Eric E. Schadt writes: It’s been 10 years since an international consortium of scientists successfully completed the mapping of the human genome — a world-changing project that couldn’t have happened without public and private support. The feat neatly coincided with the 50th anniversary of the description of DNA’s double helix by Nobel laureates James Watson and Francis Crick. These are incredible achievements, and today, we couldn’t conceive of the future of medicine without them.
Equally unfathomable is a view of medicine that doesn’t take into account the trove of clinically relevant information available for any individual person, and for all people more generally. DNA holds (among other things) your personal architectural blueprint, but unto itself, it is a fairly static factor, the genome in your normal, healthy cells changing very little over the course of your life. We know with certainty that DNA alone is not a categorical predictor of disease. The BRCA1 or BRCA2 gene mutation, for example, signals significantly higher risk for breast cancer in women, but people with the same defective gene often have remarkably different outcomes. Researchers and the public are asking: why is that?
Whether disease manifests, the age at which it manifests, and how severe it becomes, all depend on a multitude of other factors and the dynamic interplay between them: RNA, metabolites, proteins, healthy and diseased tissues, insulin and cholesterol levels, weight, age, gender, tobacco use, and toxic exposures — to name just a few. To achieve a comprehensive understanding of disease so that we can better diagnose and treat it, researchers must examine a hierarchy of levels — multiple scales — of all observable characteristics. Each element — from molecules, to cells, to tissues, to organs, to the person, and then to the community at large — and the flow of information between these elements, is a biological data point at a particular point in time, and the observation of many millions of these elements in a given individual and population of time is where “big data” meets medicine. [Continue reading…]