Gut microbiome, IBD, Denmark and Spain
395 gut metagenome samples from adults and elderly individuals in Denmark and Spain, comparing healthy controls to IBD cases in a cross-sectional design. machine-written summary
396 samples · 1,704 runs · ES, DK · Age unknown · 2014 · 3.76 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 2,332 sample values (collection date, country, latitude, location region, longitude, subject id, timepoint) |
| ○ Abstract / description | read; no usable statement |
| ○ Full text | read; no usable statement or table · PMC10246480, PMC10258454, PMC10418321, PMC10810176, PMC11239293, PMC11317153, PMC11510655, PMC12268991, PMC13059687, PMC13469089, PMC6961876, PMC7931821, PMC8424563, PMC9685977 |
| ✓ Supplementary tables | 4 sample values (age, bmi, health condition, health condition detail) |
| ✓ External resources | 2,034 sample values (age, antibiotic exposure, bmi, health condition, health condition detail, sex) · from curatedMetagenomicData 3 (cMD 3), GMrepo v3 |
| – User contribution | nothing uploaded yet |
| – Human verified | not yet checked by a person · I checked this project — verify it |
bmi: curatedMetagenomicData and GMrepo disagree for 1 sample (e.g. 19.98 vs 28.3531) — withheld; sex differs between samples of the same subject id (22 subjects, 66 samples) — sex withheld; sex: curatedMetagenomicData and GMrepo disagree for 4 samples (e.g. male vs female) — withheld; subject ids shared by samples of both sexes (26 ids, 82 samples) — ids withheld.
The sources disagree on 93 samples. Where two incompatible values exist for one sample (or one person's samples disagree on sex), neither value is published: the field is left empty here, in the sample sheet and in the downloads. Both sides, with their sources, are in gut_metadata_contradictions.parquet of the data package (what counts as a contradiction).
Contradicted values (40 of 153)
| sample | field | value | other value | handling |
|---|---|---|---|---|
| SAMEA2042660 | bmi | 19.98 (curatedMetagenomicData) | 28.3531 (GMrepo) | withheld: neither value published |
| SAMEA1964895 | sex | male (curatedMetagenomicData) | subject UC56: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA1964914 | sex | female (curatedMetagenomicData) | subject UC47: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA1965906 | sex | male (curatedMetagenomicData) | subject UC46: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA1966253 | sex | female (curatedMetagenomicData) | subject UC14: female in 3 samples, male in 1 sample | withheld: neither value published |
| SAMEA1968035 | sex | female (curatedMetagenomicData) | subject UC48: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA1971886 | sex | male (curatedMetagenomicData) | subject UC43: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA1972440 | sex | male (curatedMetagenomicData) | subject UC19: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA1972463 | sex | female (curatedMetagenomicData) | subject UC27: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2041927 | sex | male (curatedMetagenomicData) | subject UC50: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2041928 | sex | male (curatedMetagenomicData) | subject UC50: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042000 | sex | male (curatedMetagenomicData) | subject UC56: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042001 | sex | male (curatedMetagenomicData) | subject UC57: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042002 | sex | male (curatedMetagenomicData) | subject UC57: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042010 | sex | female (curatedMetagenomicData) | subject UC9: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042011 | sex | female (curatedMetagenomicData) | subject UC9: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042402 | sex | female (curatedMetagenomicData) | subject UC1: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042439 | sex | female (curatedMetagenomicData) | subject UC13: female in 3 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042440 | sex | female (curatedMetagenomicData) | subject UC13: female in 3 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042441 | sex | female (curatedMetagenomicData) | subject UC14: female in 3 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042447 | sex | female (curatedMetagenomicData) | subject UC18: female in 1 sample, male in 1 sample | withheld: neither value published |
| SAMEA2042448 | sex | female (curatedMetagenomicData) | subject UC19: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042510 | sex | male (curatedMetagenomicData) | subject UC27: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042512 | sex | male (curatedMetagenomicData) | subject UC29: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042516 | sex | female (curatedMetagenomicData) | subject UC30: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042519 | sex | male (curatedMetagenomicData) | subject UC32: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042570 | sex | male (curatedMetagenomicData) | subject UC34: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042573 | sex | female (curatedMetagenomicData) | subject UC36: female in 1 sample, male in 1 sample | withheld: neither value published |
| SAMEA2042574 | sex | male (curatedMetagenomicData) | subject UC37: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042579 | sex | female (curatedMetagenomicData) | subject UC40: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042582 | sex | female (curatedMetagenomicData) | subject UC43: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042583 | sex | male (curatedMetagenomicData) | subject UC44: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042585 | sex | female (curatedMetagenomicData) | subject UC46: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042618 | sex | male (curatedMetagenomicData) | subject UC47: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042619 | sex | male (curatedMetagenomicData) | subject UC48: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042624 | sex | female (curatedMetagenomicData) | subject UC50: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042659 | sex | female (curatedMetagenomicData) | subject UC56: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042661 | sex | female (curatedMetagenomicData) | subject UC57: male in 2 samples, female in 1 sample | withheld: neither value published |
| SAMEA2042665 | sex | male (curatedMetagenomicData) | subject UC9: female in 2 samples, male in 1 sample | withheld: neither value published |
| SAMEA2042741 | sex | male (curatedMetagenomicData) | subject UC1: male in 2 samples, female in 1 sample | withheld: neither value published |
longitudinal
34 of 71 people sampled more than once (100 samples; median 3, up to 4 per person) · follow-up median 12.0 y (max 31.0 y) · median interval between samples 12.0 y (time from age at collection). Schedule stated by the source: “Subjects sampled at multiple timepoints labeled 0,1,2,3,4,5; 60 of 96 subjects with subject IDs have more than one sample.”.
