Personalized nutrition and glycemic response diet intervention
969 gut metagenome samples from adults (mostly healthy controls), part of a dietary intervention study predicting personalized postprandial glycemic responses to meals. machine-written summary
969 samples · 1,523 runs · IL · Adult · 2015 · 2.74 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 | read; no usable statement |
| ○ Full text | read; no usable statement or table · PMC10122048, PMC10182631, PMC10810176, PMC11239293, PMC11302968, PMC11423519, PMC12365913, PMC13377033, PMC5807925, PMC6961876, PMC7664509, PMC8288446, PMC8515199, PMC8947124, PMC9426582, PMC9685977 |
| ✓ Supplementary tables | 477 sample values (age) |
| ✓ External resources | 5,370 sample values (antibiotic exposure, bmi, country, health condition, health condition detail, sex) · from curatedMetagenomicData 3 (cMD 3) |
| – User contribution | nothing uploaded yet |
| – Human verified | not yet checked by a person · I checked this project — verify it |
intervention — arms not resolved
Controlled / prescribed diet or feeding regimen design randomized_controlled_trial · Personalized diet intervention based on predicted glycemic response algorithm
“blinded randomized controlled dietary intervention” — abstract:26590418 (study level; per-sample arms are in the intervention column below)
longitudinal — not resolved
Schedule stated by the source: “continuously monitored week-long glucose levels”; stated follow-up 7 d.
Genera, mean relative abundance over 893 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 | 969 | 100% | ||||
| country | 900 | 93% | 900 | |||
| health_condition | 900 | 93% | 900 | |||
| subject_id | 0 | 0% | ||||
| antibiotic_exposure | 900 | 93% | 900 | |||
| health_condition_detail | 900 | 93% | 900 | |||
| sex | 900 | 93% | 900 | |||
| bmi | 870 | 90% | 870 | |||
| age_at_collection_days | 477 | 49% | 477 |
- Personalized Nutrition by Prediction of Glycemic Responses. 2015 PMID 26590418 own_data
- Detection of stable community structures within gut microbiota co-occurrence networks from different human populations. 2018 PMID 29441232 PMC5807925 own_data
- Large-scale association analyses identify host factors influencing human gut microbiome composition. 2021 PMID 33462485 PMC8515199 own_data
- Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease. 2022 PMID 35177859 PMC12365913 own_data
- An atlas of robust microbiome associations with phenotypic traits based on large-scale cohorts from two continents. 2022 PMID 35324954 PMC8947124 own_data
12 more
- Assessing the relationship between gut microbiota and irritable bowel syndrome: a two-sample Mendelian randomization analysis. 2023 PMID 37173627 PMC10182631
- Toxigenic Clostridium perfringens Isolated from At-Risk Paediatric Inflammatory Bowel Disease Patients. 2024 PMID 38267224 PMC11302968
- Biogeographic study of human gut-associated crAssphage suggests impacts from industrialization and recent expansion. 2020 PMID 31940321 PMC6961876
- Gut microbiome stability and dynamics in healthy donors and patients with non-gastrointestinal cancers. 2021 PMID 33175106 PMC7664509
- Dispersal strategies shape persistence and evolution of human gut bacteria. 2021 PMID 34111423 PMC8288446
- Phage Cocktails Constrain the Growth of Enterococcus. 2022 PMID 35762793 PMC9426582
- Machine learning for data integration in human gut microbiome. 2022 PMID 36419034 PMC9685977
- Combing fecal microbial community data to identify consistent obesity-specific microbial signatures and shared metabolic pathways. 2023 PMID 37096041 PMC10122048
- Meta-analysis reveals obesity associated gut microbial alteration patterns and reproducible contributors of functional shift. 2024 PMID 38265338 PMC10810176
- Discovery of disease-adapted bacterial lineages in inflammatory bowel diseases. 2024 PMID 38917808 PMC11239293
- A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies. 2024 PMID 39322959 PMC11423519
- CroCoDeEL: accurate control-free detection of cross-sample contamination in metagenomic data. 2026 PMID 42103726 PMC13377033
Archive description
Elevated postprandial blood glucose levels constitute a global epidemic and a major risk factor for prediabetes and type-II diabetes, but existing dietary methods for controlling them have limited efficacy. Here, we continuously monitored week-long glucose levels in a 800-person cohort, measured responses to 46,898 meals, and found high variability in the response to identical meals, suggesting that universal dietary recommendations may have limited utility. We devised a machine-learning algorithm that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in this cohort and showed that it accurately predicts personalized postprandial glycemic response to real-life meals. We validated these predictions in an independent 100-person cohort. Finally, a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postprandial responses and consistent alterations to gut microbiota configuration. Together, our results suggest that personalized diets may successfully modify elevated postprandial blood glucose and its metabolic consequences.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of adult by sonnet_x2 with confidence 0.65. Assay shotgun_dna.
