Testing in Microbiome-Profiling Studies with MiRKAT, the Microbiome Regression-Based Kernel Association Test

Zhao, Ni; Chen, Jun; Carroll, Ian M.; Ringel–Kulka, Tamar; Epstein, Michael P.; Zhou, Hua; Zhou, Jin; Ringel, Yehuda; Li, Hongzhe; Wu, Michael C.

doi:10.1016/j.ajhg.2015.04.003

Cited by 256 publications

(406 citation statements)

References 38 publications

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“…A Wald test was used to determine significance. To assess the association between adenoma status and β-diversity measures, we used the recently proposed MiRKAT, which is a kernel-based association test based on ecological distance matrices (25). We also used MiRKAT to assess the relationship between polyp characteristics (size, number, location, architecture, histology) and β-diversity measures.…”

Section: Methodsmentioning

confidence: 99%

Shifts in the Fecal Microbiota Associated with Adenomatous Polyps

Hale

Chen

Johnson

et al. 2017

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background Adenomatous polyps are the most common precursor to colorectal cancer (CRC), the second leading cause of cancer death in the United States. We sought to learn more about early events of carcinogenesis by investigating shifts in the gut microbiota of patients with adenomas. Methods We analyzed 16S rRNA gene sequences from the fecal microbiota of patients with adenomas (n=233) and without (n=547). Results Multiple taxa were significantly more abundant in patients with adenomas, including Bilophila, Desulfovibrio, pro-inflammatory bacteria in the genus Mogibacterium, and multiple Bacteroidetes species. Patients without adenomas had greater abundances of Veillonella, Firmicutes (Order Clostridia), and Actinobacteria (family Bifidobacteriales). Our findings were consistent with previously reported shifts in the gut microbiota of CRC patients. Importantly, the altered adenoma profile is predicted to increase primary and secondary bile acid production, as well as starch, sucrose, lipid, and phenylpropanoid metabolism. Conclusions These data hint that increased sugar, protein, and lipid metabolism along with increased bile acid production could promote a colonic environment that supports the growth of bile-tolerant microbes such as Bilophilia and Desulfovibrio. In turn, these microbes may produce genotoxic or inflammatory metabolites such as H2S and secondary bile acids, which could play a role in catalyzing adenoma development and eventually CRC. Impact This study suggests a plausible biological mechanism to explain the links between shifts in the microbiota and CRC. This represents a first step toward resolving the complex interactions that shape the adenoma-carcinoma sequence of CRC and may facilitate personalized therapeutics focused on the microbiota.

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Section: Methodsmentioning

confidence: 99%

Shifts in the Fecal Microbiota Associated with Adenomatous Polyps

Hale

Chen

Johnson

et al. 2017

Cancer Epidemiology, Biomarkers &Amp; Prevention

Self Cite

165

143

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“…Since OMiAT is based on two existing methods, SPU [31] and MiRKAT [25], we start with the descriptions of SPU and MiRKAT. OMiAT shares some of the useful features of SPU and MiRKAT, as follows.…”

Section: Methodsmentioning

confidence: 99%

“…Here, we describe its key formula and ideas and refer to the original paper [25] for more details. MiRKAT is built on the kernel machine regression framework with the kernel formula, Eq.…”

Section: Methodsmentioning

confidence: 99%

A powerful microbiome-based association test and a microbial taxa discovery framework for comprehensive association mapping

2017

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BackgroundThe role of the microbiota in human health and disease has been increasingly studied, gathering momentum through the use of high-throughput technologies. Further identification of the roles of specific microbes is necessary to better understand the mechanisms involved in diseases related to microbiome perturbations. MethodsHere, we introduce a new microbiome-based group association testing method, optimal microbiome-based association test (OMiAT). OMiAT is a data-driven testing method which takes an optimal test throughout different tests from the sum of powered score tests (SPU) and microbiome regression-based kernel association test (MiRKAT). We illustrate that OMiAT efficiently discovers significant association signals arising from varying microbial abundances and different relative contributions from microbial abundance and phylogenetic information. We also propose a way to apply it to fine-mapping of diverse upper-level taxa at different taxonomic ranks (e.g., phylum, class, order, family, and genus), as well as the entire microbial community, within a newly introduced microbial taxa discovery framework, microbiome comprehensive association mapping (MiCAM).ResultsOur extensive simulations demonstrate that OMiAT is highly robust and powerful compared with other existing methods, while correctly controlling type I error rates. Our real data analyses also confirm that MiCAM is especially efficient for the assessment of upper-level taxa by integrating OMiAT as a group analytic method.ConclusionsOMiAT is attractive in practice due to the high complexity of microbiome data and the unknown true nature of the state. MiCAM also provides a hierarchical association map for numerous microbial taxa and can also be used as a guideline for further investigation on the roles of discovered taxa in human health and disease.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-017-0262-x) contains supplementary material, which is available to authorized users.

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“…For instance, Zhao et al (2015) cast the problem in the kernel machine framework and developed a regression-based kernel test MiRKAT. Their framework allows for multiple distances.…”

Section: Discussionmentioning

confidence: 99%

PERMANOVA-S: association test for microbial community composition that accommodates confounders and multiple distances

2016

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Motivation: Recent advances in sequencing technology have made it possible to obtain high-throughput data on the composition of microbial communities and to study the effects of dysbiosis on the human host. Analysis of pairwise intersample distances quantifies the association between the microbiome diversity and covariates of interest (e.g. environmental factors, clinical outcomes, treatment groups). In the design of these analyses, multiple choices for distance metrics are available. Most distance-based methods, however, use a single distance and are underpowered if the distance is poorly chosen. In addition, distance-based tests cannot flexibly handle confounding variables, which can result in excessive false-positive findings.Results: We derive presence-weighted UniFrac to complement the existing UniFrac distances for more powerful detection of the variation in species richness. We develop PERMANOVA-S, a new distance-based method that tests the association of microbiome composition with any covariates of interest. PERMANOVA-S improves the commonly-used Permutation Multivariate Analysis of Variance (PERMANOVA) test by allowing flexible confounder adjustments and ensembling multiple distances. We conducted extensive simulation studies to evaluate the performance of different distances under various patterns of association. Our simulation studies demonstrate that the power of the test relies on how well the selected distance captures the nature of the association. The PERMANOVA-S unified test combines multiple distances and achieves good power regardless of the patterns of the underlying association. We demonstrate the usefulness of our approach by reanalyzing several real microbiome datasets.Availability and Implementation: miProfile software is freely available at https://medschool.vanderbilt.edu/tang-lab/software/miProfile.Contact: z.tang@vanderbilt.edu or g.chen@vanderbilt.eduSupplementary information: Supplementary data are available at Bioinformatics online.

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Testing in Microbiome-Profiling Studies with MiRKAT, the Microbiome Regression-Based Kernel Association Test

Cited by 256 publications

References 38 publications

Shifts in the Fecal Microbiota Associated with Adenomatous Polyps

Shifts in the Fecal Microbiota Associated with Adenomatous Polyps

A powerful microbiome-based association test and a microbial taxa discovery framework for comprehensive association mapping

PERMANOVA-S: association test for microbial community composition that accommodates confounders and multiple distances

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