Personal Omics for Precision Health

Abstract

The convergence of scientific capability and technology that generates vast health data at diminishing cost has generated opportunities, challenges, and anticipation surrounding future data-centric healthcare models. Individualized health data spanning biomolecular, physiological, and environmental dimensions comprise a “personal omics profile”. Here we discuss methods and opportunities to bridge genome and dynamic physiology, detect disease at an early stage, and uncover lifestyle and environmental patterns associated with disease. Significant challenges exist to aggregate, integrate, and protect personal omics data to advance our understanding of disease, enable data-driven clinical decisions, and motivate individuals to sustain behavioral change.

Keywords: clinical decision-making; metabolomics; proteome; transcriptome; whole exome sequencing.

Figure 1.. Overview of personal omics.

A) Omic measures span genotype, phenotype, and environment and range from mostly static to highly dynamic. Sequencing, mass spectrometry, and smartphone/wearable sensors are principal technologies driving personal omics. B) Multiomic measures of human-associated microbes that play a vital role in human health. C) The past two decades have seen a dramatic increase in NCBI PubMed records containing personal omics keywords. D) Through regular sampling and high frequency sampling during health perturbations such as disease progression or infection, personal omics reveals the cause, consequence, and course of health changes. E) Personal omics comprises holistic molecular, physiological, and environmental profiling of an individual over time.