Each row is one person (15 shown of 34); dots are samples at days since that person's first sample.
Genera, mean relative abundance over 284 profiled gut samples of this project (Sandpiper SingleM profiles, GTDB R232; low-depth and non-metagenome profiles left out).
| field | samples | coverage | R1 | R2 | R3 | R4 |
|---|---|---|---|---|---|---|
| age_category | 396 | 100% | ||||
| country | 396 | 100% | 396 | |||
| health_condition | 396 | 100% | 396 | |||
| subject_id | 137 | 35% | 137 | |||
| health_condition_detail | 396 | 100% | 396 | |||
| bmi | 395 | 100% | 395 | |||
| collection_date | 395 | 100% | 395 | |||
| detailed_location | 395 | 100% | ||||
| latitude | 395 | 100% | 395 | |||
| location_region | 395 | 100% | 395 | |||
| longitude | 395 | 100% | 395 | |||
| age_at_collection_days | 347 | 88% | 347 | |||
| sex | 327 | 83% | 327 | |||
| timepoint_label | 219 | 55% | 219 | |||
| antibiotic_exposure | 177 | 45% | 177 |
- Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes. 2014 PMID 24997787 own_data
- Search Engine for Antimicrobial Resistance: A Cloud Compatible Pipeline and Web Interface for Rapidly Detecting Antimicrobial Resistance Genes Directly from Sequence Data. 2015 PMID 26197475 PMC4510569 own_data
- Automated and Accurate Estimation of Gene Family Abundance from Shotgun Metagenomes. 2015 PMID 26565399 PMC4643905 own_data
- MB-GAN: Microbiome Simulation via Generative Adversarial Network. 2021 PMID 33543271 PMC7931821 own_data
- FunOMIC: Pipeline with built-in fungal taxonomic and functional databases for human mycobiome profiling. 2022 PMID 35891785 PMC9293737 own_data
56 more
- Adlercreutzia equolifaciens Is an Anti-Inflammatory Commensal Bacterium with Decreased Abundance in Gut Microbiota of Patients with Metabolic Liver Disease. 2023 PMID 37569608 PMC10418321
- MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. 2015 PMID 26336640 PMC4556158
- Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. 2015 PMID 26633628 PMC4681099
- Genomic characterization of the uncultured Bacteroidales family S24-7 inhabiting the guts of homeothermic animals. 2016 PMID 27388460 PMC4936053
- Subspecies in the global human gut microbiome. 2017 PMID 29242367 PMC5740502
- GePMI: A statistical model for personal intestinal microbiome identification. 2018 PMID 30210803 PMC6123480
- Host-Microbe-Drug-Nutrient Screen Identifies Bacterial Effectors of Metformin Therapy. 2019 PMID 31474368 PMC6736778
- Biogeographic study of human gut-associated crAssphage suggests impacts from industrialization and recent expansion. 2020 PMID 31940321 PMC6961876
- Human Gut Microbiome Aging Clock Based on Taxonomic Profiling and Deep Learning. 2020 PMID 32534441 PMC7298543
- Deciphering functional redundancy in the human microbiome. 2020 PMID 33277504 PMC7719190
- Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models. 2021 PMID 33947803 PMC8269207
- Alterations in bile acid metabolizing gut microbiota and specific bile acid genes as a precision medicine to subclassify NAFLD. 2021 PMID 34151600 PMC8424563
- The taxonomic distribution of histamine-secreting bacteria in the human gut microbiome. 2021 PMID 34563136 PMC8465708
- MetaGeneBank: a standardized database to study deep sequenced metagenomic data from human fecal specimen. 2021 PMID 34592929 PMC8485520
- The human microbiome encodes resistance to the antidiabetic drug acarbose. 2021 PMID 34819672 PMC10258454
- Multi-kingdom microbiota analyses identify bacterial-fungal interactions and biomarkers of colorectal cancer across cohorts. 2022 PMID 35087227 PMC8813618
- Inflammatory bowel disease biomarkers of human gut microbiota selected via different feature selection methods. 2022 PMID 35497193 PMC9048649
