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PRJNA1201249 SRP553146

Legume diet RCT in Singapore prediabetes adults

Legume-enriched diet improves metabolic health in prediabetes partially mediated through gut microbiome: a randomized controlled trial

662 samples from Chinese prediabetes adults in Singapore, from a 16-week randomized controlled trial comparing a calorie-restricted, legume-enriched diet versus a calorie-restricted control diet. machine-written summary

662 samples · 662 runs · SG · Adult · 2024 · 7.93 Gbp / sample

Sources
✓Sequence archive 4,634○Abstract / description○Full text○Supplementary tables–External resources–User contribution–Human verified

Checked this project's papers and archive records yourself? Mark it human-verified.

what each source gave
✓ Sequence archive4,634 sample values (collection date, country, latitude, location locality, longitude, subject id, timepoint)
○ Abstract / descriptionread; no usable statement
○ Full textread; no usable statement or table · PMC11754483
○ Supplementary tablesfiles read; no table could be matched to the samples
– External resourcesnot covered by the external resources we ingest
– User contributionnothing uploaded yet
– Human verifiednot yet checked by a person · I checked this project — verify it
Interventions

intervention — arms not resolved

Controlled / prescribed diet or feeding regimen design randomized_controlled_trial · population type2_diabetes · Calorie-restricted, legume-enriched diet vs calorie-restricted control diet

“Legume-enriched diet improves metabolic health in prediabetes” — study.title (study level; per-sample arms are in the intervention column below)

Samples at a glance
1 sampling locations · 1 country
Age
adult662
Country
SG662
Body site
primary662
Sequencing depth per sample · this project all projects
all projects, 0–0.03 Gbp: 25,080 samples (4 %)all projects, 0.03–0.1 Gbp: 17,066 samples (3 %)all projects, 0.1–0.3 Gbp: 29,179 samples (5 %)all projects, 0.3–1 Gbp: 47,044 samples (8 %)all projects, 1–3 Gbp: 124,983 samples (22 %)all projects, 3–10 Gbp: 253,728 samples (44 %)this project, 3–10 Gbp: 626 samplesall projects, 10–30 Gbp: 72,533 samples (13 %)this project, 10–30 Gbp: 36 samplesall projects, 30–100 Gbp: 3,024 samples (1 %)all projects, 100–300 Gbp: 106 samples (0 %)all projects, ≥ 300 Gbp: 9 samples (0 %)project median 7.93 Gbp per sample0130Gbp
Sampling design and relatedness

longitudinal

111 of 111 people sampled more than once (662 samples; median 6, up to 6 per person) · follow-up median 4 mo (max 4 mo) · median interval between samples 28 d (time from timepoint labels). Schedule stated by the source: “Fecal samples collected at baseline, week 2, week 4, week 8, week 12, and week 16” (time origin: baseline); stated follow-up 4 mo.

