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Analyses of blood RNA in a study of 64 patients with or without major depression showed significant differences in gene transcript levels between groups, in ways that suggest blood transcriptomic markers may provide an objective way to diagnose depression, predict response to cognitive-behavioral therapy, and identify people with a predisposition to depression.
As a secondary part of a randomized study comparing the efficacy of 18 weeks of live versus telephone-based cognitive-behavioral therapy (CBT), investigators studied a panel of blood transcriptomic markers before treatment in 32 patients with major depressive disorder and 32 matched controls without depression, and in 22 patients in each group after treatment.
The abundance of nine transcripts differed significantly between groups at baseline, suggesting that a panel of transcriptomic markers could be diagnostic in a clinical population, Eva E. Redei, Ph.D., and her associates reported (Transl. Psychiatry 2014 Aug. 16 [doi:10.1038/tp.2014.66]).
These markers include adenylate cyclase 3 (ADCY3); diacylglycerol kinase, alpha (DGKA); family with sequence similarity 46, member A (FAM46A); immunoglobulin superfamily, member 4 (IGSF4), which also is known as cell adhesion molecule 1 (CADM1); KIAA1539; myristoylated alanine-rich protein kinase C substrate (MARCKS); proteasome activator subunit 1 (PSME1); Ras association and pleckstrin homology domains 1, also known as LPD (RAPH1); and intracellular Toll-like receptor 7 (TLR7).
After CBT, the abundance of five transcripts – DGKA, IGSF4A/CADM1, KIAA1539, MARCKS, and RAPH1 – remained significantly different between the two patient groups.
Receiver-operating characteristic (ROC) analyses of blood transcript levels showed that RAPH1, KIAA1539, and DGKA also had significant areas under the curve (AUC) in the depressed patients after cognitive-behavioral therapy both in the nine patients who achieved a full remission of disease and in the 13 patients who did not. “These markers come closest to the ultimate goal of identifying predisposition to depression, even in the absence of a current depressive episode,” reported Dr. Redei, professor in psychiatry and behavioral sciences, and physiology at Northwestern University, Chicago.
In addition, coexpression patterns of transcripts might help predict remission or persistence of clinical depression after CBT. Patients whose depression remitted had 11 “hubs” of coexpressed gene-pairs that correlated significantly with three or more transcripts, compared with five hubs in patients who did not achieve remission. Transcript levels of ADCY3, DGKA, IGSF4A/CADM1, PSME1, and RAPH1 significantly correlated in their expression at baseline in patients whose disease remitted after treatment but not in patients who remained clinically depressed after treatment.
Subjects in the control group were matched to patients with depression by age, sex, and race. Most patients in the depressed group were on medication, including those who did not achieve remission, so it was thought that the medications did not interfere with the blood marker measurements.
The results support findings from previous studies using animal models of depression, and from a pilot study of teenagers with and without major depressive disorder, which showed differences between groups in the abundance of some transcriptomic markers, Dr. Redei said. Unlike the current study, which accepted a wide range of ages (23-83 years) and concurrent medical therapy, the study of adolescents required participants to be 15-19 years of age and medication free. Blood levels of three transcripts – PSME1, RAPH1, and IGSF4A – differed significantly in the teens with depression, compared with nondepressed controls (Transl. Psychiatry 2012 April 17 [doi:10.1038/tp.2012.26]).
At least one separate pilot study previously has proposed using serum levels of nine biomarkers and a proprietary algorithm to diagnose major depressive disorder, Dr. Redei noted (Mol. Psychiatry 2013;18:332-9).
Future validation studies should include more patients and try to assess the usefulness of a panel of blood transcriptomic markers in patients with other psychiatric illnesses, the investigators suggested.
Dr. Redei is named as an inventor on two pending patent applications. She and her associates reported having no other financial disclosures. The National Institute of Mental Health and the Davee Foundation funded the study.
On Twitter @sherryboschert
Analyses of blood RNA in a study of 64 patients with or without major depression showed significant differences in gene transcript levels between groups, in ways that suggest blood transcriptomic markers may provide an objective way to diagnose depression, predict response to cognitive-behavioral therapy, and identify people with a predisposition to depression.