- The systemic anti-microbiota IgG repertoire can identify gut bacteria that translocate across gut barrier surfaces. 2022 PMID 35976997 PMC9741845
- Intercontinental Gut Microbiome Variances in IBD. 2022 PMID 36142786 PMC9506019
- Integrating phylogenetic and functional data in microbiome studies. 2022 PMID 36179077 PMC9665866
- Faecal microbiome-based machine learning for multi-class disease diagnosis. 2022 PMID 36357393 PMC9649010
- Alternation of the gut microbiota in metabolically healthy obesity: An integrated multiomics analysis. 2022 PMID 36389176 PMC9663839
- Machine learning for data integration in human gut microbiome. 2022 PMID 36419034 PMC9685977
- Machine learning framework for gut microbiome biomarkers discovery and modulation analysis in large-scale obese population. 2022 PMID 36564713 PMC9789565
- Toward an improved definition of a healthy microbiome for healthy aging. 2022 PMID 37118093 PMC10154212
- Microbial genes outperform species and SNVs as diagnostic markers for Crohn's disease on multicohort fecal metagenomes empowered by artificial intelligence. 2023 PMID 37278203 PMC10246480
- Four functional profiles for fibre and mucin metabolism in the human gut microbiome. 2023 PMID 37858269 PMC10588041
- Microbiome and metabolome features in inflammatory bowel disease via multi-omics integration analyses across cohorts. 2023 PMID 37932270 PMC10628233
- Enteral nutrition promotes the remission of colitis by gut bacteria-mediated histidine biosynthesis. 2024 PMID 38215690 PMC10827402
- Meta-analysis reveals obesity associated gut microbial alteration patterns and reproducible contributors of functional shift. 2024 PMID 38265338 PMC10810176
- Plasmids in the human gut reveal neutral dispersal and recombination that is overpowered by inflammatory diseases. 2024 PMID 38605009 PMC11009399
- Changes in the type 2 diabetes gut mycobiome associate with metformin treatment across populations. 2024 PMID 38767350 PMC11237675
- Establishing a novel inflammatory bowel disease prediction model based on gene markers identified from single nucleotide variants of the intestinal microbiota. 2022 PMID 38868717 PMC10989788
- Enhancing insights into diseases through horizontal gene transfer event detection from gut microbiome. 2024 PMID 38884260 PMC11317153
- Discovery of disease-adapted bacterial lineages in inflammatory bowel diseases. 2024 PMID 38917808 PMC11239293
- Enhanced microbiota profiling in patients with quiescent Crohn's disease through comparison with paired healthy first-degree relatives. 2024 PMID 38942021 PMC11293350
- Meta-analysis of the human gut microbiome uncovers shared and distinct microbial signatures between diseases. 2024 PMID 39078158 PMC11334437
- An expanded database and analytical toolkit for identifying bacterial virulence factors and their associations with chronic diseases. 2024 PMID 39278950 PMC11402979
- Noninvasive, microbiome-based diagnosis of inflammatory bowel disease. 2024 PMID 39367251 PMC11645270
- Oral Microbial Translocation Genes in Gastrointestinal Cancers: Insights from Metagenomic Analysis. 2024 PMID 39458395 PMC11510655
- Systematic identification of secondary bile acid production genes in global microbiome. 2025 PMID 39688414 PMC11748489
- A meta-analysis of the gut microbiome in inflammatory bowel disease patients identifies disease-associated small molecules. 2025 PMID 39947133 PMC12268991
- Healthy microbiome-moving towards functional interpretation. 2025 PMID 40117176 PMC11927397
- Balance between bile acid conjugation and hydrolysis activity can alter outcomes of gut inflammation. 2025 PMID 40210868 PMC11985902
