Gut microbiota associations with common diseases and prescription medications in a population-based cohort

Integration of microbiology, molecular pathology, and epidemiology: a new paradigm to explore the pathogenesis of microbiome-driven neoplasms

Molecular pathological epidemiology (MPE) is an integrative transdisciplinary field that addresses heterogeneous effects of exogenous and endogenous factors (collectively termed 'exposures'), including microorganisms, on disease occurrence and consequences, utilising molecular pathological signatures of the disease. In parallel with the paradigm of precision medicine, findings from MPE research can provide aetiological insights into tailored strategies of disease prevention and treatment. Due to the availability of molecular pathological tests on tumours, the MPE approach has been utilised predominantly in research on cancers including breast, lung, prostate, and colorectal carcinomas. Mounting evidence indicates that the microbiome (inclusive of viruses, bacteria, fungi, and parasites) plays an important role in a variety of human diseases including neoplasms. An alteration of the microbiome may be not only a cause of neoplasia but also an informative biomarker that indicates or mediates the association of an epidemiological exposure with health conditions and outcomes. To adequately educate and train investigators in this emerging area, we herein propose the integration of microbiology into the MPE model (termed 'microbiology-MPE'), which could improve our understanding of the complex interactions of environment, tumour cells, the immune system, and microbes in the tumour microenvironment during the carcinogenic process. Using this approach, we can examine how lifestyle factors, dietary patterns, medications, environmental exposures, and germline genetics influence cancer development and progression through impacting the microbial communities in the human body. Further integration of other disciplines (e.g. pharmacology, immunology, nutrition) into microbiology-MPE would expand this developing research frontier. With the advent of high-throughput next-generation sequencing technologies, researchers now have increasing access to large-scale metagenomics as well as other omics data (e.g. genomics, epigenomics, proteomics, and metabolomics) in population-based research. The integrative field of microbiology-MPE will open new opportunities for personalised medicine and public health. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

'RA and the microbiome: do host genetic factors provide the link?

Rheumatoid arthritis (RA) is a chronic autoimmune disease, characterised by painful synovium inflammation, bony erosions, immune activation and the circulation of autoantibodies. Despite recent advances in therapeutics enabling disease suppression, there is a considerable demand for alternative therapeutic strategies as well as optimising those available at present. The relatively low concordance rate between monozygotic twins, 20–30% contrasts with heritability estimates of ∼65%, indicating a substantive role of other risk factors in RA pathogenesis. There is established evidence that RA has an infective component to its aetiology. More recently, differences in the commensal microbiota in RA compared to controls have been identified. Studies have shown that the gut, oral and lung microbiota is different in new onset treatment naïve, and established RA patients, compared to controls. Key taxonomic associations are an increase in abundance of Porphyromonas gingivalis and Prevotella copri in RA patients, compared to healthy controls. Host genetics may provide the link between disease and the microbiome. Genetic influence may be mediated by the host immune system; a differential response to RA associated taxa is suggested. The gut microbiome contains elements which are as much as 30% heritable. A better understanding of the influence of host genetics will shed light onto the role of the microbiome in RA. Here we review the role of the microbiome in RA through the lens of host genetics, and consider future research areas addressing microbiome study design and bioinformatics approaches.

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Rheumatoid arthritis (RA) affects 1% of the population and is highly debilitating.

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RA is ~65% heritable, yet the concordance rate between monozygotic twins is just 20–30%, indicating a substantive role of other risk factors.

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Studies have shown that the gut, oral and lung microbiome is different in treatment naïve and established RA patients, compared to controls.

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Current findings suggest an important influence of host genetics on the microbiome, which may contribute to RA via the host immune system.

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Associations of the microbiome with RA described thus far are confounded by host genetics, and future studies need to take account of this.

