Gut microbiota and antidiabetic drug response in T2D, China
188 fecal samples from treatment-naive type 2 diabetes patients in China, from a randomized clinical trial comparing Acarbose versus Glipizide, examining gut microbiota and bile acid changes with treatment. machine-written summary
188 samples · 188 runs · CN · Adult · 2016 · 5.70 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 376 sample values (collection date, country) |
| ✓ Abstract / description | 188 sample values (health condition detail) |
| ✓ Full text | 376 sample values (health condition, location locality) · PMC11009399, PMC11170963, PMC11418011, PMC5702614, PMC7157763, PMC8262883, PMC9096808 |
| ✓ Supplementary tables | 1,034 sample values (age, bmi, intervention, sex, subject id, timepoint) |
| – 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
Non-antibiotic pharmaceutical given as the study intervention (metformin design randomized_controlled_trial · population type2_diabetes · Acarbose vs Glipizide (sulfonylurea) oral antidiabetic drugs in treatment-naive T2D patients
“randomized clinical trial on new onset untreated Type 2 Diabetes patients applied” — bioproject.description (study level; per-sample arms are in the intervention column below)
longitudinal
94 of 94 people sampled more than once (188 samples; median 2, up to 2 per person) · follow-up median 3 mo (max 3 mo) · median interval between samples 3 mo (time from timepoint labels). Schedule stated by the source: “Faecal samples collected at baseline (D0) and after 3 months of Acarbose/Glipizide treatment (D90)” (time origin: baseline); stated follow-up 3 mo.
Each row is one person (36 shown of 94); dots are samples at days since that person's first sample.
Genera, mean relative abundance over 167 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 | 188 | 100% | ||||
| country | 188 | 100% | 188 | |||
| health_condition | 188 | 100% | 188 | |||
| subject_id | 188 | 100% | 188 | |||
| age_at_collection_days | 188 | 100% | 188 | |||
| bmi | 188 | 100% | 188 | |||
| collection_date | 188 | 100% | 188 | |||
| detailed_location | 188 | 100% | ||||
| health_condition_detail | 188 | 100% | 188 | |||
| location_locality | 188 | 100% | 188 | |||
| sex | 188 | 100% | 188 | |||
| timepoint_label | 188 | 100% | 188 | |||
| intervention | 94 | 50% | 94 |
- Analyses of gut microbiota and plasma bile acids enable stratification of patients for antidiabetic treatment. 2017 PMID 29176714 PMC5702614 own_data
- Synergy between Cell Surface Glycosidases and Glycan-Binding Proteins Dictates the Utilization of Specific Beta(1,3)-Glucans by Human Gut Bacteroides. 2020 PMID 32265336 PMC7157763 unsure
- Human Gut Faecalibacterium prausnitzii Deploys a Highly Efficient Conserved System To Cross-Feed on β-Mannan-Derived Oligosaccharides. 2021 PMID 34061597 PMC8262883 unsure
- Diverse events have transferred genes for edible seaweed digestion from marine to human gut bacteria. 2022 PMID 35240043 PMC9096808 unsure
- Plasmids in the human gut reveal neutral dispersal and recombination that is overpowered by inflammatory diseases. 2024 PMID 38605009 PMC11009399 unsure
3 more
- Deciphering unique and shared interactions between the human gut microbiota and oral antidiabetic drugs. 2024 PMID 38882498 PMC11170963
- The molecular basis of cereal mixed-linkage β-glucan utilization by the human gut bacterium Segatella copri. 2024 PMID 39122003 PMC11418011
- Plasmid dispersal and recombination across human gut microbiomes is neutral, but overpowered by inflammatory diseases 2023
Archive description
Dysbosis of intestinal microbiota could contribute to the pathogenesis of Type 2 Diabetes. It is yet to be known whether intestinal flora could be related to differential responds to antidiabetic therapies. This study, herein for the first time, metagenomic sequenced fecal samples from a randomized clinical trial on new onset untreated Type 2 Diabetes patients applied two treatment arms, Acarbose and Glipizide (Sulfonylurea) and analyzed the differential responses of intestinal flora in different groups. Results showed substantial impact of Acarbose on gut microbiota community but minor of Glipizide. Enterotypes with similar baseline clinical characteristics, had significant different pharmacologic respond to Acarbose on insulin resistance, gut hormones, bile acids and cardiovascular risks, indicating that different pattern of intestinal microbiota component could determine different responses of Type 2 Diabetes to antidiabetic pharmacological therapies.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of adult by sonnet_x2 with confidence 0.75. Assay shotgun_dna.
