Challenges in the construction of knowledge bases for human microbiome-disease associations

Badal, Varsha D.; Wright, Dustin; Katsis, Yannis; Kim, Ho-Cheol; Swafford, Austin D.; Knight, Rob; Hsu, Chun‐Nan

doi:10.1186/s40168-019-0742-2

Cited by 39 publications

(28 citation statements)

References 105 publications

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“…For example, in a study by Vandeputte et al, the absolute quantity of microbes (measured using quantitative microbiome profiling) was preferred and utilized over the classic relative abundance profiling, since the latter cannot provide information about the extent of directionality of changes in taxa abundance or metabolic potential [270,271]. Building a knowledge base to consolidate the disconnected pieces of knowledge in the field of microbiome, as well as additional innovations including natural language processing, text mining, taxonomic representations, and field wide vocabulary standardization in microbiome research, can accelerate our understanding and aid in moving towards causality [272]. Therefore, further investigations and improvements in quality control, methodology, and pipelines used are required in order to develop global models of gut ecosystem dynamics.…”

Section: Other Challenges Of Clinical Microbiome Studiesmentioning

confidence: 99%

Gut microbiota and cardiovascular disease: opportunities and challenges

et al. 2020

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Coronary artery disease (CAD) is the most common health problem worldwide and remains the leading cause of morbidity and mortality. Over the past decade, it has become clear that the inhabitants of our gut, the gut microbiota, play a vital role in human metabolism, immunity, and reactions to diseases, including CAD. Although correlations have been shown between CAD and the gut microbiota, demonstration of potential causal relationships is much more complex and challenging. In this review, we will discuss the potential direct and indirect causal roots between gut microbiota and CAD development via microbial metabolites and interaction with the immune system. Uncovering the causal relationship of gut microbiota and CAD development can lead to novel microbiome-based preventative and therapeutic interventions. However, an interdisciplinary approach is required to shed light on gut bacterial-mediated mechanisms (e.g., using advanced nanomedicine technologies and incorporation of demographic factors such as age, sex, and ethnicity) to enable efficacious and high-precision preventative and therapeutic strategies for CAD. Key points The causal relationship between gut microbiota and CAD development has yet to be confirmed. It is imperative to understand the potential direct and indirect causal roots between gut microbiota and CAD development via microbial metabolites and interaction with the immune system. Dynamic elements including our diet and demographic factors such as age, sex, and ethnicity can also affect our gut microbiota and CAD development and complicate this matter. Interdisciplinary approaches are required to shed light on the factors involved in the modulation of gut microbiota and its association with CAD development. Elucidating the system-level multifaceted web of factors involved in microbiome-mediated mechanisms and human health and disease can guide novel preventative and therapeutic interventions for CAD.

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Section: Other Challenges Of Clinical Microbiome Studiesmentioning

confidence: 99%

Gut microbiota and cardiovascular disease: opportunities and challenges

et al. 2020

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“…In recent years, many studies have been published, mainly due to the great technical progress and the decrease in the cost of sequencing. 73 Although much effort has been invested, it is still difficult to deduce a clear trend regarding the role of host genetics in the gut microbiome. This difficulty is caused by the inconsistency and unevenness between the studies' results.…”

Section: Discussionmentioning

confidence: 99%

Impact of host genetics on gut microbiome: Take‐home lessons from human and mouse studies

Cahana

Iraqi

2020

Anim Models and Exp Med

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The intestinal microbiome has emerged as an important component involved in various diseases. Therefore, the interest in understanding the factors shaping its composition is growing. The gut microbiome, often defined as a complex trait, contains diverse components and its properties are determined by a combination of external and internal effects. Although much effort has been invested so far, it is still difficult to evaluate the extent to which human genetics shape the composition of the gut microbiota. However, in mouse studies, where the environmental factors are better controlled, the effect of the genetic background was significant. The purpose of this paper is to provide a current assessment of the role of human host genetics in shaping the gut microbiome composition. Despite the inconsistency of the reported results, it can be estimated that the genetic factor affects a portion of the microbiome. However, this effect is currently lower than the initial estimates, and it is difficult to separate the genetic influence from the environmental effect. Additionally, despite the differences between the microbial composition of humans and mice, results from mouse models can strengthen our knowledge of host genetics underlying the human gut microbial variation.

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“…Thus, one important outcome of OHMI is to identify opportunities to collect microbiome data related to pervasive exposures that cut across multiple disease states (for example tobacco smoking and Western versus traditional diets) and which were not captured by the Human Microbiome project. OHMI is expected to become an ontology-based interoperable knowledge base of host-microbiome interactions, which can be used to address many technical challenges in constructing microbiome-disease association knowledge bases [57] and thereby help to solve fundamental scientific questions. We also welcome researchers interested in the topic to participate in the community-based OHMI development and its application to other use cases.…”

Section: Discussionmentioning

confidence: 99%

OHMI: the ontology of host-microbiome interactions

Wang

Zheng

et al. 2019

J Biomed Semant

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BackgroundHost-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases. Extensive HMI studies have generated large amounts of data. We propose that the logical representation of the knowledge derived from these data and the standardized representation of experimental variables and processes can foster integration of data and reproducibility of experiments and thereby further HMI knowledge discovery.MethodsThrough a multi-institutional collaboration, a community-based Ontology of Host-Microbiome Interactions (OHMI) was developed following the Open Biological/Biomedical Ontologies (OBO) Foundry principles. As an OBO library ontology, OHMI leverages established ontologies to create logically structured representations of (1) microbiomes, microbial taxonomy, host species, host anatomical entities, and HMIs under different conditions and (2) associated study protocols and types of data analysis and experimental results.ResultsAligned with the Basic Formal Ontology, OHMI comprises over 1000 terms, including terms imported from more than 10 existing ontologies together with some 500 OHMI-specific terms. A specific OHMI design pattern was generated to represent typical host-microbiome interaction studies. As one major OHMI use case, drawing on data from over 50 peer-reviewed publications, we identified over 100 bacteria and fungi from the gut, oral cavity, skin, and airway that are associated with six rheumatic diseases including rheumatoid arthritis. Our ontological study identified new high-level microbiota taxonomical structures. Two microbiome-related competency questions were also designed and addressed. We were also able to use OHMI to represent statistically significant results identified from a large existing microbiome database data analysis.ConclusionOHMI represents entities and relations in the domain of HMIs. It supports shared knowledge representation, data and metadata standardization and integration, and can be used in formulation of advanced queries for purposes of data analysis.

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Challenges in the construction of knowledge bases for human microbiome-disease associations

Cited by 39 publications

References 105 publications

Gut microbiota and cardiovascular disease: opportunities and challenges

Gut microbiota and cardiovascular disease: opportunities and challenges

Impact of host genetics on gut microbiome: Take‐home lessons from human and mouse studies

OHMI: the ontology of host-microbiome interactions

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