Peanut allergy gut microbiome case-control study
12 stool samples from adults in Berlin, Germany, comparing peanut-allergic versus non-allergic controls in a case-control design examining gut microbiota differences alongside immune and methylation profiling. machine-written summary
12 samples · 12 runs · DE · Mixed ages · 2022 · 8.83 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 108 sample values (collection date, country, health condition, health condition detail, latitude, location locality, location region, longitude) |
| ○ Abstract / description | read; no usable statement |
| ✓ Full text | 12 sample values (location site) · PMC9533219 |
| ○ 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 |
| – Human verified | not yet checked by a person · I checked this project — verify it |
Genera, mean relative abundance over 12 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 | 12 | 100% | ||||
| country | 12 | 100% | 12 | |||
| health_condition | 12 | 100% | 12 | |||
| subject_id | 12 | 100% | 12 | |||
| collection_date | 12 | 100% | 12 | |||
| detailed_location | 12 | 100% | ||||
| health_condition_detail | 12 | 100% | 12 | |||
| latitude | 12 | 100% | 12 | |||
| location_locality | 12 | 100% | 12 | |||
| location_region | 12 | 100% | 12 | |||
| location_site | 12 | 100% | 12 | |||
| longitude | 12 | 100% | 12 |
- An interdisciplinary approach to characterize peanut-allergic patients—First data from the FOOD@ consortium 2022 PMID 36225266 PMC9533219 own_data
Archive description
Background: Peanut allergy is a frequent cause of food allergy and potentially life-threatening.</p><p>Within this interdisciplinary research approach, we aim to unravel the complex mechanisms of peanut allergy. As a first step were applied in an exploratory manner the analysis of peanut allergic versus non-allergic controls.</p><p>Methods: Biosamples were studied regarding DNA methylation signatures, gut microbiome, adaptive and innate immune cell populations, soluble signaling molecules and allergen-reactive antibody specificities. We applied a scalable systems medicine computational workflow to the assembled data.</p><p>Results: We identified combined cellular and soluble biomarker signatures that stratify donors into peanut-allergic and non-allergic with high specificity. DNA methylation profiling revealed various genes of interest and stool microbiota differences in bacteria abundances. Conclusion: By extending our findings to a larger set of patients (e.g. children versus adults), we will establish predictors for food allergy and tolerance and translate these as e.g. indicators for interventional studies.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of mixed ages by sonnet_x2 with confidence 0.55. Assay shotgun_dna.
- host run.host_tax_id · “9606”
- body site run.scientific_name · “human gut metagenome”
- body site study.description · “stool microbiota differences in bacteria abundances”
- life stage study.description · “children versus adults”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMN30885127 | collection_date | 2020-06-14 | R1 | 0.90 | biosample.attribute:collection_date | 2020-06-14 |
| SAMN30885127 | country | DE | R1 | 0.90 | sample.attr.geo_loc_name | Germany: Berlin |
| SAMN30885127 | health_condition | allergy_or_atopy | R1 | 0.85 | biosample.attribute:description | allergic |
| SAMN30885127 | health_condition_detail | allergic | R1 | 0.85 | biosample.attribute:description | allergic |
| SAMN30885127 | latitude | 52.5261 | R1 | 0.90 | biosample.attribute:lat_lon | 52.526136 N 13.3745186 E |
| SAMN30885127 | location_locality | Berlin | R1 | 0.85 | biosample.attribute:geo_loc_name | Germany: Berlin |
| SAMN30885127 | location_region | Berlin | R1 | 0.60 | biosample.attribute:lat_lon | 52.526136 N 13.3745186 E |
| SAMN30885127 | location_site | Charité - Universitätsmedizin Berlin, Division of Allergy and Immunology | R3 | 0.70 | paper.fulltext.methods | Division of Allergy and Immunology, Department of Dermatology, Venereology and Allergy, Campus |
| SAMN30885127 | longitude | 13.3745 | R1 | 0.90 | biosample.attribute:lat_lon | 52.526136 N 13.3745186 E |
| SAMN30885127 | subject_id | A004 | R1 | 0.85 | biosample.attribute:source_material_id | A004 |
Sequencing
12 runs over 12 samples · mean 8.87 Gbp per run (median 8.83 Gbp, total 106.46 Gbp; 12 runs with a base count) · layout PAIRED 12 · platform ILLUMINA 12 · models Illumina NovaSeq 6000 (12) · 100% of runs with a Sandpiper profile · first public 2022-10-06
Authors (31)
Worm M first · Alexiou A · Höfer V · Birkner T · Jeanrenaud ACSN · Fauchère F · Pazur K · Steinert C · Arnau-Soler A · Banerjee P · Diefenbach A · Dobbertin-Welsch J · Dölle-Bierke S · Francuzik W · Ghauri A · Heller S · Kalb B · Löber U · Marenholz I · Markó L · Scheffel J · Potapenko O · Roll S · Lau S · Lee YA · Braun J · Thiel A · Babina M · Altrichter S · Forslund SK · Beyer K last
Downloads
PRJNA881055.csv.gz (1.4 KB) · parquet (71.4 KB) — all 12 samples, every field with route and confidence · PRJNA881055_determinations.csv.gz (1.8 KB) — 120 evidence rows