Gut microbiome/mycobiome in ACVD vs controls, China
385 stool samples from adults and elderly individuals in China, comparing atherosclerotic cardiovascular disease patients (214) to healthy controls (171) in a case-control study of gut bacterial and fungal communities. machine-written summary
385 samples · 385 runs · CN · Adult · 2017 · 5.39 Gbp / sample · cohort Cholesterol Metabolism by Uncultured Human Gut Bac
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 770 sample values (collection date, country) |
| ○ Abstract / description | read; no usable statement |
| ✓ Full text | 385 sample values (subject id) · PMC10291474, PMC10782949, PMC11170972, PMC11705818, PMC5635030, PMC7465921, PMC7913240, PMC9839529 |
| ✓ Supplementary tables | 1,626 sample values (age, bmi, health condition, health condition detail, sex) |
| ✓ External resources | 599 sample values (antibiotic exposure, health condition) · from curatedMetagenomicData 3 (cMD 3) |
| – User contribution | nothing uploaded yet |
| – Human verified | not yet checked by a person · I checked this project — verify it |
age: supplementary table and Meta2DB disagree for 1 sample (e.g. 18993 vs 11688.0) — withheld.
The sources disagree on 1 sample. 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 (1)
| sample | field | value | other value | handling |
|---|---|---|---|---|
| SAMEA104142374 | age | 18993 (supplementary table) | 11688.0 (Meta2DB) | withheld: neither value published |
Genera, mean relative abundance over 347 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 | 385 | 100% | ||||
| country | 385 | 100% | 385 | |||
| health_condition | 385 | 100% | 385 | |||
| subject_id | 385 | 100% | 385 | |||
| antibiotic_exposure | 385 | 100% | 385 | |||
| collection_date | 385 | 100% | 385 | |||
| health_condition_detail | 385 | 100% | 385 | |||
| sex | 380 | 99% | 380 | |||
| age_at_collection_days | 377 | 98% | 377 | |||
| bmi | 313 | 81% | 313 |
- The gut microbiome in atherosclerotic cardiovascular disease. 2017 PMID 29018189 PMC5635030 own_data
- Assembling Reads Improves Taxonomic Classification of Species. 2020 PMID 32824429 PMC7465921 own_data
- Information Theoretic Metagenome Assembly Allows the Discovery of Disease Biomarkers in Human Microbiome. 2021 PMID 33540903 PMC7913240 own_data
- Two distinct gut microbial pathways contribute to meta-organismal production of phenylacetylglutamine with links to cardiovascular disease. 2023 PMID 36549300 PMC9839529 own_data
- A consortium of three-bacteria isolated from human feces inhibits formation of atherosclerotic deposits and lowers lipid levels in a mouse model. 2023 PMID 37378328 PMC10291474 own_data
25 more
- Structural changes in the gut virome of patients with atherosclerotic cardiovascular disease. 2024 PMID 38051048 PMC10782949
- Isolation of potentially novel species expands the genomic and functional diversity of Lachnospiraceae. 2024 PMID 38882499 PMC11170972
- Gut mycobiome alterations and network interactions with the bacteriome in patients with atherosclerotic cardiovascular disease. 2025 PMID 39660898 PMC11705818
- Diagnostic Potential of Shallow Depth Gut Metagenomics Sequencing for Atherosclerotic Cardiovascular Disease Risk Stratification 2023
- Cholesterol Metabolism by Uncultured Human Gut Bacteria Influences Host Cholesterol Level. 2020 PMID 32544460 PMC7435688
- MetaGeneBank: a standardized database to study deep sequenced metagenomic data from human fecal specimen. 2021 PMID 34592929 PMC8485520
- Integrated metagenomics identifies a crucial role for trimethylamine-producing Lachnoclostridium in promoting atherosclerosis. 2022 PMID 35273169 PMC8913745
- Identification and Characterization of Major Bile Acid 7α-Dehydroxylating Bacteria in the Human Gut. 2022 PMID 35736002 PMC9426597
- Genome-scale metabolic modelling of the human gut microbiome reveals changes in the glyoxylate and dicarboxylate metabolism in metabolic disorders. 2022 PMID 35754734 PMC9213702
- Landscape of the gut archaeome in association with geography, ethnicity, urbanization, and diet in the Chinese population. 2022 PMID 36100953 PMC9469561
- Faecal microbiome-based machine learning for multi-class disease diagnosis. 2022 PMID 36357393 PMC9649010
- 2 Hydroxybutyric Acid-Producing Bacteria in Gut Microbiome and Fusobacterium nucleatum Regulates 2 Hydroxybutyric Acid Level In Vivo. 2023 PMID 36984891 PMC10059959
- Toward an improved definition of a healthy microbiome for healthy aging. 2022 PMID 37118093 PMC10154212
- Meta-analysis reveals obesity associated gut microbial alteration patterns and reproducible contributors of functional shift. 2024 PMID 38265338 PMC10810176
- Christensenella strain resources, genomic/metabolomic profiling, and association with host at species level. 2024 PMID 38722028 PMC11085954
- Genomic and functional diversity of the human-derived isolates of <i>Faecalibacterium</i>. 2024 PMID 38873165 PMC11169845
- An expanded database and analytical toolkit for identifying bacterial virulence factors and their associations with chronic diseases. 2024 PMID 39278950 PMC11402979
- Discovery of robust and highly specific microbiome signatures of non-alcoholic fatty liver disease. 2025 PMID 39810263 PMC11730835
- γBMGC: A Comprehensive and Accurate Database for Screening TMAO-Associated Cardiovascular Diseases. 2025 PMID 40005591 PMC11857547
- Microbiota-driven antitumour immunity mediated by dendritic cell migration. 2025 PMID 40659786 PMC12390848
- Chinese soy-based microbiome and associated microbial risks: a metagenomic investigation. 2025 PMID 40681522 PMC12274573
- Multi-omics integration reveals functional signatures of gut microbiome in atherosclerosis. 2025 PMID 40785047 PMC12341049
- <i>Christensenella intestinihominis</i> MNO-863 improve obesity and related metabolic disorders via SCFAs-induced GLP-1 hormone secretion. 2025 PMID 41356823 PMC12677068
- gutMSNP: a comprehensive database for human gut microbial single-nucleotide polymorphisms. 2026 PMID 41359024 PMC12807719
- Streptococcus species abundance in the gut is linked to subclinical coronary atherosclerosis in 8973 participants from the SCAPIS cohort 2022
Archive description
The gut microbiota has been linked to cardiovascular diseases, most notably through the production of trimethylamine and its hepatic conversion to the proatherogenic metabolite, trimethylamine-N-oxide. However, the composition and functional capacity of the gut microbiome in relation to cardiovascular diseases have not been systematically examined. Here we perform a metagenome-wide association study on stools from 218 individuals with atherosclerotic cardiovascular disease (ACVD) and 187 healthy controls. The ACVD gut microbiome deviates from the healthy status by increased abundance of Enterobacteriaceae and Streptococcus spp. and, functionally, in the potential for metabolism or transport of several molecules important for cardiovascular health. We further identify common themes by comparison with gut microbiome data associated with other cardiometabolic diseases (obesity and type 2 diabetes), liver cirrhosis, and an autoimmune disease, rheumatoid arthritis. Our data represent a comprehensive resource for further investigations on the role of the gut microbiome in promoting or preventing ACVD as well as other related diseases.
How this project entered the registry
Classified as human gut / stool / blood / tissue / internal fluids shotgun DNA metagenome of adult by deterministic_prior with confidence 0.90. Assay shotgun_dna.
- host external_curation.infant_catalog · “infant triage reason_code age_adult_only”
- body site study.title · “study (MWAS) on stools from 218 individuals”
- body site study.description · “The gut microbiota has been”
- body site study.description · “type 2 diabetes), liver cirrhosis, and an”
- life stage external_curation.infant_catalog · “infant triage reason_code age_adult_only”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMEA104142075 | age_at_collection_days | 39082 | R2 | 0.85 | paper.supp.spectrum.01050-23-s0001.xlsx[S.Table1!Age] | 107 |
| SAMEA104142072 | antibiotic_exposure | no | R2 | 0.75 | external.cmd source | antibiotics_current_use: No |
| SAMEA104142072 | bmi | 25.1 | R2 | 0.85 | paper.supp.spectrum.01050-23-s0001.xlsx[S.Table1!BMI] | 25.1 |
| SAMEA104142072 | collection_date | 2012 | R1 | 0.90 | biosample.attribute:collection_date | 2012 |
| SAMEA104142072 | country | CN | R1 | 0.90 | sample.attr.geographic_location_country_and_or_sea | China |
| SAMEA104142072 | health_condition | healthy_control | R2 | 0.80 | paper.supp.spectrum.01050-23-s0001.xlsx[S.Table1!group] | HC |
| SAMEA104142079 | health_condition | cardiometabolic_other | R2 | 0.75 | external.cmd source | disease: Atherosclerosis |
| SAMEA104142072 | health_condition_detail | HC | R2 | 0.85 | paper.supp.spectrum.01050-23-s0001.xlsx[S.Table1!group] | HC |
| SAMEA104142072 | sex | female | R2 | 0.85 | paper.supp.spectrum.01050-23-s0001.xlsx[S.Table1!Gender] | female |
| SAMEA104142072 | subject_id | SAMEA104142072 | R3 | 0.70 | design.one_sample_per_subject:fulltext | we performed metagenomic shotgun sequencing on a total of 405 fecal samples from 218 individuals |
Sequencing
385 runs over 385 samples · mean 5.21 Gbp per run (median 5.39 Gbp, total 2,007.43 Gbp; 385 runs with a base count) · layout PAIRED 385 · platform ILLUMINA 385 · models Illumina HiSeq 2000 (385) · 90% of runs with a Sandpiper profile · first public 2017-12-14
Authors (79)
Ormaasen I first · Rudi K · Diep DB · Snipen L last · Argentini C first · Lugli GA · Tarracchini C · Fontana F · Mancabelli L · Viappiani A · Anzalone R · Angelini L · Alessandri G · Longhi G · Bianchi MG · Taurino G · Bussolati O · Milani C · van Sinderen D · Turroni F · Ventura M last · Li W first · Lin X · Liang H · Wu Z · Wang M · Sun J · Li X · He W · Gao X · Hu T · Xiao L · Zou Y last · Su G first · Huang P · Liu D · Xing G · Guo R · Li S · Fan S · Cheng L · Yan Q · Yang W last · Nooij S first · Plomp N · Sanders IMJG · Schout L · van der Meulen AE · Terveer EM · Norman JM · Karcher N · Larralde MF · Vossen RHAM · Kloet SL · Faber KN · Harmsen HJM · Zeller GF · Kuijper EJ · Smits WK · Ducarmon QR last · Yang G first · Tao T · Yu G · Zhang H · Wu Y · Sun S · Guo K · Jia S last · Qian K first · Du M · Tan S · Ding M · Song M · Lu M · Qi C · Zhang X last · Sing JC first · Whitley O · Davis S last
Downloads
PRJEB21528.csv.gz (13.1 KB) · parquet (89.5 KB) — all 385 samples, every field with route and confidence · PRJEB21528_determinations.csv.gz (28.2 KB) — 3,380 evidence rows