatory bowel diseases (gut microbiome) and prediabetes (gut and nasal microbiomes). These studies followed the dynamics of these conditions through multi-omic analyses of multiple measurement types over time, including changes in microbial community composition, viromics, metabolomic profiles, gene expression and protein profiles from both host and microbiome, and host-specific properties such as genetic, epigenomic, antibody, and cytokine profiles, along with other study-specific features. All sequences and multi-omic data, clinical information, and tools from both HMP1 and HMP2 are housed in the HMP Data Coordination Center (DCC) or referenced public or controlled-access repositories to serve as a central resource for the research community.CC BY · PubMed Central
Fig. 2 The vaginal microbiome and its relationships with host factors in pregnancy and preterm birth. The MOMS-PI project followed 1,527 pregnancies longitudinally and involved the collection of 206,437 biospecimens for analysis of host and microbial factors (16S amplicon, metagenomic, and metatranscriptomic sequencing; cytokine profiling; metabolomics; proteomics; genomics; and microbial isolate culture). Around 600 pregnancies were analysed in depth to assess features that lead to preterm birth; this analysis identified both host (for example, cytokine) and microbial (for example, ecological and specific strain) factors. As pregnancy progresses, with predictable changes in systemic oestradiol levels, the uterine and vaginal environments undergo various changes. The uterus switches from an early pro-inflammatory condition to an anti-inflammatory condition in the second trimester, and then back to a pro-inflammatory condition before the onset of labour. Meanwhile, specific changes in the microbiome of the vaginal lumen can be associated with preterm birth, possibly through mechanisms involving microorganisms travelling from the vagina to the uterus. The figure depicts an overview of longitudinal changes in the vaginal mucosal ecosystem and uterus during pregnancy.
Fig. 2 The vaginal microbiome and its relationships with host factors in pregnancy and preterm birth. The MOMS-PI project followed 1,527 pregnancies longitudinally and involved the collection of 206,437 biospecimens for analysis of host and microbial factors (16S amplicon, metagenomic, and metatranscriptomic sequencing; cytokine profiling; metabolomics; proteomics; genomics; and microbial isolate culture). Around 600 pregnancies were analysed in depth to assess features that lead to preterm birth; this analysis identified both host (for example, cytokine) and microbial (for example, ecological and specific strain) factors. As pregnancy progresses, with predictable changes in systemic oestradiol levels, the uterine and vaginal environments undergo various changes. The uterus switches from an early pro-inflammatory condition to an anti-inflammatory condition in the second trimester, and then back to a pro-inflammatory condition before the onset of labour. Meanwhile, specific changes in the microbiome of the vaginal lumen can be associated with preterm birth, possibly through mechanisms involving microorganisms travelling from the vagina to the uterus. The figure depicts an overview of longitudinal changes in the vaginal mucosal ecosystem and uterus during pregnancy.CC BY · PubMed Central
Fig. 3 Host–microbiome dynamics in IBD. The IBDMDB followed more than 100 participants with IBD (Crohn’s disease or ulcerative colitis), as well control individuals without IBD, for one year each to assess host and microbial molecular activity during changes in disease activity and gastrointestinal inflammation. Nearly all measured host–microbiome properties showed changes in either activity or stability during disease, including those shown here—not only microbial taxa and microbial transcription, but also host- and microbiota-derived small molecules in the gut, epithelial transcriptional responses at multiple points along the colon, and circulating antibody levels in peripheral blood serology.
Fig. 3 Host–microbiome dynamics in IBD. The IBDMDB followed more than 100 participants with IBD (Crohn’s disease or ulcerative colitis), as well control individuals without IBD, for one year each to assess host and microbial molecular activity during changes in disease activity and gastrointestinal inflammation. Nearly all measured host–microbiome properties showed changes in either activity or stability during disease, including those shown here—not only microbial taxa and microbial transcription, but also host- and microbiota-derived small molecules in the gut, epithelial transcriptional responses at multiple points along the colon, and circulating antibody levels in peripheral blood serology.CC BY · PubMed Central
Fig. 4 Differential host and microbial responses to dietary perturbations and infectious disease in individuals with prediabetes. For integrated personal ’omics profiling of the microbiome during prediabetes, 106 participants were followed for up to four years, with samples (primarily blood and stool) collected quarterly and additional samples collected during periods of RVI and other stresses. The genomes of the participants were sequenced and measurements of transcriptomes, proteomes, metabolomes, and microbiomes taken at each visit, in addition to clinical details. Insulin-resistant individuals showed differences from insulin-sensitive participants in various measurements, both at baseline and in response to the stresses such as weight loss and RVI.
Fig. 4 Differential host and microbial responses to dietary perturbations and infectious disease in individuals with prediabetes. For integrated personal ’omics profiling of the microbiome during prediabetes, 106 participants were followed for up to four years, with samples (primarily blood and stool) collected quarterly and additional samples collected during periods of RVI and other stresses. The genomes of the participants were sequenced and measurements of transcriptomes, proteomes, metabolomes, and microbiomes taken at each visit, in addition to clinical details. Insulin-resistant individuals showed differences from insulin-sensitive participants in various measurements, both at baseline and in response to the stresses such as weight loss and RVI.CC BY · PubMed Central
Fig. 5 Resources from HMP1 and HMP2 available at the DCC. The HMP DCC (http://ihmpdcc.org) hosts raw and processed data from both phases of the Human Microbiome Project, comprising in total more than 42 Tb of multi-omic data. From the HMP1, these include 16S rRNA gene amplicons and metagenomes from the healthy human subjects (HHS) baseline cohort, as well as resources from demonstration projects (https://www.hmpdacc.org/health/projectdemos.php) and genomes of associated microbial isolates. From the HMP2, these include data that IRBs gave permission to be made publicly available from the pregnancy and preterm birth (MOMS-PI), inflammatory bowel disease (IBDMDB), and prediabetes (IPOP) projects, with links to raw data in other repositories. Additional data deposited elsewhere including microbial reference genomes, HMP1 human genomes, and controlled access data for all HMP2 projects is also linked from the DCC. Categories of data are colour coded, and the number of items in each dataset is indicated by the size of the circles.
Fig. 5 Resources from HMP1 and HMP2 available at the DCC. The HMP DCC (http://ihmpdcc.org) hosts raw and processed data from both phases of the Human Microbiome Project, comprising in total more than 42 Tb of multi-omic data. From the HMP1, these include 16S rRNA gene amplicons and metagenomes from the healthy human subjects (HHS) baseline cohort, as well as resources from demonstration projects (https://www.hmpdacc.org/health/projectdemos.php) and genomes of associated microbial isolates. From the HMP2, these include data that IRBs gave permission to be made publicly available from the pregnancy and preterm birth (MOMS-PI), inflammatory bowel disease (IBDMDB), and prediabetes (IPOP) projects, with links to raw data in other repositories. Additional data deposited elsewhere including microbial reference genomes, HMP1 human genomes, and controlled access data for all HMP2 projects is also linked from the DCC. Categories of data are colour coded, and the number of items in each dataset is indicated by the size of the circles.CC BY · PubMed Central