- Improved detection of microbiome-disease associations via population structure-aware generalized linear mixed effects models (microSLAM). 2025 PMID 40424276 PMC12136445
- Microbiota-driven antitumour immunity mediated by dendritic cell migration. 2025 PMID 40659786 PMC12390848
- Megasphaera Elesdenii Dysregulates Colon Epithelial Homeostasis, Aggravates Colitis-Associated Tumorigenesis. 2025 PMID 40801433 PMC12591162
- Systematically investigating and identifying bacteriocins in the human gut microbiome. 2025 PMID 40902606 PMC12648112
- Gut bacteria metabolize natural and synthetic steroid hormones via the reductive OsrABC pathway. 2025 PMID 41118772 PMC13059687
- Human intestinal fungus Clavispora lusitaniae attenuates colitis through Pyruvate decarboxylase-derived Indole-3-ethanol. 2025 PMID 41233306 PMC12615640
- Deciphering the personalized functional redundancy hierarchy in the gut microbiome. 2025 PMID 41345980 PMC12781464
- A signature-protein-based approach for accurate and efficient profiling of the human gut virome. 2026 PMID 41365303 PMC12853188
- Gut Lactate Boosts Ruminococcus via Histone Lactylation to Mediate Time-Restricted Feeding Protection in Crohn's Disease. 2026 PMID 41945859 PMC13271634
- Fecal microbiome of patients with ulcerative colitis reflects their phenotype and inflammatory level. 2026 PMID 42156414 PMC13469089
- Global gut microbiome atlas identifies epidemiologic-stage-specific signatures in inflammatory bowel disease. 2026 PMID 42575094 PMC13589510
- Plasmid dispersal and recombination across human gut microbiomes is neutral, but overpowered by inflammatory diseases 2023
Archive description
The microbial diversity of environments like the human gut extends far beyond what is covered by reference genomes. Here we present a method for exhaustive and unsupervised co-abundance gene binning across a series of highly complex metagenomic samples. As the method does not rely on previously sequenced reference genomes it allows for discovery of new species, viruses and clonal heterogeneity. We demonstrate the method on human gut microbiome data and identify 7,381 co-abundance gene groups (CAGs) ranging in size from 3 to 6,319 genes. The CAGs represent a wide variety of biological entities including microbial genomes, phages and clonal differences. We name the 741 largest of these metagenomic species (MGS), because they correspond to microbial species. In addition, we establish microbial host affiliations by dependency-associations for many small CAGs. Longitudinal sampling in the same individuals indicates that some of these dependency-associations are important for the persistence of their microbial host
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of age unknown by opus_adjudicated with confidence 0.70. Assay shotgun_dna.
- host study.description · “human gut microbiome data”
- host run.scientific_name · “human gut metagenome”
- body site study.description · “human gut microbiome data”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMEA1963786 | age_at_collection_days | 13149.0 | R2 | 0.75 | external.gmrepo source | host_age: 36.0 |
| SAMEA2042839 | age_at_collection_days | 17532.0 | R2 | 0.75 | paper.supp.Table S1.xlsx[phenotype!age] | sample SAMEA2042839; age 48 |
| SAMEA1965033 | antibiotic_exposure | no | R2 | 0.75 | external.cmd source | antibiotics_current_use: No |
| SAMEA1963786 | bmi | 19.77 | R2 | 0.75 | external.cmd source | bmi: 19.7710718 |
| SAMEA2042839 | bmi | 24.00 | R2 | 0.75 | paper.supp.Table S1.xlsx[phenotype!BMI] | sample SAMEA2042839; BMI 24 |
| SAMEA1963786 | collection_date | 2008/2010 | R1 | 0.90 | biosample.attribute:collection_date | 2008/2010 |
