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PRJNA904924 SRP409586

Stool microbiome in celiac disease, gluten-free diet, Turin

Stool microbiome profiling of celiac disease patients on gluten-free diet

132 stool samples from celiac disease patients (strict and non-strict gluten-free diet adherence) and matched healthy controls in Turin, Italy, profiled by shotgun metagenomics in a cross-sectional study. machine-written summary

132 samples · 132 runs · IT · Mixed ages · 2022 · 11.87 Gbp / sample

Sources
✓Sequence archive 893○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 archive893 sample values (collection date, country, latitude, location locality, location region, longitude, subject id)
○ Abstract / descriptionread; no usable statement
○ Full textread; no usable statement or table · PMC12282095, PMC9928459
○ Supplementary tablesfiles read; no table could be matched to the samples
– External resourcesnot covered by the external resources we ingest
– User contributionnothing uploaded yet · share metadata
– Human verifiednot yet checked by a person · I checked this project — verify it
Interventions

intervention — arms not resolved

design observational_with_procedure

Samples at a glance
1 sampling locations · 1 country
Age
unknown132
Country
IT132
Body site
primary132
Collected 2018–2021
2018: 19 samples2019: 33 samples2020: 71 samples2021: 9 samples20182021
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 %)this project, 1–3 Gbp: 1 samplesall projects, 3–10 Gbp: 253,728 samples (44 %)this project, 3–10 Gbp: 35 samplesall projects, 10–30 Gbp: 72,533 samples (13 %)this project, 10–30 Gbp: 93 samplesall projects, 30–100 Gbp: 3,024 samples (1 %)this project, 30–100 Gbp: 3 samplesall projects, 100–300 Gbp: 106 samples (0 %)all projects, ≥ 300 Gbp: 9 samples (0 %)project median 11.87 Gbp per sample0130Gbp
Sampling design and relatedness

longitudinal

2 of 98 people sampled more than once (5 samples; median 2, up to 3 per person) · follow-up median 7 mo (max 8 mo) · median interval between samples 4 mo (time from collection dates).

CMa010CMa010: day 0CMa010: day 256Cii044Cii044: day 0Cii044: day 110Cii044: day 2000 d2 mo4 mo6 mo8 mo

Each row is one person (2 shown); dots are samples at days since that person's first sample.

How longitudinal and relatedness information is derived

Community composition
Bacteroides 11.6%Phocaeicola 10.4%Alistipes 7.2%Faecalibacterium 7.0%Prevotella 6.9%Roseburia 3.0%Blautia_A 2.3%Parabacteroides 1.9%Lachnospira 1.9%Gemmiger 1.8%Bifidobacterium 1.7%Vescimonas 1.6%not assigned to a genus 3.4%other genera 39.2%

Genera, mean relative abundance over 123 profiled gut samples of this project (Sandpiper SingleM profiles, GTDB R232; low-depth and non-metagenome profiles left out).

Field coverage
fieldsamplescoverageR1R2R3R4
age_category0 0%
country132 100%132
health_condition0 0%
subject_id101 77%101
collection_date132 100%132
detailed_location132 100%
latitude132 100%132
location_locality132 100%132
location_region132 100%132
longitude132 100%132
Papers (2)
  • Gluten-free diet affects fecal small non-coding RNA profiles and microbiome composition in celiac disease supporting a host-gut microbiota crosstalk. 2023 PMID 36751856 PMC9928459 own_data
  • Microbiome gut community structure and functionality are associated with symptom severity in non-responsive celiac disease patients undergoing a gluten-free diet. 2025 PMID 40476734 PMC12282095 own_data
Details
Archive description

