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Research on oral microbiota of monozygotic twins with discordant caries experience - in vitro and in vivo study.

ABSTRACT: Oral microbiome is potentially correlated with many diseases, such as dental caries, periodontitis, oral cancer and some systemic diseases. Twin model, as an effective method for studying human microbiota, is widely used in research of relationship between oral microbiota and dental caries. However, there were few researches focusing on caries discordant twins. In this study, in vitro assays were conducted combined with 16S rRNA sequencing analysis on oral microbiota sampled from twins who presented discordant caries experience and mice model was developed as well. Results showed that oral microbiota from caries-active twin possessed higher metabolic activity and produced more lactic production. 16S rRNA sequencing analysis showed that more than 80% of family taxa could be transferred into gnotobiotic-mice. Key caries-associated genera were significantly different between twins and the same difference in genus level could be found in mice as well (p?

SUBMITTER: Wu H

PROVIDER: S-EPMC5940813 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Research on oral microbiota of monozygotic twins with discordant caries experience - in vitro and in vivo study.

Wu Hongle H Zeng Benhua B Li Bolei B Ren Biao B Zhao Jianhua J Li Mingyun M Peng Xian X Feng Mingye M Li Jiyao J Wei Hong H Cheng Lei L Zhou Xuedong X

Scientific reports 20180508 1

Oral microbiome is potentially correlated with many diseases, such as dental caries, periodontitis, oral cancer and some systemic diseases. Twin model, as an effective method for studying human microbiota, is widely used in research of relationship between oral microbiota and dental caries. However, there were few researches focusing on caries discordant twins. In this study, in vitro assays were conducted combined with 16S rRNA sequencing analysis on oral microbiota sampled from twins who prese ...[more]

PMID: 29740156

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Project description:BackgroundRheumatoid arthritis is a common autoimmune disorder influenced by both genetic and environmental factors. Epigenome-wide association studies can identify environmentally mediated epigenetic changes such as altered DNA methylation, which may also be influenced by genetic factors. To investigate possible contributions of DNA methylation to the aetiology of rheumatoid arthritis with minimum confounding genetic heterogeneity, we investigated genome-wide DNA methylation in disease-discordant monozygotic twin pairs.MethodsGenome-wide DNA methylation was assessed in 79 monozygotic twin pairs discordant for rheumatoid arthritis using the HumanMethylation450 BeadChip array (Illumina). Discordant twins were tested for both differential DNA methylation and methylation variability between rheumatoid arthritis and healthy twins. The methylation variability signature was then compared with methylation variants from studies of other autoimmune diseases and with an independent healthy population.ResultsWe have identified a differentially variable DNA methylation signature that suggests multiple stress response pathways may be involved in the aetiology of the disease. This methylation variability signature also highlighted potential epigenetic disruption of multiple RUNX3 transcription factor binding sites as being associated with disease development. Comparison with previously performed epigenome-wide association studies of rheumatoid arthritis and type 1 diabetes identified shared pathways for autoimmune disorders, suggesting that epigenetics plays a role in autoimmunity and offering the possibility of identifying new targets for intervention.ConclusionsThrough genome-wide analysis of DNA methylation in disease-discordant monozygotic twins, we have identified a differentially variable DNA methylation signature, in the absence of differential methylation in rheumatoid arthritis. This finding supports the importance of epigenetic variability as an emerging component in autoimmune disorders.

Project description:Although monozygotic (MZ) twins share the majority of their genetic makeup, they can be phenotypically discordant on several traits and diseases. DNA methylation is an epigenetic mechanism that can be influenced by genetic, environmental and stochastic events and may have an important impact on individual variability. In this study we explored epigenetic differences in peripheral blood samples in three MZ twin studies on major depressive disorder (MDD). Epigenetic data for twin pairs were collected as part of a previous study using 8.1-K-CpG microarrays tagging DNA modification in white blood cells from MZ twins discordant for MDD. Data originated from three geographical regions: UK, Australia and the Netherlands. Ninety-seven MZ pairs (194 individuals) discordant for MDD were included. Different methods to address non independently-and-identically distributed (non-i.i.d.) data were evaluated. Machine-learning methods with feature selection centered on support vector machine and random forest were used to build a classifier to predict cases and controls based on epivariations. The most informative variants were mapped to genes and carried forward for network analysis. A mixture approach using principal component analysis (PCA) and Bayes methods allowed to combine the three studies and to leverage the increased predictive power provided by the larger sample. A machine-learning algorithm with feature reduction classified affected from non-affected twins above chance levels in an independent training-testing design. Network analysis revealed gene networks centered on the PPAR-γ (NR1C3) and C-MYC gene hubs interacting through the AP-1 (c-Jun) transcription factor. PPAR-γ (NR1C3) is a drug target for pioglitazone, which has been shown to reduce depression symptoms in patients with MDD. Using a data-driven approach we were able to overcome challenges of non-i.i.d. data when combining epigenetic studies from MZ twins discordant for MDD. Individually, the studies yielded negative results but when combined classification of the disease state from blood epigenome alone was possible. Network analysis revealed genes and gene networks that support the inflammation hypothesis of MDD.

Dataset Information

Research on oral microbiota of monozygotic twins with discordant caries experience - in vitro and in vivo study.

Publications

Research on oral microbiota of monozygotic twins with discordant caries experience - in vitro and in vivo study.

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