Severe Early Childhood Caries microbiome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA454811 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7647540_1.fastq.gz | Fastqsanger.gz | |||
| SRR7647540_2.fastq.gz | Fastqsanger.gz | |||
| SRR7647550_1.fastq.gz | Fastqsanger.gz | |||
| SRR7647550_2.fastq.gz | Fastqsanger.gz | |||
| SRR7647560_1.fastq.gz | Fastqsanger.gz |
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Similar Datasets
Project description:Characterization of taste genetics and oral microbiome in severe early childhood caries
| PRJNA1294419 | ENA
Project description:Characterization of taste genetics and oral microbiome in severe early childhood caries
| PRJNA1294420 | ENA
Project description:<p><strong>Purpose:</strong> Dental caries is characterized by a dysbiotic shift at the biofilm-tooth surface interface, yet comprehensive biochemical characterizations of the biofilm are scant. We used metabolomics to identify biochemical features of the supragingival biofilm associated with early childhood caries (ECC) prevalence and severity. </p><p><strong>Methods:</strong> The study’s analytical sample comprised 289 children ages 3-5 (51% with ECC) who attended public preschools in North Carolina and were enrolled in a community-based cross-sectional study of early childhood oral health. Clinical examinations were conducted by calibrated examiners in community locations using ICDAS criteria. Supragingival plaque collected from the facial/buccal surfaces of all primary teeth in the upper-left quadrant were analyzed using Ultra Performance Liquid Chromatography-tandem Mass Spectrometry. Associations between individual metabolites and 18 clinical traits (based on different ECC definitions and sets of tooth surfaces) were quantified using Brownian distance correlations (dCor) and linear regression modeling of log2-transformed values, applying a False Discovery Rate multiple testing correction. A tree-based pipeline optimization tool (TPOT)-machine learning process was used to identify the best-fitting ECC classification metabolite model. </p><p><strong>Results:</strong> There were 503 named metabolites identified, including microbial, host and exogenous biochemicals. Most significant ECC-metabolite associations were positive (i.e., upregulations/enrichments). The localized ECC case definition (ICDAS≥1 caries experience within the surfaces from which plaque was collected) had the strongest correlation with the metabolome (dCor p=8x10-3). Sixteen metabolites were significantly associated with ECC after multiple testing correction, including: fucose (p=3.0x10-6) and N-acetylneuraminate (p=6.8x10-6) with higher ECC prevalence; catechin (p=4.7x10-6) and epicatechin (p=2.9x10-6) with lower. Catechin, epicatechin, imidazole propionate, fucose, 9,10-DiHOME, and N-acetylneuraminate were among the top 15 metabolites in terms of ECC classification importance in the automated TPOT model. </p><p><strong>Conclusion:</strong> These supragingival biofilm metabolite findings provide novel insights in ECC biology and can serve as the basis for the development of measures of disease activity or risk assessment.</p>
2021-01-29 | MTBLS2215 | MetaboLights
Project description:Genome-Wide Association Study of Early Childhood Caries: CIDR
| PRJNA671298 | ENA
Project description:Genome-Wide Association Study of Early Childhood Caries: CIDR
| PRJNA671299 | ENA
Project description:Oral microbiome and HIV in early childhood caries
| PRJEB52879 | ENA
Project description:The development of early childhood caries (ECC) is closely related to the salivary microenvironment, but the role of host factors in the pathogenesis of ECC has not been fully characterized. The aim of this study was to investigate the mechanism of ECC development and to search for salivary protein biomarkers that can predict ECC development by quantitative proteomic analysis of saliva host-derived proteins.
2024-01-17 | PXD048619 |
Project description:BackgroundSevere early childhood caries (SECC) is an inflammatory disease with complex pathology. Although changes in the oral microbiota and metabolic profile of patients with SECC have been identified, the salivary metabolites and the relationship between oral bacteria and biochemical metabolism remains unclear. We aimed to analyse alterations in the salivary microbiome and metabolome of children with SECC as well as their correlations. Accordingly, we aimed to explore potential salivary biomarkers in order to gain further insight into the pathophysiology of dental caries.MethodsWe collected 120 saliva samples from 30 children with SECC and 30 children without caries. The microbial community was identified through 16S ribosomal RNA (rRNA) gene high-throughput sequencing. Additionally, we conducted non-targeted metabolomic analysis through ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry to determine the relative metabolite levels and their correlation with the clinical caries status.ResultsThere was a significant between-group difference in 8 phyla and 32 genera in the microbiome. Further, metabolomic and enrichment analyses revealed significantly altered 32 salivary metabolites in children with dental caries, which involved pathways such as amino acid metabolism, pyrimidine metabolism, purine metabolism, ATP-binding cassette transporters, and cyclic adenosine monophosphate signalling pathway. Moreover, four in vivo differential metabolites (2-benzylmalate, epinephrine, 2-formaminobenzoylacetate, and 3-Indoleacrylic acid) might be jointly applied as biomarkers (area under the curve = 0.734). Furthermore, the caries status was correlated with microorganisms and metabolites. Additionally, Spearman's correlation analysis of differential microorganisms and metabolites revealed that Veillonella, Staphylococcus, Neisseria, and Porphyromonas were closely associated with differential metabolites.ConclusionThis study identified different microbial communities and metabolic profiles in saliva, which may be closely related to caries status. Our findings could inform future strategies for personalized caries prevention, detection, and treatment.
| S-EPMC9850820 | biostudies-literature
Project description:The study aims to assess gene expression in plaque samples collected from twin pairs that are both concordant and discordant with respect to dental Caries diagnosis. File Naming Conventions are as follows: Patient ID : 4 digit identifier Diagnosis : Caries Negative(CN) or Caries Positive(CP) Type of Twin: Monozygotic(MZ)or Dizygotic(DZ) Pair to xxxx: 4 digit twin identifier maps to the Patient ID E.g: 2126_CP_MZ_PairTo_2125_fastqc - 2126 is a caries positive patient and pairs to monozygotic twin pair 2125. Plaque samples from twin pairs that are both concordant and discordant with respect to dental Caries diagnosis are enriched for bacterial messenger RNA to study the gene expression differences in the samples.
2011-09-26 | GSE31439 | GEO
Project description:The study aims to assess gene expression in plaque samples collected from twin pairs that are both concordant and discordant with respect to dental Caries diagnosis. File Naming Conventions are as follows: Patient ID : 4 digit identifier Diagnosis : Caries Negative(CN) or Caries Positive(CP) Type of Twin: Monozygotic(MZ)or Dizygotic(DZ) Pair to xxxx: 4 digit twin identifier maps to the Patient ID E.g: 2126_CP_MZ_PairTo_2125_fastqc - 2126 is a caries positive patient and pairs to monozygotic twin pair 2125. Plaque samples from twin pairs that are both concordant and discordant with respect to dental Caries diagnosis are enriched for bacterial messenger RNA to study the gene expression differences in the samples. RNA was extracted from RNAprotect (Qiagen, In c.) treated dental plaque scrapings from 38 patients. Amplified cDNA was created and rRNA sequence was removed by subtractive hybridization. Individual patient samples were run on a single lane of an Illumina Genome Analyzer.
2011-09-26 | E-GEOD-31439 | biostudies-arrayexpress