| SAMEA1963786 | country | ES | R1 | 0.90 | sample.attr.geographic_location_country_and_or_sea_region | Spain |
| SAMEA1963786 | health_condition | ibd_unspecified | R2 | 0.75 | external.cmd source | disease: Inflammatory Bowel Disease;Crohn Disease |
| SAMEA2042839 | health_condition | ibd_unspecified | R2 | 0.75 | paper.supp.Table S1.xlsx[phenotype!disease] | sample SAMEA2042839; disease IBD; full_disease IBD |
| SAMEA1963786 | health_condition_detail | Inflammatory Bowel Disease;Crohn Disease | R2 | 0.75 | external.cmd source | disease: Inflammatory Bowel Disease;Crohn Disease |
| SAMEA2042839 | health_condition_detail | IBD | R2 | 0.75 | paper.supp.Table S1.xlsx[phenotype!full_disease] | sample SAMEA2042839; full_disease IBD |
| SAMEA1963786 | latitude | 40.4166 | R1 | 0.90 | biosample.attribute:geographic_location_latitude+geographic_location_longitude | 40.41663279 -3.703765869 |
| SAMEA1963786 | location_region | Madrid | R1 | 0.60 | biosample.attribute:geographic_location_latitude+geographic_location_longitude | 40.41663279 -3.703765869 |
| SAMEA1963786 | longitude | -3.7038 | R1 | 0.90 | biosample.attribute:geographic_location_latitude+geographic_location_longitude | 40.41663279 -3.703765869 |
| SAMEA1963786 | sex | female | R2 | 0.75 | external.cmd source | sex: Female |
| SAMEA1963786 | subject_id | CD6 | R1 | 0.70 | sample.name_rule:alias | CD6 |
| SAMEA1963786 | timepoint_label | 4 | R1 | 0.70 | sample.name_rule:alias | V1.CD6-4 |
Sequencing
1,704 runs over 396 samples · mean 0.85 Gbp per run (median 0.23 Gbp, total 1,455.11 Gbp; 1,704 runs with a base count) · layout PAIRED 852, SINGLE 852 · platform ILLUMINA 1,704 · models Illumina Genome Analyzer IIx (1,310), Illumina Genome Analyzer II (264), Illumina HiSeq 2000 (130) · 21% of runs with a Sandpiper profile · first public 2014-05-15
Authors (141)
Nielsen HB first · Almeida M · Juncker AS · Rasmussen S · Li J · Sunagawa S · Plichta DR · Gautier L · Pedersen AG · Le Chatelier E · Pelletier E · Bonde I · Nielsen T · Manichanh C · Arumugam M · Batto JM · Quintanilha Dos Santos MB · Blom N · Borruel N · Burgdorf KS · Boumezbeur F · Casellas F · Doré J · Dworzynski P · Guarner F · Hansen T · Hildebrand F · Kaas RS · Kennedy S · Kristiansen K · Kultima JR · Léonard P · Levenez F · Lund O · Moumen B · Le Paslier D · Pons N · Pedersen O · Prifti E · Qin J · Raes J · Sørensen S · Tap J · Tims S · Ussery DW · Yamada T · MetaHIT Consortium · Renault P · Sicheritz-Ponten T · Bork P · Wang J · Brunak S · Ehrlich SD · Tarracchini C first · Fontana F · Mancabelli L · Lugli GA · Alessandri G · Turroni F · Ventura M · Milani C last · Ormaasen I first · Rudi K · Diep DB · Snipen L last · Levy S · Arp G · Zhong A · Ndjite GM · Weiss A · Braccia D · Jenkins C · Grant MR · Abeysinghe S · Yang Y · Jermain MD · Wu CH · Ma B · De Biase R · Bocchio F · Viappiani A · De Conto F · Nouvenne A · Ticinesi A · Bussolati O · Meschi T · Cecchi R · van Sinderen D · Jacoby C first · Scorza K · Ecker L · Nol Bernardino P · Little AS · McMillin M · Ramaswamy R · Sundararajan A · Sidebottom AM · Lin H · Dufault-Thompson K · Hall B · Jiang X · Light SH last · Huang L first · Tan H · Weng S · Liu Y · Song L · Cheng S · Lin Z · Chen J · Tan F · Huang J · Cai L · Chai J · Zhong C · Shi Y · Zhang W · Zhang H · Huang C last · Maziers N first · Plaza Oñate F · Fromentin S · Thirion F · Torrejon A · Robles-Alonso V · Varela E · Derrien M · Veiga P · Oozeer R · Lombard V · Terrapon N · Henrissat B · Zhai J first · Li Y · Liu J · Su X · Cui R · Zheng D · Sun Y · Yu J · Dai C last
Downloads
PRJEB1220.csv.gz (13.0 KB) · parquet (89.1 KB) — all 396 samples, every field with route and confidence · PRJEB1220_determinations.csv.gz (48.3 KB) — 4,370 evidence rows