Biological markers, or biomarkers, are substances that indicate a particular biological state. Today, neuroscientific researchers are using a vast array of biomarkers, ranging from neuroimaging results to genetic variations to levels of cell proteins, to help predict, diagnose, and treat a variety of brain-related disease states and neuropsychiatric disorders.
What is a biomarker?[i]
The simplest example of a biomarker is an antibody. When someone suffers from an infection, the body’s immune system mounts a defensive front through the production of antibodies. These antibodies are specific to the virus or bacteria invading the body. As such, the presence of a particular antibody in the blood is evidence, or a biomarker, of a specific infection, even if the virus or bacterium itself cannot be directly measured. For example, physicians use an antibody test to diagnose Human-Immunodeficiency Virus (HIV) in patients—an invaluable biomarker in the identification and treatment of this sobering disease.
Biomarkers are used across scientific disciplines—for example, in geology, the presence of certain soil extracts can help predict where scientists might find rich oil deposits. But in the field of neuroscience, these biological characteristics are offering valuable and much-needed insight into the causes and development of debilitating disorders that affect millions of people across the globe. Current neuroscientific biomarkers are helping researchers better understand the etiology of Alzheimer’s disease, the prognosis after brain injury, and the selection of antidepressant medication to treat chronic depression.
How do biomarkers help predict or diagnose neuropsychiatric disease? An example.[ii] [iii] [iv]
Disorders of the nervous system are often complex. However, biomarkers can assist in predicting, diagnosing, and sub-typing complicated neuropsychiatric disorders alongside behavioral assessment and other clinical tools. Researchers from the University of California Los Angeles and Rush University Medical Center identified specific changes to the brain that might help predict who will develop Alzheimer’s disease. Using neuroimaging techniques, these researchers have discovered loss of brain tissue in an area of the brain called the caudate nucleus as well as thinning in regions of the cortex that receive input from a brain structure called the substantia innominata. These biomarkers helped to predict who was at risk to develop Alzheimer’s disease, and may assist future clinicians by allowing them to make early diagnoses and better understand the progression of the disease.
Major depressive disorder often manifests itself differently across individuals—for example, some patients with the disorder may be suicidal, others may not be. Both low cholesterol and decreased brain-derived neurotrophic factor have been linked with suicidal behavior in individuals. Adding these neurobiological predictors to an arsenal of diagnostic tools, psychiatrists can better predict which patients may be more at greater risk for taking their own life.
How do biomarkers help clinicians better predict disease outcomes? An example.[v]
Brain injuries result in a cascade of molecular changes in the brain. Researchers from the Department of Applied Neurobiology at the Walter Reed Army Institute of Research have identified specific changes in the regulation of different proteins after two types of brain injury, one being a stroke and the other being the ballistic type injury you see after a gunshot wound, in a rat model. By understanding these protein changes correlated with specific types of injury, the researchers hope these biomarkers may offer clinicians ways to better characterize how these acute brain injuries may impact function.
How might biomarkers help clinicians select personalized treatments for disease? An example.[vi]
For many neuropsychiatric disorders, there are a variety of possible treatment options. In the case of depression, selecting an antidepressant medication is often a process of trial and error for psychiatrists. With over twenty Food and Drug Administration (FDA) approved medications to choose from, it can be a long, arduous process to find the drug that will alleviate depressive symptoms in an individual patient. Researchers at the University of California Los Angeles’ Semel Institute for Neuroscience and Human Behavior have demonstrated that a particular pattern of brain activation measured by quantitative electroencephalography (QEEG), a clinical biomarker, can help predict whether a depressed patient will respond better to one type of antidepressant medication over another. They are hopeful the discovery of other clinical biomarkers using this technique may also pinpoint the right treatment options for Attention Deficit and Hyperactivity Disorder (ADHD), Huntington’s disease, and chronic pain disorders in the future.
What are the challenges to using biomarkers in the study of the nervous system?[vii]
The nervous system is very complex, with a variety of different neurotransmitters, neurohormones, and neuropeptides not only influencing neural signaling directly but modulating each other’s ability to work in the synapse. This complexity can make it difficult to pinpoint specific biomarkers and understand how they are related to disease. Specifically, even when a particular biomarker is discovered, it is often unclear whether that particular marker, be it a molecule or some type of clinical measurement, is directly correlated to the disease state in question or simply associated with other factors related to the disease.
The blood-brain barrier, the protective layer of endothelial cells that separates the brain from circulating blood, also complicates matters when considering molecular biomarkers. Clinicians cannot directly access brain tissue to look for or measure specific biomarkers of interest. Instead, they must rely on measurements of those biological characteristics in blood, saliva, or cerebrospinal fluid, which may or may not reflect the levels found inside the brain. This is sometimes referred to as “finding windows to the brain.”
What can we expect to see from biomarkers in the future?[viii]
Given the need for reliable neuroscientific biomarkers in the detection and treatment of psychiatric and neurological disorders, there has been a concerted effort to bring academia and industry together to help identify new and promising candidates. Despite the challenges involved in discovering biomarkers in the study of brain-related disease, neuroscientists are quite optimistic about their contribution to our future understanding of these disorders. As data from fields like genetics, molecular and cellular biology, neuroimaging, and behavioral research converge from the bench and the bedside, it is expected that more precise and reliable biological characteristics will provide clinicians the right tools to diagnose and manage the brain-related diseases and disorders that plague millions of people every day.
[ii] Madsen SK, Ho AJ, Hua X, Saharan PS, Jack Jr. CR, Weiner MW, Toga AW and Thompson PM. Caudate atrophy and its clinical correlates in 400 Alzheimer’s disease, MCI and healthy elderly subjects. Program No. 348.4. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2010. Online.
[iii] George S, Mufson EF, Shah RC and Detoledo-Morrell L. Cortical thinning in the substantia innominate project sites in incipient Alzheimer’s disease. Program No. 756.9. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2010. Online.
[iv] Lee BH and Kim YK. Potential peripheral biological predictors of suicidal behavior in major depressive disorder. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 11 August 2010.
[v] Yao C, Williams AJ, Ottens AK, May Lu XC, Chen R, Wang KK, Hayes RL, Tortella FC and Dave JR. Detection of protein biomarkers using high-throughput immunoblotting following focal ischemic or penetrating ballistic-like brain injuries in rats. Brain Injury. 2008, 22(10): 723-732
[vi] Leuchter AF, Cook IA, Hamilton SP, Narr KL, Toga A, Hunter AM, Faull K, Whitelegge J, Andrews AM, Loo J, Way B, Nelson SF, Horvath S and Lebowitz BD. Biomarkers to predict antidepressant response. Current Psychiatry Reports. 2010, 12(6): 553-562.