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1.
Nat Commun ; 10(1): 4505, 2019 Oct 03.
Artigo em Inglês | MEDLINE | ID: mdl-31582752

RESUMO

The human gut is inhabited by a complex and metabolically active microbial ecosystem. While many studies focused on the effect of individual microbial taxa on human health, their overall metabolic potential has been under-explored. Using whole-metagenome shotgun sequencing data in 1,004 twins, we first observed that unrelated subjects share, on average, almost double the number of metabolic pathways (82%) than species (43%). Then, using 673 blood and 713 faecal metabolites, we found metabolic pathways to be associated with 34% of blood and 95% of faecal metabolites, with over 18,000 significant associations, while species showed less than 3,000 associations. Finally, we estimated that the microbiome was involved in a dialogue between 71% of faecal, and 15% of blood, metabolites. This study underlines the importance of studying the microbial metabolic potential rather than focusing purely on taxonomy to find therapeutic and diagnostic targets, and provides a unique resource describing the interplay between the microbiome and the systemic and faecal metabolic environments.

2.
Nat Commun ; 10(1): 2581, 2019 06 13.
Artigo em Inglês | MEDLINE | ID: mdl-31197173

RESUMO

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D.


Assuntos
Metilação de DNA/fisiologia , Diabetes Mellitus Tipo 2/genética , Glucose/metabolismo , Insulina/metabolismo , Obesidade/genética , Adulto , Idoso , Idoso de 80 Anos ou mais , Simulação por Computador , Ilhas de CpG/genética , Diabetes Mellitus Tipo 2/metabolismo , Epigênese Genética/fisiologia , Epigenômica/métodos , Feminino , Perfilação da Expressão Gênica/métodos , Regulação da Expressão Gênica/genética , Estudo de Associação Genômica Ampla/métodos , Homeostase/genética , Humanos , Masculino , Redes e Vias Metabólicas/genética , Pessoa de Meia-Idade , Obesidade/metabolismo , Polimorfismo de Nucleotídeo Único/fisiologia , Adulto Jovem
3.
Clin Epigenetics ; 10(1): 126, 2018 Oct 20.
Artigo em Inglês | MEDLINE | ID: mdl-30342560

RESUMO

BACKGROUND: Tobacco smoking is a risk factor for multiple diseases, including cardiovascular disease and diabetes. Many smoking-associated signals have been detected in the blood methylome, but the extent to which these changes are widespread to metabolically relevant tissues, and impact gene expression or metabolic health, remains unclear. METHODS: We investigated smoking-associated DNA methylation and gene expression variation in adipose tissue biopsies from 542 healthy female twins. Replication, tissue specificity, and longitudinal stability of the smoking-associated effects were explored in additional adipose, blood, skin, and lung samples. We characterized the impact of adipose tissue smoking methylation and expression signals on metabolic disease risk phenotypes, including visceral fat. RESULTS: We identified 42 smoking-methylation and 42 smoking-expression signals, where five genes (AHRR, CYP1A1, CYP1B1, CYTL1, F2RL3) were both hypo-methylated and upregulated in current smokers. CYP1A1 gene expression achieved 95% prediction performance of current smoking status. We validated and replicated a proportion of the signals in additional primary tissue samples, identifying tissue-shared effects. Smoking leaves systemic imprints on DNA methylation after smoking cessation, with stronger but shorter-lived effects on gene expression. Metabolic disease risk traits such as visceral fat and android-to-gynoid ratio showed association with methylation at smoking markers with functional impacts on expression, such as CYP1A1, and at tissue-shared smoking signals, such as NOTCH1. At smoking-signals, BHLHE40 and AHRR DNA methylation and gene expression levels in current smokers were predictive of future gain in visceral fat upon smoking cessation. CONCLUSIONS: Our results provide the first comprehensive characterization of coordinated DNA methylation and gene expression markers of smoking in adipose tissue. The findings relate to human metabolic health and give insights into understanding the widespread health consequence of smoking outside of the lung.