FBI001FBI001: day 0FBI001: day 14FBI001: day 28FBI001: day 56FBI001: day 84FBI001: day 112FBI002FBI002: day 0FBI002: day 14FBI002: day 28FBI002: day 56FBI002: day 84FBI002: day 112FBI003FBI003: day 0FBI003: day 14FBI003: day 28FBI003: day 56FBI003: day 84FBI003: day 112FBI004FBI004: day 0FBI004: day 14FBI004: day 28FBI004: day 56FBI004: day 84FBI004: day 112FBI005FBI005: day 0FBI005: day 14FBI005: day 28FBI005: day 56FBI005: day 84FBI005: day 112FBI006FBI006: day 0FBI006: day 14FBI006: day 28FBI006: day 56FBI006: day 84FBI006: day 112FBI007FBI007: day 0FBI007: day 14FBI007: day 28FBI007: day 56FBI007: day 84FBI007: day 112FBI010FBI010: day 0FBI010: day 14FBI010: day 28FBI010: day 56FBI010: day 84FBI010: day 112FBI011FBI011: day 0FBI011: day 14FBI011: day 28FBI011: day 56FBI011: day 84FBI011: day 112FBI012FBI012: day 0FBI012: day 14FBI012: day 28FBI012: day 56FBI012: day 84FBI012: day 112FBI013FBI013: day 0FBI013: day 14FBI013: day 28FBI013: day 56FBI013: day 84FBI013: day 112FBI014FBI014: day 0FBI014: day 14FBI014: day 28FBI014: day 56FBI014: day 84FBI014: day 112FBI015FBI015: day 0FBI015: day 14FBI015: day 28FBI015: day 56FBI015: day 84FBI015: day 112FBI016FBI016: day 0FBI016: day 14FBI016: day 28FBI016: day 56FBI016: day 84FBI016: day 112FBI017FBI017: day 0FBI017: day 14FBI017: day 28FBI017: day 56FBI017: day 84FBI017: day 112FBI020FBI020: day 0FBI020: day 14FBI020: day 28FBI020: day 56FBI020: day 84FBI020: day 112FBI023FBI023: day 0FBI023: day 14FBI023: day 28FBI023: day 56FBI023: day 84FBI023: day 112FBI024FBI024: day 0FBI024: day 14FBI024: day 28FBI024: day 56FBI024: day 84FBI024: day 112FBI025FBI025: day 0FBI025: day 14FBI025: day 28FBI025: day 56FBI025: day 84FBI025: day 112FBI026FBI026: day 0FBI026: day 14FBI026: day 28FBI026: day 56FBI026: day 84FBI026: day 112FBI027FBI027: day 0FBI027: day 14FBI027: day 28FBI027: day 56FBI027: day 84FBI027: day 112FBI028FBI028: day 0FBI028: day 14FBI028: day 28FBI028: day 56FBI028: day 84FBI028: day 112FBI029FBI029: day 0FBI029: day 14FBI029: day 28FBI029: day 56FBI029: day 84FBI029: day 112FBI030FBI030: day 0FBI030: day 14FBI030: day 28FBI030: day 56FBI030: day 84FBI030: day 112FBI031FBI031: day 0FBI031: day 14FBI031: day 28FBI031: day 56FBI031: day 84FBI031: day 112FBI032FBI032: day 0FBI032: day 14FBI032: day 28FBI032: day 56FBI032: day 84FBI032: day 112FBI033FBI033: day 0FBI033: day 14FBI033: day 28FBI033: day 56FBI033: day 84FBI033: day 112FBI034FBI034: day 0FBI034: day 14FBI034: day 28FBI034: day 56FBI034: day 84FBI034: day 112FBI035FBI035: day 0FBI035: day 14FBI035: day 28FBI035: day 56FBI035: day 84FBI035: day 112FBI036FBI036: day 0FBI036: day 14FBI036: day 28FBI036: day 56FBI036: day 84FBI036: day 112FBI037FBI037: day 0FBI037: day 14FBI037: day 28FBI037: day 56FBI037: day 84FBI037: day 112FBI039FBI039: day 0FBI039: day 14FBI039: day 28FBI039: day 56FBI039: day 84FBI039: day 112FBI040FBI040: day 0FBI040: day 14FBI040: day 28FBI040: day 56FBI040: day 84FBI040: day 112FBI043FBI043: day 0FBI043: day 14FBI043: day 28FBI043: day 56FBI043: day 84FBI043: day 112FBI045FBI045: day 0FBI045: day 14FBI045: day 28FBI045: day 56FBI045: day 84FBI045: day 112FBI046FBI046: day 0FBI046: day 14FBI046: day 28FBI046: day 56FBI046: day 84FBI046: day 1120 d28 d56 d3 mo4 mo

Each row is one person (36 shown of 111); dots are samples at days since that person's first sample.

How longitudinal and relatedness information is derived

Community composition
Bacteroides 10.4%Phocaeicola 10.0%Prevotella 6.7%Blautia_A 6.6%Faecalibacterium 5.8%Roseburia 4.1%Bifidobacterium 3.8%Ruminococcoides 2.3%Alistipes 2.2%Lachnospira 2.2%Megamonas 2.1%Fusicatenibacter 1.8%not assigned to a genus 3.5%other genera 38.5%

Genera, mean relative abundance over 609 profiled gut samples of this project (Sandpiper SingleM profiles, GTDB R232; low-depth and non-metagenome profiles left out).

