Editorial: The microbiome as a source of new enterprises and job creation Meta-analysis generates and prioritizes hypotheses for translational microbiome research

The potential for microbiome-based therapeutics and diagnostics has generated significant excitement among scientists, clinicians and entrepreneurs. Much of basic microbiome research remains clinically relevant and readily translatable. Most human-associated microbial communities are fairly non-invasive to sample (e.g. stool, skin swabs, vaginal swabs), allowing for relatively easy access to clinical human samples. Once identified and developed, microbiome-based interventions are likely to be non-invasive and quickly adopted into standards of care. For example, identifying new uses for existing antibiotics and probiotics in microbiome-related diseases could quickly transform clinical practice. From a clinical perspective, the microbial communities in our guts have been implicated in many diseases, including neurological conditions, metabolic disorders and autoimmune diseases. Encouraged by the remarkable success of faecal microbiota transplants (FMTs) in treating recurrent Clostridium difficile infection, clinicians are pursuing FMTs in hundreds of ongoing clinical trials. Finally, established biotechnology companies are expanding into the microbiome and start-ups related to the microbiome are rapidly growing in number. Although the potential for impact is vast, successes have so far been limited: a recent clinical trial testing a defined microbial consortia for treating C. diff yielded disappointing results (Ratner, 2016), and results from FMT trials in conditions other than recurrent C. diff infection indicate that many conditions may have a variable and complex response to FMT (Moayyedi et al., 2015). Despite the increasing research in this field, we have few generalizable insights into the human microbiome and disease, which may partially explain our current limited translational successes. Microbiome research has few established and standardized experimental and analysis methods, and individual studies often provide inconsistent or conflicting results. Clinical trials often report only outcome measures (e.g. remission rates) and broad microbial community characteristics (e.g. alpha diversity), without investigating specific microbiome alterations in detail. Microbiome studies which investigate specific microbial changes associated with disease frequently report finding ‘dysbiosis’, which is usually poorly defined and of uncertain therapeutic or diagnostic relevance to the disease of interest (Olesen and Alm, 2016; Hooks and O’Malley, 2017). Improving our foundational understanding of the relationship between the human microbiome and disease would likely lead to more and faster translational successes. One way to generalize and integrate knowledge across studies is to perform a meta-analysis of existing work (Glass, 1976). In the microbiome field, where basic science, clinical trials and commercialization are all happening simultaneously, meta-analysis can be used to integrate the knowledge from these many perspectives and choose avenues to pursue which are more likely to lead to successful outcomes. For scientific researchers, meta-analysis of existing studies increases our power to detect true signals, reduces the number of false positives by identifying consistencies across independent studies and can strengthen existing findings by demonstrating their reproducibility. In clinical trials and entrepreneurship, meta-analysis can help identify therapies or products that are most likely to generalize across a variety of patient cohorts. Meta-analysis across multiple diseases could perhaps even identify therapies that may be applicable to multiple indications.