Sample Studies Relationship List

HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "links": {
        "first": "https://www.ebi.ac.uk/metagenomics/api/v1/samples/SRS1541279/studies?format=api&page=1",
        "last": "https://www.ebi.ac.uk/metagenomics/api/v1/samples/SRS1541279/studies?format=api&page=1",
        "next": null,
        "prev": null
    },
    "data": [
        {
            "type": "studies",
            "id": "MGYS00005527",
            "attributes": {
                "samples-count": 549,
                "bioproject": "PRJNA327565",
                "accession": "MGYS00005527",
                "is-private": false,
                "last-update": "2020-06-14T13:37:08",
                "secondary-accession": "SRP077932",
                "centre-name": "Baylor College of Medicine",
                "public-release-date": null,
                "study-abstract": "Background: Although we and our microbial community and genomes (the human microbiome) have co-evolved over millions of years, to what extent the human host maternally inherited ancestral genome (mitochondrial genome) informs both microbial community composition and risk of human disease is unclear. We have previously demonstrated a significant association between the placental microbiome and risk of preterm birth, as well as (in non-pregnant subjects) association of mitochondrial DNA (mtDNA) variants (mtSNPs) with the vaginal and gut microbiome. In this study, we aimed to explore complex interactions between human host mtSNPs and the vaginal and placental membrane microbiome with associated risk of preterm birth.Methods: Maternal blood and placental tissue samples from 93 gravidae (n=54 with preterm deliveries between 23 and 0/7 and <37 and 0/7 weeks; n=39 term =37 and 0/7 weeks) were deep sequenced, and mtSNPs were called with high confidence. The microbial taxonomic abundance of the vagina (introitus and posterior fornix) and placental membranes (maternal and fetal side swabs) from the same subjects were obtained via 16S ribosomal RNA sequencing, and inferred metagenomics was employed for metabolic pathway analysis. Interactions among both microbial taxa and their inferred metagenomics pathways were examined for association with mtSNPs employing multiple linear regressions modeling for both genotype and clinical covariates with PLINK quantitative trait associations. Analyses were adjusted for multiple comparisons, with a q value <0.05 denoting significance.Results: Consistent with ours and others recent published observations, we observed an association between preterm birth and the composition of the placental membrane microbiome community (PERMANOVA p=0.042). In our cohort, no significant association between any mtSNP with the occurrence of preterm birth was observed. However, overall associations between mitochondrial genome variations and both the vaginal and placental membrane preterm microbial community were observed. Of note, several functional mtSNPs (within coding regions for electron transport genes) demonstrated significant and robust associations (q value <0.05) with both occurrence and abundance of certain taxa and their metagenomics pathways among preterm births.Conclusions: We have demonstrated for the first time that maternally inherited human mtSNPs are associated with variations in both placental membrane and vaginal microbial taxa membership and their inferred metabolic function during pregnancy, and consequentially linked to the occurrence of preterm birth.",
                "study-name": "Integrated Analysis of mtDNA Single Nucleotide Polymorphisms with the Vaginal and Placental Membrane Microbiome and Rendered Risk Estimation for Preterm Birth",
                "data-origination": "HARVESTED"
            },
            "relationships": {
                "analyses": {
                    "links": {
                        "related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00005527/analyses?format=api"
                    }
                },
                "publications": {
                    "links": {
                        "related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00005527/publications?format=api"
                    }
                },
                "biomes": {
                    "links": {
                        "related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00005527/biomes?format=api"
                    },
                    "data": [
                        {
                            "type": "biomes",
                            "id": "root:Host-associated:Human",
                            "links": {
                                "self": "https://www.ebi.ac.uk/metagenomics/api/v1/biomes/root:Host-associated:Human?format=api"
                            }
                        }
                    ]
                },
                "geocoordinates": {
                    "links": {
                        "related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00005527/geocoordinates?format=api"
                    }
                },
                "samples": {
                    "links": {
                        "related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00005527/samples?format=api"
                    }
                },
                "downloads": {
                    "links": {
                        "related": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00005527/downloads?format=api"
                    }
                }
            },
            "links": {
                "self": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00005527?format=api"
            }
        }
    ],
    "meta": {
        "pagination": {
            "page": 1,
            "pages": 1,
            "count": 1
        }
    }
}