The Microbiome Stress Project: Toward a Global Meta-Analysis of Environmental Stressors and Their Effects on Microbial Communities

Microbial community structure is highly sensitive to natural (e.g., drought, temperature, fire) and anthropogenic (e.g., heavy metal exposure, land-use change) stressors. However, despite an immense amount of data generated, systematic, cross-environment analyses of microbiome responses to multiple disturbances are lacking. Here, we present the Microbiome Stress Project, an open-access database of environmental and host-associated 16S rRNA amplicon sequencing studies collected to facilitate cross-study analyses of microbiome responses to stressors. This database will comprise published and unpublished datasets re-processed from the raw sequences into exact sequence variants using our standardized computational pipeline. Our database will provide insight into general response patterns of microbiome diversity, structure, and stability to environmental stressors. It will also enable the identification of cross-study associations between single or multiple stressors and specific microbial clades. Here, we present a proof-of-concept meta-analysis of 606 microbiomes (from nine studies) to assess microbial community responses to: (1) one stressor in one environment: soil warming across a variety of soil types, (2) a range of stressors in one environment: soil microbiome responses to a comprehensive set of stressors (incl. temperature, diesel, antibiotics, land use change, drought, and heavy metals), (3) one stressor across a range of environments: copper exposure effects on soil, sediment, activated-sludge reactors, and gut environments, and (4) the general trends of microbiome stressor responses. Overall, we found that stressor exposure significantly decreases microbiome alpha diversity and increases beta diversity (community dispersion) across a range of environments and stressor types. We observed a hump-shaped relationship between microbial community resistance to stressors (i.e., the average pairwise similarity score between the control and stressed communities) and alpha diversity. We used Phylofactor to identify microbial clades and individual taxa as potential bioindicators of copper contamination across different environments. Using standardized computational and statistical methods, the Microbiome Stress Project will leverage thousands of existing datasets to build a general framework for how microbial communities respond to environmental stress.

Urinary Levels of Trimethylamine-N-Oxide and Incident Coronary Heart Disease: A Prospective Investigation Among Urban Chinese Adults

Background Trimethylamine-N-oxide ( TMAO ), a diet-derived, gut microbial-host cometabolite, has been associated with adverse cardiovascular outcomes in patient populations; however, evidence is lacking from prospective studies conducted in general populations and non-Western populations. Methods and Results We evaluated urinary levels of TMAO and its precursor metabolites (ie, choline, betaine, and carnitine) in relation to risk of coronary heart disease ( CHD ) among Chinese adults in a nested case-control study, including 275 participants with incident CHD and 275 individually matched controls. We found that urinary TMAO , but not its precursors, was associated with risk of CHD . The odds ratio for the highest versus lowest quartiles of TMAO was 1.91 (95% CI, 1.08-3.35; Ptrend=0.008) after adjusting for CHD risk factors including obesity, diet, lifestyle, and metabolic diseases and 1.75 (95% CI, 0.96-3.18; Ptrend=0.03) after further adjusting for potential confounders or mediators including central obesity, dyslipidemia, inflammation, and intake of seafood and deep-fried meat or fish, which were associated with TMAO level in this study. The odds ratio per standard deviation increase in log- TMAO was 1.30 (95% CI, 1.03-1.63) in the fully adjusted model. A history of diabetes mellitus modified the TMAO - CHD association. A high TMAO level (greater than or equal to versus lower than the median) was associated with odds ratios of 6.21 (95% CI, 1.64-23.6) and 1.56 (95% CI, 1.00-2.43), respectively, among diabetic and nondiabetic participants ( Pinteraction=0.02). Diabetes mellitus status also modified the associations of choline, betaine, and carnitine with risk of CHD ; significant positive associations were found among diabetic participants, but null associations were noted among total and nondiabetic participants. Conclusions Our study suggests that TMAO may accelerate the development of CHD , highlighting the importance of diet-gut microbiota-host interplay in cardiometabolic health.

The alteration of gut microbiota in newly diagnosed type 2 diabetic patients

OBJECTIVES

Gut microbiota dysbiosis is known to be associated with diabetes; however, the findings of previous studies are conflicting. To clarify the association between type 2 diabetes and the gut microbiota, the present study analyzed the composition of fecal gut microbiota and its correlation with specific clinical parameters in newly diagnosed, treatment-naive diabetic patients and healthy controls.

METHODS

A total of 50 patients with newly diagnosed type 2 diabetes and 50 healthy control participants were enrolled in the study. Fecal samples, blood samples, and food diaries were collected from the diabetic patients before and 3 mo after the start of their antidiabetic treatment. These samples were also collected from the healthy controls. The gut microbiota was characterized by 16S ribosomal RNA analysis using quantitative polymerase chain reaction.