- host run.scientific_name · “human gut metagenome”
- body site run.scientific_name · “human gut metagenome”
- life stage study.description · “800-person cohort”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMEA3646674 | age_at_collection_days | 24106.5 | R2 | 0.85 | paper.supp.KGMI_A_2304900_SM8867.zip::Table S1.xlsx[Israel!Age] | ERR1110297 | Age: 66 |
| SAMEA3646671 | antibiotic_exposure | no | R2 | 0.75 | external.cmd source | antibiotics_current_use: No |
| SAMEA3646672 | bmi | 29.8 | R2 | 0.75 | external.cmd source | bmi: 29.8 |
| SAMEA3646671 | country | IL | R2 | 0.75 | external.cmd source | country: Israel |
| SAMEA3646671 | health_condition | healthy_control | R2 | 0.75 | external.cmd source | disease: Healthy |
| SAMEA3646671 | health_condition_detail | Healthy | R2 | 0.75 | external.cmd source | disease: Healthy |
| SAMEA3646671 | sex | female | R2 | 0.75 | external.cmd source | sex: Female |
Sequencing
1,523 runs over 969 samples · mean 1.93 Gbp per run (median 1.62 Gbp, total 2,940.14 Gbp; 1,523 runs with a base count) · layout PAIRED 1,303, SINGLE 220 · platform ILLUMINA 1,523 · models NextSeq 500 (833), Illumina HiSeq 2500 (676), Illumina MiSeq (14) · 89% of runs with a Sandpiper profile · first public 2015-11-26
Authors (73)
Zeevi D first · Korem T · Zmora N · Israeli D · Rothschild D · Weinberger A · Ben-Yacov O · Lador D · Avnit-Sagi T · Lotan-Pompan M · Suez J · Mahdi JA · Matot E · Malka G · Kosower N · Rein M · Zilberman-Schapira G · Dohnalová L · Pevsner-Fischer M · Bikovsky R · Halpern Z · Elinav E · Segal E last · Liu B first · Ye D · Yang H · Song J · Sun X · He Z · Mao Y · Hao G last · Kuo J first · Uzunovic J · Jacobson A · Dourado M · Gierke S · Rajendram M · Keilberg D · Mar J · Stekol E · Curry J · Verstraete S · Lund J · Liang Y · Tamburini FB · Omattage NS · Masureel M · Rutherford ST · Hackos DH · Tan MW · Byrd AL · Keir ME · Skippington E · Storek KM last · Tarracchini C first · Lugli GA · Mancabelli L · van Sinderen D · Turroni F · Ventura M · Milani C last · Wirbel J first · Essex M · Forslund SK · Zeller G last · Goulet L first · Plaza Oñate F · Famechon A · Quinquis B · Belda E · Prifti E · Le Chatelier E · Gautreau G last
Downloads
PRJEB11532.csv.gz (26.1 KB) · parquet (107.5 KB) — all 969 samples, every field with route and confidence · PRJEB11532_determinations.csv.gz (59.1 KB) — 5,847 evidence rows