Sharpening Precision Medicine by a Thorough Interrogation of Metabolic Individuality

• Main Authors: Kirk Beebe, Adam D. Kennedy
• Format: Article
• Language: English
• Published: Elsevier 2016-01-01
• Series: Computational and Structural Biotechnology Journal
• Subjects: Precision Medicine; Metabolomics; Inborn Errors of Metabolism; Mass Spectrometry; Genome Wide Association Study; Untargeted Analysis; Diagnostics
• Online Access: http://www.sciencedirect.com/science/article/pii/S2001037015300209

Precision medicine is an active component of medical practice today, but aspirations are to both broaden its reach to a greater diversity of individuals and improve its “precision” by enhancing the ability to define even more disease states in combination with associated treatments. Given complexity of human phenotypes, much work is required. In this review, we deconstruct this challenge at a high level to define what is needed to move closer toward these aspirations. In the context of the variables that influence the diverse array of phenotypes across human health and disease – genetics, epigenetics, environmental influences, and the microbiome – we detail the factors behind why an individual's biochemical (metabolite) composition is increasingly regarded as a key element to precisely defining phenotypes. Although an individual's biochemical (metabolite) composition is generally regarded, and frequently shown, to be a surrogate to the phenotypic state, we review how metabolites (and therefore an individual's metabolic profile) are also functionally related to the myriad of phenotypic influencers like genetics and the microbiota. We describe how using the technology to comprehensively measure an individual's biochemical profile – metabolomics – is integrative to defining individual phenotypes and how it is currently being deployed in efforts to continue to elaborate on human health and disease in large population studies. Finally, we summarize instances where metabolomics is being used to assess individual health in instances where signatures (i.e. biomarkers) have been defined.