As a secondary part of a randomized study comparing the efficacy of 18 weeks of live versus telephone-based cognitive-behavioral therapy (CBT), investigators studied a panel of blood transcriptomic markers before treatment in 32 patients with major depressive disorder and 32 matched controls without depression, and in 22 patients in each group after treatment.
The abundance of nine transcripts differed significantly between groups at baseline, suggesting that a panel of transcriptomic markers could be diagnostic in a clinical population, Eva E. Redei, Ph.D., and her associates reported (Transl. Psychiatry 2014 Aug. 16 [doi:10.1038/tp.2014.66]).
These markers include adenylate cyclase 3 (ADCY3); diacylglycerol kinase, alpha (DGKA); family with sequence similarity 46, member A (FAM46A); immunoglobulin superfamily, member 4 (IGSF4), which also is known as cell adhesion molecule 1 (CADM1); KIAA1539; myristoylated alanine-rich protein kinase C substrate (MARCKS); proteasome activator subunit 1 (PSME1); Ras association and pleckstrin homology domains 1, also known as LPD (RAPH1); and intracellular Toll-like receptor 7 (TLR7).
After CBT, the abundance of five transcripts – DGKA, IGSF4A/CADM1, KIAA1539, MARCKS, and RAPH1 – remained significantly different between the two patient groups.
Receiver-operating characteristic (ROC) analyses of blood transcript levels showed that RAPH1, KIAA1539, and DGKA also had significant areas under the curve (AUC) in the depressed patients after cognitive-behavioral therapy both in the nine patients who achieved a full remission of disease and in the 13 patients who did not. “These markers come closest to the ultimate goal of identifying predisposition to depression, even in the absence of a current depressive episode,” reported Dr. Redei, professor in psychiatry and behavioral sciences, and physiology at Northwestern University, Chicago.
In addition, coexpression patterns of transcripts might help predict remission or persistence of clinical depression after CBT. Patients whose depression remitted had 11 “hubs” of coexpressed gene-pairs that correlated significantly with three or more transcripts, compared with five hubs in patients who did not achieve remission. Transcript levels of ADCY3, DGKA, IGSF4A/CADM1, PSME1, and RAPH1 significantly correlated in their expression at baseline in patients whose disease remitted after treatment but not in patients who remained clinically depressed after treatment.
Subjects in the control group were matched to patients with depression by age, sex, and race. Most patients in the depressed group were on medication, including those who did not achieve remission, so it was thought that the medications did not interfere with the blood marker measurements.
The results support findings from previous studies using animal models of depression, and from a pilot study of teenagers with and without major depressive disorder, which showed differences between groups in the abundance of some transcriptomic markers, Dr. Redei said. Unlike the current study, which accepted a wide range of ages (23-83 years) and concurrent medical therapy, the study of adolescents required participants to be 15-19 years of age and medication free. Blood levels of three transcripts – PSME1, RAPH1, and IGSF4A – differed significantly in the teens with depression, compared with nondepressed controls (Transl. Psychiatry 2012 April 17 [doi:10.1038/tp.2012.26]).
At least one separate pilot study previously has proposed using serum levels of nine biomarkers and a proprietary algorithm to diagnose major depressive disorder, Dr. Redei noted (Mol. Psychiatry 2013;18:332-9).
Future validation studies should include more patients and try to assess the usefulness of a panel of blood transcriptomic markers in patients with other psychiatric illnesses, the investigators suggested.
Dr. Redei is named as an inventor on two pending patent applications. She and her associates reported having no other financial disclosures. The National Institute of Mental Health and the Davee Foundation funded the study.
On Twitter @sherryboschert
Analyses of blood RNA in a study of 64 patients with or without major depression showed significant differences in gene transcript levels between groups, in ways that suggest blood transcriptomic markers may provide an objective way to diagnose depression, predict response to cognitive-behavioral therapy, and identify people with a predisposition to depression.
