Personalized diet vs standard diet in T2D adults, India
30 samples from adults in India with type 2 diabetes and hyperlipidaemia, comparing microbiome-based personalized nutrition versus standard diabetic dietary guidance in a prospective, randomized, controlled intervention study. machine-written summary
30 samples · 30 runs · IN · Age unknown · 2023 · 0.12 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 180 sample values (collection date, country, latitude, longitude, subject id, timepoint) |
| ○ Abstract / description | read; no usable statement |
| ✓ Full text | 120 sample values (health condition, health condition detail, location locality, location site) · PMC11214429 |
| ○ 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 |
intervention — arms not resolved
Controlled / prescribed diet or feeding regimen design randomized_controlled_trial · population type2_diabetes · Microbiome-based personalized diet vs diabetic nutritional guidance, 3 months
“microbiome-based targeted personalized diet” — abstract:38948211 (study level; per-sample arms are in the intervention column below)
longitudinal
15 of 15 people sampled more than once (30 samples; median 2, up to 2 per person) · follow-up median 3 mo (max 3 mo) · median interval between samples 3 mo (time from visit codes mapped to the stated schedule). Schedule stated by the source: “Stool collected PRE and POST a 90-day intervention, with clinic visits on Day 1, 30, 60, 90”; stated follow-up 3 mo.
Each row is one person (15 shown); dots are samples at days since that person's first sample.
No Sandpiper profile for this project's samples yet.
| field | samples | coverage | R1 | R2 | R3 | R4 |
|---|---|---|---|---|---|---|
| age_category | 30 | 100% | ||||
| country | 30 | 100% | 30 | |||
| health_condition | 30 | 100% | 30 | |||
| subject_id | 30 | 100% | 30 | |||
| collection_date | 30 | 100% | 30 | |||
| detailed_location | 30 | 100% | ||||
| health_condition_detail | 30 | 100% | 30 | |||
| latitude | 30 | 100% | 30 | |||
| location_locality | 30 | 100% | 30 | |||
| location_site | 30 | 100% | 30 | |||
| longitude | 30 | 100% | 30 | |||
| timepoint_label | 30 | 100% | 30 |
- Microbiota based personalized nutrition improves hyperglycaemia and hypertension parameters and reduces inflammation: a prospective, open label, controlled, randomized, comparative, proof of concept study. 2024 PMID 38948211 PMC11214429 own_data
Archive description
Recent studies suggest that gut microbiota composition, abundance and diversity can influence many chronic diseases such as type 2 diabetes. Modulating gut microbiota through targeted nutrition can provide beneficial effects leading to the concept of personalized nutrition for health improvement. In this prospective clinical trial we evaluated the impact of a microbiome-based targeted personalized diet on hyperglycaemic and hyperlipidaemic individuals.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of age unknown by opus_adjudicated with confidence 0.70. Assay shotgun_dna.
- host run.host_tax_id · “9606”
- body site run.scientific_name · “gut metagenome”
- body site study.description · “Modulating gut microbiota through targeted nutrition”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMN38481096 | collection_date | 2022-05-14/2022-06-15 | R1 | 0.90 | biosample.attribute:collection_date | 2022-05-14/2022-06-15 |
| SAMN38481096 | country | IN | R1 | 0.90 | sample.attr.geo_loc_name | India |
| SAMN38481096 | health_condition | type2_diabetes | R3 | 0.70 | paper.fulltext.abstract | participants with type 2 diabetes and hyperlipidaemia were recruited |
| SAMN38481096 | health_condition_detail | 30 participants with type 2 diabetes and hyperlipidaemia | R3 | 0.70 | paper.fulltext.abstract | participants with type 2 diabetes and hyperlipidaemia were recruited |
| SAMN38481096 | latitude | 20.5937 | R1 | 0.90 | biosample.attribute:lat_lon | 20.5937 N 78.9629 E |
| SAMN38481096 | location_locality | Bhopal | R3 | 0.70 | paper.fulltext.methods | at Samadhan Pathology and Diagnostics, Bhopal |
| SAMN38481096 | location_site | Charak Hospital, Bhopal, India | R3 | 0.70 | paper.fulltext.methods | Charak Hospital- Reg:ECR/152/Inst/MP/2021, Bhopal, India |
| SAMN38481096 | longitude | 78.9629 | R1 | 0.90 | biosample.attribute:lat_lon | 20.5937 N 78.9629 E |
| SAMN38481096 | subject_id | 1 | R1 | 0.70 | sample.name_rule:TITLE | PRE_1 |
| SAMN38481096 | timepoint_label | PRE | R1 | 0.70 | sample.name_rule:TITLE | PRE_1 |
Sequencing
30 runs over 30 samples · mean 0.17 Gbp per run (median 0.12 Gbp, total 4.97 Gbp; 30 runs with a base count) · layout SINGLE 30 · platform OXFORD_NANOPORE 30 · models MinION (30) · 0% of runs with a Sandpiper profile · first public 2023-12-31
Authors (7)
Kallapura G first · Prakash AS · Sankaran K · Manjappa P · Chaudhary P · Ambhore S · Dhar D last
Downloads
PRJNA1046298.csv.gz (1.8 KB) · parquet (71.8 KB) — all 30 samples, every field with route and confidence · PRJNA1046298_determinations.csv.gz (2.9 KB) — 300 evidence rows