A new electroencephalography (EEG) biomarker has been identified by an international team of researchers. This neural biomarker can facilitate in predicting the efficacy of antidepressants in treating depression, according to the Science and Technology Daily.
Conducted by researchers from the South China University of Technology and their international collaborators, the research was published in the journal Nature Biotechnology.
A bio-marker, or biological marker is a measurable indicator of some biological state or condition. Biomarkers are often measured and evaluated to examine normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Biomarkers are used in many scientific fields.
Antidepressants are widely prescribed to relieve depression, but their efficacy varies from person to person and there is a lack of quantitative biomarkers to assist personalized treatment of mental diseases.
Antidepressants are medications used to treat major depressive disorder, some anxiety disorders, some chronic pain conditions, and to help manage some addictions.
Common side-effects of antidepressants include dry mouth, weight gain, dizziness, headaches, and sexual dysfunction. Most types of antidepressants are typically safe to take, but may cause increased thoughts of suicide when taken by children, adolescents, and young adults.
Discontinuation syndrome can occur after stopping any antidepressant which resembles recurrent depression.
The research team proposed a machine-learning algorithm to analyze a large EEG dataset and discovered the EEG signature that can predict the efficacy of antidepressants. Then they validated the signature in multiple datasets and explored the related neural mechanism.
Wu Wei, one of the researchers, told the newspaper that EEG is a low-cost and accessible tool and the research finding is expected to improve treatment plans and promote the personalized treatment of mental diseases. Enditem