- host run.scientific_name · “human gut metagenome”
- body site study.description · “metagenomic sequenced fecal samples”
- life stage study.description · “new onset untreated Type 2 Diabetes patients”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMEA3708715 | age_at_collection_days | 17291.0 | R2 | 0.85 | paper.supp.IMT2-3-e179-s001.xlsx[ Table S2!Age (Years)] | P003V1: 47.34 |
| SAMEA3708715 | bmi | 24.03 | R2 | 0.85 | paper.supp.IMT2-3-e179-s001.xlsx[ Table S2!BMI (kg/m^2)] | P003V1: 24.03 |
| SAMEA3708715 | collection_date | 2014 | R1 | 0.90 | biosample.attribute:collection_date | 2014 |
| SAMEA3708715 | country | CN | R1 | 0.90 | sample.attr.geographic_location_country_and_or_sea | China |
| SAMEA3708715 | health_condition | type2_diabetes | R3 | 0.70 | paper.fulltext.abstract | treatment-naive type 2 diabetes (T2D) patients |
| SAMEA3708715 | health_condition_detail | Type 2 Diabetes, treatment-naive | R4 | 0.50 | study.description | new onset untreated Type 2 Diabetes patients |
| SAMEA3708716 | intervention | drug_therapy | R2 | 0.85 | paper.supp.IMT2-3-e179-s001.xlsx[ Table S2!Intervention] | P003V6: Acarbose |
| SAMEA3708715 | location_locality | Shanghai | R3 | 0.60 | paper.fulltext.results | we recruited patients from five centres in Shanghai, China |
| SAMEA3708715 | sex | female | R2 | 0.85 | paper.supp.IMT2-3-e179-s001.xlsx[ Table S2!Sex] | P003V1: female |
| SAMEA3708715 | subject_id | P003 | R2 | 0.85 | paper.supp.IMT2-3-e179-s001.xlsx[ Table S2!Patient ID] | P003V1: P003 |
| SAMEA3708715 | timepoint_label | D0 | R2 | 0.85 | paper.supp.IMT2-3-e179-s001.xlsx[ Table S2!Time] | P003V1: D0 |
Sequencing
188 runs over 188 samples · mean 7.40 Gbp per run (median 5.70 Gbp, total 1,391.19 Gbp; 188 runs with a base count) · layout PAIRED 188 · platform ILLUMINA 188 · models Illumina HiSeq 2500 (188) · 89% of runs with a Sandpiper profile · first public 2016-05-04
Authors (57)
Gu Y first · Wang X · Li J · Zhang Y · Zhong H · Liu R · Zhang D · Feng Q · Xie X · Hong J · Ren H · Liu W · Ma J · Su Q · Zhang H · Yang J · Zhao X · Gu W · Bi Y · Peng Y · Xu X · Xia H · Li F · Yang H · Xu G · Madsen L · Kristiansen K · Ning G · Wang W last · Zorea A first · Pellow D · Levin L · Pilosof S · Friedman J · Shamir R · Mizrahi I last · Kavanova K first · Kostovova I · Moravkova M · Kubasova T · Babak V · Crhanova M last · Shi Z · Yang F · Wang S · Yuan F · Li T · Li M · Zhu J · Wu K · Golisch B first · Cordeiro RL · Fraser ASC · Briggs J · Stewart WA · Van Petegem F · Brumer H last
Downloads
PRJEB12124.csv.gz (6.9 KB) · parquet (79.3 KB) — all 188 samples, every field with route and confidence · PRJEB12124_determinations.csv.gz (16.0 KB) — 1,974 evidence rows