Scientists are both captivated by the potential of the biggest life science data-gathering project ever undertaken, and challenged with the immensity of the undertaking. Yet even with the vast riches of data currently available, life scientists typically approach a new project by determining how to procure their samples, and then they collect discrete data around a narrow focus (genome, transcriptome, proteome, or microbiome), and analyze those data in isolation.
The Quantified Human Initiative is an effort to combine our natural curiosity about self with new research paradigms that unite narrow studies into multi-faceted analyses to provide deeper insights into the human condition. The initiative was launched in May 2013 during the annual meeting of the Data-Enabled Life Sciences Alliance, DELSA Global. DELSA Global is a transdisciplinary alliance of individuals and organizations from around the world with a common commitment to utilize data-enabled science to benefit society. The alliance was formed 18 months ago from a series of National Science Foundation (NSF) sponsored workshops, as part of a nationwide search for big data solutions.
Two members of DELSA, Dr. Larry Smarr and Dr. Mike Snyder, are pioneers at collecting personal health data. Prof Smarr used a change in job location to inspire a personal health improvement effort. When his efforts proved puzzlingly ineffective he began to delve into his personal physical condition data, cataloging diverse parameters for years in an effort to control his health. Ultimately he found himself ahead of conventional medicine as his data allowed him to identify his heightened state of inflammation that was later determined to be early onset subclinical Crohn’s disease. Prof. Snyder is a geneticist and so embarked on his personal health exploration out of scientific curiosity yet he too uncovered the beginnings of a health condition. That information enabled him to make life choices to manage and perhaps avoid any serious consequences.
These examples show what two individuals, deeply connected to the scientific community and with diverse resources at their disposal, can accomplish. Yet the time is not that far off when these types of data will be routinely gathered for large populations in an effort to better understand the human condition. It is already possible to buy one’s genomic profile (one million of the most-researched SNPs) for $99 and microbiomic profiling is available for $89 from uBiome.
These data are urgently needed because the more we learn about biological systems the more we realize that a true picture requires multi-omics data (data from genomic, transcriptomic, proteomic, and microbiomic studies) with the complexities of a sample captured consistently and concurrently. The life sciences community will use these data to build coherent datasets for studying the “normal condition”, and from that foundation work toward an understanding of genotype-to-phenotype, environment as an influence, or biological variability.
The need for these data was highlighted by a recent study of the health risks of obesity [Science vol. 341, p. 856-858. 2013]. The usual measure of obesity, Body Mass Index (BMI), has long been considered to be inadequate, and was found to sometimes even correlate with increased survival when higher. Further examination has found a complex interplay between BMI and metabolic health, one that will only be understood if multiple diverse parameters are measured for a true picture of health status. Given the enormity of this health issue in terms of emotional, environmental, and financial resources, it is imperative to be able to accurately assess and understand obesity so that it can be managed appropriately.
The Quantified Human Initiative is working to enable that understanding, of not just obesity, but of the complexities of the human condition, both “normal” and disease. With this understanding we hope each individual will be able to make more informed and effective decisions in their everyday lives.