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PRJNA1146994 SRP532847

Diet and gut microbiome in healthy Spanish adults

Personal traits, lifestyle decisions, and geography shape our dietary intake and consequently our bacterial and fungal gut microbiome Raw sequence reads

497 samples from healthy adult participants across Spanish regions, examining how dietary intake and lifestyle factors relate to gut bacterial and fungal microbiome composition, in a cross-sectional design. machine-written summary

497 samples · 497 runs · ES · Adult · 2026 · 5.90 Gbp / sample · cohort Microbial, functional, and virulence biomarkers as

Sources
✓Sequence archive 2,485○Abstract / description✓Full text 1,988○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 archive2,485 sample values (collection date, country, latitude, location locality, longitude)
○ Abstract / descriptionread; no usable statement
✓ Full text1,988 sample values (antibiotic exposure, health condition, health condition detail, subject id) · PMC12254420
○ 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
Samples at a glance
1 sampling locations · 1 country
Age
adult497
Condition
healthy_control497
Country
ES497
Body site
primary497
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: 496 samplesall projects, 10–30 Gbp: 72,533 samples (13 %)this project, 10–30 Gbp: 1 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 5.90 Gbp per sample0130Gbp
Community composition

No Sandpiper profile for this project's samples yet.

Field coverage
fieldsamplescoverageR1R2R3R4
age_category497 100%
country497 100%497
health_condition497 100%497
subject_id497 100%497
antibiotic_exposure497 100%497
collection_date497 100%497
detailed_location497 100%
health_condition_detail497 100%497
latitude497 100%497
location_locality497 100%497
longitude497 100%497
Papers (3)
  • Microbiome composition recovery after liver transplantation correlates with initial liver disease severity and antibiotics treatment. 2024 PMID 38556088 own_data
  • A contributory citizen science project reveals the impact of dietary keys to microbiome health in Spain. 2025 PMID 40646012 PMC12254420 own_data
  • Microbial, functional, and virulence biomarkers associated with familial risk of Crohn's disease and ulcerative colitis. 2026 PMID 42277905 PMC13352609 unsure
Details
Archive description

Background</p><p>The Global Burden of Disease 2017 (GBD-2017) study identified high sodium intake,</p><p>low whole grain intake, and low fruit consumption as key dietary risk factors for non-</p><p>communicable diseases (NCDs). We hypothesize that individual characteristics and</p><p>lifestyle factors influence these dietary risks, thereby modulating the composition of the</p><p>gut bacterial and fungal communities.</p><p>Methods</p><p>From 2020 to 2024, we enrolled 1001 participants from four Spanish regions. Participants</p><p>completed a short Food Frequency Questionnaire (sFFQ) at baseline, month six, and</p><p>month 12 (n = 2475). We calculated six distinct eating quality indices (EQIs) and</p><p>analyzed their influence on gut microbiome composition and diversity, alongside</p><p>demographic and lifestyle factors, using Spearman tests and linear regression models.</p><p>Microbial diversity and composition were assessed on baseline samples through shotgun</p><p>sequencing (n = 500).</p><p>Findings</p><p>Age, gender, and geography significantly influenced dietary patterns. Older age and</p><p>healthier diets, particularly high in fruits and vegetables, had increased gut microbiome</p><p>diversity. Compared to the GBD-2017 guidelines, participants consumed less legumes,</p><p>whole grains, and nuts but exceeded recommended red meat and sugar intake levels.</p><p>Faster gut transit time correlated with distinct microbiome profiles and lower diversity.</p><p>Men exhibited poorer dietary habits than women, and regional dietary patterns also</p><p>impacted diet quality and microbiome diversity. Seasonal effects were noted, with higher</p><p>bacterial diversity in summer. Fungal microbiome analysis revealed that healthier diets</p><p>also promoted more diverse and stable fungal communities. Participants can learn about</p><p>the study, their diet and their microbiome here</p><p>(https://manichanh.vhir.org/POP/ username:reviewers password:reviewers)</p><p>Interpretation</p><p>Adherence to national dietary guidelines, particularly the Mediterranean diet, enhances</p><p>gut microbial diversity. Personal, lifestyle, and geographic factors significantly influence</p><p>dietary quality, highlighting the need for targeted interventions. The study suggests that</p><p>improving dietary patterns positively impacts the gut microbiome and overall health in</p><p>Spain.

How this project entered the registry

Classified as human gut / stool shotgun DNA metagenome of adult by deterministic_prior with confidence 0.90. Assay shotgun_dna.

  • host external_curation.infant_catalog · “infant triage reason_code age_adult_only”
  • body site study.title · “bacterial and fungal gut microbiome Raw sequence”
  • body site study.description · “composition of the</p><p> gut bacterial and fungal”
  • life stage external_curation.infant_catalog · “infant triage reason_code age_adult_only”
  • life stage study.description · “and lower diversity.</p><p> Men exhibited poorer dietary”
Evidence examples (one per field × route)
samplefieldvaluerouteconf.sourcequote
SAMN43779368antibiotic_exposurenoR30.70paper.fulltext.methodsnot taken antibiotics for at least three months
SAMN43779368collection_date2020R10.90biosample.attribute:collection_date2020
SAMN43779368countryESR10.90sample.attr.geo_loc_nameSpain: Barcelona
SAMN43779368health_conditionhealthy_controlR30.70paper.fulltext.abstract1001 healthy participants from all Spanish regions
SAMN43779368health_condition_detail1001 healthy participants ... none had any diagnosed chronic intestinal disordersR30.70paper.fulltext.abstract1001 healthy participants from all Spanish regions
SAMN43779368latitude41.4280R10.90biosample.attribute:lat_lon41.427991 N 2.141921 E
SAMN43779368location_localityBarcelonaR10.85biosample.attribute:geo_loc_nameSpain: Barcelona
SAMN43779368longitude2.1419R10.90biosample.attribute:lat_lon41.427991 N 2.141921 E
SAMN43779368subject_idSAMN43779368R30.75design.one_sample_per_subject:fulltextDue to budget constraints, a random subset of 500 samples was selected from the total 1001 baseline samples for microbiome analysis
Sequencing

497 runs over 497 samples · mean 5.97 Gbp per run (median 5.90 Gbp, total 2,969.18 Gbp; 497 runs with a base count) · layout PAIRED 497 · platform ILLUMINA 497 · models Illumina NovaSeq 6000 (497) · 0% of runs with a Sandpiper profile · first public 2026-07-16 – 2026-07-19

Authors (20)

Vega-Abellaneda S first · Dopazo C · Yañez F · Soler Z · Xie Z · Canalda-Baltrons A · Pons-Tarín M · Bilbao I · Manichanh C last · Serrano-Gómez G · Manjón I · Cognard C · Varela E · Noguera-Segura A · Roca-Bosch M · Zaida S · Mayorga L · Maria TC · Natalia B · Francisco G

Downloads

PRJNA1146994.csv.gz (13.2 KB) · parquet (91.2 KB) — all 497 samples, every field with route and confidence · PRJNA1146994_determinations.csv.gz (25.4 KB) — 4,473 evidence rows

Samples (497 · every field this project has values for · hover a cell for its source)
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