GET /metagenomics/api/v1/samples/SRS9692103/studies?format=api
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept
{
"links": {
"first": "https://www.ebi.ac.uk/metagenomics/api/v1/samples/SRS9692103/studies?format=api&page=1",
"last": "https://www.ebi.ac.uk/metagenomics/api/v1/samples/SRS9692103/studies?format=api&page=1",
"next": null,
"prev": null
},
"data": [
{
"type": "studies",
"id": "MGYS00006559",
"attributes": {
"accession": "MGYS00006559",
"bioproject": "PRJNA752174",
"samples-count": 102,
"is-private": false,
"last-update": "2023-12-21T11:28:40",
"secondary-accession": "SRP331280",
"centre-name": "Institute of Microbiology, GuangdongAcademy of Sciences",
"public-release-date": null,
"study-abstract": "To date, much progress has been made in dietary therapy for obese patients. A low-carbohydrate diet (LCD) has reached a revival in its clinical use during the past decade with undefined mechanisms and debatable efficacy. Gut microbiota has been suggested to promote energy harvesting. Here, we propose that gut microbiota contributes to the inconsistent outcome under LCD. To test this hypothesis, patients with obesity or overweight were randomly assigned either to a normal diet (ND) or LCD group with ad libitum energy intake for 12 weeks. Using matched sampling, the microbiome profile at baseline and end-stage was examined. The relative abundance of butyrate-producing bacteria, Porphyromonadaceae Parabacteroides and Ruminococcaceae Oscillospira, was markedly increased after LCD intervention for 12 weeks. Moreover, within LCD group, participants with a higher relative abundance of Bacteroidaceae Bacteroides at baseline exhibited a better response to LCD intervention and achieved greater weight loss outcomes. Nevertheless, the adoption of an artificial neural network (ANN)-based prediction model greatly surpasses general linear model in predicting weight loss outcomes after LCD intervention. Therefore, gut microbiota served as a positive outcome predictor has the potential to predict weight loss outcomes after short-term LCD intervention. Gut microbiota may help to guide the clinical application of short-term LCD intervention to develop effective weight loss strategies.",
"study-name": "Influence of gut microbiota on short-term low carbohydrate diet intervention for weight loss therapy",
"data-origination": "HARVESTED"
},
"relationships": {
"downloads": {
"links": {
"related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006559/downloads?format=api"
}
},
"geocoordinates": {
"links": {
"related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006559/geocoordinates?format=api"
}
},
"analyses": {
"links": {
"related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006559/analyses?format=api"
}
},
"biomes": {
"links": {
"related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006559/biomes?format=api"
},
"data": [
{
"type": "biomes",
"id": "root:Host-associated:Human:Digestive system:Large intestine:Fecal",
"links": {
"self": "https://www.ebi.ac.uk/metagenomics/api/v1/biomes/root:Host-associated:Human:Digestive%20system:Large%20intestine:Fecal?format=api"
}
}
]
},
"publications": {
"links": {
"related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006559/publications?format=api"
}
},
"samples": {
"links": {
"related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006559/samples?format=api"
}
}
},
"links": {
"self": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006559?format=api"
}
}
],
"meta": {
"pagination": {
"page": 1,
"pages": 1,
"count": 1
}
}
}