As a secondary part of a randomized study comparing the efficacy of 18 weeks of live versus telephone-based cognitive-behavioral therapy (CBT), investigators studied a panel of blood transcriptomic markers before treatment in 32 patients with major depressive disorder and 32 matched controls without depression, and in 22 patients in each group after treatment.
The abundance of nine transcripts differed significantly between groups at baseline, suggesting that a panel of transcriptomic markers could be diagnostic in a clinical population, Eva E. Redei, Ph.D., and her associates reported (Transl. Psychiatry 2014 Aug. 16 [doi:10.1038/tp.2014.66]).
These markers include adenylate cyclase 3 (ADCY3); diacylglycerol kinase, alpha (DGKA); family with sequence similarity 46, member A (FAM46A); immunoglobulin superfamily, member 4 (IGSF4), which also is known as cell adhesion molecule 1 (CADM1); KIAA1539; myristoylated alanine-rich protein kinase C substrate (MARCKS); proteasome activator subunit 1 (PSME1); Ras association and pleckstrin homology domains 1, also known as LPD (RAPH1); and intracellular Toll-like receptor 7 (TLR7).
After CBT, the abundance of five transcripts – DGKA, IGSF4A/CADM1, KIAA1539, MARCKS, and RAPH1 – remained significantly different between the two patient groups.
Receiver-operating characteristic (ROC) analyses of blood transcript levels showed that RAPH1, KIAA1539, and DGKA also had significant areas under the curve (AUC) in the depressed patients after cognitive-behavioral therapy both in the nine patients who achieved a full remission of disease and in the 13 patients who did not. “These markers come closest to the ultimate goal of identifying predisposition to depression, even in the absence of a current depressive episode,” reported Dr. Redei, professor in psychiatry and behavioral sciences, and physiology at Northwestern University, Chicago.
In addition, coexpression patterns of transcripts might help predict remission or persistence of clinical depression after CBT. Patients whose depression remitted had 11 “hubs” of coexpressed gene-pairs that correlated significantly with three or more transcripts, compared with five hubs in patients who did not achieve remission. Transcript levels of ADCY3, DGKA, IGSF4A/CADM1, PSME1, and RAPH1 significantly correlated in their expression at baseline in patients whose disease remitted after treatment but not in patients who remained clinically depressed after treatment.
Subjects in the control group were matched to patients with depression by age, sex, and race. Most patients in the depressed group were on medication, including those who did not achieve remission, so it was thought that the medications did not interfere with the blood marker measurements.
The results support findings from previous studies using animal models of depression, and from a pilot study of teenagers with and without major depressive disorder, which showed differences between groups in the abundance of some transcriptomic markers, Dr. Redei said. Unlike the current study, which accepted a wide range of ages (23-83 years) and concurrent medical therapy, the study of adolescents required participants to be 15-19 years of age and medication free. Blood levels of three transcripts – PSME1, RAPH1, and IGSF4A – differed significantly in the teens with depression, compared with nondepressed controls (Transl. Psychiatry 2012 April 17 [doi:10.1038/tp.2012.26]).
At least one separate pilot study previously has proposed using serum levels of nine biomarkers and a proprietary algorithm to diagnose major depressive disorder, Dr. Redei noted (Mol. Psychiatry 2013;18:332-9).
Future validation studies should include more patients and try to assess the usefulness of a panel of blood transcriptomic markers in patients with other psychiatric illnesses, the investigators suggested.
Dr. Redei is named as an inventor on two pending patent applications. She and her associates reported having no other financial disclosures. The National Institute of Mental Health and the Davee Foundation funded the study.
On Twitter @sherryboschert
FROM TRANSLATIONAL PSYCHIATRY
Key clinical point: Blood levels of transcript panels differentiated depressed patients from controls.
Major finding: Blood transcript levels of nine markers differed significantly between groups.
Data source: Secondary analyses from a study of 32 depressed patients and 32 nondepressed subjects.
Disclosures: Dr. Redei is named as an inventor on two pending patent applications. She and her associates reported having no other financial disclosures. The National Institute of Mental Health and the Davee Foundation funded the study.