4.
Appl Microbiol Biotechnol ; 102(20): 8629-8646, 2018 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-30078138

RESUMO

Owing to the increased cost-effectiveness of high-throughput technologies, the number of studies focusing on the human microbiome and its connections to human health and disease has recently surged. However, best practices in microbiology and clinical research have yet to be clearly established. Here, we present an overview of the challenges and opportunities involved in conducting a metagenomic study, with a particular focus on data processing and analytical methods.


Assuntos
Bactérias/isolamento & purificação , Infecções Bacterianas/microbiologia , Metagenômica , Bactérias/classificação , Bactérias/genética , Protocolos Clínicos , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Metagenômica/métodos , Microbiologia
5.
Gigascience ; 7(7)2018 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-29917068

RESUMO

YAMP ("Yet Another Metagenomics Pipeline") is a user-friendly workflow that enables the analysis of whole shotgun metagenomic data while using containerization to ensure computational reproducibility and facilitate collaborative research. YAMP can be executed on any UNIX-like system and offers seamless support for multiple job schedulers as well as for the Amazon AWS cloud. Although YAMP was developed to be ready to use by nonexperts, bioinformaticians will appreciate its flexibility, modularization, and simple customization.


Assuntos
Biologia Computacional/métodos , Metagenômica/métodos , Fluxo de Trabalho , Simulação por Computador , Humanos , Internet , Reprodutibilidade dos Testes , Software
6.
Sci Rep ; 7(1): 13670, 2017 Oct 20.
Artigo em Inglês | MEDLINE | ID: mdl-29057986

RESUMO

Reduced gut microbiome diversity is associated with multiple disorders including metabolic syndrome (MetS) features, though metabolomic markers have not been investigated. Our objective was to identify blood metabolite markers of gut microbiome diversity, and explore their relationship with dietary intake and MetS. We examined associations between Shannon diversity and 292 metabolites profiled by the untargeted metabolomics provider Metabolon Inc. in 1529 females from TwinsUK using linear regressions adjusting for confounders and multiple testing (Bonferroni: P < 1.71 × 10-4). We replicated the top results in an independent sample of 420 individuals as well as discordant identical twin pairs and explored associations with self-reported intakes of 20 food groups. Longitudinal changes in circulating levels of the top metabolite, were examined for their association with food intake at baseline and with MetS at endpoint. Five metabolites were associated with microbiome diversity and replicated in the independent sample. Higher intakes of fruit and whole grains were associated with higher levels of hippurate cross-sectionally and longitudinally. An increasing hippurate trend was associated with reduced odds of having MetS (OR: 0.795[0.082]; P = 0.026). These data add further weight to the key role of the microbiome as a potential mediator of the impact of dietary intake on metabolic status and health.

7.
BMC Bioinformatics ; 16: 131, 2015 Apr 28.
Artigo em Inglês | MEDLINE | ID: mdl-25928765

RESUMO

BACKGROUND: Epigenome-wide association scans (EWAS) are an increasingly powerful and widely-used approach to assess the role of epigenetic variation in human complex traits. However, this rapidly emerging field lacks dedicated visualisation tools that can display features specific to epigenetic datasets. RESULT: We developed coMET, an R package and online tool for visualisation of EWAS results in a genomic region of interest. coMET generates a regional plot of epigenetic-phenotype association results and the estimated DNA methylation correlation between CpG sites (co-methylation), with further options to visualise genomic annotations based on ENCODE data, gene tracks, reference CpG-sites, and user-defined features. The tool can be used to display phenotype association signals and correlation patterns of microarray or sequencing-based DNA methylation data, such as Illumina Infinium 450k, WGBS, or MeDIP-seq, as well as other types of genomic data, such as gene expression profiles. The software is available as a user-friendly online tool from http://epigen.kcl.ac.uk/comet and as an R Bioconductor package. Source code, examples, and full documentation are also available from GitHub. CONCLUSION: Our new software allows visualisation of EWAS results with functional genomic annotations and with estimation of co-methylation patterns. coMET is available to a wide audience as an online tool and R package, and can be a valuable resource to interpret results in the fast growing field of epigenetics. The software is designed for epigenetic data, but can also be applied to genomic and functional genomic datasets in any species.


Assuntos
Gráficos por Computador , Metilação de DNA , DNA/genética , Epigênese Genética/genética , Software , Algoritmos , Ilhas de CpG , Humanos , Fenótipo
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