We have initiated and developed over the last two decades a translational methodology for identifying clinically informative and actionable biomarkers, from bench to bedside. This was made possible by our long-term longitudinal studies combining deep phenotyping, genomics, and clinical outcomes. Biomarkers, as their name implies, are biological measures that serve as objective quantitative markers of the function of an organ or system. In the case of the brain, they can be molecular, electrophysiological, or imaging. Each has advantages and limitations, and synergy may be obtained by their integration. One useful analogy is with cardiology, where cardiac enzymes, EKG, and cardiac imaging may be useful in terms of assessing function and risk. For the brain, surrogate molecular markers can be found in peripheral tissues and fluids. In particular blood, containing secretion products of various tissues, and cells of the immune system, has become a useful accessible source of biomarkers. In cancer, the comparable term of the art for this is “liquid biopsy”.

Why would markers in the blood correlate with brain function and with behavior? First, there are in some instances leakage, direct secretions and exosomes from the nervous system into the blood and other fluids. Second, and more importantly, the vagus nerve directly connects the nervous system with the rest of the body, influencing multiple physiological systems. Third, and most importantly, next to the nervous system, the immune system is the most reactive, active and complex system in the body. It has some developmental commonalities with the nervous system, and has bi-directional interactions during all of life. Moreover, common internal milieu (hormones, al.) and external environmental factors (medications, al.) lead to some common gene expression patterns in brain and white blood cells. Our approach has focused on whole-blood gene expression (RNA) biomarkers. These can be identified using a careful and systematic four-step approach: discovery, prioritization, validation, and testing for clinical utility, in independent cohorts. RNA can be more easily assessed in a comprehensive fashion (whole genome) than the proteome, or metabolome. This is important for unbiased discovery. These type of RNA biomarkers vary over time, unlike DNA, i.e. they have a state severity component. They also have some integration of past events, and predictive ability for future events, i.e. have a trait component as well.

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