title: Biomarkers for assessing population and individual health and disease related to stress and adaptation.
abstract: Biomarkers are important in stress biology in relation to assessing individual and population health. They facilitate tapping meaningfully into the complex, non-linear interactions that affect the brain and multiple systems of the body and promote adaptation or, when dysregulated, they can accelerate disease processes. This has demanded a multifactorial approach to the choice of biomarkers. This is necessary in order to adequately describe and predict how an individual embedded in a particular social and physical environment, and with a unique genotype and set of lifetime experiences, will fare in terms of health and disease risk, as well as how that individual will respond to an intervention. Yet, at the same time, single biomarkers can have a predictive or diagnostic value when combined with carefully designed longitudinal assessment of behavior and disease related to stress. Moreover, the methods of brain imaging, themselves the reflection of the complexity of brain functional architecture, have provided new ways of diagnosing, and possibly differentiating, subtypes of depressive illness and anxiety disorders that are precipitated or exacerbated by stress. Furthermore, postmortem assessment of brain biomarkers provides important clues about individual vulnerability for suicide related to depression and this may lead to predictive biomarkers to better treat individuals with suicidal depression. Once biomarkers are available, approaches to prevention and treatment should take advantage of the emerging evidence that activating brain plasticity together with targeted behavioral interventions is a promising strategy.
authors.affiliation: Harold and Margaret Milliken Hatch, Laboratory of Neuroendocrinology, The Rockefeller University, 1230 York Avenue, New York, NY 10065. Electronic address: mcewen@rockefeller.edu.
authors.forename: Bruce S
authors.initials: BS
authors.lastname: McEwen
mesh_terms: D000223:Adaptation, Psychological; D052636:Allostasis; D000818:Animals; D018687:Antidepressive Agents, Second-Generation / Q000627:therapeutic use; D001007:Anxiety / Q000097:blood; D001008:Anxiety Disorders / Q000097:blood; D015415:Biomarkers / Q000097:blood*; D001921:Brain / Q000378:metabolism / Q000473:pathology* / Q000503:physiopathology*; D003863:Depression / Q000097:blood; D003866:Depressive Disorder / Q000097:blood; D005473:Fluoxetine / Q000627:therapeutic use; D059907:Functional Neuroimaging; D005947:Glucose / Q000378:metabolism; D006304:Health Status; D006801:Humans; D006854:Hydrocortisone / Q000097:blood; D001523:Mental Disorders / Q000097:blood / Q000175:diagnosis* / Q000473:pathology; D023421:Models, Animal; D011159:Population Surveillance / Q000379:methods*; D011237:Predictive Value of Tests; D017367:Selective Serotonin Reuptake Inhibitors / Q000627:therapeutic use; D013315:Stress, Psychological / Q000097:blood / Q000150:complications*; D013405:Suicide / Q000523:psychology; D000092864:Suicide Prevention
chemical_list: D018687:Antidepressive Agents, Second-Generation; D015415:Biomarkers; D005473:Fluoxetine; D005947:Glucose; D006854:Hydrocortisone; D017367:Selective Serotonin Reuptake Inhibitors
keywords: Allostatic load; Amygdala; Hippocampus; Mood disorders; Prefrontal cortex