Summary: A new blood test can distinguish the severity of a person’s depression and their risk for developing severe depression at a later point. The test can also determine if a person is at risk for developing bipolar disorder. Researchers say the blood test can also assist in tailoring individual options for therapeutic interventions.
Source: Indiana University
Worldwide, 1 in 4 people will suffer from a depressive episode in their lifetime.
While current diagnosis and treatment approaches are largely trial and error, a breakthrough study by Indiana University School of Medicine researchers sheds new light on the biological basis of mood disorders, and offers a promising blood test aimed at a precision medicine approach to treatment.
Led by Alexander B. Niculescu, MD, PhD, Professor of Psychiatry at IU School of Medicine, the study was published today in the high impact journal Molecular Psychiatry . The work builds on previous research conducted by Niculescu and his colleagues into blood biomarkers that track suicidality as well as pain, post-traumatic stress disorder and Alzheimer’s disease.
“We have pioneered the area of precision medicine in psychiatry over the last two decades, particularly over the last 10 years. This study represents a current state-of-the-art outcome of our efforts,” said Niculescu. “This is part of our effort to bring psychiatry from the 19th century into the 21st century. To help it become like other contemporary fields such as oncology. Ultimately, the mission is to save and improve lives.”
The team’s work describes the development of a blood test, composed of RNA biomarkers, that can distinguish how severe a patient’s depression is, the risk of them developing severe depression in the future, and the risk of future bipolar disorder (manic-depressive illness). The test also informs tailored medication choices for patients.
This comprehensive study took place over four years, with over 300 participants recruited primarily from the patient population at the Richard L. Roudebush VA Medical Center in Indianapolis. The team used a careful four-step approach of discovery, prioritization, validation and testing.
First, the participants were followed over time, with researchers observing them in both high and low mood states–each time recording what changed in terms of the biological markers (biomarkers) in their blood between the two states.
Next, Niculescu’s team utilized large databases developed from all previous studies in the field, to cross-validate and prioritize their findings. From here, researchers validated the top 26 candidate biomarkers in independent cohorts of clinically severe people with depression or mania. Last, the biomarkers were tested in additional independent cohorts to determine how strong they were at predicting who is ill, and who will become ill in the future.
From this approach, researchers were then able to demonstrate how to match patients with medications–even finding a new potential medication to treat depression.
“Through this work, we wanted to develop blood tests for depression and for bipolar disorder, to distinguish between the two, and to match people to the right treatments,” said Niculescu.
“Blood biomarkers are emerging as important tools in disorders where subjective self-report by an individual, or a clinical impression of a health care professional, are not always reliable. These blood tests can open the door to precise, personalized matching with medications, and objective monitoring of response to treatment.”
In addition to the diagnostic and therapeutic advances discovered in their latest study, Niculescu’s team found that mood disorders are underlined by circadian clock genes–the genes that regulate seasonal, day-night and sleep-wake cycles.
“That explains why some patients get worse with seasonal changes, and the sleep alterations that occur in mood disorders,” said Niculescu.
According to Niculescu, the work done by his team has opened the door for their findings to be translated into clinical practice, as well as help with new drug development. Focusing on collaboration with pharmaceutical companies and other doctors in a push to start applying some of their tools and discoveries in real-world scenarios, Niculescu said he believes the work being done by his team is vital in improving the quality of life for countless patients.
“Blood biomarkers offer real-world clinical practice advantages. The brain cannot be easily biopsied in live individuals, so we’ve worked hard over the years to identify blood biomarkers for neuropsychiatric disorders,” said Niculescu. “Given the fact that 1 in 4 people will have a clinical mood disorder episode in their lifetime, the need for and importance of efforts such as ours cannot be overstated.”
Funding: This research was supported by the National Institutes of Health under Award Number 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
Mood disorders (depression, bipolar disorders) are prevalent and disabling. They are also highly co-morbid with other psychiatric disorders. Currently there are no objective measures, such as blood tests, used in clinical practice, and available treatments do not work in everybody.
