Candidate Biomarkers in Psychiatric Disorders: State of the Field

Details

• Personal Author:
  Abi-Dargham A ; Ali F ; DeLorenzo C ; Domschke K ; Horga G ; Jutla A ; Kotov R ; Krystal JH ; Moeller SJ ; Paulus MP ; Rubio JM ; Sanacora G ; Veenstra-VanderWeele J
• Description:
  The field of psychiatry is hampered by a lack of robust, reliable and valid biomarkers that can aid in objectively diagnosing patients and providing individualized treatment recommendations. Here we review and critically evaluate the evidence for the most promising biomarkers in the psychiatric neuroscience literature for autism spectrum disorder, schizophrenia, anxiety disorders and post-traumatic stress disorder, major depression and bipolar disorder, and substance use disorders. Candidate biomarkers reviewed include various neuroimaging, genetic, molecular and peripheral assays, for the purposes of determining susceptibility or presence of illness, and predicting treatment response or safety. This review highlights a critical gap in the biomarker validation process. An enormous societal investment over the past 50 years has identified numerous candidate biomarkers. However, to date, the overwhelming majority of these measures have not been proven sufficiently reliable, valid and useful to be adopted clinically. It is time to consider whether strategic investments might break this impasse, focusing on a limited number of promising candidates to advance through a process of definitive testing for a specific indication. Some promising candidates for definitive testing include the N170 signal, an event-related brain potential measured using electroencephalography, for subgroup identification within autism spectrum disorder; striatal resting-state functional magnetic resonance imaging (fMRI) measures, such as the striatal connectivity index (SCI) and the functional striatal abnormalities (FSA) index, for prediction of treatment response in schizophrenia; error-related negativity (ERN), an electrophysiological index, for prediction of first onset of generalized anxiety disorder, and resting-state and structural brain connectomic measures for prediction of treatment response in social anxiety disorder. Alternate forms of classification may be useful for conceptualizing and testing potential biomarkers. Collaborative efforts allowing the inclusion of biosystems beyond genetics and neuroimaging are needed, and online remote acquisition of selected measures in a naturalistic setting using mobile health tools may significantly advance the field. Setting specific benchmarks for well-defined target application, along with development of appropriate funding and partnership mechanisms, would also be crucial. Finally, it should never be forgotten that, for a biomarker to be actionable, it will need to be clinically predictive at the individual level and viable in clinical settings. [Description provided by NIOSH]
• Subjects:
  Biomarkers Mental Health Nervous System Occupational Health Safety
• Keywords:
  Anxiety Disorders Author Keywords: Biomarkers Autism Spectrum Disorder Bipolar Disorder Brain Function Depression Genetic Factors GWAS Imaging Techniques Mental Health Neuroimaging Post-traumatic Stress Disorder Precision Medicine Psychological Testing PTSD Schizophrenia Substance Use Disorder Treatment Response

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• ISSN:
  1723-8617
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  Connecticut ; New York ; Oklahoma ; OSHA Region 1 ; OSHA Region 2 ; OSHA Region 6
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  236-262
• Volume:
  22
• Issue:
  2
• NIOSHTIC Number:
  nn:20069698
• Citation:
  World Psychiatry 2023 Jun; 22(2):236-262
• Federal Fiscal Year:
  2023
• Performing Organization:
  State University of New York - Stony Brook
• Peer Reviewed:
  True
• Start Date:
  20190701
• Source Full Name:
  World Psychiatry
• End Date:
  20210630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:310ebe5e3f7cfd9649601c59d7b69ba9a740a039eb701e5b83e8e2036ff064a09e75d4ca47bf6751ba4caecfc6398c7bbcb80d4d1927e1a3572c4317393f6df9
• Download URL:
  https://stacks.cdc.gov/view/cdc/208073/cdc_208073_DS1.pdf
• File Type:
  [PDF - 512.16 KB ]