Protein biomarkers of mood disorders

• Published in: International journal of immunopathology and pharmacology Vol. 30; no. 1; pp. 7 - 12
• Main Authors: Rodríguez Cerdeira, Carmen, Sánchez-Blanco, Elena, Sánchez-Blanco, Beatriz, González-Cespón, Jose Luis
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.03.2017; Sage Publications Ltd
• Subjects: Biomarkers; Biomarkers - metabolism; Catechol; Cerebrospinal fluid; Diagnosis; Emotional disorders; Enzymes; Functional anatomy; Humans; Mental disorders; Mood; Mood disorders; Mood Disorders - metabolism; Neurotransmitters; Norepinephrine; Protein structure; Proteomics; Psychotropic drugs; Receptor mechanisms; Saliva; Structure-function relationships; saliva; mood disorder; proteomics; metabolomics; cerebrospinal fluid; biomarker; serum
• ISSN: 2058-7384; 0394-6320; 2058-7384
• DOI: 10.1177/0394632016681017

Psychiatric evaluation presents a significant challenge because it conceptually integrates the input from multiple psychopathological approaches. Recent technological advances in the study of protein structure, function, and interactions have provided a breakthrough in the diagnosis and treatment of mood disorders (MD), and have identified novel biomarkers to be used as indicators of normal and disease states or response to drug treatment. The investigation of biomarkers for psychiatric disorders, such as enzymes (catechol-O-methyl transferase and monoamine oxidases) or neurotransmitters (dopamine, serotonin, norepinephrine) and their receptors, particularly their involvement in neuroendocrine activity, brain structure, and function, and response to psychotropic drugs, should facilitate the diagnosis of MD. In clinical settings, prognostic biomarkers may be revealed by analyzing serum, saliva, and/or the cerebrospinal fluid, which should promote timely diagnosis and personalized treatment. The mechanisms underlying the activity of most currently used drugs are based on the functional regulation of proteins, including receptors, enzymes, and metabolic factors. In this study, we analyzed recent advances in the identification of biomarkers for MD, which could be used for the timely diagnosis, treatment stratification, and prediction of clinical outcomes.