Summary: Researchers at Indiana University have developed a blood test that can measure how severe a person’s depression is, estimate their future risk of developing severe depression, and assess risk for bipolar disorder. The test, based on RNA biomarkers, also offers information that can help personalize treatment choices for individual patients.
Source: Indiana University
Globally, one in four people will experience a depressive episode during their lifetime.
Current approaches to diagnosing and treating mood disorders often depend on subjective reports and trial-and-error prescribing. A new study led by Alexander B. Niculescu, MD, PhD, Professor of Psychiatry at Indiana University School of Medicine, describes a blood-based panel of RNA biomarkers that advances a precision medicine approach to mood disorders. The study appears in the journal Molecular Psychiatry and builds on years of work identifying blood biomarkers for suicidality, pain, post-traumatic stress disorder, and Alzheimer’s disease.
Niculescu and colleagues report a multi-step research program that developed and validated a blood test capable of: distinguishing current depression severity, predicting the likelihood of future severe depression, identifying risk for bipolar disorder, and guiding medication selection. The research aims to bring objective biological measures into psychiatric practice to improve diagnosis, treatment matching, and monitoring.
The investigation spanned four years and enrolled more than 300 participants, primarily from the Richard L. Roudebush VA Medical Center in Indianapolis. Researchers applied a rigorous discovery-to-validation process: longitudinal within-patient discovery, evidence prioritization using large databases, independent cohort validation, and testing of predictive performance in additional samples.
In the discovery phase, participants were followed over time and evaluated in both higher and lower mood states. The team tracked within-individual changes in gene expression in blood, identifying signals that rose or fell with shifts in mood. Those candidate markers were then cross-referenced with prior literature and databases to prioritize the most promising biomarkers.
The top 26 candidate biomarkers were validated in separate cohorts of patients with clinically severe depression or mania. Finally, the panel’s predictive strength was tested in further independent groups to assess accuracy for current illness, risk of future illness, and the capacity to distinguish unipolar depression from bipolar mood disorder.
Beyond diagnosis and risk prediction, the team explored how the biomarker panel could guide pharmacological choices. By examining which biomarkers are influenced by existing psychiatric medications, and by using bioinformatic screening to identify potential repurposed drugs, the researchers produced prioritized medication lists tailored to individual biomarker profiles. This work also highlighted several candidate compounds—including some already used in other contexts—that merit further study as antidepressants.
An important biological insight from the study is the enrichment of circadian clock genes among the top biomarkers. These genes regulate sleep-wake cycles and seasonal rhythms, providing a plausible molecular explanation for why mood disorders often fluctuate with sleep disruption and seasonal changes.
Niculescu emphasizes the practical potential of blood biomarkers in clinical settings: “Because we cannot biopsy the brain in living patients, blood-based markers offer an accessible window into neuropsychiatric processes. Objective tests can support diagnosis, personalize treatment plans, and objectively monitor response.”
The authors note that their personalized analyses increased predictive accuracy, particularly in women, and propose a model clinical report that would present an objective depression score, a calculated risk for future depression and bipolar switching, and a ranked list of targeted medications—both existing and repurposed candidates—based on an individual’s biomarker profile.
Funding: This research was supported by the National Institutes of Health (Award Numbers 1DP20D007363 and R01MH117431) and a VA Merit Award (2I01CX000139).
About this depression and bipolar disorder research news
Source: Indiana University
Contact: Katie Duffey – Indiana University
Image: The image is in the public domain
Original Research: Open access. “Precision medicine for mood disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs” by H. Le‑Niculescu, K. Roseberry, S. S. Gill, D. F. Levey, P. L. Phalen, J. Mullen, A. Williams, S. Bhairo, T. Voegtline, H. Davis, A. Shekhar, S. M. Kurian & A. B. Niculescu. Molecular Psychiatry
Abstract
Mood disorders, including major depression and bipolar disorder, are common, disabling, and often co-occur with other psychiatric illnesses. Clinical practice currently lacks widely used objective biological tests, and many patients do not respond to first-line treatments. Developing blood-based diagnostic tools and approaches that match patients to the most effective treatments could significantly improve outcomes.
Using a comprehensive, multi-stage strategy, the researchers first applied a longitudinal within-subject design and whole-genome gene expression profiling to discover biomarkers that track mood when individuals shifted between low and high mood states. These signals were prioritized using convergent functional genomics, integrating prior evidence from the field.
Validation in independent cohorts of patients with severe depression and severe mania yielded 26 top candidate biomarkers with strong convergent evidence. Pathway analyses highlighted involvement of circadian regulation, neurotrophic and cell differentiation processes, and serotonergic and glutamatergic signaling—supporting a conceptualization of mood linked to energy, activity, and cellular growth.
Testing of these biomarkers across independent psychiatric cohorts assessed their ability to measure current mood state and to predict clinical course, including future hospitalizations for depression or mania. Personalizing analyses by gender and diagnosis improved accuracy, notably among women. Twelve markers demonstrated the strongest evidence for tracking and predicting depression overall, and several markers distinguished bipolar illness from unipolar depression.
The investigators also evaluated whether top biomarkers are targets of existing psychiatric drugs to enable targeted prescribing, and they used biomarker signatures to identify candidate repurposed drugs. Examples of agents highlighted for further investigation included pindolol, ciprofibrate, pioglitazone, adiphenine, and natural compounds such as asiaticoside and chlorogenic acid.
Finally, the study illustrates how a clinician-facing report could present an objective depression score, risks for future depressive episodes and bipolar switching, and individualized, prioritized medication options based on the biomarker panel. Overall, this research supports the feasibility of objective assessment, targeted therapeutics, and treatment monitoring to advance precision medicine in mood disorders.
Precision medicine for mood disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs