Biomarkers for depression: recent insights, current challenges and future prospects

Summary & key facts

Researchers reviewed a large body of studies and found hundreds of biological signals that might be linked to depression. The most promising signals involve inflammation, factors that help brain cells stay healthy, metabolism, brain chemicals, and stress-related hormones. These signals can be measured in many ways, like looking at genes, protein levels, small molecules in the blood, or brain scans. But the studies disagree a lot, and depression itself is very different from person to person. That means these biomarkers are not yet ready to diagnose people or pick the right treatment for an individual. Still, the research is promising and more careful, large-scale work could lead to better tests and treatments in the future.

Key facts:

• Researchers have found hundreds of possible biological markers linked to depression across many studies.
• The most promising marker types are tied to inflammation, brain growth and maintenance, metabolism, neurotransmitters (brain chemicals), and stress-related hormone systems.
• Scientists can look for these markers in many ways, including genetic tests, measures of gene activity, protein and metabolite tests, and brain imaging.
• Progress is limited because depression is a very mixed condition and past studies used many different methods, so results often do not match.
• Because of this mismatch and variability, no biomarker has yet been established for routine diagnosis or for reliably choosing the best treatment for a specific person.
• The authors conclude that focused, systematic research is now needed to see which biomarkers can predict treatment response, group patients for specific treatments, or point to new therapies.

Abstract

Abstract: A plethora of research has implicated hundreds of putative biomarkers for depression, but has not yet fully elucidated their roles in depressive illness or established what is abnormal in which patients and how biologic information can be used to enhance diagnosis, treatment and prognosis. This lack of progress is partially due to the nature and heterogeneity of depression, in conjunction with methodological heterogeneity within the research literature and the large array of biomarkers with potential, the expression of which often varies according to many factors. We review the available literature, which indicates that markers involved in inflammatory, neurotrophic and metabolic processes, as well as neurotransmitter and neuroendocrine system components, represent highly promising candidates. These may be measured through genetic and epigenetic, transcriptomic and proteomic, metabolomic and neuroimaging assessments. The use of novel approaches and systematic research programs is now required to determine whether, and which, biomarkers can be used to predict response to treatment, stratify patients to specific treatments and develop targets for new interventions. We conclude that there is much promise for reducing the burden of depression through further developing and expanding these research avenues. Keywords: mood disorder, major depressive disorder, inflammation, treatment response, stratification, personalized medicine

Topics

Stress Responses and Cortisol Treatment of Major Depression Tryptophan and brain disorders

Categories

Biological Psychiatry Life Sciences Neuroscience

Tags

Biochemistry Bioinformatics Biology Biomarker Depression (economics) Dopamine Economics Epigenetics Gene Internal medicine Macroeconomics Major depressive disorder Medicine Mood Neuroimaging Neuroscience Neurotransmitter systems Pathology Personalized medicine Precision medicine Psychiatry Psychological intervention Psychology

Conditions & symptoms

Depression Lack of energy or motivation Poor sleep Sadness or low mood