ABSTRACT
As summarized in Section 11.2, pharmacogenetics and genomics, from here on referred to as PGx, utilize a plethora of methods and approaches to study relationships between genes/genome and phenotype/phenome. Among those are genome-wide association studies (GWAS) to explore relationships between genetic variation and pharmacokinetic and pharmacodynamic eects as well as adverse events [4-6] (examples are provided in Section 11.2). Oen, sequence variation(s) detected in GWAS studies only reveal associations that partially explain the observed variability. Ritchie and coauthors review current methods and explore emerging approaches to integrate big omics data to reveal relationships between genomic variation and phenome. ey also argue that there is a need for even more advanced analysis strategies to utilize the high-throughput omic data to discover not only true associations, but also associations that are currently missed [3]. In addition to the host omic-composition, there is a growing body of evidence suggesting that the gut microbiome not only aects host physiology and health (see Chapter 9), but is also contributing to interindividual drug
metabolism and response (https:// pharmacomicrobiomics.com). Saad and coauthors provide a summary on gut pharmacomicrobiomics and review the complex interactions between drugs and microbes (www.gutpathogens. com/content/4/1/16). While the microbiome response-modifying eect has long been appreciated in the elds of nutrition and toxicology, we are only at the beginning to understand the intricate balance between the microbiome and the other omic layers.