The development of blood tests, as well as matching of patients with existing and new treatments, in a precise, personalized and preventive fashion, would make a significant difference at an individual and societal level. Early pilot studies by us to discover blood biomarkers for mood state were promising, and validated by others.
Recent work by us has identified blood gene expression biomarkers that track suicidality, a tragic behavioral outcome of mood disorders, using powerful longitudinal within-subject designs, validated them in suicide completers, and tested them in independent cohorts for ability to assess state (suicidal ideation), and ability to predict trait (future hospitalizations for suicidality).
These studies showed good reproducibility with subsequent independent genetic studies. More recently, we have conducted such studies also for pain, for stress disorders, and for memory/Alzheimer’s Disease.
We endeavored to use a similar comprehensive approach to identify more definitive biomarkers for mood disorders, that are transdiagnostic, by studying mood in psychiatric disorders patients.
First, we used a longitudinal within-subject design and whole-genome gene expression approach to discover biomarkers which track mood state in subjects who had diametric changes in mood state from low to high, from visit to visit, as measured by a simple visual analog scale that we had previously developed (SMS-7).
Second, we prioritized these biomarkers using a convergent functional genomics (CFG) approach encompassing in a comprehensive fashion prior published evidence in the field.
Third, we validated the biomarkers in an independent cohort of subjects with clinically severe depression (as measured by Hamilton Depression Scale, (HAMD)) and with clinically severe mania (as measured by the Young Mania Rating Scale (YMRS)). Adding the scores from the first three steps into an overall convergent functional evidence (CFE) score, we ended up with 26 top candidate blood gene expression biomarkers that had a CFE score as good as or better than SLC6A4, an empirical finding which we used as a de facto positive control and cutoff.
Notably, there was among them an enrichment in genes involved in circadian mechanisms. We further analyzed the biological pathways and networks for the top candidate biomarkers, showing that circadian, neurotrophic, and cell differentiation functions are involved, along with serotonergic and glutamatergic signaling, supporting a view of mood as reflecting energy, activity and growth.
Fourth, we tested in independent cohorts of psychiatric patients the ability of each of these 26 top candidate biomarkers to assess state (mood (SMS-7), depression (HAMD), mania (YMRS)), and to predict clinical course (future hospitalizations for depression, future hospitalizations for mania). We conducted our analyses across all patients, as well as personalized by gender and diagnosis, showing increased accuracy with the personalized approach, particularly in women.
Again, using SLC6A4 as the cutoff, twelve top biomarkers had the strongest overall evidence for tracking and predicting depression after all four steps: NRG1, DOCK10, GLS, PRPS1, TMEM161B, GLO1, FANCF, HNRNPDL, CD47, OLFM1, SMAD7, and SLC6A4. Of them, six had the strongest overall evidence for tracking and predicting both depression and mania, hence bipolar mood disorders. There were also two biomarkers (RLP3 and SLC6A4) with the strongest overall evidence for mania. These panels of biomarkers have practical implications for distinguishing between depression and bipolar disorder.
Next, we evaluated the evidence for our top biomarkers being targets of existing psychiatric drugs, which permits matching patients to medications in a targeted fashion, and the measuring of response to treatment. We also used the biomarker signatures to bioinformatically identify new/repurposed candidate drugs. Top drugs of interest as potential new antidepressants were pindolol, ciprofibrate, pioglitazone and adiphenine, as well as the natural compounds asiaticoside and chlorogenic acid. The last 3 had also been identified by our previous suicidality studies.
Finally, we provide an example of how a report to doctors would look for a patient with depression, based on the panel of top biomarkers (12 for depression and bipolar, one for mania), with an objective depression score, risk for future depression, and risk for bipolar switching, as well as personalized lists of targeted prioritized existing psychiatric medications and new potential medications.
Overall, our studies provide objective assessments, targeted therapeutics, and monitoring of response to treatment, that enable precision medicine for mood disorders.
Precision medicine for mood disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs