In the article written by William P. Hanage, there are 5 questions to be asked: Can experiments detect differences that matter? Does the study show causation or correlation? What is the mechanism? How much do experiments reflect reality? And could anything else explain the results? These questions are addressed through a skeptical lens through the following respective answers: 1) The experiments involved in studying the human microbiome are largely dependent on the use of the 16S RNA gene-a gene that is ancient and essentially universal to bacterial life. Although this kind of sequencing allows for the vast identification of bacteria, this only allows for the identification that the organisms in question are bacteria alone-it does not account for what species they are. This is where microbiome research needs improvement, but it shouldn’t be long before these improvement needs are met. Many studies in microbiology end up being more conclusive in correlative results rather than causative ones, however, correlations do signify a relation between the two variables. Whether that relation is truly causative is yet to be discovered in most microbiological studies. The mechanism by which scientists carry out microbiological studies include ways to test for metabolism, taxa properties, and protein structures. This allows for more specificity in how the correlations in question could be related. The experiments so far mainly reflect the correlation between microbes and health, more so than how it’s done. So, these studies brush the surface of reality, but not the whole of it just yet. In addition to correlative results, one needs to consider what causes what: Do microbes cause changes in health? Or do changes in health cause the proliferation of a certain microbiome?
The questions and the answers they bring are significant to scientific literature because throughout the course, it was easy to assume significant causative relations between microbes and human health. These questions make us take a step back and still take any information with a grain of salt.
