Gut microbiome and diet in IBS patients and controls
Cross-sectional shotgun metagenomic study of 144 adult samples examining associations between diet (4-day food diary) and gut microbiota in individuals with irritable bowel syndrome compared to healthy controls. machine-written summary
144 samples · 397 runs · SE · Age unknown · 2021 · 1.74 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ○ Sequence archive | records read; no usable sample values |
| ✓ Abstract / description | 144 sample values (health condition detail) |
| ✓ Full text | 288 sample values (country, location site) · PMC8004395 |
| ○ Supplementary tables | files read; no table could be matched to the samples |
| – External resources | not covered by the external resources we ingest |
| – User contribution | nothing uploaded yet · share metadata |
| – Human verified | not yet checked by a person · I checked this project — verify it |
No Sandpiper profile for this project's samples yet.
| field | samples | coverage | R1 | R2 | R3 | R4 |
|---|---|---|---|---|---|---|
| age_category | 144 | 100% | ||||
| country | 144 | 100% | 144 | |||
| health_condition | 0 | 0% | ||||
| subject_id | 0 | 0% | ||||
| detailed_location | 144 | 100% | ||||
| health_condition_detail | 144 | 100% | 144 | |||
| location_site | 144 | 100% | 144 |
- Diet and gut microbiome interactions of relevance for symptoms in irritable bowel syndrome. 2021 PMID 33771219 PMC8004395 own_data
Archive description
While several studies have documented associations between dietary habits and microbiota composition and function in healthy individuals, no study explored these associations in patients with irritable bowel syndrome (IBS), and especially with symptoms. Here, we used a novel approach that combined data from a 4-day food diary, integrated into a food tree, together with gut microbiota (shotgun metagenomic) for individuals with IBS (N = 149) and healthy controls (N = 52). Paired microbiota and food-based trees allowed us to detect new associations between subspecies and diet. Combining co-inertia analysis and linear regression models, exhaled gas levels and symptom severity could be predicted from metagenomic and dietary data. We showed that individuals with severe IBS are characterized by a higher intake of poorer-quality food items during their main meals. Our analysis suggested that covariations between gut microbiota at subspecies level and diet could be explained with IBS symptom severity, exhaled gas, glycan metabolism, and meat/plant ratio. We provided evidence that IBS severity is associated with altered gut microbiota hydrogen function in correlation with microbiota enzymes involved in animal carbohydrate metabolism. Our study provides an unprecedented resolution of diet-microbiota-symptom interactions and ultimately guides new interventional studies that aim to identify gut microbiome-based nutritional recommendations for the management of gastrointestinal symptoms.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of age unknown by sonnet_x2 with confidence 0.80. Assay shotgun_dna.
- host run.scientific_name · “human gut metagenome”
- body site run.scientific_name · “human gut metagenome”
- body site study.description · “gut microbiota (shotgun metagenomic)”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMEA9259473 | country | SE | R3 | 0.70 | paper.fulltext.methods | Sahlgrenska University Hospital, Sweden |
| SAMEA9259473 | health_condition_detail | mixed_case_control: IBS patients vs healthy controls | R4 | 0.50 | study.description | individuals with IBS (N = 149) and healthy controls (N = 52) |
| SAMEA9259473 | location_site | Sahlgrenska University Hospital | R3 | 0.70 | paper.fulltext.methods | secondary/tertiary care outpatient clinic (Sahlgrenska University Hospital, Sweden) |
Sequencing
397 runs over 144 samples · mean 0.70 Gbp per run (median 0.59 Gbp, total 276.84 Gbp; 397 runs with a base count) · layout SINGLE 397 · platform ABI_SOLID 397 · models AB 5500xl Genetic Analyzer (397) · 0% of runs with a Sandpiper profile · first public 2021-06-23
Authors (10)
Tap J first · Störsrud S · Le Nevé B · Cotillard A · Pons N · Doré J · Öhman L · Törnblom H · Derrien M · Simrén M last
Help complete this project
2 of the 4 core fields are below 50% coverage: health_condition, subject_id. Share metadata
Downloads
PRJEB34992.csv.gz (4.3 KB) · parquet (74.8 KB) — all 144 samples, every field with route and confidence · PRJEB34992_determinations.csv.gz (2.2 KB) — 432 evidence rows