Major depression is the second largest burden of disease in the developed world and a leading cause of disability. The role of inflammation in depression has been established, yet a more complete understanding of the molecular mechanisms and biological processes associated with inflammation-induced depression requires an investigation of possibilities that lie "outside the box" of individual candidate systems. The rationale of this application is to fill the void that currently exists through a genome-wide functional analysis and network reconstruction of the mechanisms of inflammation-induced depression. We will integrate our well-validated and accepted murine model of Bacillus Calmette-Guerin (BCG) induced inflammation and our indoleamine 2,3 dioxygenase knock-out (IDO KO) mice to answer two important and rate-limiting questions:
Aim 1) What genes are differentially expressed in innate immune cells in BCG-induced depression? Aim 2) What are the biological functions and networks of the BCG-induced depression genes? Aim 1 will be addressed by characterizing the transcriptome profile of innate immune cells measured using RNA-Seq. We have demonstrated the three pivotal cornerstones for this proposal. First, BCG inoculation induces long-lasting depression-like behaviors that persist for at least 3 weeks. Second, BCG-induced depression is mediated by IDO activation and IDO KO mice develop inflammation just as wild-type mice, although they do not display depression-like behaviors. Third, lung and brain macrophages play a crucial role in mounting inflammatory behavioral response. Therefore, a randomized 2x2 factorial design including two treatments (BCG-challenge and saline control) and two mice strains (wild type and IDO KO) will be used. Lung macrophages and brain microglia from 12 mice per challenge-strain group, based on power analysis, will be collected 2 weeks after challenge. Subtractive and differential expression contrasts between groups will permit identification of inflammation-induced depression genes that are expressed in a long-lasting model of depression-like behavior and: 1) are independent of changes in inflammation and immunity that may contribute to recovery, and 2) are independent of baseline strain differences.
Aim 2 will be addressed using abstractionist functional analyses of the genes identified in Aim 1 and gene network reconstruction. In addition to knowledge discovery, we will test concrete hypotheses on the functional signature of depression, including: serotonin, guanine-tetrahydrobiopterin nitric oxide, and energy metabolism pathways and transcription factors. Key transcripts will be confirmed using Real Time Quantitative PCR. A multidisciplinary team with expertise in neuroscience, behavior, immunity, transcriptome analysis and bioinformatics has been assembled to accomplish the proposed research. This application is submitted to the R21 program because a targeted RNA-Seq "exploratory experiment" and innovative comparison of pathways and networks are proposed. The outcomes of the proposed research are: 1) identification of molecular mechanisms including immune pathways and regulatory motifs that underlie inflammation-induced depression, 2) elucidation of the relationship between inflammation and depression, and 3) insights on related processes such as age-dependent inflammation-induced depression and other inflammation-associated neurological disorders, including anxiety, autism, schizophrenia, Alzheimer's disease and dementia caused by human immunodeficiency virus, and addictions to alcohol and drugs.
We already know from converging clinical and experimental data that depression develops on a background of sickness under conditions of inflammation. A comprehensive understanding of the molecular basis of inflammation-induced depression will result from this first systems biology approach to investigate the transcriptome profile using functional analysis followed by gene network reconstruction. The outcomes of this study in terms of knowledge discovery and hypothesis generation will help to develop prognostic and diagnostic tools that will lead to preventive and remedial treatments for those afflicted by inflammation-induced behavioral disorders.
|Akhtar, Malik N; Southey, Bruce R; Andrén, Per E et al. (2014) Identification of best indicators of peptide-spectrum match using a permutation resampling approach. J Bioinform Comput Biol 12:1440001|