RESULTS

The fecal count of Lactobacillus was significantly higher, whereas Clostridium coccoides and Clostridium leptum were significantly lower in the diabetic patients compared with the healthy controls. Lactobacillus was significantly positively correlated with glucose, glycated hemoglobin, and the homeostatic model assessment, whereas C. coccoides and C. leptum were significantly negatively correlated with the diabetic parameters. In addition, the newly diagnosed diabetic patients had a significant decrease in the presence of C. coccoides and C. leptum after 3 mo of treatment compared with before treatment.

CONCLUSIONS

The amount of fecal Lactobacillus, C. coccoides, and C. leptum was significantly different between the patients with type 2 diabetes and the healthy controls. The levels of Clostridium were also significantly changed after 3 mo of treatment in the diabetic patients. Further research is needed to clarify the correlation or causal relationship between the gut microbiota dysbiosis and type 2 diabetes.

Vitamin D and the gut microbiome: a systematic review of in vivo studies

PURPOSE

Variation in the human microbiome has been linked with a variety of physiological functions, including immune regulation and metabolism and biosynthesis of vitamins, hormones, and neurotransmitters. Evidence for extraskeletal effects of vitamin D has been accruing and it has been suggested that the effect of vitamin D on health is partially mediated through the microbiome. We aimed to critically evaluate the evidence linking vitamin D and the gastrointestinal microbiome.

METHODS

We systematically searched the Embase, Web of Science, PubMed and CINAHL databases, including peer-reviewed publications that reported an association between a measure of vitamin D and the gastrointestinal microbiome in humans or experimental animals.

RESULTS

We included 10 mouse and 14 human studies. Mouse studies compared mice fed diets containing different levels of vitamin D (usually high versus low), or vitamin D receptor knockout or Cyp27B1 knockout with wild-type mice. Five mouse studies reported an increase in Bacteroidetes (or taxa within that phylum) in the low vitamin D diet or gene knockout group. Human studies were predominantly observational; all but two of the included studies found some association between vitamin D and the gut microbiome, but the nature of differences observed varied across studies.

CONCLUSIONS

Despite substantial heterogeneity, we found evidence to support the hypothesis that vitamin D influences the composition of the gastrointestinal microbiome. However, the research is limited, having been conducted either in mice or in mostly small, selected human populations. Future research in larger population-based studies is needed to fully understand the extent to which vitamin D modulates the microbiome.

Oral probiotic combination of Lactobacillus and Bifidobacterium alters the gastrointestinal microbiota during antibiotic treatment for Clostridium difficile infection

Perturbations in the gastrointestinal microbiome caused by antibiotics are a major risk factor for Clostridium difficile infection (CDI). Probiotics are often recommended to mitigate CDI symptoms; however, there exists only limited evidence showing probiotic efficacy for CDI. Here, we examined changes to the GI microbiota in a study population where probiotic treatment was associated with significantly reduced duration of CDI diarrhea. Subjects being treated with standard of care antibiotics for a primary episode of CDI were randomized to probiotic treatment or placebo for 4 weeks. Probiotic treatment consisted of a daily multi-strain capsule (Lactobacillus acidophilus NCFM, ATCC 700396; Lactobacillus paracasei Lpc-37, ATCC SD5275; Bifidobacterium lactis Bi-07, ATCC SC5220; Bifidobacterium lactis B1-04, ATCC SD5219) containing 1.7 x 1010 CFUs. Stool was collected and analyzed using 16S rRNA sequencing. Microbiome analysis revealed apparent taxonomic differences between treatments and timepoints. Subjects administered probiotics had reduced Verrucomicrobiaceae at week 8 compared to controls. Bacteroides were significantly reduced between weeks 0 to 4 in probiotic treated subjects. Ruminococcus (family Lachnospiraceae), tended to be more abundant at week 8 than week 4 within the placebo group and at week 8 than week 0 within the probiotic group. Similar to these results, previous studies have associated these taxa with probiotic use and with mitigation of CDI symptoms. Compositional prediction of microbial community function revealed that subjects in the placebo group had microbiomes enriched with the iron complex transport system, while probiotic treated subjects had microbiomes enriched with the antibiotic transport system. Results indicate that probiotic use may impact the microbiome function in the face of a CDI; yet, more sensitive methods with higher resolution are warranted to better elucidate the roles associated with these changes. Continuing studies are needed to better understand probiotic effects on microbiome structure and function and the resulting impacts on CDI.