Intricacies of assessing the human microbiome in epidemiologic studies

• Causal research designs may expand the association between human microbiota and health.
• Standardization of laboratory protocols is likely to aid in interpretation of results.
• Clustering by community state types, or other data reduction mechanisms, may reveal links between the microbiota and health outcomes.
• Deposit of data into accessible databases will further our collective efforts.
• Controlling for correlation with repeated measurements and adjusting for known confounders are key statistical issues in longitudinal studies of the human microbiome.

PurposeIn the past decade, remarkable relationships have been documented between dysbiosis of the human microbiota and adverse health outcomes. This review seeks to highlight some of the challenges and pitfalls that may be encountered during all stages of microbiota research, from study design and sample collection, to nucleic acid extraction and sequencing, and bioinformatic and statistical analysis.MethodsLiterature focused on human microbiota research was reviewed and summarized.ResultsAlthough most studies have focused on surveying the composition of the microbiota, fewer have explored the causal roles of these bacteria, archaea, viruses, and fungi in affecting disease states. Microbiome research is in its relatively early years and many aspects remain challenging, including the complexity and personalized aspects of microbial communities, the influence of exogenous and often confounding factors, the need to apply fundamental principles of ecology and epidemiology, the necessity for new software tools, and the rapidly evolving genomic, technological, and analytical landscapes.ConclusionsIncorporating human microbiome research in large epidemiologic studies will soon help us unravel the intricate relationships that we have with our microbial partners and provide interventional opportunities to improve human health.