Field coverage
fieldsamplescoverageR1R2R3R4
age_category662 100%
country662 100%662
health_condition0 0%
subject_id662 100%662
collection_date662 100%662
detailed_location662 100%
latitude662 100%662
location_locality662 100%662
longitude662 100%662
timepoint_label662 100%662
Papers (2)
  • A legume-enriched diet improves metabolic health in prediabetes mediated through gut microbiome: a randomized controlled trial. 2025 PMID 39843443 PMC11754483 own_data
  • Cross-body site microbial interactions influence the human plasma metabolome. 2026 PMID 41952172 PMC13181886 unsure
Details
Archive description

Healthy dietary patterns rich in legumes can improve metabolic health, although their additional benefits in conjunction with calorie restriction has not been well-established. We investigated effects of a calorie-restricted, legume-enriched, multicomponent intervention diet compared with a calorie-restricted control diet in 127 Chinese prediabetes participants, living in Singapore. The study was a 16-week, single-blind, parallel-design, randomized controlled trial (n=63 intervention group (IG), n=64 control group (CG)). Primary outcomes were markers of glycemia and all measurements were taken at 2 or 4-weekly intervals. At the end of 16 weeks, both groups had significantly lower BMI compared with baseline, with minimal difference between groups. The IG had significantly greater reductions in LDL cholesterol, total cholesterol and HbA1c compared with CG, alongside increases in fibre degrading species in IG, mediated through metabolites such as bile acids and amino acids. A legume-enriched, multicomponent intervention diet can improve metabolic health in a prediabetes population, in addition to benefits obtained from calorie restriction alone, partially mediated through changes in gut microbial composition and function.</p><p>Trial registration: Clinical Trials NCT04745702.

How this project entered the registry

Classified as human gut / stool shotgun DNA metagenome of adult by sonnet_x2 with confidence 0.72. Assay shotgun_dna.

  • host study.description · “127 Chinese prediabetes participants”
  • body site run.scientific_name · “human gut metagenome”
  • life stage study.description · “calorie-restricted, legume-enriched, multicomponent intervention diet”
Evidence examples (one per field × route)
samplefieldvaluerouteconf.sourcequote
SAMN45930898collection_date2021R10.90biosample.attribute:collection_date2021
SAMN45930898countrySGR10.90sample.attr.geo_loc_nameSingapore
SAMN45930898latitude1.3521R10.90biosample.attribute:lat_lon1.3521 N 103.8198 E
SAMN45930898location_localitySingaporeR10.85biosample.attribute:geo_loc_nameSingapore
SAMN45930898longitude103.8198R10.90biosample.attribute:lat_lon1.3521 N 103.8198 E
SAMN45930898subject_idFBI128R10.70sample.name_rule:source_material_idFBI128, Group1, W16
SAMN45930898timepoint_labelweek 16R10.70sample.name_rule:source_material_idFBI128, Group1, W16
Sequencing

662 runs over 662 samples · mean 8.17 Gbp per run (median 7.93 Gbp, total 5,409.48 Gbp; 662 runs with a base count) · layout PAIRED 662 · platform ILLUMINA 662 · models Illumina NovaSeq X (662) · 92% of runs with a Sandpiper profile · first public 2024-12-23 – 2024-12-29

Authors (27)

Wu X first · Tjahyo AS · Volchanskaya VSB · Wong LH · Lai X · Yong YN · Osman F · Tay SL · Govindharajulu P · Ponnalagu S · Tso R · Teo HS · Khoo K · Fan H · Goh CC · Yap CPL · Leow MK · Henry CJ · Haldar S · Lim KJ last · Zhang J first · Jiang C · Zhou X · Gao P · Wong S · Snyder M · Shen X last

Downloads

PRJNA1201249.csv.gz (16.4 KB) · parquet (91.6 KB) — all 662 samples, every field with route and confidence · PRJNA1201249_determinations.csv.gz (33.1 KB) — 4,634 evidence rows

Samples (662 · every field this project has values for · hover a cell for its source)
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