Gene expression signatures as biomarkers of childhood trauma-related depression

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Exposure to serious or traumatic life events in childhood is a well-established major risk factor for developing health problems. Childhood abuse, neglect and early loss have been consistently associated with an increased risk for mental health problems in adulthood, especially in the context of chronic or repeated acute stress exposure. In a preceding project, it was shown that healthy adults with a history of childhood trauma displayed distinct gene expression profiles following acute stress exposure. Genes prominently featuring among differentially expressed transcripts are those involved in the pro-inflammatory response, receptor signaling and G-protein coupled receptor activity. We suggest that these alterations in the transcriptional stress response constitute a key vulnerability factor, and are mechanistically involved in the processes linking stress to disease in individuals exposed to early trauma. The proposed project seeks to investigate whether the identified transcripts are altered in depression, and whether these transcripts can distinguish between depressed individuals with a history of childhood trauma vs. depressed patients without such a history. Investigation of gene expression levels can provide evidence of distinct biological modifications in depression in the presence or absence of exposure to childhood abuse. In the long-term, the study may have implications for personalized medicine. Identified gene expression patterns might be utilized to sub-type depression associated with traumatic experience in childhood and characterized by distinct alterations in stress-responsive signaling pathways and might ultimately guide treatment choices.Another open question concerns the mechanism underlying differential gene expression patterns. A further aim is therefore to investigate the role of differential DNA methylation in the transcriptional stress response. Taking advantage of the existing data set (genome-wide mRNA expression profiles in response to stress), data will be complemented by adding information on genome-wide methylation levels. This will allow the integration of methylome and transcriptome analyses in the context of stress regulation.