1/2 Measuring translational dynamics and the proteome to identify potential brain biomarkers for psychiatric disease

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Abstract To further our efforts in identifying the molecular bases of bipolar disorder and schizophrenia, we propose to study protein translation and abundances at the genome-wide level in frontal cortex tissue from 300 brains from patients and healthy controls. We have already amassed an enormous amount of data from these brains, including genotypes, transcriptome profiles and chromatin states. The next step is to look for alterations in protein function in the same brains, since proteins are the ultimate products of gene expression and a critical link between genetic variants and higher order phenotypes, including disease diagnosis. Since proteins are encoded by mRNA transcripts, it appears that protein levels should roughly correlate with transcript levels. However, measured expression levels of mRNAs and their corresponding proteins are often discordant, as are maps of their respective quantitative trait loci. Since we are unable to explain these discrepancies, our picture of molecular changes underlying psychiatric disorders is clearly incomplete. Most previous population-based studies of proteins in neuropsychiatry have been limited to candidate proteins, for which antibodies are already available. For example, in our PsychENCODE project, we are the process of using microwestern arrays to assay ~1000 proteins. In this study, we will use the recently developed technique of ribosome profiling and next-generation proteomics to identify which transcripts are actively being translated in brain and to quantify the abundance of more than 12,000 proteins. Through integrative data analysis, we use the two complementary technologies to detect translational products and to measure their quantitative relationships. Furthermore, these proteins and their translation efficiencies will be assessed for association with disorders. To further improve the specificity of quantification, we will use state-of-the-art deconvolution methods to quantify cell type specific measures of translation efficiency and protein products. This will allow protein translation and abundance in specific major brain cell types to be studied for their changes in affected brains. This study is innovative for being the first genome-wide, population-based study of protein translation and abundance in brains of psychiatric patients. It offers a unique opportunity to fill the gaps between transcriptome and proteome data, and between genetic variants and higher-order phenotypes. It will be a huge step forward in studying the proteins of human brains and the regulatory changes associated with psychiatric disorders, which should ultimately lead to better diagnosis and treatment of these diseases.