NEW YORK (GenomeWeb) – Northwestern University researchers have assessed a blood-based biomarker panel for major depressive disorder, reporting in Translational Psychiatry today that it could distinguish people with depression from those without.
Researchers led by Eva Redei, a professor of psychiatry at Northwestern, tested their panel of 20 markers in 32 patients and 32 controls. The patients were also retested some 18 weeks after therapy.
The panel, Redei and her team reported, could also differentiate patients who responded to cognitive behavioral therapy from those who did not.
"This clearly indicates that you can have a blood-based laboratory test for depression, providing a scientific diagnosis in the same way someone is diagnosed with high blood pressure or high cholesterol," Redei said in a statement.
Major depressive disorder affects 6.7 percent of adults in the US each year, and can be difficult to diagnose as a diagnosis is based on patients' self-reported symptoms.
Aiming to create a better diagnostic tool, Redei and her colleagues developed a set of 20 gene transcripts whose levels they suspected were associated with depression — they'd tested previous version of the panel in adolescents. This panel includes genes like PSME1, RAPH1, KIAA12539, and IGSF4A.
To test the panel, the researchers obtained blood samples from 32 people with depression and 32 matched controls. Post-treatment blood samples were also taken from 22 people who had depression at baseline testing. A diagnosis of depression was determined through the Mini International Neuropsychiatry Interview and the severity of disease was gauged using the PHQ-9 questionnaire.
Using a qPCR-based approach, the researchers examined the levels of these gene transcripts in the blood of patients and controls.
At baseline, Redei and her colleagues reported that the blood transcript levels of nine members of the gene panel — including IGSF4A/CADM1, KIAA1539, PSME1, and RAPH1— differed between patients and matched controls. Three of these nine transcripts also differed between teenage cases and controls in a previous study from the group.
"[These results] suggest that these transcripts participate in processes that are characteristic of depressed mood, or of other endophenotypes intricately involved in [major depression]," the researchers said.
Some of these transcript level differences persisted even when the patients no longer had a clinical diagnosis of depression, as gauged by PHQ-9 scores. Levels of three transcripts — RAPH1, KIAA1539, and DGKA — remained different between patients and controls, even when the patients got better.
"These three markers move us towards the ultimate goal of identifying predisposition to depression, even in the absence of a current depressive episode," Redei said.
She and her colleagues also noted a difference in the levels of a set of three other transcripts — ASAH1, ATP11C, and KIAA1539 — between patients who remitted at the end of therapy, as gauged by PHQ-9 scores, versus those who did not.
This, the researchers said, suggested that these transcripts might be able to evaluate treatment efficacy. However, they noted that the differences were not significant when adjusted for multiple comparisons.
Still, they said these three transcripts might mark depressive state rather than vulnerability to disease.
The researchers further identified some 15 co-expressed gene pairs in the non-remitted group and 20 in the remitted group. In particular, the researchers noted that transcript patterns of ADCY3, DGKA, IGSF4A/ CADM1, PSME1, and RAPH1 at baseline were correlated with remission in response to therapy.
"This distinction could be used in the future to predict who would respond to the therapy," Redei said.
Redei and her colleagues noted that this study had a small sample size and said that they plan to further validate their findings in a larger population.