Home › Studies › PRJEB46098
PRJEB46098 ERP130293

Gut Metagenome in Ischaemic Heart Disease, Europe

Microbiome and Metabolome in Ischaemic Heart Disease

15 gut metagenome samples from middle-aged European adults across healthy, dysmetabolic (obesity/type 2 diabetes), and ischaemic heart disease stages; cross-sectional design. machine-written summary

15 samples · 69 runs · Adult · 2022 · 2.90 Gbp / sample · cohort Evidence of a causal and modifiable relationship b

Sources
○Sequence archive○Abstract / description✓Full text 30○Supplementary tables–External resources–User contribution–Human verified

Checked this project's papers and archive records yourself? Mark it human-verified.

what each source gave
○ Sequence archiverecords read; no usable sample values
○ Abstract / descriptionread; no usable statement
✓ Full text30 sample values (antibiotic exposure, collection date) · PMC10511707, PMC11620793, PMC12363224, PMC12795280, PMC8863577
○ Supplementary tablesfiles read; no table could be matched to the samples
– External resourcesnot covered by the external resources we ingest
– User contributionnothing uploaded yet
– Human verifiednot yet checked by a person · I checked this project — verify it
Samples at a glance
Age
adult15
Body site
primary15
Sequencing depth per sample · this project all projects
all projects, 0–0.03 Gbp: 25,080 samples (4 %)all projects, 0.03–0.1 Gbp: 17,066 samples (3 %)all projects, 0.1–0.3 Gbp: 29,179 samples (5 %)all projects, 0.3–1 Gbp: 47,044 samples (8 %)all projects, 1–3 Gbp: 124,983 samples (22 %)this project, 1–3 Gbp: 9 samplesall projects, 3–10 Gbp: 253,728 samples (44 %)this project, 3–10 Gbp: 6 samplesall projects, 10–30 Gbp: 72,533 samples (13 %)all projects, 30–100 Gbp: 3,024 samples (1 %)all projects, 100–300 Gbp: 106 samples (0 %)all projects, ≥ 300 Gbp: 9 samples (0 %)project median 2.90 Gbp per sample0130Gbp
Community composition

No Sandpiper profile for this project's samples yet.

Field coverage
fieldsamplescoverageR1R2R3R4
age_category15 100%
country0 0%
health_condition0 0%
subject_id0 0%
antibiotic_exposure15 100%15
collection_date15 100%15
Papers (6)
  • Microbiome and metabolome features of the cardiometabolic disease spectrum. 2022 PMID 35177860 PMC8863577 own_data
  • Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine N-oxide. 2023 PMID 37730687 PMC10511707 unsure
  • Strain-specific gut microbial signatures in type 2 diabetes identified in a cross-cohort analysis of 8,117 metagenomes. 2024 PMID 38918632 PMC11620793 unsure
  • Metagenomic estimation of absolute bacterial biomass in the mammalian gut through host-derived read normalization. 2025 PMID 40742180 PMC12363224 unsure
  • Prominent mediatory role of gut microbiome in the effect of lifestyle on host metabolic phenotypes. 2025 PMID 41408736 PMC12795280 unsure
1 more
  • Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamineN-oxide with implications for heart and kidney disorders 2022
Details
Archive description

Numerous epidemiological studies have combined gut metagenomics with metabolomics to explore pathophysiology and pathogenesis of human non-communicable diseases. However, scant attention was paid to major confounders of study outcomes, such as common pre-morbid conditions or polypharmacy. In the context of ischaemic heart disease (IHD), a leading cause of mortality in the Western world, here we used a unique study design to recapitulate disease initiation, escalation, worsening and response to treatment over time, mimicking a longitudinal study otherwise difficult given the protacted IHD pathogenesis. For this, we recruited 1,241 middle-aged Europeans including healthy controls, controls with dysmetabolic pre-morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis, and finally IHD cases at three different stages acute coronary syndrome, chronic IHD and heart failure. We characterized their phenome, gut metagenome and metabolome. We show that about 75% of microbiome and metabolome features that distinguish IHD cases from healthy controls after adjustment for effects of medication and lifestyle are present already in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome begin long before clinical onset of IHD. In addition, with the applied adjustments for polypharmacy and premorbidites we developed a novel classification approach, which reveals multiple microbiome and metabolome pathophysiological signatures related to prodromal dysmetabolism, specific to IHD and disease subgroups or related to escalation and de-escalation of IHD and its subtypes.

How this project entered the registry

Classified as human gut / stool 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.description · “studies have combined gut metagenomics with metabolomics”
  • body site external_curation.infant_catalog · “body_site_call gut”
  • life stage external_curation.infant_catalog · “infant triage reason_code age_adult_only”
Evidence examples (one per field × route)
samplefieldvaluerouteconf.sourcequote
SAMEA13959289antibiotic_exposurenoR30.70paper.fulltext.methodsantibiotic use in the 3 months before inclusion
SAMEA13959289collection_date2013/2015R30.70paper.fulltext.methodsrecruited from Denmark, France and Germany between 2013 and 2015
Sequencing

69 runs over 15 samples · mean 0.66 Gbp per run (median 0.64 Gbp, total 45.71 Gbp; 69 runs with a base count) · layout SINGLE 69 · platform ION_TORRENT 69 · models Ion Torrent Proton (69) · 0% of runs with a Sandpiper profile · first public 2022-04-12

Authors (120)

Fromentin S first · Forslund SK · Chechi K · Aron-Wisnewsky J · Chakaroun R · Nielsen T · Tremaroli V · Ji B · Prifti E · Myridakis A · Chilloux J · Andrikopoulos P · Fan Y · Olanipekun MT · Alves R · Adiouch S · Bar N · Talmor-Barkan Y · Belda E · Caesar R · Coelho LP · Falony G · Fellahi S · Galan P · Galleron N · Helft G · Hoyles L · Isnard R · Le Chatelier E · Julienne H · Olsson L · Pedersen HK · Pons N · Quinquis B · Rouault C · Roume H · Salem JE · Schmidt TSB · Vieira-Silva S · Li P · Zimmermann-Kogadeeva M · Lewinter C · Søndertoft NB · Hansen TH · Gauguier D · Gøtze JP · Køber L · Kornowski R · Vestergaard H · Hansen T · Zucker JD · Hercberg S · Letunic I · Bäckhed F · Oppert JM · Nielsen J · Raes J · Bork P · Stumvoll M · Segal E · Clément K · Dumas ME · Ehrlich SD · Pedersen O last · Mei Z first · Wang F · Bhosle A · Dong D · Mehta R · Ghazi A · Zhang Y · Liu Y · Rinott E · Ma S · Rimm EB · Daviglus M · Willett WC · Knight R · Hu FB · Qi Q · Chan AT · Burk RD · Stampfer MJ · Shai I · Kaplan RC · Huttenhower C · Wang DD last · Tang G first · Carr AV · Perez C · Ramos Sarmiento K · Levy L · Lampe JW · Diener C · Gibbons SM last · Adriouch S first · Swartz TD · Forslund S · Poitou C · Bel-Lassen P · Le Roy T · Puig-Castellví F · Dionicio IC · Froguel P · Holmes B · Alili R · Andreelli F · Soula H · Dao MC · Salem J · Kieswich J · Puig-Castellvi F · Chevalier M · Pedro Coelho L · MetaCardis Consortium · Zucker J · Oppert J · Blüher M · Yaqoob MM · Dumas M last

Downloads

PRJEB46098.csv.gz (1.2 KB) · parquet (69.0 KB) — all 15 samples, every field with route and confidence · PRJEB46098_determinations.csv.gz (583 B) — 30 evidence rows

Samples (15 · every field this project has values for · hover a cell for its source)
Loading the sample table…