Replicable and Coupled Changes in Innate and Adaptive Immune Gene Expression in Two Case-Control Studies of Blood Microarrays in Major Depressive Disorder

Gwenaël G R Leday, Petra E Vértes, Sylvia Richardson, Jonathan R Greene, Tim Regan, Shahid Khan, Robbie Henderson, Tom C Freeman, Carmine M Pariante, Neil A Harrison, MRC Immunopsychiatry Consortium, V Hugh Perry, Wayne C Drevets, Gayle M Wittenberg, Edward T Bullmore, Edward Bullmore, Petra Vertes, Rudolf Cardinal, Sylvia Richardson, Gwenael Leday, Tom Freeman, Tim Regan, David Hume, Zhaozong Wu, Carmine Pariante, Annamaria Cattaneo, Patricia Zunszain, Alessandra Borsini, Robert Stewart, David Chandran, Livia Carvalho, Joshua Bell, Luis Souza-Teodoro, Hugh Perry, Neil Harrison, Wayne Drevets, Gayle Wittenberg, Declan Jones, Edward Bullmore, Shahid Khan, Annie Stylianou, Robbie Henderson, Gwenaël G R Leday, Petra E Vértes, Sylvia Richardson, Jonathan R Greene, Tim Regan, Shahid Khan, Robbie Henderson, Tom C Freeman, Carmine M Pariante, Neil A Harrison, MRC Immunopsychiatry Consortium, V Hugh Perry, Wayne C Drevets, Gayle M Wittenberg, Edward T Bullmore, Edward Bullmore, Petra Vertes, Rudolf Cardinal, Sylvia Richardson, Gwenael Leday, Tom Freeman, Tim Regan, David Hume, Zhaozong Wu, Carmine Pariante, Annamaria Cattaneo, Patricia Zunszain, Alessandra Borsini, Robert Stewart, David Chandran, Livia Carvalho, Joshua Bell, Luis Souza-Teodoro, Hugh Perry, Neil Harrison, Wayne Drevets, Gayle Wittenberg, Declan Jones, Edward Bullmore, Shahid Khan, Annie Stylianou, Robbie Henderson

Abstract

Background: Peripheral inflammation is often associated with major depressive disorder (MDD), and immunological biomarkers of depression remain a focus of investigation.

Methods: We used microarray data on whole blood from two independent case-control studies of MDD: the GlaxoSmithKline-High-Throughput Disease-specific target Identification Program [GSK-HiTDiP] study (113 patients and 57 healthy control subjects) and the Janssen-Brain Resource Company study (94 patients and 100 control subjects). Genome-wide differential gene expression analysis (18,863 probes) resulted in a p value for each gene in each study. A Bayesian method identified the largest p-value threshold (q = .025) associated with twice the number of genes differentially expressed in both studies compared with the number of coincidental case-control differences expected by chance.

Results: A total of 165 genes were differentially expressed in both studies with concordant direction of fold change. The 90 genes overexpressed (or UP genes) in MDD were significantly enriched for immune response to infection, were concentrated in a module of the gene coexpression network associated with innate immunity, and included clusters of genes with correlated expression in monocytes, monocyte-derived dendritic cells, and neutrophils. In contrast, the 75 genes underexpressed (or DOWN genes) in MDD were associated with the adaptive immune response and included clusters of genes with correlated expression in T cells, natural killer cells, and erythroblasts. Consistently, the MDD patients with overexpression of UP genes also had underexpression of DOWN genes (correlation > .70 in both studies).

Conclusions: MDD was replicably associated with proinflammatory activation of the peripheral innate immune system, coupled with relative inactivation of the adaptive immune system, indicating the potential of transcriptional biomarkers for immunological stratification of patients with depression.

Keywords: Affymetrix; Bayesian; Biomarker; Inflammation; Systems; Transcriptome.

Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1
Figure 1
Protein–protein interaction network for proteins coded by the set of 165 replicably concordant genes differentially expressed in both case-control studies of major depressive disorder. The network is represented by an undirected graph where links correspond to known protein–protein interactions and weights are proportional to the Search Tool for the Retrieval of Interacting Genes/Proteins confidence score . Only high-confidence (>0.7) links are retained, and disconnected genes are not shown. Red (blue) nodes correspond to genes over- (under-) expressed in major depressive disorder in both the GlaxoSmithKline–High-Throughput Disease-specific target Identification Program and Janssen–Brain Resource Company datasets. Smaller inner circles highlight proteins that are coded by genes also differentially expressed and with the same sign of fold change in a third large independent case-control study of major depressive disorder (Netherlands Study of Depression and Anxiety [NESDA]) thresholded to control false discovery rate (FDR) at 20% (white circles), 10% (gray circles), and 5% (black circles).
Figure 2
Figure 2
Major depressive disorder (MDD)-related genes in the context of the normative whole-genome transcriptome. Overexpressed genes (or UP genes) in patients with MDD are concentrated in a module of the normative gene coexpression network specialized for innate immune response, whereas underexpressed genes (or DOWN genes) are concentrated in a module partially specialized for adaptive immune response. (A) The modules of the normative transcriptome are highlighted in different colors. (B) The MDD-related genes are colored according to their normative module affiliation, and representative genes are text-labeled. (C) The MDD-related genes are colored green for overexpressed (or UP) genes and are colored red for underexpressed (or DOWN) genes. The text labels highlight the functions of the corresponding modules of the normative transcriptome. rRNA, ribosomal RNA; SRP, signal recognition particle.
Figure 3
Figure 3
Cell class–specific expression patterns for the set of 165 replicably concordant genes. We estimated the correlation between each possible pair of the 165 major depressive disorder (MDD)-related genes and identified clusters of genes with similar expression patterns in an independent microarray dataset on specific cell types. The set of 165 replicably concordant genes formed six clusters, with each cluster comprising a subset of genes that had strong mutual coexpression across a range of eight distinct cell classes: erythroblasts, monocytes, monocyte-derived dendritic cells (MDDCs), neutrophils, B cells, CD4+ T cells, CD8+ T cells, and natural killer (NK) cells. (A) The six clusters of genes with strongly correlated expression profiles. Clusters 1 to 4 (left) comprised genes that were overexpressed in MDD (or UP genes), and clusters 5 and 6 (right) comprised genes that were underexpressed in MDD (or DOWN genes). (B) Histograms of clustered gene expression across cell types for each of the four clusters of UP genes overexpressed in MDD (from top to bottom: clusters 1–4). The x-axis color legend codes for different cell types. (C) Histograms of clustered gene expression across cell types for each of the two clusters of DOWN genes underexpressed in MDD (from top to bottom: clusters 5 and 6). The x-axis color legend codes for different cell types.
Figure 4
Figure 4
Opposing and coordinated expression of innate and adaptive immune transcripts in patients with major depressive disorder (MDD). (A, B) Scatter plots for the mean expression across the 75 underexpressed (DOWN) genes plotted against the mean expression of 90 overexpressed (UP) genes in the Janssen–Brain Resource Company (Janssen–BRC) (A) and GlaxoSmithKline–High-Throughput Disease-specific target Identification Program (GSK–HiTDiP) (B) datasets. Each point corresponds to a patient. Blue indicates case, and gray indicates control (CTL). Regression lines are shown in blue and gray, respectively. In (A), an individual patient’s data point (red outline) is projected onto the regression line (red circle). The distance from the origin to the point on the regression line is the bioscalar value for that patient. Inset illustrates the projection (black) of all individual patient data points (blue) onto the sample regression line. (C, D) Left panels: Box plot of MDD-165 bioscalar values in controls and cases. Green line indicates the threshold identifying the top third (tertile) of the MDD-165 bioscalar distribution as a subgroup of inflamed patients with MDD (designated immune-MDD). Right panels: Receiver operating characteristic curves were calculated for MDD vs. CTL and immune-MDD vs. CTL classifications. (E) Correlation of each depressed patient’s MDD-165 bioscalar with body mass index (BMI). (F, G) Box plots of MDD-165 bioscalar for subgroups defined by a comorbid diagnosis of anxiety disorder. AUC, area under the curve.

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