Verification

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  • Probably not a substantial claim. 10
  • It may state two separate claims as one. 15
24 of 24
  • The paper relies on this without support.

    Little is known about systemic alterations during prediabetes, their effects on biological processes, or the critical transition to full-blown T2D.

    “but little is known about systemic alterations during prediabetes, their effects on biological processes, or the critical transition to full-blown T2D.”
  • The paper relies on this without support.

    Prediabetes and T2D are often associated with insulin resistance.

    “Prediabetes and T2D are often associated with insulin resistance”
  • The paper relies on this without support.

    Environmental factors, including the microbiome of the female reproductive tract, are important contributors to prematurity.

    “Environmental factors, including the microbiome of the female reproductive tract, are important contributors to prematurity.”
  • The paper relies on this without support.

    The three HMP2 studies' multi-omic measurements and populations are sufficiently comparable to allow identification of common host–microbiome features across them.

    “a surprising range of host–microbiome immune and ecological features were common among them”
  • The paper relies on this without support.

    A consistently high rate of user access to the DCC web resources is a valid indicator of the success of the HMP DCC data-sharing efforts.

    “The success of these efforts is evidenced by a consistently high rate of user access to the web resources, with 9,000–12,000 user sessions each month”
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Citations

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  1. Behrman, R. E. & Butler A. S. (eds.) Preterm Birth: Causes, Consequences, and Prevention (National Academies Press, 2007).

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Metadata

Authors
The Integrative HMP (iHMP) Research Network Consortium, Proctor, L. M., Creasy, H. H., Fettweis, J. M., Lloyd-Price, J., Mahurkar, A., Zhou, W., Buck, G. A., Snyder, M. P., Strauss, J. F., Weinstock, G. M., White, O., & Huttenhower, C.
Affiliations
  • National Institutes of Health (US)
  • University of Maryland, Baltimore (US)
  • Virginia Commonwealth University (US)
  • Stanford Medicine (US)
  • The Jackson Laboratory for Genomic Medicine (US)
  • Broad Institute (US)
Corresponding author
  • Buck, Gregory A.
  • Snyder, Michael P.
  • Strauss, Jerome F.
  • Weinstock, George M.
  • White, Owen
  • Huttenhower, Curtis
Venue
Nature
Published
2019-05-29
Volume
569
Issue
7758
Pages
641-648
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W2990249310
Cited by
1,381
References
89
Citations by year
2026: 193 · 2025: 184 · 2024: 196 · 2023: 198 · 2022: 203 · 2021: 195 · 2020: 166 · 2019: 44
FWCI
50.48
Type
journal article
Language
en
Open access
Locations
  • Nature (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • Office of Dietary Supplements
  • National Institutes of Health
  • National Institute of Allergy and Infectious Diseases (UH3AI083263)
  • National Institute of Diabetes and Digestive and Kidney Diseases (U54DK102556, U54DK102557)
  • National Institute of Dental and Craniofacial Research (U54DE023786)
  • Office of Research on Women's Health
  • National Center for Complementary and Integrative Health
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (U54HD080784, R01HD092415)
  • Common Fund
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
  • Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
Keywords
human microbiome, host-microbiome interactions, pregnancy, preterm birth, inflammatory bowel disease, prediabetes, stress, microbiome dynamics, multi-omics
MeSH terms
Gastrointestinal Microbiome, Host Microbial Interactions, Diet, Female, Humans, Infant, Newborn, Infant, Premature, Infections, National Institutes of Health (U.S.), Prediabetic State, Pregnancy, Research, Time Factors, United States, Vagina, Inflammatory Bowel Diseases, Microbiota

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