The current treatment for Celiac Disease (CD) is adhering to a gluten-free diet (GFD), although its long-term molecular effects are still undescribed. New molecular features detectable in faecal samples may improve and facilitate non-invasive clinical management of CD on GFD. For this purpose, faecal small non-coding RNAs (sncRNAs) and gut microbiome profiles were concomitantly explored in CD subjects in relation to strict (or not) GFD adherence over time. In the present observational study, we performed small RNA and shotgun metagenomic sequencing in stool from 63 treated CD (tCD) subjects and 66 sex- and age-matched healthy controls. tCD included 51 individuals on strict GFD and with negative transglutaminase (TG) serology (tCD-TG-) and 12 symptomatic with not strict/short-time of GFD adherence and positive TG serology (tCD-TG+). Samples from additional 40 adult healthy individuals and from a cohort of 19 untreated paediatric CD subjects and 19 sex/age matched controls were analyzed to further test the outcomes. Several miRNA, other sncRNA (piRNA and tRNA) and microbiota profiles were altered in tCD subjects(adj.p<0.05). Findings were validated in one external group of controls. In tCD-TG-, GFD duration correlated with five miRNA levels (p<0.05): for miR-4533-3p and miR-2681-3p, the longer the diet adherence, the less the expression differed from controls. tCD-TG+ and untreated paediatric CD patients showed a similar miRNA dysregulation. Immune-response, trans-membrane transport and cell death pathways were enriched in targets of identified miRNAs. Bifidobacterium longum, Ruminococcus bicirculans and Haemophilus parainfluenzae abundances shifted (adj. p<0.05) with a progressive reduction of denitrification pathways with GFD length. Integrative analysis highlighted 121 miRNA-bacterial relationships (adj.p<0.05). Specific faecal sncRNA and microbial patterns characterise CD subjects on GFD, reflecting either the long-term effects or the gut inflammatory status, in case of a not strict/short-time adherence. Our findings suggest novel host-microbial interplays and could help the discovery of biomarkers for the clinical monitoring of GFD over time.

How this project entered the registry

Classified as human gut / stool shotgun DNA metagenome of adult and child and mixed ages by sonnet_x2 with confidence 0.70. Assay shotgun_dna.

  • host study.description · “faecal small non-coding RNAs”
  • body site study.description · “shotgun metagenomic sequencing in stool”
  • life stage study.description · “19 untreated paediatric CD subjects”
  • life stage study.description · “63 treated CD (tCD) subjects”
Evidence examples (one per field × route)
samplefieldvaluerouteconf.sourcequote
SAMN31857837collection_date2018-02-22R10.90biosample.attribute:collection_date2018-02-22
SAMN31857837countryITR10.90sample.attr.geo_loc_nameItaly: Turin
SAMN31857837latitude45.0400R10.90biosample.attribute:lat_lon45.04 N 7.41 E
SAMN31857837location_localityTurinR10.85biosample.attribute:geo_loc_nameItaly: Turin
SAMN31857837location_regionPiedmontR10.60biosample.attribute:lat_lon45.04 N 7.41 E
SAMN31857837longitude7.4100R10.90biosample.attribute:lat_lon45.04 N 7.41 E
SAMN31857837subject_idCii031R10.70sample.name_rule:aliasCii031
Sequencing

132 runs over 132 samples · mean 13.25 Gbp per run (median 11.87 Gbp, total 1,749.20 Gbp; 132 runs with a base count) · layout PAIRED 132 · platform ILLUMINA 132 · models Illumina NovaSeq 6000 (132) · 93% of runs with a Sandpiper profile · first public 2022-11-25

Authors (29)

Francavilla A first · Ferrero G · Pardini B · Tarallo S · Zanatto L · Caviglia GP · Sieri S · Grioni S · Francescato G · Stalla F · Guiotto C · Crocella L · Astegiano M · Bruno M · Calvo PL · Vineis P · Ribaldone DG · Naccarati A last · Marcos-Zambrano LJ first · Lacruz-Pleguezuelos B · Aguilar-Aguilar E · Marcos-Pasero H · Valdés A · Loria-Kohen V · Cifuentes A · Ramirez de Molina A · Diaz-Ruiz A · Pancaldi V · Carrillo de Santa Pau E last

Help complete this project

2 of the 4 core fields are below 50% coverage: age_category, health_condition. Share metadata

Downloads

PRJNA904924.csv.gz (4.8 KB) · parquet (76.2 KB) — all 132 samples, every field with route and confidence · PRJNA904924_determinations.csv.gz (7.8 KB) — 893 evidence rows

Samples (132 · every field this project has values for · hover a cell for its source)
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