The Potential of Microbiome Big Data in Precision Medicine: Predicting Outcomes Through Machine Learning

Massive sequencing techniques for compositional and functional profiling of the gut microbiome, a key modifier of human health, are generating thousands of data that are well suited to machine learning approaches. In particular, there is now full awareness that such microbiome data, if properly exploited, can improve the prediction of a range of clinical outcomes in disparate contexts. Here, we first discuss the importance of the gut microbiome in human physiology and pathophysiology and then provide some practical examples of machine learning applied to microbiome research in the context of specific disorders, such as obesity and cancer (with a particular focus on colorectal cancer [CRC]), in the field of personalized nutrition, and within the meta-community framework for inter-microbiome predictions. While there is still a long way to go to integrate machine learning into the clinical decision-making scheme, its potential in microbiome-based precision medicine is emerging more than ever.